case study biodiversity loss

The South African National Biodiversity Institute (SANBI) contributes to South Africa’s sustainable development by facilitating access to biodiversity data, generating information and knowledge, building capacity, providing policy advice, showcasing and conserving biodiversity in its national botanical and zoological gardens.

Terms and conditions

QUICK LINKS

• Biodiversity
• Community Initiatives

Postal: Private Bag X101, Silverton, 0184

Physical: 2 Cussonia Ave, Brummeria, Pretoria.

Tel: +27 (0)12 843 5000 Fax: +27 (0)12 804 3211

To report suspected fraud at SANBI Email: [email protected] Call: 0800 160 999

Report complaints on environmental and/or social harms and gender discrimination arising from SANBI’s activities Email:  [email protected]

RSA COVID-19 portal

STAY UP TO DATE

Email address:

Interests Succulent Karoo Programme CAPE Programme Biodiversity Science

• Conservation Enterprises
• Combating Wildlife Trafficking
• Marine Conservation and Sustainable Fisheries
• LAC Environment Private Sector Engagement
• LAC Environment Combating Conservation Crime

Biodiversity Integration Case Studies

This collection of 17 cases from the 2019 USAID Biodiversity Integration Case Study Competition illustrates how biodiversity conservation is critically linked to the journey to self-reliance—by reducing extreme poverty, increasing food security, improving human health, managing climate impacts, building resilience to recurrent crises, and achieving many other development objectives. Together, the cases provide a snapshot of how USAID Missions and implementing partners conceptualize, design, and implement cross-sectoral integration.

Each case describes a USAID activity and shares lessons learned and common tools used to advance integrated programming. Cases provide examples of different approaches to integration, including integrated geographies and/or funding streams, and situations in which funding from one sector generates benefits across sectors.

Advancing the Health of Gorillas and Humans: Population, Health, and Environment in Uganda

Protecting Ecosystem Goods and Services: Integrated Approach to Biodiversity Conservation in a Philippine Protected Area

Allies in Biodiversity Conservation: Integrating Indigenous Human Rights and Biodiversity Conservation in the Amazon

Local Communities Address Drivers of Biodiversity Loss: Iguana Habitat in the Dominican Republic-Integrating Biodiversity, Climate Risk Management, and Sustainable Landscapes

Recognizing Connections: Conserving Guatemala’s Biodiversity by Strengthening Governance

Incorporating Political and Economic Approaches: CARPE’s Longstanding Biodiversity Conservation Efforts

An Interdependent Vision: Conserving Biodiversity While Reducing Greenhouse Gas Emissions From Land Use Change In Indonesia

Coastal Resilience to Climate Change: Integrating Biodiversity, Adaptation, and Sustainable Landscapes in West Africa

Community Stewards of Natural Resources: Integrating Democracy, Human Rights, and Governance with Sustainable Forest Management in Liberia

Turning to Science to Build Consensus: The Seasonal Fishing Closure in Balayan Bay, Philippines

Alternative Livelihoods Create Incentives for Stewardship: Sustainable Marine Resource Use for People in Eastern Indonesia

Supporting Beneficiaries in a Limited Funding Environment: Climate Change Adaptation and WASH Programming with Biodiversity Benefits in the Dominican Republic

Population, Health, and Environment: Integration of Health, Environment, and Development in the Lake Victoria Basin through the PHE Approach

Amazonia Verde: Productive Conservation in Amazonian Landscapes

A Coastal Community’s Persistence: Sustaining the Biodiversity, Climate, and Livelihoods Gains of Siete Pecados Marine Park, the Philippines

Wildlife and Communities Gain: Transforming Approaches to Conservation in Kenya

Enhancing Watershed Management: Integrated Water Resources Management in Nepal

Single Funded w/Co-benefits

Biodiversity

Climate Change

Democracy, Rights, and Governance

Economic Growth

Food Security

• USAID Flickr
• About BiodiversityLinks
• Learning and Evidence
• Accessibility

Companion Sites

• Conditions of Membership
• Privacy Policy
• Terms of Use

Explore USAID’s LINKS sites for learning and knowledge sharing

Achieving agriculture-led food security

BiodiversityLinks

Advancing biodiversity conservation

ClimateLinks

Improving climate change and development programming

Fostering resilient democratic societies

EducationLinks

Creating successful and effective education programs

GenderLinks

Promoting gender equality and integration

Globalwaters

Solving global water and sanitation challenges

Strengthening land tenure and property rights

Learning Lab

Maximizing development outcomes

Marketlinks

Sharing market-based solutions for development

ResilienceLinks

Helping communities withstand crisis and thrive

Supporting sustainable urban development

Sustainable Development Goals

• About the UCL SDG Initiative
• All UCL SDG case studies
• The SDGs and me

Evidence-based solutions to prevent biodiversity loss

UCL experts are studying some of world’s most precious ecosystems to understand how conservation interventions can help reduce the impacts of human activity on the world’s biodiversity.

8 October 2020

Biomes are large areas of interconnected ecosystems, ranging from aquatic to desert to tropical forest, which can be characterised by local climate and environmental conditions. Protecting these natural ecosystems is vital for a sustainable and resilient future planet. 

 “Complex ecosystems of vegetation and wildlife around the world are under pressure from human influences such as climate change and land management,” explains Professor Kate Jones (UCL Centre for Biodiversity and Environment Research, CBER), who is leading the Biome Health Project, in partnership with the World Wildlife Fund. The project is exploring the effects of human activities on four distinct biomes around the world: sub-tropical dry forest in Nepal; coral reefs in Fiji; tropical forest in Malaysian Borneo; and savanna grassland in Kenya. 

In collaboration with local partners, the team is designing a field-based study system that will help uncover how biodiversity responds to human influence, and how conservation activities can help reduce the impacts of these pressures. 

“ “Complex ecosystems of vegetation and wildlife around the world are under pressure from human influences such as climate change and land management.”  

“We’re using a range of technologies, such as camera traps, audio recordings and videos of underwater habitats, to monitor indicators of biodiversity at each location,” says Guilherme Braga Ferreira (UCL CBER), who is overseeing the data collection and analysis from the four field sites.  

The team chooses sites within each biome where the levels of human pressure vary and where conservation efforts are underway, to monitor how different species are responding to human activity at each field site.  

For example, preliminary data from the Maasai Mara National Park in Kenya, where the team are using a grid of camera traps and acoustic recording devices, suggest that grazing cattle have a negative impact on the number of buffalo and eland in the area, but beneficial effects on the number of smaller herbivores. 

“We are developing a framework that will help identify tipping points, where dramatic declines in biodiversity occur and offer evidence-based solutions to help halt biodiversity loss at these precious sites,” Professor Jones adds. 

Related links

>  Biome Health Project

Helping to achieve:

Goal 14: Conserve and sustainably use the oceans, seas and marine resources

Target 14.2  By 2020, sustainably manage and protect marine and coastal ecosystems to avoid significant adverse impacts, including by strengthening their resilience, and take action for their restoration in order to achieve healthy and productive oceans.

> UN SDG14: Life below water

View all UCL case studies for SDG14​ →

Goal 15: Sustainably manage forests, combat desertification, halt and reverse land degradation, halt biodiversity loss

Target 15.9  By 2020, integrate ecosystem and biodiversity values into national and local planning, development processes, poverty reduction strategies and accounts.

> UN SDG15: Biodiversity

View all UCL case studies for SDG15 →

Research outputs

View all UCL’s published research related to the SDGs.

UCL’s SDG research →

How are you making the world a better place?

Staff and student are encouraged to use this short form to tell us how your UCL activity is making the world a better place.

Submit your suggested activity →

About the UN's SDGs

Visit the UN website​ →

• Air quality
• Soil degradation
• Pests and weeds
• Reporting pollution
• Climate Change
• Communities
• Service providers
• Biodiversity legislation
• Conserving biodiversity
• Conservation programs
• Native animals
• Native vegetation
• Atlas of NSW Wildlife
• Geodiversity, karst and caves
• Landscapes and soils
• Threatened species
• Wildlife licences
• Protected areas
• How you can help
• Cultures and heritage of NSW
• Aboriginal heritage law reform
• State heritage
• Conservation
• Heritage registers
• Publications
• Ask Environment Line
• Nature Near Me
• Maps and data
• Statewide environmental reporting
• Knowledge strategy
• Public registers
• For business
• For state and local government
• For teachers, schools and community educators
• For catchment management authorities
• Obtaining information
• Our environmental performance
• Careers with us
• Events and activities
• Doing business with us
• Public consultation
• Grants and funding
• Legislation
• Parks and reserves around NSW
• Closures and alerts
• Things to do
• Camping and accommodation
• School excursions
• Conservation and heritage
• Volunteering

Nature Conservation

• Advisory Committees
• National Parks and Wildlife Advisory Council
• National parks consumer brand
• Performance
• Work as a ranger or field officer
• A family and community friendly workplace
• Commercial activities in parks
• OEH media releases
• Ministerial media releases
• Search media releases
• Video gallery
• Agency information guide
• Overseas travel reports
• Accessing personal information
• Responding to privacy decisions
• Requesting a review or lodging a complaint
• Disclosure log
• Tabled documents
• Office locations
• Get answers
• Report a problem
• Have your say
• Subscribe to newsletters
• Connect with us on social media
• Our website
• Privacy and security
• Copyright and disclaimer
• Aboriginal Lands Clean-Up Program
• About the Trust
• Grant locations
• Community recycling centres
• Eco schools
• Environmental Education
• Environmental Research
• More information for applicants
• Landfill Consolidation and Environmental Improvements
• Lead environmental community groups
• Major Resource Recovery Infrastructure
• Organics Collections
• Steam 1: Processing Infrastructure
• Stream 2: Business Organics Recycling
• Stream 3: Food Donation
• Stream 4: Product Quality
• Protecting our Places
• Recycling Innovation
• River Connections
• Waste grant programs
• Grant assessment process
• Funding acknowledgement
• Planning and reporting
• Financial reporting
• Learn from funded projects
• Major projects
• Bush Connect
• Community Bush Regeneration
• Emergency pollution clean-up
• Resource Recovery Facility Expansion and Enhancement
• Saving our Species Contestable Grants
• Saving our Species Partnership
• Annual reports
• Quarterly reports
• Sponsorship
• Green Globe Awards
• Legislation reviews
• Park policies
• Wildlife management

Avoiding and offsetting biodiversity loss - case studies

Introduction

The Department of Environment and Conservation NSW (DEC) often negotiates with landholders and developers to minimise the impact of development on biodiversity. If impacts are unavoidable, biodiversity offsets can be used to achieve environmental outcomes. A biodiversity offset is one or more appropriate actions that are put in place to counterbalance (offset) the impacts of development on biodiversity.

The following three case studies illustrate how DEC has worked with stakeholders to avoid, minimise or offset biodiversity losses:

• Wallarah Peninsula – avoiding and minimising impacts
• Karuah Bypass – offsetting habitat loss
• Federal Highway upgrade – offsetting impacts on threatened species .

The Wallarah Peninsula case study demonstrates a case where impacts could be avoided and minimised without resorting to biodiversity offsets. The developer recognised that biodiversity was an asset to the area and established an environmentally sensitive residential development.

In the case of the Karuah bypass, the Roads and Traffic Authority (RTA) acknowledged that it could not avoid, minimise and mitigate all the impacts on biodiversity on-site. The RTA provided 89 hectares of compensatory habitat to offset the loss.

In the Federal Highway upgrade project, the RTA purchased a property with a known population of Striped Legless Lizards and protected this land from development, to offset impacts on a smaller population at another location.

Whilst these case studies demonstrate good outcomes, negotiating biodiversity offsets on a case-by-case basis can be resource intensive and slow, and there is potential for inconsistency in the process and outcome.

DEC proposes to develop a biodiversity offsets and banking scheme to:

• address the impacts of development on biodiversity values
• recognise the market values of biodiversity
• create new opportunities for conservation management on privately-owned land, to complement the State's national parks and other protected areas
• provide transparent, consistent assessment procedures and defined ecological principles for offsetting.

Back to top

Table 1: A comparison of case studies

Case study 1: Wallarah Peninsula

Wallarah Peninsula features approximately 600 ha of near undisturbed bushland. Its natural beauty and easy access to the beach and lake, along with its close proximity to Newcastle and Sydney, make it a very attractive place to live.

The landowner gained rezoning approval to develop the land as a residential area, by working with stakeholders to preserve the natural environment and maintain biodiversity.

The main stakeholders in the development process were the landowner and developer, the then NSW Department of Infrastructure, Planning and Natural Resources (now the NSW Department of Planning and NSW Department of Natural Resources) and Lake Macquarie City Council. The National Parks and Wildlife Service (NPWS, now part of DEC) assessed Aboriginal heritage and the ecological values of the site.

The land determines development

After negotiating, stakeholders agreed on issues concerning biodiversity, social equity, public access and commercial land development. A memorandum of understanding was drafted to define roles, recognise different interests and agree to transparency.

The developer's vision was to create a collection of villages where the lifestyle of the residents and the health of the environment had equal priority. The principles guiding development were ecological health, sustainable settlement, community lifestyle, and environmental stewardship.

Planning was dictated by the landscape rather than by a master planning document. The site was assessed to determine its capability to support different forms of development. In this sense, planning was literally from the ground up.

The environmental, geophysical and visual assets of the site were evaluated and development scenarios constructed. Maps were drawn showing areas where critical vegetation corridors and threatened species were located, areas that were generally suitable for development, areas that were suitable if various issues were managed, and areas that were unsuitable for development.

While there were patches of critical habitat all over the site, a boundary was defined that would consolidate a sustainable habitat. DEC officers evaluated the site and agreed that there was a long-term biodiversity outcome that could be protected in perpetuity within the boundaries.

An independent consultant assessed the site under a brief prepared by the council and the assessment studies were reviewed by stakeholders to ensure that the methodology was fair and reasonable.

Development with care

After the conservation area was identified and set aside, there was a need to establish conservation principles so the rest of the land would be treated equitably. A local environmental plan (LEP) was prepared to set out subdivision planning. Ecologically significant areas, threatened species and habitat protection areas were all mapped to determine where development could occur. A Conservation Land Use Management Plan was also attached to the land. All requirements were in a statutory package, giving the council and the community certainty about development outcomes.

Working together

While the development provided clear environmental benefits, it also protected the interests of the landowner. The developer carefully researched comparable developments and consumer choices to establish the commercial value of Wallarah Peninsula.

The rezoning negotiations took three years and the final agreed land use outcomes, captured in the statutory masterplan, took another two years. Although the planning process was costly, the developer recognised that the land included valuable assets from which to build commercial value.

The personal communication skills and patience of the people involved were also a major asset. Through collaboration, the stakeholders demonstrated that development and conservation outcomes can both be achieved and support each other. Together, the stakeholders created a niche development to generate acceptable returns.

The developer, DEC and the local council are continuing to work together on long-term environmental management, bushfire management, habitat protection, tourist facilities, access for services and educational programs.

Figure 1: Development philosophy for Wallarah Peninsula

Case study 2: Karuah bypass

As part of the Pacific Highway upgrade program, the RTA proposed to construct a 9.8 km section of dual carriageway around the town of Karuah.

The preferred route for the bypass was selected to avoid or minimise environmental impacts. Nevertheless, the environmental and species site assessments identified several potential environmental impacts. These included the removal of 47 hectares of vegetation, 16 of which were from the Karuah Nature Reserve which surrounds the town.

Land transferred to compensate for habitat loss

The RTA acknowledged that it could not avoid all the impacts on habitat or threatened species and a compensatory habitat package was developed. The NPWS (now DEC) sought an offset that would deliver an outcome of overall ecological gain rather than applying specific habitat ratios.

An 89 ha block of privately owned land was identified near the proposed road alignment. It contained similar vegetation and many threatened species affected by the road upgrade. The property had a shack on it and was being moderately grazed.

The NPWS agreed to incorporate the land into the adjacent Karuah Nature Reserve. The property would fill in a missing block and, because it would be in the reserve, could be managed simply and inexpensively.

The RTA purchased the land to transfer it to DEC. For the RTA to acquire the land, an Act of Revocation under the National Parks and Wildlife (Adjustment of Areas) Act 2001 had to be approved by Parliament.

Members of Parliament agreed that the 89 hectares being added to the nature reserve was of equivalent or better value than the 47 hectares of habitat being lost, that creating a larger contiguous block of habitat had significant biodiversity benefits, and that the management benefits of taking over the private block were worthwhile.

The RTA also agreed to contribute $15,000 towards initial management costs such as weed control and active rehabilitation.

Offsetting mangrove damage

The road project also affected mangroves and saltmarsh in Karuah River. The RTA negotiated with NSW Fisheries and the NSW Department of Planning for a compensatory habitat package which included protecting mangrove areas and cleaning up old oyster leases which were creating debris.

Mitigation measures used on the project

The RTA also installed mitigation measures to reduce the long-term impact of the upgraded highway, including:

• several dedicated fauna underpasses as well as combined drainage and fauna underpasses
• dry passage access for fauna under major bridge crossings
• floppy top fauna exclusion fencing along the boundary of Karuah Nature Reserve
• retaining native vegetation in the median strip to allow for glider access
• installing experimental rope ladder/tunnel 'glider crossings' at some points (video monitoring shows brush tailed possums and squirrel gliders investigating the structures, but it is unclear if they are using them to cross the road)
• replanting disturbed areas with native species
• installing fencing round threatened flora species to protect against accidental damage during construction.

Working with a construction contractor

During road construction, the contractors needed to use a small section of the newly acquired offset land for machinery storage and stockpiles. As compensation, the contractor agreed to use their labour and machinery to remove the shack on the property, some internal fencing, fruit trees and some old tyres. This cost the contractor very little, but provided a significant logistic benefit to them. It also assisted the NPWS by reducing the work needed to incorporate the property into the reserve.

Case study 3: Federal Highway upgrade

In 1997, the Federal Highway between Sutton and the ACT border required upgrading from a single to dual carriageway to deliver a safer road and reduce travel time between Sydney and Canberra.

The RTA conducted a flora and fauna assessment of the land proposed for the new development and found the vulnerable Striped Legless Lizard ( Delmar impar ) within the proposed road alignment, suggesting a larger population was likely to be in the area.

NPWS (now DEC) advised that destroying this habitat could have dire consequences for the population, and possibly push the Striped Legless Lizard to endangered status.

The RTA investigated options to avoid, minimise and mitigate potential impacts. Not proceeding with the upgrade was not an option for the community, and realigning the road would have been too expensive. As the loss of habitat was likely to have a significant impact on the surveyed population of lizards, offsetting was the last option.

Lizards found elsewhere

The aim of the offset was to compensate for unavoidable impacts on the local Striped Legless Lizard population and help maintain the viability of the species overall.

The only opportunity for an offset came from the results of a flora and fauna survey conducted for the Eastern Gas Pipeline. The survey discovered a large population of the lizards on a property near Cooma. It was the only other population found in NSW. The property was used for occasional sheep grazing and was of good quality native grassland. It also supported other threatened species such as the Grassland Earless Dragon ( Tympanocryptis pinguicolla ).

NPWS officers examined this property more closely and found a far larger population of lizards in this location than at the highway site. They were confident that protecting this property against development would be a highly effective offset arrangement because it would protect a known and apparently healthy population of the lizards.

The RTA bought the property to offset the impact of the road upgrade and passed it to the NPWS. Although this resulted in an ongoing management cost to the NPWS, the high biodiversity value made it worthwhile. However, the location of the offset is a considerable distance from the area impacted on by the highway and some genetic variation between populations in different locations may now be lost to the species.

A biodiversity benefit

Although a small area of habitat was removed by the development of the highway, the associated biodiversity offset enabled a larger more viable population of the Striped Legless Lizard to be protected elsewhere.

The biodiversity benefit was only possible because of the simultaneous discovery of a population of Striped Legless Lizards at a site unrelated to the highway project. It highlights the importance of sharing environmental information widely.

• Phone This field is for validation purposes and should be left unchanged.
• Climate Change
• Policy & Economics
• Biodiversity
• Conservation

Get focused newsletters especially designed to be concise and easy to digest

• ESSENTIAL BRIEFING 3 times weekly
• TOP STORY ROUNDUP Once a week
• MONTHLY OVERVIEW Once a month
• Enter your email *
• Comments This field is for validation purposes and should be left unchanged.

The Statistics of Biodiversity Loss [2020 WWF Report]

The Living Planet Report 2020 (LPR) shows us that global biodiversity loss is at its worst. In order to give better directions for allocating resources, a regional assessment was performed which we will distil for you in this article.

In the LPR 2020 , five major threat categories were used to illustrate the impacts that are driving biodiversity’s decline. Through this frame, governments and organisations can better come up with solutions or mitigations that are suitable for the ecosystems as well as the local communities.

Soure: Living Planet Report 2020, WWF.

The analysis was carried out for 5 regions: Europe and Central Asia, Asia Pacific, Latin America & Caribbean, Africa and North America. Taking species population as a measure, a significant loss in biodiversity was found in all regions, with encroachment on natural land identified as the most prominent threat to wildlife. Latin America & the Caribbean have sustained a loss of 94% since 1975.

Here, we will guide you through threats each region is facing and give some current examples.

North America

Source: WWF Living Planet Report 2020.

• Possible causes: Habitat loss, chemical pollution (pesticide) 
• Water level of the Great Lakes, biggest freshwater reservoir area in North America, at a historical low
• 30% of its plant-pollination network has disappeared

You may also like: Extreme Temperatures – Part III: Canada | Biodiversity Crisis: North America Lost 2.9 Billion Birds Since 1970

Europe and central asia.

• Only 23% of species and 16% of its habitats are in good health
• 1,677 out of 15,060 European species are threatened with extinction; most endangered are snails, clams and fish
• 6 animal, bird and fish species, including the Saiga antelope, the gyrfalcon and the Persian leopard, are facing risk of extinction in Russia

You may also like: Europe’s Most Invasive Species Identified- Study |  The UK is Failing to Protect its Biodiversity- Report .

Latin america & caribbean.

• Major negative trends observed in reptiles, amphibians and fish
• A type of chytrid fungus, which originated in Asia, has been causing declines in 500 amphibian species and driven around 90 of them to extinction
• 2019 record breaking dry seasons and forest fires lead to a surge in deforestation, with 30% more than the previous year

You may also like: Deforestation in Brazilian Amazon Soars to a 12-Year High

• The ecosystem provides livelihood for around 1.1 million locals
• 76% of endemic freshwater species in Lake Victoria are threatened with extinction
• Illegal hunting and mining have driven down the Grauer’s gorilla population in the Congo by 87% .

You may also like: Top Court in West Africa Finds Guinea Officials Guilty in Mine Conflict | A Planned Oil Drilling Project Threatens the Okavango Delta Ecosystem

Asia pacific.

Source: Living Planet Report 2020.

• Nearly 3 billion animals were killed or displaced by Australia’s devastating bushfire season of 2019 and 2020
• In India, 3% of bird species face extinction; 19% of amphibians are threatened or critically endangered; over 12% of wild mammal species are threatened with extinction
• More than 80% of East and Southeast Asia’s wetlands are classified as threatened due to human activity.

We are in a time of global upheaval, both politically, economically and in regards to our environment. The latter has not yet superseded the two former, but report like the LPR are driving a growing understanding on the gravity of the situation. Our life-support system, the world we live in, is in a critical state and to simply understand and acknowledge this is the first step.

You may also like: Australia Releases Report on 2020 Bushfires an biodiversity loss, Admitting That Climate Change Was the Driving Factor | WWF Releases ‘Emergency Action Plan’ To Save Chinese White Dolphins

This article was written by Wing Ki Leung. Photo by Warlen G Vasco on Unsplash .

You might also like: Impacts of Fast Fashion on the Environment

A Graphical History of Atmospheric CO2 Levels Over Time

11 Interesting Climate Change Facts

Is the Sahara Desert Growing?

Hand-picked stories weekly or monthly. We promise, no spam!

Boost this article By donating us $100, $50 or subscribe to Boosting $10/month – we can get this article and others in front of tens of thousands of specially targeted readers. This targeted Boosting – helps us to reach wider audiences – aiming to convince the unconvinced, to inform the uninformed, to enlighten the dogmatic.

Europe PMC requires Javascript to function effectively.

Either your web browser doesn't support Javascript or it is currently turned off. In the latter case, please turn on Javascript support in your web browser and reload this page.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Proc Natl Acad Sci U S A
• v.118(17); 2021 Apr 27

Impacts of biodiversity and biodiversity loss on zoonotic diseases

Felicia keesing.

a Program in Biology, Bard College, Annandale, NY, 12504;

Richard S. Ostfeld

b Cary Institute of Ecosystem Studies, Millbrook, NY, 12545

Author contributions: F.K. and R.S.O. designed research; F.K. analyzed data; and F.K. and R.S.O. wrote the paper.

Associated Data

All study data available from the supplemental material in Johnson et al. ( 21 ).

Zoonotic diseases are infectious diseases of humans caused by pathogens that are shared between humans and other vertebrate animals. Previously, pristine natural areas with high biodiversity were seen as likely sources of new zoonotic pathogens, suggesting that biodiversity could have negative impacts on human health. At the same time, biodiversity has been recognized as potentially benefiting human health by reducing the transmission of some pathogens that have already established themselves in human populations. These apparently opposing effects of biodiversity in human health may now be reconcilable. Recent research demonstrates that some taxa are much more likely to be zoonotic hosts than others are, and that these animals often proliferate in human-dominated landscapes, increasing the likelihood of spillover. In less-disturbed areas, however, these zoonotic reservoir hosts are less abundant and nonreservoirs predominate. Thus, biodiversity loss appears to increase the risk of human exposure to both new and established zoonotic pathogens. This new synthesis of the effects of biodiversity on zoonotic diseases presents an opportunity to articulate the next generation of research questions that can inform management and policy. Future studies should focus on collecting and analyzing data on the diversity, abundance, and capacity to transmit of the taxa that actually share zoonotic pathogens with us. To predict and prevent future epidemics, researchers should also focus on how these metrics change in response to human impacts on the environment, and how human behaviors can mitigate these effects. Restoration of biodiversity is an important frontier in the management of zoonotic disease risk.

A Confusing Role for Biodiversity in Pathogen Transmission?

Thousands of pathogens circulate in the human population; hundreds of these are bacteria ( 1 ), hundreds more are viruses ( 2 ); a smaller but still sizeable number are fungi ( 3 ). Many of these infectious agents circulated first in other vertebrate animals, such as mammals and birds. In their original host species, the microbes might have lived without harming their hosts, or they might have caused disease. Regardless, at some point they spilled over into humans and began causing illness.

The transfer of microbes from animals to humans has occurred across millennia. Some of these microbes caused the scourges of our ancestors, from plague to smallpox to tuberculosis ( 4 ). More recently, humans have confronted AIDS, Ebola, severe acute respiratory syndrome (SARS), and Middle East respiratory syndrome (MERS). These so-called zoonotic diseases, which result from cross-species transmission of pathogens between humans and other vertebrate animals, appear to be emerging more frequently ( 5 ). Certainly, the COVID-19 pandemic has made the risks of zoonotic diseases a vivid and harrowing reality for every person on Earth.

Until recently, habitats with naturally high levels of biodiversity were thought to serve as hotspots for the emergence of new zoonotic pathogens, presenting a hazard to humans ( 5 , 6 ). This expectation was based on the assumptions that a diversity of free-living organisms leads to a diversity of pathogens, and that pathogen diversity per se is a risk factor for zoonotic emergence ( 7 ). But for decades, we have also known that under some conditions, high biological diversity can decrease the transmission of zoonotic diseases that have already become established ( 8 , 9 ). Taken together, these conflicting findings appeared to mean that the loss of natural biodiversity could simultaneously increase human exposure to existing pathogens, and decrease the probability of the emergence of new ones. Such a potential contradiction has complicated the ability of scientists to provide useful information about diversity–disease relationships for public policy and management.

Here, we evaluate recent evidence indicating how biodiversity affects both the emergence of new zoonotic diseases and the transmission of established ones. We first explore the effects of overall biodiversity, versus the biodiversity of particular taxa, on the emergence of zoonotic pathogens. We then review recent studies addressing whether some taxa are more likely to serve as sources of zoonotic pathogens. We consider how changes in biodiversity, especially changes arising from anthropogenic impacts, affect community composition relevant to disease dynamics. Finally, we evaluate whether recent evidence allows the effects of biodiversity, particularly its loss, on pathogen emergence to be reconciled with their effects on subsequent transmission.

Biodiversity as a Source of Zoonotic Pathogens

Animals share their pathogens with us the same ways that humans share their pathogens with each other. A pathogen might travel from one host to another in droplets or aerosols from coughs or sneezes; through blood, urine, saliva, or other bodily fluids; through fecal material; or by being transferred during the bite of a vector like a fly, mosquito, or tick. In some cases, the pathogen might linger on a surface or in the environment so that a human might encounter the pathogen without close proximity to the animal that was its source. The pathogen might not be able to infect the human it contacts. Even if it can, the person’s immune system might stop the pathogen before it causes harm. But in some cases, the pathogen is able to infect the new human host, and that person might in turn transmit the pathogen to others.

What factors determine whether a pathogen will spill over from an animal into a human host and become established? Cross-species transmission results from a complex interplay between the characteristics of the pathogen ( 2 , 10 – 12 ): the original host’s infection, behavior, and ecology; how the pathogen is shed into and survives in the environment; how humans are exposed to the pathogen; and how susceptible those humans are to infection ( 4 , 12 – 16 ).

Natural biodiversity, and its loss, can affect this pathway at multiple points, potentially affecting the probability that a new pathogen will become established in humans. Most importantly, diverse communities of host species can serve as sources for new pathogens, and it is this role for biodiversity that has received the most attention in research on disease emergence. In the most common conceptual model linking biodiversity to disease emergence, biodiversity is made up of species that host a diversity of pathogens ( SI Appendix ), any one of which could have the characteristics enabling it to jump successfully into humans ( Fig. 1 A ) ( 7 ). Implicit in this model focusing on total host diversity is the assumption that all taxa are equally likely to be sources of zoonotic pathogens. Alternatively, certain groups—such as bats, rodents, or livestock—might be significantly more likely to serve as sources of zoonotic pathogens. In this “zoonotic host diversity” model, the diversity of these hosts, but not total host biodiversity, would be most important in determining the probability of zoonotic emergence ( Fig. 1 B ).

Alternative conceptual models linking host biodiversity to zoonotic emergence in humans. ( A ) Total host diversity: In this model, the overall diversity of hosts leads to a pool of pathogens, any one of which could jump to humans. Research assuming this model typically involves comparisons of large geographic areas with innate variation in biodiversity (e.g., along latitudinal gradients or between countries). ( B ) Zoonotic host diversity: In this model, some species are more likely to host zoonotic pathogens, and it is the diversity of these zoonotic hosts that is most important in determining the risk of zoonotic emergence. Research using the zoonotic host diversity model typically focuses on the distribution or characteristics of a particular taxon (e.g., bats or primates). ( C ) Zoonotic host diversity and abundance: In this model, the diversity and the abundance of zoonotic hosts determine the risk of zoonotic emergence. Research using this model typically focuses on the effects of changes in natural biodiversity (e.g., through human impacts, on zoonotic pathogens). Modified from an illustration in Ostfeld and Keesing ( 7 ).

Researchers explicitly or implictly applying the “total host diversity” model ( Fig. 1 A ) tend to conduct broad geographic comparisons across regions that differ in their innate levels of biodiversity. For example, in a seminal study, Jones et al. ( 5 ) identified zoonotic diseases that had emerged between 1940 and 2005, and mapped the most likely locations of their underlying emergence. After attempting to correct for potential spatial variation in reporting bias, Jones et al. compared a suite of variables to see which best predicted the locations of global zoonotic hotspots. Although zoonotic diseases arising from wildlife were only ∼1% more likely to emerge where the diversity of wild mammals was high, Jones et al. ( 5 ) concluded that “wildlife host species richness is a significant predictor for the emergence of zoonotic EIDs [emerging infectious diseases] with a wildlife origin, with no role for human population growth, latitude or rainfall.” Of note was their observation that high human population density increased the likelihood of the emergence of a zoonotic disease from wildlife by 75 to 90%, an effect almost two orders-of-magnitude greater than the effect of mammalian diversity. Allen et al. ( 17 ) expanded this analysis, incorporating more explanatory variables and new methods for estimating reporting bias. After correcting for reporting bias, they found that mammal species richness had only the fourth strongest influence on the distribution of emerging infectious diseases, after the presence of evergreen broadleaf trees first, human population density second, and climate third.

A study by Pedersen and Davies ( 18 ) exemplifies research underlain by the “zoonotic host diversity” model ( Fig. 1 B ), in which some taxa are expected to more frequently be sources of zoonotic pathogens. Pedersen and Davies focused on primates. They divided the process of spillover into a new host species into three steps—opportunity, transmission, and establishment—each of which has specific drivers. Their first step, the opportunity for transmission, is underlain by the biogeography of host and pathogen. Their analysis rested on the assumption that step 3—establishment—is critical, and that it is strongly affected by ecological and evolutionary barriers between the current host species and a new host species. For this reason, they assumed that host species that are more closely related to humans will be the most likely sources for pathogens that can become zoonotic. Thus, Pedersen and Davies focused on primates, categorizing the risk of zoonotic spillover based on phylogenetic relatedness and geographic co-occurrence of primates worldwide. They found a hotspot for probable zoonotic spillover in central and western Africa, for example, because there is broad geographic overlap between humans and primate species to which humans are particularly closely related. Identifying the geographic locations or characteristics of taxa most responsible for zoonotic pathogens has been a focus of many recent studies (e.g., refs. 10 , 11 , and 19 – 23 ).

In the “zoonotic host diversity and abundance” model, both the diversity and the abundance of the animals most likely to act as hosts for zoonotic pathogens are critical ( Fig. 1 C ). Thus, both the “zoonotic host diversity” and “zoonotic host diversity and abundance” models ( Fig. 1 B and C ) rely on weighting the importance of particular components of biodiversity by their zoonotic potential. To address whether this additional information is essential, we next review evidence addressing whether some taxa are more likely than others to serve as sources of zoonotic pathogens.

Are Some Taxa More Likely to Transmit Zoonotic Pathogens?

The identity of the taxa most likely to serve as sources of zoonotic pathogens has been a major area of research. Using a database of ∼800 zoonotic pathogens, for example, Woolhouse and Gowtage-Sequeria ( 24 ) identified “ungulates” (a paraphyletic grouping that includes hooved mammals from two mammalian Orders) and Carnivores as the sources of the greatest numbers of zoonotic pathogens, with bats hosting the fewest. At about the same time, Dobson ( 25 ) and Calisher et al. ( 26 ) highlighted the importance of bats, a taxon that has been the focus of many subsequent studies ( 11 , 27 ). In recent analyses, rodents have also emerged as the most likely source ( 21 , 23 ) or one of the most likely ( 11 , 27 ).

Why does it matter whether we can identify certain taxa as more likely zoonotic sources than others? Such knowledge might narrow research focus from studies of total biodiversity to more relevant studies on specific taxa, thereby allowing targeted surveillance of particular high-risk groups or locations. For example, Han et al. ( 22 ) identified traits associated with rodents that are zoonotic hosts compared to rodents that are not, leading to predictions about particular rodent species that might harbor undetected zoonotic pathogens. Such knowledge might also provide important insights about policy or management ( Fig. 2 ).

Relative importance of five major mammalian Orders as hosts of zoonotic viruses based on different metrics. ( A ) Mean number of viruses per host for all species in the Order. ( B ) Mean number of viruses per host for species that host at least one virus. ( C ) Proportion of all species that host at least one virus. ( D ) Total number of species in the Order that host at least one virus. The variety of metrics used in different studies is a source of confusion in competing claims about taxonomic importance. Plotted from data made available in the supplemental material from Johnson et al. ( 21 ); see caveats about these and similar data in SI Appendix .

Recent work on animal sources of zoonotic pathogens has focused on viruses because these have been identified as the pathogens most likely to cause emerging zoonotic diseases ( 5 ). Johnson et al. ( 21 ) compiled a database of 142 zoonotic viruses and determined that the Order Rodentia is the source for two-thirds of the viruses originating from mammals, more than any other Order. From this analysis, bats (Order Chiroptera) host the second greatest number of viruses, with Carnivora (e.g., dogs and cats), Cetartiodactyla (mostly hooved mammals like sheep, cows, and deer), and Primates having comparatively high numbers of viruses relative to their diversity (but see Fig. 2 ). Mollentze and Streicker ( 28 ) compiled a larger database of viruses that are both zoonotic and nonzoonotic, and that infect both mammals and birds. They concluded that mammalian and avian Orders have the number of zoonotic viruses that would be expected based on each group’s share of diversity, and that no special characteristics of a group (e.g., immunological traits) need to be invoked to explain a group’s zoonotic contributions. Like Johnson et al. ( 21 ), Mollentze and Streicker ( 28 ) identify rodents as the group hosting the greatest number of zoonotic viruses.

An important theme about zoonotic hosts has been the role of domesticated species. For example, domesticated species have been proposed to be optimal “bridge hosts” (in the sense of refs. 29 and 30 ) for zoonotic pathogens, meaning that they can acquire pathogens from wild hosts that they then transmit to humans through proximity, density, and contact frequency. Including variables to attempt to account for reporting bias, Johnson et al. ( 21 ) found that domesticated species from across mammalian Orders, especially Cetartiodactyla and Carnivora, hosted on average 100 times as many viruses per species as their wild counterparts did. Wells et al. ( 31 ) used a more expansive definition of domesticated animals that included common commensal rodent species, such as house mice ( Mus musculus ) and rats ( Rattus norvegicus , Rattus rattus ). They included both viruses that are known to be zoonotic ( n = 138 viruses) and those that are not ( n = 1,647). Based on patterns of shared viruses, domesticated species had significantly higher centrality—an index of the degree to which that species is connected to other host species—than wild species did. Wardeh et al. ( 19 ) found that domestication status was a strong predictor of whether a species shares pathogens with humans. Johnson et al. ( 32 ) came to a different conclusion about the role of domesticated species, concluding that wild species were significantly more likely to have been the source of spillover events. Rodents, for example, were determined to be the source for 58% of the 95 zoonotic viruses in their analysis.

Although different research groups draw different conclusions regarding which vertebrate taxa are more likely to transmit pathogens to humans, the evidence for unequal impacts among the taxonomic groups is strong. Five Orders of mammals (Primates, Cetartiodactyla, Carnivora, Rodentia, and Chiroptera) are the most common sources. This evidence strongly reduces the appropriateness of the “total host diversity” model and increases that of the two models that focus on zoonotic host diversity ( Fig. 1 ).

Johnson et al. ( 21 ) and Wells et al. ( 31 ) conducted their analyses with data that included hosts known to have been infected with a particular virus, and for which there was some evidence that they could share the pathogen with humans ( SI Appendix ). However, they did not attempt to identify the species that served as the original transmitter of the pathogen to humans: that is, the source of the primary spillover event that first resulted in a human infection. Instead, they focused on secondary spillover to humans, which can occur when the original host of the pathogen transmits to another host, which then transmits infection to humans, or when there is reciprocal transmission between humans and other animals. Making a distinction between primary and secondary spillover is difficult. Most pathogens that spill over to humans have broad host ranges ( 24 , 30 , 32 , 33 ), so identifying a single species or taxon as the primary source is problematic. In practice, the primary source of a zoonotic pathogen is rarely identified definitively. For example, the primary source of SARS-CoV-2, which causes COVID-19, has not been identified. Relatives of the virus, with genetic similarities to SARS-CoV-2 in the high 90% range, have been found in horseshoe bats and pangolins ( 34 , 35 ), but the only nonhuman animals currently known to host SARS-CoV-2 are those to which humans have transmitted it, either intentionally or unintentionally. These species include tigers ( Panthera tigris ), lions ( Panthera leo ), minks ( Neovison vison ), rhesus macaques ( Macaca mulatta ), and Siberian hamsters ( Phodopus sungorus ) ( 34 , 36 ). Of these, at least minks appear to be able to transmit SARS-CoV-2 back to humans ( 37 ), so they could be considered a secondary spillover host, but they were not the primary spillover host. Most analyses of spillover focus on secondary spillover hosts like minks rather than primary spillover hosts, though this distinction is rarely explicit.

How Human Impacts Influence Zoonotic Hosts

Human impacts like land-use change have been linked to emerging infectious diseases of humans in many studies (e.g., refs. 5 , 8 , 29 , 38 , and 39 ). Murray and Daszak ( 38 ), for example, explored how land-use changes, like deforestation and agricultural conversion, could affect the emergence of zoonotic viruses and presented two hypotheses. In one, land-use change increases contact between humans and a pool of diverse pathogens, without directly affecting the pool of pathogens. In the other, land-use change perturbs ecological communities, affecting zoonotic host species, such as rodents or bats, resulting in changes to cross-species transmission rates. These hypotheses are not mutually exclusive. Species that thrive in human-impacted habitats could provide opportunities for spillover based on both the diversity of their potential pathogens and their abundance, which might result in greater contact with humans ( Fig. 1 C ). Simultaneously, human activity in these altered habitats could affect contact rates.

Johnson et al. ( 21 ) found that 11% of 5,335 wild terrestrial mammal species were hosts of zoonotic viruses and most of these hosted only one such virus. Species that host zoonotic pathogens were more likely to be of lower conservation concern (e.g., they were more abundant) than species that do not ( Fig. 3 ). Their results suggest that zoonotic host status in mammals may be positively correlated with resilience to human impacts, such as land conversion, direct exploitation (e.g., hunting, trade), pollution, and the spread of invasive species.

Proportion of species in each conservation category for nonhosts, hosts, and superhosts in the five Orders of mammals that host the majority of zoonotic viruses. “Non-hosts” harbor no known zoonotic viruses, “Hosts” harbor one to two, and “Super-hosts” harbor three or more. For all five Orders, hosts and superhosts are more likely to be in the conservation category of least concern. Plotted from data made available in supplementary materials from Johnson et al. ( 21 ); see caveats about these and similar data in SI Appendix . Species for which data needed to assign a conservation status were unavailable have been excluded.

Gibb et al. ( 40 ) directly analyzed the effect of human impacts on host diversity and abundance. By combining multiple databases, they compiled a catalog of 6,801 ecological assemblages and 376 host species to ask whether zoonotic host species were more diverse or abundant, or both, in habitats intensively used or managed by humans. After controlling for research effort, they found that wild species known to be zoonotic hosts were more abundant and more diverse (as measured by species richness) in human-impacted habitats compared to less disturbed habitats. In contrast, wild species not known to be zoonotic hosts declined in diversity and abundance in human-impacted habitats. Mendoza et al. ( 41 ) came to a similar conclusion using a smaller dataset of ecological communities and zoonotic hosts.

Because the evidence linking hosts and pathogens in Gibb et al. ( 40 ) varied in quality, they reran their analyses on mammals using only host–pathogen associations for which they had a more rigorous metric, such as PCR detection of the pathogen or known reservoir status. Their conclusions remained unchanged.

Gibb et al. ( 40 ) provide evidence that the diversity and abundance of animals in human-impacted habitats shifts toward species that are more likely to be competent zoonotic hosts ( SI Appendix ). There is less evidence evaluating the effect of host abundance on emergence, but some studies suggest abundance is a key factor (e.g., ref. 42 ). The “zoonotic host diversity and abundance” model thus appears to be more realistic than the model that considers only “zoonotic host diversity”, and it is far more appropriate than the “total host diversity” model ( Fig. 1 ).

Reconciling the Role of Biodiversity in Emergence and Transmission

The analyses by Gibb et al. ( 40 ) and Johnson et al. ( 21 ) set the stage for a new understanding of the role of biodiversity, and changes to biodiversity, in the emergence and transmission of zoonotic diseases. Two decades ago, we proposed that innate biodiversity can reduce the risk of infectious diseases through a dilution effect, in which species in diverse communities dilute the impact of host species that thrive when diversity declines ( 43 ). In the years since, this phenomenon has been explored, debated, and reviewed ( 8 , 9 , 44 – 47 ), its mechanisms delineated ( 48 ) and explored ( 49 – 52 ), and its most basic principles regularly reexamined ( 53 ).

The dilution effect occurs when the transmission of a pathogen ( SI Appendix ) increases as diversity declines, as has been demonstrated for a number of disease systems. For example, in a series of comparative and experimental studies, Pieter Johnson and his colleagues ( 54 , 55 ) have shown that the most competent reservoir species for a trematode parasite of amphibians, Ribeiroia ondatrae , is the Pacific tree frog, Pseudacris regilla . The frogs are also the species most likely to thrive as diversity declines in the ponds in which they live, which results in increased transmission of the parasite ( 54 , 55 ). Similar examples are found in both plant and wildlife disease systems ( 45 ). One major question has been whether the dilution effect operates for zoonotic diseases. An early metaanalysis suggested that it did not ( 56 ). However, a larger metaanalysis found that the dilution effect was as strong for zoonoses as for other types of diseases ( 9 ), a conclusion that was robust to criticisms from the authors of the earlier study ( 57 , 58 ).

Despite abundant evidence for the dilution effect, the more general idea that biodiversity can reduce human disease risk has been controversial ( 47 , 59 ), in large part because biodiversity was thought to be a source of new zoonotic pathogens via spillover (in the sense of Fig. 1 A ) ( 5 , 8 , 17 , 47 ). The conflation of the effects of native biodiversity and the effects of the loss of biodiversity was also problematic, as described below. And much of the confusion arose because the process of zoonotic spillover was treated as distinct from the process of transmission once a zoonotic disease had already spilled over and become endemic.

Reconciling the effects of biodiversity on emergence and ongoing transmission requires acknowledging three critical points. First, most zoonotic pathogens are harbored by multiple host species ( Fig. 4 ) that share the pathogen via cross-species transmission. Second, the emergence of a pathogen in a new host species, including humans, is just a special case of cross-species transmission. And finally, transmission from a current host to a potential new one, human or otherwise, is affected by the degree to which the current host actually transmits the pathogen ( SI Appendix ), which in turn is affected by the current host’s abundance, infectiousness, and infection prevalence ( 60 ). The majority of spillover studies have not included quantitative measures of transmission, relying instead on databases compiled from qualitative host–pathogen associations.

The paradigm and the reality for research on spillover of zoonotic pathogens into humans. ( A ) The paradigm emphasizes a single animal host species for a zoonotic pathogen and an original spillover event, though the event and the species are rarely identified. ( B ) In reality, most zoonotic pathogens have multiple host species whose specific roles in transmission to and from humans are rarely known. ( C ) The number of viral zoonotic diseases that have 1, 2 to 5, 6 to 10, or 11+ known animal host species other than humans. Plotted from data made available in supplementary materials from Johnson et al. ( 21 ); see caveats about these and similar data in SI Appendix .

Plourde et al. ( 61 ) illustrate the potential of unifying spillover and transmission, and of relying on more quantitative metrics. They compiled a database of 330 zoonotic and nonzoonotic disease systems with pathogens that infect multiple host species and in which reservoir species ( SI Appendix ) are established or strongly implicated. Reservoir status is a more meaningful metric than the host–pathogen associations used in most spillover studies because it signifies transmission. Reservoirs for pathogens that cause diseases in humans were most commonly found in the Orders Rodentia (36%), Carnivora (25%), and Artiodactyla (21%) ( 61 ). Bats were reservoirs for only 8 (3%) of 261 disease systems, although 5 of these were high-priority zoonotic pathogens (based on an index of the number of publications about them). The most common reservoir hosts for zoonotic disease systems were commensal and domestic species, such as rats, dogs, cats, cattle, pigs, sheep, and goats.

Plourde et al. ( 61 ) found that reservoirs have significantly “faster” life histories—including shorter gestation periods, larger litters, lower neonate body mass, and younger age at sexual maturity—compared to nonreservoirs ( 62 ). Species with faster life histories have emerged as important from studies using other methods as well. Han et al. ( 22 ) found a similar pattern in rodents using host-pathogen associations for zoonotic diseases. Huang et al. ( 63 ) compared quantitative measures of transmission for three zoonotic diseases and found that hosts with the fastest life histories were more likely to transmit pathogens.

Why might life-history traits be related to the potential for a host to transmit a pathogen? A variety of studies suggest a tradeoff in investment in innate versus adaptive immunity, with shorter-lived species investing more in the former while longer-lived species invest more in the latter ( 64 ). Hosts that mount a weaker adaptive immune response (i.e., shorter-lived species) are thought to be more likely to maintain higher infectiousness, with an associated increase in transmission, as compared to hosts with stronger adaptive immunity. Previtali et al. ( 51 ) tested this idea by comparing immune responses among rodents that varied in life-history traits. They found that species with faster life histories mounted stronger innate immune responses, measured by bacterial killing capacity, compared to closely related species with slower life-history traits. These species also mounted weaker adaptive immune responses, measured by their antibody responses to a lipopolysaccharide challenge. Species with faster life histories were more likely to transmit Borrelia burgdorferi , the pathogen that causes Lyme disease in humans. Together, these results suggest a mechanism by which life-history strategies might be linked to the probability that a host species transmits a pathogen. Further evidence for a relationship between immune investment and host status is suggested by Gibb et al. ( 40 ), who found that mammal species that harbor a greater number of pathogen species are more abundant in human-impacted habitats. They conclude that there may be mammalian traits that impact both tolerance to human disturbance and tolerance to infection.

Quantifying differences between species in the ability to transmit zoonotic pathogens, and in the life-history and immunological traits associated with these abilities, facilitates the understanding of diversity–disease relationships. Because host species with fast life histories appear to be more likely to transmit pathogens, whether to species that are already hosts or to new hosts, including humans, zoonotic emergence, and transmission should be highest where hosts with fast life histories are abundant. Predicting the locations where these taxa thrive, and thus where transmission and emergence are likely, requires integrating what we know about biodiversity loss in natural ecosystems.

Impacts of Biodiversity Loss on Zoonotic Diseases

When biodiversity is lost from ecological communities, the species most likely to disappear are large-bodied species with slower life histories (e.g., ref. 65 ), while smaller-bodied species with fast life histories tend to increase in abundance (e.g., ref. 66 ). Recent research shows that fast-lived species are more likely to transmit zoonotic pathogens ( 61 ). Together, these processes are likely to lead to increases in the abundance of zoonotic reservoirs when biodiversity is lost from ecological systems.

Supporting these predictions, Johnson et al. ( 21 ) found that mammalian hosts of zoonotic viruses are less likely to be of conservation concern ( Fig. 3 ). For both mammals and birds, Gibb et al. ( 40 ) linked land-use changes caused by humans to increases in the abundance of zoonotic host species. They also report that declines in diversity of nonhosts are correlated with increases in the abundance and diversity of hosts, but they do not report whether there are net changes in overall biodiversity. A rich literature on infectious diseases of wildlife, livestock, and plants demonstrates increased pathogen transmission when biodiversity is lost from some ecological communities ( 9 , 53 ), supporting the generality of this relationship across nonzoonotic disease systems as well.

Concluding Remarks

Recent research has begun to reconcile the perceived conflict between the beneficial effects of maintaining natural biodiversity, through the dilution effect, with its purported costs as a source for new human pathogens. Cross-species transmission of pathogens to humans is a special case of an ongoing process that occasionally results in successful spillover into a new species, human or otherwise. Those pathogens that do spill over to infect humans—zoonotic pathogens—appear to be most likely to come from particular taxa, which often proliferate as a result of human impacts.

While the taxonomic group determined to be most responsible for zoonotic pathogens varies between studies, certain taxa—rodents, bats, primates, (cet)artiodactyls, and carnivores—consistently arise as the most important of the mammals. Given this knowledge, it is time to explore which metrics of host contributions are most useful for predicting and preventing spillover ( SI Appendix ) rather than continuing to debate the prime importance of one taxon or another. Because most pathogens that jump to humans have multiple nonhuman hosts ( Fig. 4 ), it is time for the scientific community to at last put to rest the myth of there being “a reservoir” for most pathogens ( 67 ). Furthermore, domesticated and commensal species from across these taxonomic categories often serve as critical hosts, whether as the original source of a pathogen or as a secondary host with elevated contact with humans. It is time to focus on rigorous assessments of the relative contributions of changes in human behavior versus changes in ecological communities, and of their synergies.

Going forward, we need to acknowledge that the “total host diversity” model ( Fig. 1 A ) is no longer adequate or appropriate given what we have learned over the past decade about the emergence and transmission of zoonotic pathogens. Instead, we need to focus on gathering and analyzing data that are relevant to transmission—data on the diversity, abundance, and capacity to transmit of the taxa that actually share zoonotic pathogens with us ( Fig. 1 C )—rather than continuing to succumb to the allure of readily available low-quality data and overly simple conceptual models. Certainly, we need more data on the effects of the abundance of hosts on zoonotic emergence, which will allow us to more confidently evaluate the “zoonotic host diversity” model versus the “zoonotic host diversity and abundance” model ( Fig. 1 ). And we need to disentangle the effects of the innate characteristics of host species (such as their immune strategies, resilience to disturbance, and habitat preferences) from the effects of human behaviors (including management of domesticated species), which affect contact rates and other important factors in transmission.

Efforts to understand the role of biodiversity in zoonotic diseases should also clearly distinguish between the effects of natural levels of biodiversity and the effects of changes to this diversity, for example, through human impacts ( 53 ). Geographic comparisons through large-scale correlational studies (based on the “total host diversity” model in Fig. 1 ) have tended to report a weak but positive effect of mammal species richness on zoonotic diseases, but these studies show much stronger positive correlations with other factors, such as human population density (e.g., refs. 5 and 17 ). In contrast, biodiversity loss has been shown to often increase the risk of zoonotic diseases, for example, through the dilution effect ( 9 ). This distinction takes on particular importance in the context of policy and management because biodiversity loss can be addressed by human actions, however difficult this might be, while latitudinal gradients in diversity, for example, cannot be. Determining how different anthropogenic impacts (e.g., habitat conversion, climate change, overharvesting) affect zoonotic hosts is an important area of future research and has great promise, as recent research has demonstrated ( 21 , 40 ).

Many other questions remain as well, including how best to gather data on the relative contributions of hosts for zoonotic pathogens and whether restoring biodiversity to areas degraded by human impacts reduces the abundance of zoonotic hosts. Understanding the factors that contribute to zoonotic disease emergence and transmission has never been more urgent, nor have the costs of failing to address them ever been more apparent.

Supplementary Material

Supplementary file, acknowledgments.

This research was supported by NSF Grant OPUS 1948419 (to F.K.).

The authors declare no competing interest.

This article is a PNAS Direct Submission.

This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2023540118/-/DCSupplemental .

Data Availability

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• My Bibliography
• Collections
• Citation manager

Save citation to file

Email citation, add to collections.

• Create a new collection
• Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed.

• Search in PubMed
• Search in NLM Catalog
• Add to Search

Saving wild tigers: a case study in biodiversity loss and challenges to be met for recovery beyond 2010

Affiliation.

• 1 Smithsonian Conservation Biology Institute, National Zoological Park, Washington, DC, USA.
• PMID: 21392347
• DOI: 10.1111/j.1749-4877.2010.00214.x

Wild tigers are being annihilated. Tiger range countries and their partners met at the 1st Asian Ministerial Conference on Tiger Conservation in January 2010 to mandate the creation of the Global Tiger Recovery Program to double the number of tigers by 2022. Only 3200-3600 wild adult tigers remain, approximately half of the population estimated a decade ago. Tigers now live in only 13 countries, all of which are experiencing severe environmental challenges and degradation from the effects of human population growth, brisk economic expansion, rapid urbanization, massive infrastructure development and climate change. The overarching challenge of tiger conservation, and the conservation of biodiversity generally, is that there is insufficient demand for the survival of wild tigers living in natural landscapes. This allows the criminal activities of poaching wild tigers and their prey and trafficking in tiger derivatives to flourish and tiger landscapes to be diminished. The Global Tiger Recovery Program will support scaling up of practices already proven effective in one or more tiger range countries that need wider policy support, usually resources, and new transnational actions that enhance the effectiveness of individual country actions. The program is built on robust National Tiger Recovery Priorities that are grouped into themes: (i) strengthening policies that protect tigers; (ii) protecting tiger conservation landscapes; (iii) scientific management and monitoring; (iv) engaging communities; (v) cooperative management of international tiger landscapes; (vi) eliminating transnational illegal wildlife trade; (vii) persuading people to stop consuming tiger; (viii) enhancing professional capacity of policy-makers and practitioners; and (ix) developing sustainable, long-term financing mechanisms for tiger and biodiversity conservation.

© 2010 ISZS, Blackwell Publishing and IOZ/CAS.

PubMed Disclaimer

Similar articles

• Sumatran tiger (Panthera tigris sumatrae): a review of conservation status. Wibisono HT, Pusparini W. Wibisono HT, et al. Integr Zool. 2010 Dec;5(4):313-323. doi: 10.1111/j.1749-4877.2010.00219.x. Integr Zool. 2010. PMID: 21392349 Review.
• Developing a national tiger action plan for The Union of Myanmar. Lynam AJ, Khaing ST, Zaw KM. Lynam AJ, et al. Environ Manage. 2006 Jan;37(1):30-9. doi: 10.1007/s00267-004-0273-9. Environ Manage. 2006. PMID: 16362487
• Tracking changes and preventing loss in critical tiger habitat. Joshi AR, Dinerstein E, Wikramanayake E, Anderson ML, Olson D, Jones BS, Seidensticker J, Lumpkin S, Hansen MC, Sizer NC, Davis CL, Palminteri S, Hahn NR. Joshi AR, et al. Sci Adv. 2016 Apr 1;2(4):e1501675. doi: 10.1126/sciadv.1501675. eCollection 2016 Apr. Sci Adv. 2016. PMID: 27051881 Free PMC article.
• Securing a future for wild Indochinese tigers: Transforming tiger vacuums into tiger source sites. Lynam AJ. Lynam AJ. Integr Zool. 2010 Dec;5(4):324-334. doi: 10.1111/j.1749-4877.2010.00220.x. Integr Zool. 2010. PMID: 21392350 Review.
• Forecasting effects of transport infrastructure on endangered tigers: a tool for conservation planning. Carter NH, Pradhan N, Hengaju K, Sonawane C, Sage AH, Grimm V. Carter NH, et al. PeerJ. 2022 May 17;10:e13472. doi: 10.7717/peerj.13472. eCollection 2022. PeerJ. 2022. PMID: 35602904 Free PMC article.
• Community attitudes towards Amur tigers (Panthera tigris altaica) and their prey species in Yanbian, Jilin province, a region of northeast China where tigers are returning. Li Y, Powell J, Jin A, Ryoo HK, Li H, Pandey P, Zhu W, Li D, Lee H. Li Y, et al. PLoS One. 2022 Oct 27;17(10):e0276554. doi: 10.1371/journal.pone.0276554. eCollection 2022. PLoS One. 2022. PMID: 36301816 Free PMC article.
• Chromosome-scale genomes reveal genomic consequences of inbreeding in the South China tiger: A comparative study with the Amur tiger. Zhang L, Lan T, Lin C, Fu W, Yuan Y, Lin K, Li H, Sahu SK, Liu Z, Chen D, Liu Q, Wang A, Wang X, Ma Y, Li S, Zhu Y, Wang X, Ren X, Lu H, Huang Y, Yu J, Liu B, Wang Q, Zhang S, Xu X, Yang H, Liu D, Liu H, Xu Y. Zhang L, et al. Mol Ecol Resour. 2023 Feb;23(2):330-347. doi: 10.1111/1755-0998.13669. Epub 2022 Jul 1. Mol Ecol Resour. 2023. PMID: 35723950 Free PMC article.
• Synthesizing habitat connectivity analyses of a globally important human-dominated tiger-conservation landscape. Schoen JM, Neelakantan A, Cushman SA, Dutta T, Habib B, Jhala YV, Mondal I, Ramakrishnan U, Reddy PA, Saini S, Sharma S, Thatte P, Yumnam B, DeFries R. Schoen JM, et al. Conserv Biol. 2022 Mar 14;36(4):e13909. doi: 10.1111/cobi.13909. Online ahead of print. Conserv Biol. 2022. PMID: 35288989 Free PMC article.
• Hematological and Biochemical Reference Values in Healthy Captive Tigers ( Panthera tigris ). Proverbio D, Perego R, Baggiani L, Ravasio G, Giambellini D, Spada E. Proverbio D, et al. Animals (Basel). 2021 Dec 2;11(12):3440. doi: 10.3390/ani11123440. Animals (Basel). 2021. PMID: 34944217 Free PMC article.
• Cerebral cysticercosis in a wild Bengal tiger (Panthera tigris tigris) in Bhutan: A first report in non-domestic felids. Phuentshok Y, Choden K, Alvarez Rojas CA, Deplazes P, Wangdi S, Gyeltshen K, Rinzin K, Thapa NK, Tenzinla T, Dorjee D, Valitutto M, Gilbert M, Siriaroonrat B, Jairak W, Piewbang C, Sharma PM, Dema T, Gurung RB. Phuentshok Y, et al. Int J Parasitol Parasites Wildl. 2021 Feb 10;14:150-156. doi: 10.1016/j.ijppaw.2021.02.003. eCollection 2021 Apr. Int J Parasitol Parasites Wildl. 2021. PMID: 33665082 Free PMC article.

Publication types

• Search in MeSH

LinkOut - more resources

Full text sources, miscellaneous.

• NCI CPTAC Assay Portal

• Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

Advertisement

Impact of climate change on biodiversity loss: global evidence

• Research Article
• Published: 03 August 2021
• Volume 29 , pages 1073–1086, ( 2022 )

Cite this article

• Muzafar Shah Habibullah   ORCID: orcid.org/0000-0002-2853-8019 1 ,
• Badariah Haji Din 2 ,
• Siow-Hooi Tan 3 &
• Hasan Zahid 4  

20k Accesses

128 Citations

43 Altmetric

Explore all metrics

The present study investigates the impact of climate change on biodiversity loss using global data consisting of 115 countries. In this study, we measure biodiversity loss using data on the total number of threatened species of amphibians, birds, fishes, mammals, mollusks, plants, and reptiles. The data were compiled from the Red List published by the International Union for Conservation of Nature (IUCN). For climate change variables, we have included temperature, precipitation, and the number of natural disaster occurrences. As for the control variable, we have considered governance indicator and the level of economic development. By employing ordinary least square with robust standard error and robust regression (M-estimation), our results suggest that all three climate change variables – temperature, precipitation, and the number of natural disasters occurrences – increase biodiversity loss. Higher economic development also impacted biodiversity loss positively. On the other hand, good governance such as the control of corruption, regulatory quality, and rule of law reduces biodiversity loss. Thus, practicing good governance, promoting conservation of the environment, and the control of greenhouse gasses would able to mitigate biodiversity loss.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Climate change is a major problem for biodiversity conservation: a systematic review of recent studies in iran.

Impacts of Climate Change on Biodiversity in Pakistan: Current Challenges and Policy Recommendations

A biodiversity-crisis hierarchy to evaluate and refine conservation indicators

Data availability.

The datasets used and analyzed during the current study are available from the corresponding author upon request

Adler PB, Leiker J, Levine JM (2009) Direct and indirect effects of climate change on a Prairie plant community. PLoS One 4(9):e6887. https://doi.org/10.1371/journal.pone.0006887

Article   CAS   Google Scholar  

Amano T, Szekely T, Sandel B, Nagy S, Mundkur T, Langendoen T, Blanco D, Soykan CU, Sutherland WJ (2018) Successful conservation of global waterbird populations depends on effective governance. Nature 553:199–202. https://doi.org/10.1038/nature25139

Asafu-Adjaye J (2003) Biodiversity loss and economic growth: a cross-country analysis. Contemp Econ Anal 21(2):173–185. https://doi.org/10.1093/cep/byg003

Article   Google Scholar  

Barnett V, Lewis T (1994) Outliers in statistical data. New York: Wiley. https://www.wiley.com/en-us/Outliers+in+Statistical+Data%2C+3rd+Edition-p-9780471930945

Barrett CB, Gibson CC, Hoffman B, McCubbins MD (2006) The complex links between governance and biodiversity. Conserv Biol 20(5):1358–1366. https://doi.org/10.1111/j.1523-1739.2006.00521.x

Baynham-Herd Z, Amano T, Sutherland WJ, Donald PF (2018) Governance explains variation in national responses to the biodiversity crisis. Environ Conserv 45(4):407–418. https://doi.org/10.1017/S037689291700056X

Benhin JKA, Barbier EB (2004) Structural adjustment programme, deforestation and biodiversity loss in Ghana. Environ Resour Econ 27:337–366. https://doi.org/10.1023/B:EARE.0000017653.15107.0f

Bennun L, Regan EC, Bird J, van Bochove JW, Katariya V, Livinstone S, Mitchell R, Savy C, Starkey M, Temple H, Pilgrim JD (2018) The value of the IUCN Red list for business decision-making. Conserv Lett 11(1):1–8. https://doi.org/10.1111/conl.12353

Bixby RJ, Cooper SD, Gresswell RE, Brown LE, Dahm CN, Dwire KA (2015) Fire effects on aquatic ecosystems: an assessment of the current state of the science. Freshw Sci 34(4):1340–1350. https://doi.org/10.1086/684073

Brook BW, Sodhi NS, Bradshaw CJA (2008) Synergies among extinction drivers under global change. Trends Ecol Evol 23:453–460. https://doi.org/10.1016/j.tree.2008.03.011

Busse M, Hefeker C (2007) Political risk, institutions and foreign direct investment. Eur J Polit Econ 23:397–415. https://doi.org/10.1016/j.ejpoleco.2006.02.003

Butler R (2006) Rainforest diversity – origins and implications. Retrieved 1/22/2014 from http://rainforests.mongabay.com/0301.htm .

CBD (Convention on Biological Diversity) (2019) COP 7 Decision VII/30. https://www.cbd.int/decision/cop/?id=7767

CBD (Convention on Biological Diversity) (2020) Global biodiversity outlook 5. Secretariat of the CBD, Montreal. https://www.cbd.int/gbo5

Chapin FS III, Diaz S (2020) Interactions between changing climate and biodiversity: shaping humanity’s future. PNAS 117(12):6295–6296 www.pnas.org/cgi/doi/10.1073/pnas.2001686117

Chivian E, Bernstein A (2010) How our health depends on biodiversity. Center for health and the global environment, Boston https://www.researchgate.net/publication/265187166

Google Scholar  

Clausen R, York R (2008) Global biodiversity decline of marine and freshwater fish: a cross-national analysis of economic, demographic and ecological influences. Soc Sci Res 37:1310–1320. https://doi.org/10.1016/j.ssresearch.2007.10.002

Culas RJ (2007) Deforestation and the environmental Kuznets curve: an institutional perspective. Ecol Econ 61:429–437. https://doi.org/10.1016/j.ecolecon.2006.03.014

Darnaedi D, Zulkarnaen I (2017) Disasters and biodiversity in the ring of fire of the Indonesian archipelago. Biology International Special Issue 36:39-46. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjswujjs6PrAhUK4nMBHTG5DT0QFjAAegQIARAB&url=http%3A%2F%2Fwww.iubs.org%2Ffileadmin%2Fuser_upload%2FBiology-International%2FBI-Specials%2FBI_Special_Issue_No-36_beta_2_web.pdf&usg=AOvVaw0s4F7P9KnFHZ5Mn8_tmxmh

Daszykowski M, Kaczmarek K, Heyden YV, Walczak B (2007) Robust statistics in data analysis – a review basic concepts. Chemom Intell Lab Syst 85:203–219. https://doi.org/10.1016/j.chemolab.2006.06.016

Eagles PFJ (2009) Governance of recreation and tourism partnerships in parks and protected areas. J Sustain Tour 17(2):231–248. https://doi.org/10.1080/09669580802495725

Earthwatch Institute (2002) Business & biodiversity: the handbook for corporate action. Earthwatch Institute, IUCN and World Business Council for Sustainable Development, Switzerland. https://www.iucn.org/content/business-and-biodiversity-handbook-corporate-action

Ehrhardt-Martinez K, Crenshaw EM, Jenkins JC (2002) Deforestation and the environmental Kuznets curve: a cross-national investigation of intervening mechanisms. Soc Sci Q 83(1):226–243. https://doi.org/10.1111/1540-6237.00080

Eklund J, Arponen A, Visconti P, Cabeza M (2011) Governance factors in the identification of global conservation priorities for mammals. Philos Trans R Soc B 366:2661–2669. https://doi.org/10.1098/rstb.2011.0114

European Commission (2008) The European Union’s biodiversity action plan: halting the loss of biodiversity by 2010 – and beyond. European Commission, Belgium. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjBpYbIt6PrAhXBILcAHSMBDUgQFjACegQIBRAB&url=http%3A%2F%2Fwww.ab.gov.tr%2Ffiles%2Fardb%2Fevt%2F1_avrupa_birligi%2F1_6_raporlar%2F1_3_diger%2Fenvironment%2Feu_biodiversity_action_plan___2010_and_beyond.pdf&usg=AOvVaw1m_wSdJ8BfnsjbzIiH-y5f

Fattorini S, Di Lorenzo T, Galassi DM (2018) Earthquake impacts on microcrustacean communities inhabiting groundwater-fed springs alter species-abundance distribution patterns. Sci Rep-UK 8:1501. https://doi.org/10.1038/s41598-018-20011-1

Ferraro P (2005) Corruption and conservation: the need for empirical analyses. A response to Smith & Walpole. Oyx 39(3):1–3. https://doi.org/10.1017/S00306053050000000

Fraver S, Dodds KJ, Kenefic LS, Morrill R, Seymour RS, Sypitkowski E (2017) Forest structure following tornado damage and salvage logging in northern Maine, USA. Can J Forestry 47:560–564. https://doi.org/10.1139/cjfr-2016-0395

GRI (Global Reporting Initiative) (2007) Biodiversity: a GRI reporting resource. Global Reporting Initiative, Amsterdam. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjg88uhuaPrAhV74XMBHWVaCvQQFjAAegQIAxAB&url=https%3A%2F%2Fwww.globalreporting.org%2Fresourcelibrary%2FBiodiversity-A-GRI-Resource-Document.pdf&usg=AOvVaw2O1TLr2khAiPnrFaOtKXt_

Gren IM, Campos M, Gustafsson L (2016) Economic development, institutions and biodiversity loss at the global scale. Reg Environ Chang 16:445–457. https://doi.org/10.1007/s10113-015-0754-9

Guan K (2017) Disaster and biodiversity in China. Biology International Special Issue 36:30-38. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjswujjs6PrAhUK4nMBHTG5DT0QFjAAegQIARAB&url=http%3A%2F%2Fwww.iubs.org%2Ffileadmin%2Fuser_upload%2FBiology-International%2FBI-Specials%2FBI_Special_Issue_No-36_beta_2_web.pdf&usg=AOvVaw0s4F7P9KnFHZ5Mn8_tmxmh

Guo D, Desmet PG, Powrie LW (2017) Impact of the future changing climate on the Southern Africa biomes and the importance of geology. J Geosci Environ Protect 5:1–9 http://www.scirp.org/journal/gep

Halkos GE (2011) Nonparametric modelling of biodiversity: determinants of threatened species. J Policy Model 33:618–635. https://doi.org/10.1016/j.jpolmod.2010.12.005

Hoffmann JP (2004) Social and environmental influences on endangered species: a cross-national study. Sociol Perspect 47(1):79–107. https://doi.org/10.1525/sop.2004.47.1.79

Huber PJ (1964) Robust estimation of a location parameter. Ann Math Stat 35:73–101 https://link.springer.com/chapter/10.1007/978-1-4612-4380-9_35

Hui D (2013) Global climate change and biodiversity: issues and future research. J Biodivers Endanger Species 1:e105. https://doi.org/10.4172/2332-2543.1000e105

IPCC (Intergovernmental Panel on Climate Change) (2001) IPCC third assessment report – climate change 2001. Working group II: impacts, adaptation and vulnerability. World Meteorological Organization and United Nations Environment Programme, Geneva. https://www.ipcc.ch/report/ar3/wg2/

Kanaya G, Suzuki T, Kinoshita K, Matsumasa M, Yamada K, Seike K, Okoshi K, et al. (2017) Disaster-induced changes in coastal wetlands and soft-bottom habitats: an overview of the impacts of the 2011 tsunami and Great East Japan earthquake. Biology International Special Issue 36:62-80. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjswujjs6PrAhUK4nMBHTG5DT0QFjAAegQIARAB&url=http%3A%2F%2Fwww.iubs.org%2Ffileadmin%2Fuser_upload%2FBiology-International%2FBI-Specials%2FBI_Special_Issue_No-36_beta_2_web.pdf&usg=AOvVaw0s4F7P9KnFHZ5Mn8_tmxmh

Kaufman D, Kraay A, Mastruzzi M (2008) Governance matters VII: governance indicators for 1996-2007. World Bank Policy Research June 2008. The World Bank, Washington DC. https://documents.worldbank.org/en/publication/documents-reports/documentdetail/810501468338351727/governance-matters-vii-aggregate-and-individual-governance-indicators-1996-2007

Kwit C, Platt WJ, Slater HH (2000) Post-hurricane regeneration of pioneer plant species in south Florida subtropical hardwood hammocks. Biotropica 32(2):244–251. https://doi.org/10.1111/j.1744-7429.2000.tb00467.x

Lallement M, Macchi PJ, Vigliano P, Juarez S, Recheong M, Baker M, Bouwes N, Crowl T (2016) Rising from the ashes: changes in salmonid fish assemblages after 30 months of the Puyehue-Cordon Caulle volcanic eruption. Sci Total Environ 541:1041–1051. https://doi.org/10.1016/j.scitotenv.2015.09.156

McClanahan TR, Rankin PS (2016) Geography of conservation spending, biodiversity and culture. Conserv Biol 30:1089–1101. https://doi.org/10.1111/cobi.12720

McKinney LA, Fulkerson GM, Kick EL (2009) Investigating the correlates of biodiversity loss: a cross-national quantitative analysis of threatened bird species. Hum Ecol Rev 16(1):103–113 https://www.jstor.org/stable/24707741

Melick DR, Kinch JP, Govan H (2012) How global biodiversity targets risk becoming counterproductive: the case of Papua New Guinea. Conserv Soc 10(4):344–353. https://doi.org/10.4103/0972-4923.105559

MEA (Millennium Ecosystem Assessment) (2005) Ecosystems and human well-being: synthesis. Island Press, Washington, D.C. https://www.cifor.org/knowledge/publication/1888/

Milner AM, Robertson AL, McDermott MJ, Klaar MJ, Brown LE (2013) Major flood disturbance alters river ecosystem evolution. Nat Clim Chang 3:137–141. https://doi.org/10.1038/nclimate1665

Miura O, Kanaya G (2017) Impact of the 2011 Tohoku earthquake tsunami on marine and coastal organisms. Biol Int Special Issue 36:81–92 https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjswujjs6PrAhUK4nMBHTG5DT0QFjAAegQIARAB&url=http%3A%2F%2Fwww.iubs.org%2Ffileadmin%2Fuser_upload%2FBiology-International%2FBI-Specials%2FBI_Special_Issue_No-36_beta_2_web.pdf&usg=AOvVaw0s4F7P9KnFHZ5Mn8_tmxmh

Naidoo R, Adamowicz WL (2001) Effects of economic prosperity on numbers of threatened species. Conserv Biol 15(4):1021–1029. https://doi.org/10.1046/j.1523-1739.2001.0150041021.x

Newey WK, West KD (1987) A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55:703–708. https://doi.org/10.2307/1913610

Perez B, Molina I, Pena D (2013) Outlier detection and robust estimation in linear regression models with fixed group effects. J Stat Comput Simul 84:2652–2669. https://doi.org/10.1080/00949655.2013.811669

Porwal MC, Padalia H, Roy PS (2012) Impact of tsunami on the forest and biodiversity richness in Nicobar Islands (Andaman and Nicobar Islands), India. Biodivers Conserv 21:1267–1287. https://doi.org/10.1007/s10531-011-0214-x

Rousseeuw PJ (1984) Least median of squares regression. J Am Stat Assoc 79:871–880. https://doi.org/10.1080/01621459.1984.10477105

Reed DH (2012) Impact of climate change on biodiversity. In: Chen WY, Seiner J, Suzuki T, Lackner M (eds) Handbook of Climate Change Mitigation. Springer-Verlag, New York, pp 505-530. https://link.springer.com/referencework/10.1007%2F978-1-4419-7991-9

Rinawati F, Stein K, Lindner A (2013) Climate change impacts on biodiversity – the setting of a lingering global crisis. Diversity 5:114–123. https://doi.org/10.3390/d5010114

Rodrigues ASL, Brooks TM, Butchart SHM, Chanson J, Cox N, Hoffmann M, Stuart SN (2014) Spatially explicit trends in the global conservation status of vertebrates. PLoS One 10(3):e0121040. https://doi.org/10.1371/journal.pone.0121040

Rosales J (2008) Economic growth, climate change, biodiversity loss: distributive justice for the global North and South. Conserv Biol 22(6):1409–1417. https://doi.org/10.1111/j.1523-1739.2008.01091.x

Ryden O, Zizka A, Jagers SC, Lindberg SI, Antonelli A (2020) Linking democracy and biodiversity conservation: empirical evidence and research gaps. Ambio 49:419–433. https://doi.org/10.1007/s13280-019-01210-0

Sarkar S (2012) Impact of global warming on biodiversity. The Science Probe 1(2):22–33 https://www.scribd.com/document/452705683/23f0a64930cb83ab4d228460eddc2211411b

Schnaiberg A, Gould KA (1994) Environment and society: the enduring conflict. New York: St. Martin Press. https://www.amazon.com/Environment-Society-Enduring-Allan-Schnaiberg/dp/1930665008

Shandra JM (2007) The world polity and deforestation: a quantitative, cross-national analysis. Int J Comp Sociol 48(1):5–27. https://doi.org/10.1177/0020715207072157

Shandra JM, McKinney LA, Leckband C, London B (2010) Debt, structural adjustment and biodiversity loss: a cross-national analysis of threatened mammals and birds. Hum Ecol Rev 17(1):18–33 https://www.jstor.org/stable/24707512

Shandra JM, Rademacher H, Coburn C (2016) The World Bank and organized hypocrisy? A cross-national analysis of structural adjustment and forest loss. Environ Soc 2(2):192–207. https://doi.org/10.1080/23251042.2016.1160471

Shandra JM, Shircliff E, London B (2011) The International Monetary Fund, World Bank and structural adjustment: a cross-national analysis of forest loss. Soc Sci Res 40:210–225. https://doi.org/10.1016/j.ssresearch.2010.08.004

Sintayehu DW (2018) Impact of climate change on biodiversity and associated key ecosystem services in Africa: a systemic review. Ecosyst Health Sustain 4(9):225–239. https://doi.org/10.1080/20964129.2018.1530054

Smith RJ, Muir RDJ, Walpole MJ, Balmford A, Leader-Williams N (2003) Governance and the loss of biodiversity. Nature 426:67–70. https://doi.org/10.1038/nature02025

Suh S (2006) Are services better for climate change? Environ Sci Technol 40:6555–6560. https://doi.org/10.1021/es0609351

Thomas CD, Cameron A, Green RE, Bakkenes M, Beaumont LJ, Collingham YC, Erasmus BFN, De Siqueira MF, Grainger A, Hannah L, Hughes L, Huntley B, Jaarsveld ASV, Midgley GF, Miles L, Ortega-Huerta MA, Peterson AT, Phillips OL, Williams SE (2004) Extinction risk from climate change. Nature 427:145–148. https://doi.org/10.1038/nature02121

Tol RSJ (2009) The economic effects of climate change. J Econ Perspect 23(2):29–51 https://www.jstor.org/stable/27740523

Umemiya C, Rametsteiner E, Kraxner F (2010) Quantifying the impacts of the quality of governance on deforestation. Environ Sci Pol 13:695–701. https://doi.org/10.1016/j.envsci.2010.07.002

UNEP (United Nations Environment Programme) (2002) State of the environment and policy retrospective: 1972-2002. Earthscan, London. https://www.ircwash.org/resources/chap-2-state-environment-and-policy-retrospective-1972%C2%BF2002-freshwater

UNU-IAS (United Nations University Institute of Advanced Studies) (2010) Climate and human-related drivers of biodiversity decline in Southeast Asia. UNU-IAS Policy Report. United Nations University Institute of Advanced Studies, Japan. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwit4J3Q-KPrAhWRX3wKHV5JDzkQFjABegQIBBAB&url=http%3A%2F%2Farchive.unu.edu%2Fclimate%2Ffiles%2F2010_Climate-and-Human-Related-Drivers-of-Biodiversity-Decli.pdf&usg=AOvVaw0a1hMrg8wK9ihXmH8MmCcW

Villen-Perez S, Heikkinen J, Salemaa M, Makipaa R (2020) Global warming will affect the maximum potential abundance of boreal plant species. Ecography 43:1–11. https://doi.org/10.1111/ecog.047720

Wagstaff SJ (2017) Disaster and biodiversity in New Zealand: review and consideration. Biology International Special Issue 36: 47-61. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjswujjs6PrAhUK4nMBHTG5DT0QFjAAegQIARAB&url=http%3A%2F%2Fwww.iubs.org%2Ffileadmin%2Fuser_upload%2FBiology-International%2FBI-Specials%2FBI_Special_Issue_No-36_beta_2_web.pdf&usg=AOvVaw0s4F7P9KnFHZ5Mn8_tmxmh

Wilting HC, Schipper AM, Bakkenes M, Meijer JR, Huijbregts MAJ (2017) Quantifying biodiversity losses due to human consumption: a global-scale footprint analysis. Environ Sci Technol 51:3298–3306. https://doi.org/10.1021/acs.est.6b05296

WWF (World Wildlife Fund) (2016) Living planet report 2016: risk and resilience in a new era. WWF International, Switzerland. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjSr_2X-aPrAhW8IbcAHRWXDvUQFjAAegQIBRAB&url=https%3A%2F%2Fawsassets.panda.org%2Fdownloads%2Flpr_2016_full_report_low_res.pdf&usg=AOvVaw2JmRg9VlAX_cKy_Svx6Mwu

WWF (World Wildlife Fund) (2020) Living planet report 2020: bending the curve of biodiversity loss. LPR 2020 Full report.pdf

York R, Rosa EA, Diete T (2003) Footprints on the earth: the environmental consequences of modernity. Am Sociol Rev 68:279–300 http://www.jstor.org/stable/1519769

Download references

Research financial support was provided by the Ministry of Higher Education (MOHE) Malaysia.

Author information

Authors and affiliations.

Putra Business School, Serdang, Malaysia

Muzafar Shah Habibullah

College of Law, Government and International Studies, Universiti Utara Malaysia, Changlun, Malaysia

Badariah Haji Din

Faculty of Management, Multimedia University, Cyberjaya, Malaysia

Siow-Hooi Tan

Iqra University, Karachi, Pakistan

Hasan Zahid

You can also search for this author in PubMed   Google Scholar

Contributions

MSH has major contribution in all sections of this article, while BHD, SHT, and HZ assist in working over the literature review, data organization, resources, interpretation of results, and referencing.

Corresponding author

Correspondence to Muzafar Shah Habibullah .

Ethics declarations

Ethics approval and consent to participate.

This research work does not involve human participants, human data, or human tissue. This research was based on published materials.

Consent for publication

This research work does not contain any individual person’s data in the form of individual details, images, or videos. This work based on published literature.

Competing interests

The authors declare no competing interests.

Additional information

Responsible Editor: Philippe Garrigues

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Habibullah, .S., Din, B.H., Tan, SH. et al. Impact of climate change on biodiversity loss: global evidence. Environ Sci Pollut Res 29 , 1073–1086 (2022). https://doi.org/10.1007/s11356-021-15702-8

Download citation

Received : 26 August 2020

Accepted : 25 July 2021

Published : 03 August 2021

Issue Date : January 2022

DOI : https://doi.org/10.1007/s11356-021-15702-8

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Climate change
• Biodiversity loss
• Threatened species
• Global evidence
• Find a journal
• Publish with us
• Track your research

Case study: People ‘don’t see what we’ve lost’ in biodiversity crisis

Scale of biodiversity loss to date across ireland is ‘terrifying’, an taisce officer says.

People looking out across green fields and hedgerows in the Irish countryside “don’t see what we’ve lost” as a result of the biodiversity crisis affecting plants and animals, according to Dr Elaine McGoff.

Dr McGoff, natural environment officer with heritage and environmental charity An Taisce, said the scale of the current threat to biodiversity and ecosystems was “terrifying”.

On Wednesday, the Citizens’ Assembly on biodiversity loss issued its final report to the Government, which included a host of recommendations.

The group of 99 members of the public recommended a referendum be held to include biodiversity protection in the Constitution, as well as a range of policies that would protect water quality, forestry and endangered species.

Plan in place to fix Lough Neagh’s pollution problems but the ‘challenges faced are gargantuan’

Our urban lives are wrapped up in the swift’s fate. To survive, they need our help

Music festival tents: can you save money while saving the planet?

Friends of the Earth calls for temporary ban on new data centres over electricity use

“For years it feels like we’ve been shouting into the wind ... It’s really nice to finally have a group of people who have listened to us and are saying the same things as us, and I’d be really hopeful that the Government might listen to them,” Dr McGoff said.

“When they look at the countryside they don’t see the same things as somebody like me would see. They don’t see what we’ve lost, they just see nice green fields and hedges and they think that everything is great,” she said.

The curlew is “on the brink of extinction” while the hen harrier is also in “really rapid decline”, she told The Irish Times.

[  Melanie McDonagh: You want an index for Ireland’s biodiversity crisis? I give you the humble curlew Opens in new window  ]

The freshwater pearl mussel, which needed to live in “the cleanest of clean water”, was also in trouble. “We’re losing those, they are no longer reproducing because our water quality is in decline so much,” she said.

The country was also losing thousands of kilometres of hedgerows a year, which were the “arteries of biodiversity,” she said.

The State has been “dragging its heels and trying to water down the ambition” of European Union attempts to address the crisis, she said.

“But now they very much have the mandate from the Irish people to lead the pack and stop being a laggard and step up and embrace this opportunity to protect biodiversity,” she said.

[  EPA criticises low level of water quality inspections by councils Opens in new window  ]

When it came to the agricultural sector, the trends were “still going in the wrong direction”, she said.

“I think there is willingness among the farmers but there’s a lack of honesty about how far we have to go, politicians are shying away from that”, she said.

One of the assembly’s recommendations that people be encouraged to switch to a more plant-based diet would not be “that difficult to sell” to younger generations, she said.

“I think we’re seeing more plant-based options, I’m vegan myself so I don’t have any difficulty when I move around finding food,” Dr McGoff said.

More people were already trying to cut down on meat consumption, she said. “A switch to a totally plant-based diet might be a bridge too far, but I do think a lot of people are reducing,” she said.

Jack Power is acting Europe Correspondent of The Irish Times

IN THIS SECTION

Planet earth sets record for hottest day in history, twice in a row, hse employee was paid €700,000 last year for treating patients out of normal hours, report reveals, kneecap: ‘paul mescal was flirting with us. he was wearing adidas shorts, not gaa shorts. it’s all a farce’, victim in tallaght assault stabbed after man believed van was being broken into, gardaí suspect, double child benefit weeks higher electricity bills five key decisions for october’s budget, ‘we are caring for your parents like they are our parents - but we can’t bring our families here’, latest stories, olympics: complete day-by-day guide to the irish athletes in action in paris, man (30s) charged in connection with investigation into fatal stabbing of jordan pakenham in tallaght, at least 30 killed in israeli strike on school, gaza health officials say, olympics at a glance: men’s double sculls set best time; ireland to play all blacks for fifth place, small protest taking place at site earmarked for asylum seekers in coolock.

• Terms & Conditions
• Privacy Policy
• Cookie Information
• Cookie Settings
• Community Standards

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• 29 November 2022

Biodiversity loss and climate extremes — study the feedbacks

• Miguel D. Mahecha 0 ,
• Ana Bastos 1 ,
• Friedrich J. Bohn 2 ,
• Nico Eisenhauer 3 ,
• Hannes Feilhauer 4 ,
• Henrik Hartmann 5 ,
• Thomas Hickler 6 ,
• Heike Kalesse-Los 7 ,
• Mirco Migliavacca 8 ,
• Friederike E. L. Otto 9 ,
• Jian Peng 10 ,
• Johannes Quaas 11 ,
• Ina Tegen 12 ,
• Alexandra Weigelt 13 ,
• Manfred Wendisch 14 &
• Christian Wirth 15

Miguel D. Mahecha is professor of modelling approaches in remote sensing at the Remote Sensing Centre for Earth System Research of Leipzig University and the Helmholtz Centre for Environmental Research (UFZ), and a member of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Germany.

You can also search for this author in PubMed   Google Scholar

Ana Bastos is a group leader at the Department of Biogeochemical Integration of the Max Planck Institute for Biogeochemistry, Jena, Germany.

Friedrich J. Bohn is a postdoctoral scientist at the Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany.

Nico Eisenhauer is professor of experimental interaction ecology at Leipzig University and research group leader at the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Germany.

Hannes Feilhauer is professor at the Remote Sensing Centre for Earth System Research of Leipzig University and the Helmholtz Centre for Environmental Research (UFZ).

Henrik Hartmann is director of the Institute for Forest Protection, Julius Kühn Institute Federal Research Centre for Cultivated Plants, Quedlinburg, Germany, and group leader at the Max Planck Institute for Biogeochemistry, Jena, Germany.

Thomas Hickler is professor of biogeography at the Senckenberg Biodiversity and Climate Research Centre (SBiK-F) and the Department of Physical Geography at Goethe University, Frankfurt am Main, Germany.

Heike Kalesse-Los is a junior professor of remote sensing of the atmosphere and the arctic climate system, Leipzig Institute for Meteorology (LIM), Leipzig University, Germany.

Mirco Migliavacca is a scientific research project officer at the European Commission Joint Research Centre, Ispra, Italy.

Friederike E. L. Otto is a senior lecturer in climate science at the Grantham Institute for Climate Change and the Environment at Imperial College London, UK.

Jian Peng is head of the department of remote sensing at the Helmholtz Centre for Environmental Research (UFZ), and professor at the Remote Sensing Centre for Earth System Research of Leipzig University, Germany.

Johannes Quaas is professor of theoretical meteorology at the Leipzig Institute for Meteorology, Leipzig University, and a member of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig.

Ina Tegen is head of the Modelling of Atmospheric Processes Department, TROPOS, Leipzig, and professor of atmospheric modelling at the Leipzig Institute for Meteorology (LIM), Leipzig University, Germany.

Alexandra Weigelt is professor of botany and functional biodiversity at Leipzig University, and a member of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Germany.

Manfred Wendisch is professor of atmospheric radiation at the Leipzig Institute for Meteorology (LIM), Leipzig University, and director of LIM, Germany.

Christian Wirth is professor of systematic botany and functional biodiversity, Institute of Biology, Leipzig University; managing director of the Botanical Garden of Leipzig University; and speaker of the German Centre for Integrative Biodiversity Research (iDiv); and is also affiliated with the Max Planck Institute for Biogeochemistry, Jena, Germany.

Dead spruce trees in Schleiden, Germany, as seen at infrared wavelengths. Credit: Bernd Lauter/Getty

As humans warm the planet, biodiversity is plummeting. These two global crises are connected in multiple ways. But the details of the intricate feedback loops between biodiversity decline and climate change are astonishingly under-studied.

Access options

Access Nature and 54 other Nature Portfolio journals

Get Nature+, our best-value online-access subscription

24,99 € / 30 days

cancel any time

Subscribe to this journal

Receive 51 print issues and online access

185,98 € per year

only 3,65 € per issue

Rent or buy this article

Prices vary by article type

Prices may be subject to local taxes which are calculated during checkout

Nature 612 , 30-32 (2022)

doi: https://doi.org/10.1038/d41586-022-04152-y

Popkin, G. Science 374 , 1184–1189 (2021).

Article   PubMed   Google Scholar  

Pörtner, H.-O. et al. Scientific outcome of the IPBES-IPCC co-sponsored workshop on biodiversity and climate change (IPBES Secretariat, 2021).

Jandt, U. et al. Nature 611 , 512–518 (2022).

Oliver, T. H. et al. Nature Commun. 6 , 10122 (2015).

Isbell, F. et al. Nature 546 , 65–72 (2017).

Loreau, M. et al. Biol. Rev. 96 , 2333–2354 (2021).

Anderegg, W. R. et al. Nature 561 , 538–541 (2018).

Searle, E. B., Chen, H. Y. H. & Paquette, A. Proc. Natl Acad. Sci. USA 119 , e2013171119 (2022).

Article   Google Scholar  

Wu, X. et al. Earths Future 10 , e2021EF002530 (2022).

Hartmann, H. et al. Annu. Rev. Plant Biol. 73 , 673–702 (2022).

Google Scholar  

Pfenninger, M. et al. eLife 10 , e65532 (2021).

Lin, M. et al. Nature Clim. Change 10 , 444–451 (2020).

O’Sullivan, D. et al. Sci. Rep. 8 , 13821 (2018).

Mülmenstädt, J., Sourdeval, O., Delanoë, J. & Quaas, J. Geophys. Res. Lett. 42 , 6502–6509 (2015).

Duveiller, G. et al. Nature Commun. 12 , 4337 (2021).

Fischer, E. M., Sippel, S. & Knutti, R. Nature Clim. Change 11 , 689–695 (2021).

Zscheischler, J. et al. Nature Rev. Earth Environ. 1 , 333–347 (2020).

Wolf, S. et al. Nature Ecol. Evol . https://doi.org/10.1038/s41559-022-01904-x (2022).

Kattenborn, T., Richter, R., Guimarães-Steinicke, C., Feilhauer, H. & Wirth, C. Methods Ecol. Evol. 13 , 2531–2545 (2022).

Bauer, P., Stevens, B. & Hazeleger, W. Nature Clim. Change 11 , 80–83 (2021).

Download references

Reprints and permissions

Competing Interests

The authors declare no competing interests.

Related Articles

• Biodiversity
• Climate change
• Solid Earth sciences

Airborne DNA reveals predictable spatial and seasonal dynamics of fungi

Article 10 JUL 24

Cenozoic history of the tropical marine biodiversity hotspot

Article 26 JUN 24

Global shortfalls in documented actions to conserve biodiversity

Article 05 JUN 24

Carbon pricing reduces emissions

News & Views 24 JUL 24

Exclusive: the Trump administration demoted this climate scientist — now she wants reform

News 24 JUL 24

Global net climate effects of anthropogenic reactive nitrogen

Article 24 JUL 24

Deep, hot, ancient melting recorded by ultralow oxygen fugacity in peridotites

How mud brought France and England together — 150 years ago

News & Views 09 JUL 24

James Clerk Maxwell’s ode to bubble blowing

News & Views 18 JUN 24

Stadtman Investigator Search 2024-2025

Stadtman Investigator Search 2024-2025 Deadline: September 30, 2024 The National Institutes of Health, the U.S. government’s premier biomedical and...

Bethesda, Maryland

National Institute of Health- Office of Intramural Research

Research Manager, Open Access

The Research Manager is a great opportunity for someone with experience of policy and open access to join Springer Nature.

London, Berlin or New York (Hybrid Working)

Springer Nature Ltd

Postdoctoral Research Scientist

Computational Postdoctoral Research Scientist in Neurodegenerative Disease

New York City, New York (US)

Columbia University Department of Pathology

Associate or Senior Editor (Chemical Engineering), Nature Sustainability

Associate or Senior Editor (Chemical engineering), Nature Sustainability Locations: New York, Philadelphia, Berlin, or Heidelberg Closing date: Aug...

Postdoctoral Research Scientist - Mouse Model

The Stavros Niarchos Foundation Center for Precision Psychiatry & Mental Health is seeking a Postdoctoral Research Scientist for the Mouse Model.

Columbia University Irving Medical Center / Vagelos College of Physicians and Surgeons

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

• News & Events
• Eastern and Southern Africa
• Eastern Europe and Central Asia
• Mediterranean
• Mexico, Central America and the Caribbean
• North America
• South America
• West and Central Africa
• IUCN Academy
• IUCN Contributions for Nature
• IUCN Library
• IUCN Red List of Threatened Species TM
• IUCN Green List of Protected and Conserved Areas
• IUCN World Heritage Outlook
• IUCN Leaders Forum
• Protected Planet
• Union Portal (login required)
• IUCN Engage (login required)
• Commission portal (login required)

Data, analysis, convening and action.

• Open Project Portal
• SCIENCE-LED APPROACH
• INFORMING POLICY
• SUPPORTING CONSERVATION ACTION
• GEF AND GCF IMPLEMENTATION
• IUCN CONVENING
• IUCN ACADEMY

The world’s largest and most diverse environmental network.

CORE COMPONENTS

• Expert Commissions
• Secretariat and Director General
• IUCN Council

• IUCN WORLD CONSERVATION CONGRESS
• REGIONAL CONSERVATION FORA
• CONTRIBUTIONS FOR NATURE
• IUCN ENGAGE (LOGIN REQUIRED)

IUCN tools, publications and other resources.

Get involved

New 'State of the World’s Mangroves' report underscores critical links to biodiversity, climate, and communities

A new report released today on World Mangrove Day highlights efforts to protect and restore these important ecosystems, which billions of people depend on for food, protection, and their livelihoods. 

Mangroves are threatened by deforestation, development, pollution, and dam construction, but the risk to these ecosystems is increasing due to sea-level rise and the increased frequency of severe storms associated with climate change.

Produced by the Global Mangrove Alliance (GMA) – a coalition of more than 100 government and non-government organisations, along with IUCN – the State of the World’s Mangroves 2024 report provides a comprehensive assessment of the latest scientific advancements and policy efforts to protect these valuable ecosystems. The report also features more than 60 case studies and examples of field-based research that are contributing to national and global biodiversity and climate goals.

"Under the Convention on Biological Diversity, the global community has recognised the importance of biodiversity, not only for its own sake, but also for the many ecosystem services and functions it provides for our well-being and survival,” said Ms Astrid Schomaker, the Executive Secretary of the Convention . “In many ways, mangroves are the poster child of the interdependence between people and nature.” 

Mangrove ecosystems are an important indicator of biodiversity health, and critical for climate mitigation and adaptation. However, a first-of-its-kind global assessment published in May by IUCN’s Red List of Ecosystems shows that half of all mangrove ecosystems are at risk of collapse by 2050 due to climate change. 

The GMA report highlights how land-based conversion activities are also having an impact on mangrove ecosystems. A recent study from the Food and Agriculture Organisation found that conversion to aquaculture, oil palm plantations, and rice cultivation account for up to 43% of mangrove losses between 2000 and 2020.  

The loss of mangrove ecosystems can have wide-ranging impacts, say experts. 

“Through their multitude of benefits, mangroves sustain and safeguard entire communities,” write  Maricé Leal and Mark Spalding, both with The Nature Conservancy (TNC) .  “Mangroves are critical to our response to climate change, both in mitigating change through carbon storage and sequestration, and through more local benefits - by helping us adapt to the change we are already too late to avoid.”   

“We’ve seen the global community increasingly recognise the importance of mangroves, our roots of hope,” said Minna Epps, IUCN Global Ocean Director . “But at this crucial moment, much more investment in our blue natural capital and coordination is needed. Now is the moment to act. No single person or organisation can do it alone, and we need all hands on deck to achieve the ambitious global targets."

According to the report, new data and better mapping are helping identify and inform decisionmakers responsible for setting policies to protect these valuable ecosystems. GMA, for example, has confirmed a six-fold improvement in their ability to map mangroves, adding six new territories to their database.  

Globally, Southeast Asia has almost 50,000 km2 of mangrove cover, or about one-third of all mangroves across the world. (Indonesia alone has 21% of the world’s mangroves.) This region is followed by West and Central Africa and then the Americas. 

The Mangrove Breakthrough , a global campaign launched in late 2022 to restore and protect mangrove ecosystems, has placed mangroves centre stage, gaining support from 50 governments with a goal of mobilising USD 4 billion to ensure the future of 15 million hectares of mangroves. These efforts will contribute to the Kunming-Montreal Global Biodiversity Framework, the Paris Agreement, and Sustainable Development Goals on climate, oceans, and more. 

The Global Mangrove Alliance is coordinated by Conservation International, IUCN, The Nature Conservancy, Wetlands International, and the World Wildlife Fund, as well as Audubon Americas representing the GMA National Chapters and the South Asia Consortium for Interdisciplinary Water Resources Studies (SaciWATERs) representing GMA members.   

The GMA is also currently conducting the 2024 Impact Stock Take to measure worldwide progress towards 2030 Goals to halt loss, increase protection of mangroves, and identify and connect viable projects with funding and training opportunities. Anyone working on mangrove projects, policy, research, or diversified livelihood projects in mangrove ecosystems are warmly welcome to fill out the survey by 31 August 2024 here .   

For more information, download the report here . 

Related content

The Regenerative Seascapes for People, Climate and Nature (ReSea) Project was launched at…

The International Union for Conservation of Nature (IUCN) West Asia Office congratulates the…

During the first session of the NAbSA Dialogues, participants from the Partnering for Climate (P4C…

Sign up for an IUCN newsletter

Biodiversity loss impacts our societies and economies – How can Europe confront the spread of invasive species?

Associate professor, Universitat de Girona

Disclosure statement

Núria Roura-Pascual has receive funding from the 2017-2018 Belmont Forum -- BiodivERsA international joint call for research proposals, with organisational financing from AEI, grant number PCI2018-092966.

Universitat de Girona provides funding as a member of The Conversation ES.

View all partners

Biological invasions are the main cause of biodiversity loss, but they can also have serious social and economic repercussions. In Europe, over 13,000 non-native (or “alien”) species have an established presence, around 1,500 of which are invasive species that have a negative impact on their surroundings. Species of particular concern are the brown rat, raccoon, red swamp crayfish, tiger mosquito, varroa mite, ragweed, and tree of heaven, among many others .

Various studies have predicted that, by 2050, the number of non-native species in Europe will grow by as much as 64%. This estimate assumes that current trends will continue unchanged. However, the number and repercussions of invasive species depend on a range of environmental and socioeconomic factors that will evolve in ways that are hard to predict.

Four possible future scenarios

Researchers, managers and policymakers from various countries have developed four qualitative scenarios on the future of biological invasions up to 2050 . This was done as part of the AlienScenarios and InvasiBES projects, which were funded by the 2017-2018 Belmont Forum and BiodivERsA joint call for research proposals.

The scenarios are not predictions as such – they are narrative descriptions and accounts of what could happen in the future under a range of different circumstances.

In particular, our scenarios take into account the socio-ecological developments that are critical for invasive species, and they are more biodiversity-focused than other global change scenarios, such as the shared socioeconomic pathways (SSPs) used by many climate change reports. The scenarios are as follows:

Big Tech Rules Europe : Distrust in governments leads to companies having increased power, while populations concentrate in cities and suffer economic hardship. An increase in invasive species and a reduction in their coordinated management.

Technological (Pseudo-)Panacea : Rapid technological development, large trade volumes and high biosecurity. European societies concentrate in ‘smart cities’. The rate of invasive species spreading and becoming established is low due to solid, strict biosecurity measures.

Green Local Governance : Local governments acquire more influence. By adopting degrowth, society begins to value locally produced goods, and spreads from urban centres to rural areas. Reduced trade limits the spread of invasive species, but inefficient coordination is an obstacle to management and biosecurity.

Read more: Green growth or degrowth: what is the right way to tackle climate change?

• Lost (in) Europe : Reduced international cooperation and increased social inequality. Pollution, climate change and biodiversity loss get worse. There are fewer invasive species due to reduced trade, but they are barely controlled or managed.

Going beyond direct management

We have used these scenarios to develop a strategy for the management of biological invasions .

The strategy was built around the vision that “by 2050, the harmful impacts of invasive species in Europe (EU member states and non-EU states) are substantially reduced compared to today”, and that we can adapt to the uncertainties arising from the scenarios mentioned above.

This management strategy covers 19 different objectives, grouped into four categories:

Political : improving political competence on the issue, increasing funding, scanning the horizon for future alien species, prioritisation of invasive species, invaded areas and pathways for management.

Research : establishing research networks, detecting gaps in data and knowledge regarding invasive species, and developing critical tools to record and control their spread.

Public awareness : setting up communication strategies, funding to raise awareness, and enhancing public engagement.

Biosecurity : an increase in international and European cooperation, creating a monitoring system and developing systems for rapid response, control, erradication and restoration.

This range of goals highlights the complexity of managing invasive species, and the need to consider actions beyond direct management, such as prevention, eradication and control.

Several of these objectives have been identified by other studies, but the AlienScenarios and InvasiBES projects expand on them, integrating existing knowledge into a comprehensive framework. This framework will guide actions on invasive species in different future scenarios, and help to design a long-term management strategy for biological invasions in Europe.

Main recommendations

Based on the relationship between our goals and the main elements of the management strategy, we have four main recommendations for managing invasive species in Europe :

Establish a dedicated European agency, or an intergovernmental agreement, that has the mandate and resources to regulate and oversee activities related to the management of invasive species.

Establish a cross-sectoral communication strategy on invasive species (including a dedicated curriculum for schools) and a centralised, multilingual communication platform at the European level.

Adopt standard protocols to gather and provide access to data on invasive species, with the aim of guiding management decisions.

Set up a monitoring system to assess biological invasions on a European and national level.

None of these recommendations will be sufficient on their own, but they are the pillars of a long-term strategy for managing biological invasions at the European level. It is time to shift the focus towards a more holistic perspective, one that accounts for the unique situations of different sectors and countries, and that explicitly considers plausible future scenarios.

This article was originally published in Spanish

• Biodiversity
• Invasive species
• The Conversation Europe

Educational Designer

Lecturer, Small Animal Clinical Studies (Primary Care)

Organizational Behaviour – Assistant / Associate Professor (Tenure-Track)

Apply for State Library of Queensland's next round of research opportunities

Associate Professor, Psychology

Why is biodiversity important?

Biodiversity is essential for the processes that support all life on Earth, including humans. Without a wide range of animals, plants and microorganisms, we cannot have the healthy ecosystems that we rely on to provide us with the air we breathe and the food we eat. And people also value nature of itself.

Some aspects of biodiversity are instinctively widely valued by people but the more we study biodiversity the more we see that all of it is important – even bugs and bacteria that we can’t see or may not like the look of. There are lots of ways that humans depend upon biodiversity and it is vital for us to conserve it. Pollinators such as birds, bees and other insects are estimated to be responsible for a third of the world’s crop production. Without pollinators we would not have apples, cherries, blueberries, almonds and many other foods we eat. Agriculture is also reliant upon invertebrates – they help to maintain the health of the soil crops grow in.  Soil is teeming with microbes that are vital for liberating nutrients that plants need to grow, which are then also passed to us when we eat them. Life from the oceans provides the main source of animal protein for many people.

Trees, bushes and wetlands and wild grasslands naturally slow down water and help soil to absorb rainfall. When they are removed it can increase flooding. Trees and other plants clean the air we breathe and help us tackle the global challenge of climate change by absorbing carbon dioxide. Coral reefs and mangrove forests act as natural defences protecting coastlines from waves and storms. 

Many of our medicines, along with other complex chemicals that we use in our daily lives such as latex and rubber, also originate from plants. Spending time in nature is increasingly understood to lead to improvements in people’s physical and mental health. Simply having green spaces and trees in cities has been shown to decrease hospital admissions, reduce stress and lower blood pressure.

Further reading

Plural valuation of nature matters for environmental sustainability and justice by Berta Martin-Lopez, Social-Ecological Systems Institute, Faculty of Sustainability, Leuphana University of Lüneburg, Germany

Climate change and biodiversity

Human activities are changing the climate. Science can help us understand what we are doing to habitats and the climate, but also find solutions.

Email updates

We promote excellence in science so that, together, we can benefit humanity and tackle the biggest challenges of our time.

Subscribe to our newsletters to be updated with the latest news on innovation, events, articles and reports.

What subscription are you interested in receiving? (Choose at least one subject)

ORIGINAL RESEARCH article

Do forest reserves help maintain pollinator diversity and pollination services in tropical agricultural highlands a case study using brassica rapa as a model.

• 1 Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico
• 2 Unidad de Investigación para el Conocimiento, Uso y Valoración de la Biodiversidad, Centro de Estudios Conservacionistas, Universidad de San Carlos de Guatemala, Guatemala City, Guatemala
• 3 Laboratorio de Ecología, Unidad de Biología Tecnología y Prototipos (UBIPRO), Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla de Baz, Estado de México, Mexico

Introduction: Habitat loss and fragmentation have negative impacts on pollinator populations and thus on the pollination services they provide. Negative effects can be lessened by the presence of forest remnants that serve as refuges and sources of food for pollinators. However, few studies have analyzed the influence of highly heterogeneous agricultural landscapes (as commonly found in many developing countries), on pollination services.

Methods: We compared native bee diversity, pollination visitation, and fruit set of Brassica rapa L. between two land use conditions (sites maintaining more than 15% of the original forest coverture [Moderately Modified], and sites with less of 10% [Highly Modified]) in the highlands of Guatemala.

Results: Native bee diversity was higher in HM areas, although social bees were more abundant in MM sites. We did not find differences in pollinator visitation rate between conditions. HM sites were mainly visited by honeybees ( Apis mellifera Linnaeus), while native bees and syrphid flies were more frequent in the MM condition. Fruit set was significantly higher in MM sites and was positively affected by natural forest areas. Experiments on pollen limitation and on pollinator efficiency stressed the importance of native pollinators in fruit production, especially in moderately modified areas.

Discussion: Our results highlight the role of forest remnants for the provision of pollination services in tropical agricultural highlands and underline the relevance of appropriate management of introduced bees such as A. mellifera .

Introduction

Animal-mediated pollination is necessary for sexual reproduction of many wild and cultivated plants, and it is considered a key service provided by ecosystems ( Sharma and Abrol, 2014 ). Most pollinating animals are insects, and bees are considered to be the most important pollinators due to their high abundance and relative efficiency ( Allen-Wardell et al., 1998 ; Buchmann and Nabhan, 1996 ; Kearns et al., 1998 ). Klein et al. (2006) reported at least 75 crops showing an increase in productivity if animal pollinators are available, and these crops represent 35% of global crop production. They also identified that 63 crops are vulnerable to pollinator diversity decline caused by crop intensification and land use change. Estimations of the economic value of pollination services have increased in recent years. In 2016, the estimated worldwide value of pollination was calculated between US $235 and 577 billion ( Kuriakose et al., 2009 ; Ricketts et al., 2004 ). In the particular case of Guatemala, the income derived from exporting coffee and cardamom in 2010, both known to increase fruit production after bee pollination, amounted US $112.5 million, and animal pollinated crops, especially coffee, generated at least 500,000 yearly employments in 2020 ( MAGA, Ministerio de Agricultura, Ganadería y Alimentación, 2020 ).

Pollination services are highly vulnerable to changes in land use and agricultural practices, especially in the tropics, due to accelerating rates of land-use conversion from native vegetation to agriculture, cattle raising and human settlements ( Millard et al., 2021 ). These processes result in fragmentation and loss of natural habitats, disruption of habitat continuity at all temporal and spatial scales ( Lord and Norton, 1990 ) and ultimately produces negative effects on biodiversity and ecosystem integrity ( Aguilar et al., 2006 ; Kearns et al., 1998 ; Michener, 2007 ; Murren, 2002 ; Quesada et al., 2012 ). In particular, transformation and fragmentation of natural habitats have a negative impact on pollinator richness and pollinator abundance ( Aguirre and Dirzo, 2008 ; Kearns et al., 1998 ; Mitchell et al., 2009 ; Redhead et al., 2020 ; Wang et al., 2005 ), which in turn produce a decrease in fruit set of natural and cultivated plants ( Aizen and Feinsinger, 1994 ; Cunningham, 2000 ; Didham et al., 1996 ), changes in plant-pollinator interactions ( Lázaro et al., 2020 ), a substantial decrease in plant heterozygosity and genetic polymorphism in small patches ( Vranckx et al., 2012 ), and/or the extinction of one or the two partners involved in a particular interaction ( Murren, 2002 ).

In spite of the negative effects produced by the transformation of natural spaces, small forest reserves may function as important biological diversity reservoirs and sources of ecosystem services ( Volenec and Dobson, 2020 ). It has been shown that the presence of natural vegetation along with its proximity to agricultural fields ( Bailey et al., 2014 ), may help maintaining diversity and viable populations of pollinators ( De Marco and Coelho, 2004 ). For example, the productivity of crops (such as tomatoes, coffee and chilies) rises if plantations are surrounded by patches of natural forest that serve as habitat to native pollinators ( Greenleaf and Kremen, 2006 ; Landaverde-González et al., 2017 ; Ricketts et al., 2004 ). Hence, landscape configuration and land use heterogeneity may affect populations of wild bees and have repercussions on agricultural production ( Greenleaf and Kremen, 2006 ; Kevan and Phillips, 2001 ; Lázaro et al., 2020 ) and ecosystem functioning. Consequently, landscape management is critical for maintenance of pollination and other ecosystem services ( Shepherd et al., 2003 ).

The role of the presence and configuration of natural areas on several components of pollination services has been studied in intensive single-crop systems, mostly in temperate regions ( Kennedy et al., 2013 ; Kremen et al., 2004 ; Martins et al., 2015 ; Steckel, 2013 ; Steckel et al., 2014 ), but fewer works have addressed this issue in tropical regions ( Aguirre et al., 2010 ; Dáttilo et al., 2015 ; Tscharntke et al., 2005 ), and even less in tropical highlands ( Escobedo-Kenefic et al., 2014 ; Landaverde-González et al., 2018 ).

Unlike intensive agriculture practiced in developed countries ( Millard et al., 2021 ), the non-intensive highly diversified agroforestry practiced in the tropics may play an important role on the conservation of biological diversity, particularly in maintaining pollinator diversity by incrementing both the availability and variety of floral resources ( Jha and Vandermeer, 2010 ; Landaverde-González et al., 2017 ; Vides-Borrell et al., 2019 ). Natural habitat remnants may play a fundamental role on the efficiency of pollination services if they provide nesting refuges for bees and other insect pollinators ( Angelella et al., 2019 ; Li et al., 2020 ).

The Guatemalan highlands, mainly inhabited by Mayan populations, are characterized by a complex mosaic of traditional crops such as beans ( Phaseolus spp.), squash ( Cucurbita spp.), husk tomatoes ( Physalis spp.) and fruit trees, combined with important export crops like coffee ( Coffea arabica ), snow peas ( Pisum sativum var. saccharatum ) and different zucchini varieties ( Cucurbita pepo ) ( Guardiola and Bernal, 2009 ; personal observations), that depend to some degree on insect pollination.

In this manuscript we evaluated the role of forest remnants on pollination services in a highly heterogeneous agricultural landscape of the tropical highlands of Guatemala that has been historically indigenous-managed. Local agriculture is characterized by a combination of traditional and technified practices that allow a highly diverse pattern of land use, as it has been described for other tropical regions with similar historical backgrounds ( Altieri, 2004 ; Vides-Borrell et al., 2019 ).

We hypothesized that forest remnants have a positive effect on pollinator diversity and pollination services in the agricultural highlands of Guatemala. To this end, we evaluated the effects of land use and forest remnants on pollination services on experimental plots located in two contrasting conditions representing different levels of anthropogenic perturbation (measured as percentage of remnant forest) within the Guatemalan highlands. In each site, we established experimental plots of Brassica rapa L. and a set of variables representing different components of pollination services were measured. For every experimental plant, we estimated the diversity of native pollinators visiting each plot, the rate of pollinator visitation, and fruit set. Two additional complementary experiments were performed. In the first one we determined whether higher anthropogenic perturbation is associated with augmented pollination limitation. In the second we analyzed if native species express higher efficiency as pollinators.

The study was conducted in the volcanic highlands in the central part of Guatemala, that extend from the Sierra Madre de Chiapas ( MAGA, Ministerio de Agricultura Ganadería y Alimentación, 2001 ), into the departments of Sacatepéquez and Chimaltenango (91.0211 to 90.6475 W, and 14.6066 to 14.7100 N, municipalities of Sumpango, Patzicía and Patzún; Figure 1 ), from July 2012 to January 2013. This region is prominently agricultural and includes a few municipally managed forests, constituting the most continuous remnants from the original humid montane and low-montane tropical forests dominated by pine ( Pinus ayacahuite, P. hartwegii, P.maximinoi, P. montezumae, P. pseudostrobus ), oak ( Quercus acatenangensis, Q. brachystachys, Q. crispifolia, Q. sapotaefolia ) and alder trees ( Alnus jorulensis ) ( Pérez Irungaray et al., 2018 ). The main crops grown in the area are vegetables, mostly for exportation, and corn for local consumption ( Gálvez and Andrews, 2014 ).

Figure 1 Location of experimental plots (orange circles) in the agricultural highlands of Guatemala. The study sites are delimitated as 2 km radius circular buffers (red). The sites labelled “MM” indicate the moderately modified condition, while the sites labelled “HM” indicate the highly modified condition. Dark green areas represent continuous forest, pale green areas represent fragmented forest areas, yellow and white areas are crops (the lighter color indicates more intensive crops) and dashed areas are settlements. Each experimental plot had 36 B. rapa plants distributed 1 m apart from each other, in a 6x6 grid arrangement. Fruit-set and abundance of pollinator fauna that visited B. rapa were evaluated within the plots. One km buffers from each plot are represented in black lines. The classifications were made from 2012 land use layers ( GIMBOT, Grupo Interinstitucional de Monitoreo de Bosques y Uso de la Tierra, 2014 ).

Since we were interested in determining the effects of forest remnants on pollination services, we chose six locations (sites) with contrasting levels of anthropogenic perturbation. Three sites sustained high levels of agricultural transformation (Highly Modified [HM]) maintaining less than 10% of its original forest coverture (x forest cover % = 6.8 ± 12.95 SD). The other three sites were also dominated by an agricultural landscape but maintained more than 15% of its natural forest area coverage (Moderately Modified [MM]; x forest cover % = 35.7 ± 16.8 SD). Sites were selected based on the presence and extension of forest remnants by using land-use digital maps ( GIMBOT, Grupo Interinstitucional de Monitoreo de Bosques y Uso de la Tierra, 2014 ) and were defined as 2-km radii circular areas ( Figure 1 ).

Study system

B. rapa L. (Brassicaceae) is an annual or biannual herbaceous plant, native to Europe and Asia. The species has been present in Guatemala for a long time and it is used as an edible green vegetable by the indigenous population ( Standley and Steyermark, 1946 ) and is also frequently found as a crop-associated weed, with an annual cycle starting with the rainy season. Plants start flowering approximately one month after sprouting in favorable conditions of light and humidity, although flower production may be affected by environmental conditions ( Kapkoti et al., 2016 ). B. rapa was selected as an experimental model because of its short life cycle, a self-incompatible mating system that makes it highly dependent on insect-mediated cross pollination ( Kuang et al., 2000 ; Sobotka et al., 2000 ), and its long history of cultivation in the study area.

Effects of landscape condition on pollination fauna and B. rapa fruit set

Experimental design.

For each site of the two conditions, we set a minimum of three and maximum of five experimental plots each including 36 B. rapa plants. Experimental plants were grown from seeds obtained from two wild populations (10 plants from each population), located 50 km from each other. Seeds were mixed and sowed in germination trays and maintained inside a greenhouse to homogenize light, temperature and humidity conditions until germination. Individual seedlings were separated and planted in 10-liter plastic bags, grown in natural environment conditions for one month and then transplanted to experimental plots. Plants were positioned in a 6x6 grid arrangement, 1 m apart from each other. Site and position within a plot were randomly assigned for each seedling ( Figure 1 ).

Study site characterization

Patterns of land use around each experimental plot were characterized by estimating the area occupied by natural vegetation (forest and shrubland), grasslands, crops, orchards, and settlements, within a 1000 m radius from the plot. To this end, we used digital maps ( GIMBOT, Grupo Interinstitucional de Monitoreo de Bosques y Uso de la Tierra, 2014 ) and ArcGIS v9.3 ( ESRI Environmental Systems Research Institute, 2008 ). This area included most of the flying ranges of the bee-fauna observed in the study area ( Wolf and Moritz, 2008 ). The area of each land use obtained from the 1000 m radii and was further analyzed by means of principal components analysis (PCA). Scores from each component were then used as composed proxies of the intensity of perturbation.

The composition of the pollinator fauna associated with each plot was characterized by using two independent sampling procedures. First, to determine the composition of the native bee fauna associated to each plot, we made systematic one-hour collections of all bees foraging within a 100-m radius from each experimental plot (but not in the plot itself, Figure 1 ). Collected individuals were sacrificed using potassium cyanide killing jars, labelled, and stored in vials. Specimens were curated and identified to species and morphospecies using taxonomic keys for genera ( Michener, 2007 ) and species ( Ayala Barajas, 1999 ). For each plot, we calculated native bee richness, rarefied richness (Chao1), abundance, and diversity index (natural logarithm Shannon H’). Diversity measures were calculated using PAST 3.0 ( Hammer et al., 2001 ). Independent ANOVAs were applied to test for differences in diversity measures between conditions. In all cases, assumptions of normality (goodness of fit) and homoscedasticity (Levene’s test) were verified. For the rarefied richness test we report the Wilcoxon signed-rank test due to lack of normality. We also performed a principal components analysis (PCA) on covariances to describe native bee species composition in the areas surrounding the experimental plots.

To characterize the pollinator fauna foraging within experimental plots, we made one-hour censuses in which we counted the number of visits and registered the identity of the flower visitors. Censuses were performed by trained observers and frequent visitors (i.e., Apis mellifera L . , native bees, flies, among others) were recorded, while rare species were collected for further identification. Chrysomelid coleopterans were frequently observed but were not included since they are known to feed on B. rapa flowers ( Atmowidi et al., 2007) . Other groups like wasps and butterflies were infrequent visitors (less than 1%) and were not included into the analyses. Collected specimens were processed as described for the native bee samplings. Both native bees and insect visitors’ samplings were performed from November 2012 to January 2013, once for each experimental plot. All samplings were performed from 9:00 AM to 2:00 PM, and while the B. rapa plants were fully blooming.

Differences in visitation rates (number of visits per hour) between conditions, both cumulative and for each taxonomic group, were compared by means of Kruskal-Wallis test since the normality assumption was not achieved. Visitation data was summarized by means of principal components analysis (PCA) and scores from each component were used to test for differences between conditions and among sites within condition on the pollinator fauna that visited the experimental plots.

Analyses evaluating the effects of condition and site nested within condition on landscape composition, native bee fauna and the pollinator fauna visiting experimental plots, were independently performed by using nested ANOVA. In all cases, scores from principal components (land use, native bee fauna or pollinator composition) were used as dependent variables. Normality was verified using the Shapiro-Wilk goodness-of-fit test, and homoscedasticity was tested using the O’Brien test.

Fruit set was evaluated by marking up to 50 inflorescences in each plant. We counted the total number of flowers produced by each inflorescence and the number of fruits once they matured. We tested for differences in fruit set between perturbation conditions using a nested ANOVA. Accordingly, condition, site nested within condition, and plot nested within site and condition were used as independent variables in the model. Fruit set data was normalized with a Johnson Su transformation in combination with a trimmed mean as recommended by Luh and Guo (2001) to control for Type 1 error. Because we were interested in the effect of forest remnants on pollination success, we performed regression analysis between fruit set per plot and our composed proxies of the intensity of perturbation (the scores derived from PCA on land use).

Pollination limitation experiment

Because we hypothesized that forest remnants provide refuge to pollinators, we expected higher levels of pollination limitation in sites within the HM condition in comparison to the MM condition. To this end, we performed a hand-pollination experiment in which we compared the fruit set of hand-pollinated versus open-pollinated (Control) plants in both perturbation conditions. Accordingly, we chose two locations, one for each condition, and 25 B. rapa plants were randomly assigned to each condition (N=100 plants). Plants were kept in 2-liter grow bags throughout the experimental period.

At the flowering onset, flowers from plants in the hand-pollination treatment were marked and hand-pollinated using cotton swabs coated with a mixture of pollen from 10 other plants grown in their same condition. Flowers in plants assigned to the open-pollination treatment (25 plants in each condition) were marked and allowed to be visited by foraging insects. Once fruits matured, we counted the number of mature fruits in each plant (N=1600 flowers). Differences in fruit set between conditions were evaluated by means of a nested least-squares model in which we included condition and treatment nested within condition as independent variables. Experimental plants were grown from seeds produced by randomly mated leftover plants from the same cohort of the plants that was used to estimate fruit set. The experiment was performed from September to December 2017.

Pollination efficiency experiment

To determine the species-specific pollination efficiency of the flower visitors of B. rapa , we performed an experiment in which we recorded the probability of setting a fruit of a single visit performed by a particular species of pollinator. For this experiment, we randomly chose 80 flowering plants that were maintained within an insect-proof mesh enclosure. We then randomly selected the plants that would be used the day before the experiment and marked all the floral buds we though were going to open the next day. The day after we marked the buds, we took the plants outdoors and exposed them to pollinator visitation. Each flower was allowed to be visited only once and then it was covered with a mesh bag to exclude it from additional visitors. Observations were made during the high-activity period of pollinators (from 8:00 to 13:00 h). Each visited flower was tagged and the identity of the visitor annotated (species or the lower possible taxonomic level). After 1 h of exposure, experimental plants were moved back to the enclosure and maintained until fruit maturation or flower wilt. Six plants were used as a negative control and were kept in the mesh room for the entire duration of the experiment. Two weeks after the observations all plants were evaluated and fruit formation was recorded for each visited flower. We annotated whether a pod was produced (1) or not (0). We repeated this procedure 10 days in a row, until we obtained 20 or more visit records of the most common flower visitors. Differences in fruit set among single-visiting taxa were analyzed with Generalized Linear Models with a complementary Log-Log link function, as recommended by Zuur et al. (2009) , since our data set had a large proportion of “successful” fruit production records. The assumption of normality was verified visually using quantile-quantile plots.

The intensity of an interaction depends on the frequency of occurrence multiplied by the magnitude of its fitness consequences as stated by Herrera (1987) and Herrera (1989) . Accordingly, we built a pollination efficiency index for each pollinator species ( PE i ) by multiplying the proportion of visits performed by species i times the fruit set per visit attained by such species:

Where V i stands for the number of visits performed by species i , TV is the total number of visits observed in this experiment and FS i is the average fruit set per visit of species i .

All the ANOVA tests, linear models and PCA used in this study were performed using the JMP statistical software, version 10.0.0 ( SAS Institute Inc, 2012 ).

PCA analysis on landscape use revealed that the two first components accumulated 97.4% of the total land use variance (89.2% and 8.2% for component 1 and 2, respectively). Crop and forest areas had the higher loadings on PC1 but of opposite sign. Hence, high positive score values on PC1 are indicative of plots mainly surrounded by cropped areas (i.e., HM sites), while low or negative score values represent plots with more forested areas (i.e., MM sites, Supplementary Figure S1 ). A nested ANOVA on the first component scores, showed a significant difference between conditions ( F 4,1 = 0.89, P <0.0001) and no effect of sites within condition, thus supporting our classification of perturbation.

Native bee diversity

We collected 473 specimens from a total of 60 bee morphospecies ( Supplementary Table S1 ). Observed richness ( χ 2 1,N=22 = 4.96, P =0.021), Chao1 rarefied richness ( F 1,21 = 5.43, P =0.029) and Shannon diversity values ( F 1,21 = 8.20, P =0.009) were significantly higher in the HM areas than in MM areas ( Figure 2 ), but no significant difference in total abundance between HM and MM was observed ( F 1,21 = 3.27, P =0.09).

Figure 2 Observed richness ( P =0.021), rarefied richness (Chao1; P =0.029), total abundance ( P =0.09) and Shanon H’ diversity index ( P =0.009) of native bees sampled within a 100 m radius from the B rapa experimental plots in the agricultural highlands of Guatemala, by perturbation condition: HM, highly modified; MM, moderately modified, *P<0.05, **P<0.01, ns = not statistically significant.

A PCA analysis on bee species abundances ( Supplementary Figure S2 ) showed a relatively even distribution of eigenvalues, suggesting that species abundances are relatively independent from each other. The first three components accounted for 53.84% of the cumulated variance (21.67%, 16.88%, and 15.3% for components 1, 2 and 3, respectively; Supplementary Table S2 ). The social species Bombus wilmattae Cockerell, 1912, Partamona bilineata Schwarz, 1938 and Plebeia melanica Ayala 1999, had the highest loadings on PC1, while solitary species had the higher loadings on the second and third components ( Supplementary Table S3 ). Nested ANOVA on the scores from PC1 revealed a significant difference between perturbation conditions ( F 4,4 = 0.95, P =0.025), indicating that social species were more abundant in MM sites ( Figure 3 ). Excepting the analysis performed on the scores from PC3, where we found an effect of site within condition ( F 4,4 = 4.044, P =0.017), no other significant effect of condition was found.

Figure 3 Least square means of native bee abundance visiting B. rapa in the agricultural highlands of Guatemala, between the HM (higly modified) and MM (moderately modified) perturbation conditions ( P =0.025). Obtained from the nested ANOVA analysis on the first principal component scores of the PCA on bee species abundance. Bars are constructed from one standard error. HM, orange circle; MM green triangle, * P <0.05.

Floral visitors to B. rapa plots

There was no significant difference in visitation rate ( χ 2 1,N=22 = 0.09, P = 0.764) or by taxonomic group, (wild bees: χ 2 1,N=22 = 0.95, P =0.33; A. mellifera : χ 2 1,N=22 = 0.06, P =0.81; flies: χ 2 1,N=22 = 0.14, P =0.71) between HM and MM conditions. Nevertheless, HM sites had almost twice the number of A. mellifera visits than MM sites ( Figure 4 ). A PCA supported a general strong dominance of A. mellifera . The first principal component accounted for 87.9% of the total variance in pollinator abundance and A. mellifera was by far the most influencing species on PC1 ( Supplementary Table S4 ). Because of this, high scores from this component can be interpreted as plots dominated by A. mellifera , while low values represent plots with a diverse pollinator assemblage (native bees and syrphid flies).

Figure 4 Floral visitation rate of B. rapa insect visitors in the agricultural highlands of Guatemala, between the HM (higly modified) and MM (moderately modified) perturbation conditions, by insect group: bees (all), wild bees, honeybees and wild flies. No significant differences were found between conditions, although HM sites had almost twice honeybee visits in comparison to MM, ns, not statistically significant.

A nested ANOVA explained 64% of the variance in the composition of the pollinator assemblage visiting the experimental plots and showed a significant difference between conditions ( F 1,1 = 4.48, P= 0.049) and among sites within condition ( F 4,4 = 6.58, P= 0.002). While HM sites had a positive least square mean, a negative value was obtained for the MM condition, thus indicating that highly modified sites were dominated by A. mellifera and native bees and syrphid flies were the main pollinators in plots associated to the MM condition ( Supplementary Table S5 ).

Effects of land use on fruit set

Fruit set was significantly higher in the MM condition ( F 1,20 = 83.02, P <0.0001; Figure 5A ). Site ( F 1, 4 = 17.98, P <0.0001) and plot within site ( F 5, 16 = 6.21, P <0.0001) effects were also significant. This result suggests that besides the general effect of HM vs. MM conditions on fruit-set, there is substantial variation among sites and plots. Accordingly, we further explored the relationship between fruit set and the scores from PC1 (obtained from land use areas from 1000 m radii from experimental plots and used as a composed proxy of the intensity of perturbation, Figure 2 ). To this end we performed a linear regression analysis between the scores from PC1 on land use and fruit set per site. Results from this analysis were marginally significant ( F 1,20 = 3.76, P =0.06) suggesting that most of the variance among sites is accounted for by differences in the crop – forest ratio. A regression analysis exploring the effect of forest area on fruit set further supported our hypothesis that forested areas increase pollination success ( F 1,20 = 4.56, P =0.045; R 2  =  0.14, Figure 5B ).

Figure 5 Fruit-set of the experimental B. rapa plots in the agricultural highlands of Guatemala, in the HM (higly modified) and MM (moderately modified) perturbation conditions: (A) mean Johnson Su-transformed fruit-set ( P <0.0001), bars are constructed from one standard error; (B) fruit-set response in B. rapa to forest area within a 1 km radius from each experimental plot, the red line is the fitted least-squares model ( P =0.045; R 2 = 0.14). HM, orange circle; MM, green triangle, *P<0.05, ***P<0.001.

Pollination limitation

We found significant differences between conditions ( F 1,90 = 53.95, P <0.0001) and between pollination treatments (Control vs. Manual) within vegetation conditions ( F 2,90 = 23.54, P <0.0001). The model explained 50.6% of the total variance in fruit set ( F 3,90 = 32.77, P <0.0001). Overall fruit set was significantly higher in the HM condition, thus suggesting environmental factors affected fruit production. Nonetheless, fruit set derived from hand pollination was significantly higher only in the HM condition, thus indicating that pollen limitation occurred in the HM, but not at the MM condition ( Figure 6 ).

Figure 6 Fruit set differences between manual (Man) and open (Ctrl) pollination, nested within the two studied conditions: HM, highly modified (orange circles); MM, moderately modified (green triangles). The bars are constructed from one standard error. Significant differences were found between conditions ( P <0.0001) and between treatments (Man and Crtr, P <0.0001), ***P<0.001.

Pollination efficiency

We recorded 301 single visit observations. The most abundant visitor was A. mellifera accounting for more than twice the number of visits of Trigona fulviventris (Guérin-Méneville, 1845) or P. bilineata ( Table 1 ). These three species accounted for 73.7% of the total number of visits observed in this experiment. The average fruit set per visit showed significant differences among pollinator species (GLM; χ 2 [7, N=293] =21.19, P =0.003). The highest fruit set per visit was attained by three native visitors ( Trigona sp., an unidentified Anthophoridae and P. bilineata ( Table 1 ). Nonetheless, once the frequency of visitation was considered, A. mellifera obtained the highest index of pollination efficiency. Pollination efficiency of T. fulviventris and P. bilineata were identical ( Table 1 ).

Table 1 Visit frequency, proportion of visits, fruit set per visit and pollination efficiency for the most common visitors of B. rapa flowers.

The results from this study support our hypothesis that forest remnants have a positive effect on pollination services in the agricultural highlands of Guatemala. We found a significant relationship between the presence and extent of forested areas and the fruit set of B. rapa , an annual, self-incompatible, insect pollinated plant we used to tally pollination services at our study site. The higher fruit set observed in sites within the moderately modified condition was associated with pollinator fauna dominated by social native bees and syrphid flies, while A. mellifera was the dominant species at highly modified locations. Hence, although both richness and diversity of native bees was higher at HM sites and no differences in flower visitation between conditions were found, the dominance of native bees in MM plots seem to explain the observed differences in fruit set. We also found a positive effect of forest area on fruit set, thus suggesting these sites may function as nesting sites and refugees for native bees, especially social bees. Furthermore, pollination limitation and pollination efficiency experiments showed that pollination limitation was evident only in the HM condition. A. mellifera was the most efficient pollinator because of its abundance, but the highest efficiency per visit was attained by three native pollinators. In short, our results suggest that the positive effect of the presence and extent of forested areas on fruit set is associated with healthier populations of native bees (especially social bees), which in turn are better per capita pollinators. Overall, these findings point out the complex relationship underlying crop production and conservation and stress the relevance of maintaining natural areas around agricultural settings.

As indicated by our analyses, HM and MM conditions showed significant differences in both land use and native bee composition. The landscape composition of the HM sites was dominated by croplands and included most human settlements. The MM sites, in contrast, were mainly characterized by a higher proportion of natural forested areas, shrublands and orchards. Interestingly, PCA performed on land use variables supported the above interpretation and further revealed that the two conditions we used in this study (HM and MM) represent extremes of a perturbation continuum ranging from crop dominated sites to more forested areas. Consequently, the Guatemalan highlands constitute a complex mosaic of perturbation, which in turn influences the composition of native bees’ fauna. Plots within the HM condition showed higher richness and diversity of native bees, but highly efficient social bees such as Partamona bilineata, Plebeia melanica and Bombus wilmattae were more abundant in MM plots. It has been shown that diversified agriculture, as the one observed at the Guatemalan highlands, can promote pollinator diversity due to a more varied offer of floral resources ( Basu et al., 2016 ). Moreover, flower rich agriculture and urban areas may promote bee diversity more than mature forests, such as pine and oak forests ( Du Clos et al., 2020 ). Although general floral resource availability was not measured in this study, our results support this interpretation since HM sites are dominated by agricultural areas and maintain a richer and diverse community of native bees. Floral resource richness, indeed, has been found to be an important driver of bee diversity in other studies in the region ( Landaverde-González et al., 2017 ) and in the study area ( Escobedo-Kenefic et al., 2020 ). Social bees, on the other hand, were more abundant at the HM sites, suggesting these species are more dependent on forested areas and rely less on floral resource richness. These findings agree with other studies performed in the same area showing that native bumblebees are positively associated with natural forest, while stingless bees are negatively affected by habitat fragmentation ( Escobedo-Kenefic et al., 2020 ). Overall, these results suggest that forest remnants could function as refuges and nesting places that are scarce in open areas ( Kline and Joshi, 2020 ; Roubik, 1983 ; Samejima et al., 2004 ).

Interestingly, we did not find a significant effect of perturbation condition on visitation rate, but we did find a striking difference in the composition of the fauna visiting HM versus MM experimental plots. HM plots were dominated by A. mellifera , probably due to its higher tolerance to perturbation, and because apiculture is a common activity in the study area ( López Cárcamo, 2013 ), and frequently carried out close to populated settlements and agricultural areas, like the HM sites (personal observations). Wild native bees and flies, in contrast, were more frequent in MM plots. A comprehensive study analyzing the patterns of honeybee dominance throughout Brazil also found this species dominates highly disturbed communities due to its extremely high abundance and developed sociality ( Aizen et al., 2020 ; Garibaldi et al., 2013 ). On the other hand, the presence of honeybees may negatively affect native bees through exploitative competition, changes in plant communities, or transmission of pathogens ( Mallinger et al., 2017 ). Hence, besides the potentially negative effect of the presence of honeybees, native bees also experience the negative effects of habitat loss-reduction, less diverse floral resources, and loss of nesting sites brought about by habitat degradation ( Bennett and Isaacs, 2014 ). The dominance of A. mellifera in HM plots, could help explaining the observed difference in fruit set between HM and MM plots. MM plots sustained a significant higher fruit set than that obtained under the HM condition. Several studies have demonstrated that while A. mellifera is a very efficient nectar and pollen forager, this efficiency is not necessarily translated into pollination success ( Osorio-Beristain et al., 1997 ; Valido et al., 2019 ; Watts et al., 2013 ; Westerkamp, 1991 ; but see Hung et al., 2018 ). For example, by analyzing 41 insect pollinated crop systems worldwide, Garibaldi et al. (2013) found that wild insect pollinated crops increased fruit set by a factor of two when compared with honeybee visitation. Interestingly, honeybee and wild insect pollination were complementary instead of competitive, thus indicating that crop yield would benefit from the pollination services of both honeybees and native pollinators ( Garibaldi et al., 2013 ). Accordingly, if the combined effect of A. mellifera dominance in HM plots, along with its characteristic extreme pollen collection/deposition ratio ( Sun et al., 2013 ; Watts et al., 2013 ; Wilson and Thomson, 1991 ) resulted in a pollen shortage within HM plots, both the lower fruit set and pollen limitation observed in these sites could be explained. This is further supported by the lack of significant differences in the rates of pollinator visitation and by the per capita pollinator efficiency of A. mellifera .

Agroforestry management has been found to provide food and nesting resources to wild bees and promote pollination services ( Kay et al., 2020 ). Our results show a positive effect of natural areas on the pollination success and fruit production of B. rapa , an insect-pollinated plant. Other insect pollination-dependent crops that are grown in the study area are economically important; and therefore, such a decrease in fruit production could have significant implications for local economies in the study area, as well as in other important agricultural zones of the country. We strongly recommend that regional management policies consider the importance of preserving forest remnants, and their continuity, in sustaining and improving pollination services.

Conclusions

In this study we found a positive relationship with the presence of forested area and the fruit set of our model plant, B. rapa , that may be explained by the association between forest areas and native insect pollinators. Native bees were found to have the highest pollinating efficiency for single visits and thus may be key pollinators in our study system. Our results highlight the importance of forest remnants to maintaining pollinator diversity and pollination service in tropical agricultural highlands. Finally, results from this study also suggest that more studies addressing the impact of beekeeping on native pollinators and pollination services in general, would aid in improving our ability to develop better ecosystem management.

Data availability statement

The original contributions presented in the study are publicly available. This data can be found here: Mendeley Data, https://data.mendeley.com/datasets/6jw833yrt4/1 .

Ethics statement

The manuscript presents research on animals that do not require ethical approval for their study.

Author contributions

NE-K: Writing – review & editing, Writing – original draft, Supervision, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. EC: Writing – review & editing, Writing – original draft, Validation, Project administration, Investigation, Data curation. MA: Writing – review & editing, Writing – original draft, Validation, Supervision, Conceptualization. CD: Writing – review & editing, Writing – original draft, Visualization, Supervision, Methodology, Formal analysis, Conceptualization.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by the Universidad de San Carlos de Guatemala (USAC) and the Universidad Nacional Autónoma de México (UNAM) by providing human and logistical resources, and laboratory facilities.

Acknowledgments

We thank the Posgrado en Ciencias Biológicas, Universidad Nacional Autónoma de Mexico, for its support in the conception and design of this work, which constitutes a part of the thesis of NE-K to acquire the Doctoral Degree. We also thank the Centro de Estudios Conservacionistas, Facultad de Ciencias Químicas y Farmacia, Universidad de San Carlos de Guatemala, for providing logistical support, and the Instituto de Ciencia y Tecnología Agrícolas, for hosting and supporting the field experiments. We also thank Terry Griswold for aiding in taxonomic identification of bees, Andrea Aguilera and Oscar Martínez for field work support, and Eunice Enríquez for her continued support.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/frbee.2024.1393431/full#supplementary-material

Aguilar R., Ashworth L., Galetto L., Aizen M. A. (2006). Plant reproductive susceptibility to habitat fragmentation: review and synthesis through a meta-analysis. Ecol. Lett. 9, 968–980. doi: 10.1111/j.1461-0248.2006.00927.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Aguirre A., Dirzo R. (2008). Effects of fragmentation on pollinator abundance and fruit set of an abundant understory palm in a Mexican tropical forest. Biol. Conserv. 141, 375–384. doi: 10.1016/j.biocon.2007.09.014

CrossRef Full Text | Google Scholar

Aguirre A., Guevara R., Dirzo R. (2010). Effects of forest fragmentation on assemblages of pollinators and floral visitors to male- and female-phase inflorescences of Astrocaryum mexicanum (Arecaceae) in a Mexican rain forest. J. Trop. Ecol. 27, 25–33. doi: 10.1017/S0266467410000556

Aizen M. A., Arbetman M. P., Chacoff N. P., Chalcoff V. R., Feinsinger P., Garibaldi, et al. (2020). Invasive bees and their impact on agriculture. Adv. Ecol. Res. 63, 49–92. doi: 10.1016/bs.aecr.2020.08.001

Aizen M. A., Feinsinger P. (1994). Forest fragmentation, pollination, and plant reproduction in a Chaco dry forest, Argentina. Ecology. 75, 330–351. doi: 10.2307/1939538

Allen-Wardell G., Bernhardt P., Bitner R., Burquez A., Buchmann S., Cane J., et al. (1998). The potential consequences of pollinator declines on the conservation of biodiversity and stability of food crop yields. Conserv. Biol. 12 (1), 8–17. Available at: http://www.jstor.org/stable/2387457 .

Google Scholar

Altieri M. (2004). Linking ecology and traditional farmers in the search for sustainable agriculture. Front. Ecol. Environ. 2, 35–42. doi: 10.1890/1540-9295(2004)002[0035:LEATFI]2.0.CO;2

Angelella G. M., Stange L., Scoggins H. L., O’Rourke M. E. (2019). Pollinator refuge establishment and conservation value: Impacts of seedbed preparations, seed mixtures, and herbicides. HortScience 54, 445–451. doi: 10.21273/HORTSCI13600-18

Atmowidi T., Buchori D., Manuwoto S., Suryobroto B., Hidayat P. (2007). Diversity of pollinator insects in relation to seed set of mustard (Brassica rapa L.: Cruciferae). HAYATI J. Biosci. 14, 155–161. doi: 10.4308/hjb.14.4.155

Ayala Barajas R. (1999). Revisión de las abejas sin aguijón de México (Hymenoptera: Apidae: Meliponini). Folia Entomol. Mex. 123, 1–123.

Bailey S., Requier F., Nusillard B., Roberts S. P. M., Potts S. G., Bouget C. (2014). Distance from forest edge affects bee pollinators in oilseed rape fields. Ecol. Evol. 4, 370–380. doi: 10.1002/ece3.924

Basu P., Parui A. K., Chatterjee S., Dutta A., Chakraborty P., Roberts S., et al. (2016). Scale dependent drivers of wild bee diversity in tropical heterogeneous agricultural landscapes. Ecol. Evol. 6, 6983–6992. doi: 10.1002/ece3.2360

Bennett A. B., Isaacs R. (2014). Landscape composition influences pollinators and pollination services in perennial biofuel plantings. Agric. Ecosyst. Environ. 193, 1–8. doi: 10.1016/j.agee.2014.04.016

Buchmann S. L., Nabhan G. P. (1996). The forgotten pollinators (Washington D.C., USA: Island Press).

Cunningham S. A. (2000). Depressed pollination in habitat fragments causes low fruit. Proc. R. Soc B. Biol. Sci. 267, 1149–1152. Available at: https://www.jstor.org/stable/2665737 .

Dáttilo W., Aguirre A., Quesada M., Dirzo R. (2015). Tropical forest fragmentation affects floral visitors but not the structure of individual-based palm-pollinator networks. PloS One 10, 1–15. doi: 10.1371/journal.pone.0121275

De Marco P., Coelho F. M. (2004). Services performed by the ecosystem: forest remnants influence agricultural cultures’ pollination and production. Biodivers. Conserv. 13, 1245–1255. doi: 10.1023/B:BIOC.0000019402.51193.e8

Didham R. K., Ghazoul J., Stork N. E., Davis A. J. (1996). Insects in fragmented forests: a functional approach. Trends Ecol. Evol. 11, 255–260. doi: 10.1016/0169-5347(96)20047-3

Du Clos B., Drummond F. A., Loftin C. S. (2020). Noncrop habitat use by wild bees (Hymenoptera: Apoidea) in a mixed-use agricultural landscape. Environ. Entomol 49, 502–515. doi: 10.1093/ee/nvaa001

Escobedo-Kenefic N., Dardón M., López J., Martínez O., Cardona E. (2014). Efecto de la configuración del paisaje en las comunidades de abejas (Apoidea) de un mosaico de pino-encino y áreas agrícolas de Sacatepéquez y Chimaltenango, Guatemala. Ciencia Tecnología y Salud. 1, 13–20. doi: 10.36829/63CTS.v1i1.1

Escobedo-Kenefic N., Landaverde-González P., Theodorou P., Cardona E., Dardón M. J., Martínez O., et al. (2020). Disentangling the effects of local resources, landscape heterogeneity and climatic seasonality on bee diversity and plant-pollinator networks in tropical highlands. Oecologia 194, 333–344. doi: 10.1007/s00442-020-04715-8

ESRI Environmental Systems Research Institute (2008). ArcGIS Desktop: Release 9.3 (Redlands, California, USA: Environmental Systems Research Institute).

Gálvez J., Andrews K. L. (2014). Perfil del agro y la ruralidad de Guatemala 2014: Situación actual y tendencias . Ed. Cleaves C. (Guatemala: Universidad Rafael Landívar/Instituto de Agricultura, Recursos Naturales y Ambiente IARNA, Instituto Interamericano de Cooperación para la Agricultura IICA).

Garibaldi L. A., Steffan-Dewenter I., Winfree R., Aizen M. A., Bommarco R., Cunningham, et al. (2013). Wild pollinators enhance fruit set of crops regardless of honey bee abundance. Science 339, 1608–1611. doi: 10.1126/science.1230200

GIMBOT, Grupo Interinstitucional de Monitoreo de Bosques y Uso de la Tierra (2014). Mapa de bosques y uso de la tierra 2012 y Mapa de cambios en uso de la tierra 2001- 2010 para estimación de emisiones de gases de efecto invernadero (Guatemala: Universidad del Valle de Guatemala, Consejo Nacional de Áreas Protegidas, Instituto Nacional de Bosques, Ministerio de Agricultura, Ganadería y Alimentación, Ministerio de Ambiente y Recursos Naturales, Facultad de Agronomía de la Universidad de San Carlos de Guatemala). Available at: https://chm.cbd.int/api/v2013/documents/7023F81E-EFBD-F578-8B84-4E4045E2E8A3/attachments/209762/Cambios%20de%20uso%20de%20tierra%202001-2010.pdf .

Greenleaf S. S., Kremen C. (2006). Wild bee species increase tomato production and respond differently to surrounding land use in Northern California. Biol. Conserv. 133, 81–87. doi: 10.1016/j.biocon.2006.05.025

Guardiola J., Bernal J. (2009). Factores influyentes en la adopción de cultivos no tradicionales: el caso de Guatemala. Agroalimentaria 15, 27–39. Available at: https://ve.scielo.org/scielo.php?pid=S1316-03542009000200004&script=sci_abstract .

Hammer Ø., Harper D., Ryan P. (2001). Past: Paleontological statistics software package for education and data analysis. Paleontol. Electron. 4, 1–9. Available at: https://palaeo-electronica.org/2001_1/past/past.pdf .

Herrera C. M. (1987). Components of pollinator “quality”: comparative analysis of a diverse insect assemblage. Oikos. 50, 79–90. doi: 10.2307/3565403

Herrera C. M. (1989). Pollinator abundance, morphology, and flower visitation rate: analysis of the “quantity” component in a plant-pollinator system. Oecologia 80, 241–248. doi: 10.1007/BF00380158

Hung K. J., Kingston J. M., Albrecht M., Holway D. A., Kohn J. R. (2018). The worldwide importance of honey bees as pollinators in natural habitats. Proc. R. Soc B Biol. Sci. 285, 20172140. doi: 10.1098/rspb.2017.2140

Jha S., Vandermeer J. (2010). Impacts of coffee agroforestry management on tropical bee communities. Biol. Conserv. 146, 1423–1431. doi: 10.1016/j.biocon.2010.03.017

Kapkoti B., Rawal R. S., Joshi R. K. (2016). ). Insect pollinators of Brassica campestris in Kumaun, West Himalaya: influence of crop composition, altitude and flowering phenology. Natl. Acad. Sci. Lett. 39, 389–394. doi: 10.1007/s40009-016-0500-y

Kay S., Kühn E., Albrecht M., Sutter L., Szerencsits E., Herzog F. (2020). Agroforestry can enhance foraging and nesting resources for pollinators with focus on solitary bees at the landscape scale. Agrofor. Syst. 94, 379–387. doi: 10.1007/s10457-019-00400-9

Kearns C. A., Inouye D. W., Waser N. M. (1998). Endangered mutualisms: the conservation of plant pollinator interactions. Annu. Rev. Ecol. Evol. Syst. 29, 83–112. doi: 10.1146/annurev.ecolsys.29.1.83

Kennedy C. M., Lonsdorf E., Neel M. C., Williams N. M., Ricketts T. H., Winfree R., et al. (2013). A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems. Ecol. Lett. 16, 584–599. doi: 10.1111/ele.12082

Kevan P. G., Phillips T. P. (2001). The economic impacts of pollinator declines: an approach to assessing the consequences. Conserv. Ecol. 5 (1), 8. doi: 10.5751/ES-00272-050108

Klein A. M., Vaissière B. E., Cane J. H., Steffan-Dewenter I., Cunningham S. A., Kremen C., et al. (2006). Importance of pollinators in changing landscapes for world crops. Proc. R Soc. B Biol. Sci. 274, 303–313. doi: 10.1098/rspb.2006.3721

Kline O., Joshi N. K. (2020). Mitigating the effects of habitat loss on solitary bees in agricultural ecosystems. Agriculture. 10, 115. doi: 10.3390/agriculture10040115

Kremen C., Williams N. M., Bugg R. L., Fay J. P., Thorp R. W. (2004). The area requirements of an ecosystem service: crop pollination by native bee communities in California. Ecol. Lett. 7, 1109–1119. doi: 10.1111/j.1461-0248.2004.00662.x

Kuang A., Popova A., Xiao Y., Musgrave M. E. (2000). Pollination and embryo development in Brassica rapa L. @ in microgravity. Int. J. Plant Sci. 161, 203–211. doi: 10.1086/314254

Kuriakose G., Sinu P. A., Shivanna K. R. (2009). Domestication of cardamom (Elettaria cardamomum) in Western Ghats, India: divergence in productive traits and a shift in major pollinators. Ann. Bot. 103, 727–733. doi: 10.1093/aob/mcn262

Lázaro A., Fuster F., Alomar D., Totland Ø. (2020). Disentangling direct and indirect effects of habitat fragmentation on wild plants’ pollinator visits and seed production. Ecol. Appl. 30, 1–13. doi: 10.1002/eap.2099

Landaverde-González P., Baltz L., Escobedo-Kenefic N., Mérida J., Paxton R. J., Husemann M. (2018). Recent low levels of differentiation in the native Bombus ephippiatus (Hymenoptera: Apidae) along two Neotropical mountain-ranges in Guatemala. Biodivers. Conserv. 27, 3513–3531. doi: 10.1007/s10531-018-1612-0

Landaverde-González P., Quesada-Euán J., Theodorou P., Murray T., Husemann M., Ayala R., et al. (2017). Sweat bees on hot chilies: provision of pollination services by native bees in traditional slash-and-burn agricultural in Yucatán Peninsula of Tropical Mexico. J. Appl. Ecol. 54, 1814–1824. doi: 10.1111/1365-2664.12860

Li P., Kleijn D., Bandenhausser I., Zaragoza-Trello C., Gross N., Raemakers I., et al. (2020). The relative importance of green infrastructure as refuge habitat for pollinators increases with local land-use intensity. J. Appl. Ecol. 57, 1491–1503. doi: 10.1111/1365-2664.13658

López Cárcamo P. C. (2013). Caracterización microbiológica del polen de abeja melífera (Apis mellifera L.) comercializado por siete productores apícolas ubicados en los departamentos de Escuintla, Huehuetenango, Jalapa, Sacatepéquez, San Marcos, Sololá y Suchitepéquez [Biology Degree Thesis] (Biblioteca USAC: Universidad de San Carlos de Guatemala). Available at: http://biblioteca.usac.edu.gt/tesis/06/06_3529.pdf .

Lord J. M., Norton D. A. (1990). Scale and the spatial concept of fragmentation. Conserv. Biol. 4, 197–202. doi: 10.1111/j.1523-1739.1990.tb00109.x

Luh W. M., Guo J. H. (2001). Using Johnson’s transformation and robust estimators with heteroscedastic test statistics: An examination of the effects of non-normality and heterogeneity in the non-orthogonal two-way ANOVA design. Br. J. Math. Stat. Psychol. 54, 79–94. doi: 10.1348/000711001159438

MAGA, Ministerio de Agricultura Ganadería y Alimentación. (2001). Mapa Fisiográfico-Geomorfológico de la República de Guatemala .

MAGA, Ministerio de Agricultura, Ganadería y Alimentación. (2020). Available at: https://www.maga.gob.gt/maga-impulsa-emprendimiento-de-pequenos-caficultores/ .

Mallinger R. E., Gaines-Day H. R., Gratton C. (2017). Do managed bees have negative effects on wild bees?: A systematic review of the literature. PloS One 8, e0189268. doi: 10.1371/journal.pone.0189268

Martins K. T., Gonzalez A., Lechowicz M. J. (2015). Pollination services are mediated by bee functional diversity and landscape context. Agric. Ecosyst. Environ. 200, 12–20. doi: 10.1016/j.agee.2014.10.018

Michener C. D. (2007). The bees of the world (2nd ed.) (Baltimore: The Johns Hopkins University Press, Baltimore, USA).

Millard J., Outhwaite C. L., Kinnersley R., Freeman R., Gregory R. D., Adedoja O., et al. (2021). Global effects of land-use intensity on local pol-linator biodiversity. Nat. Commun. 12, 1–11. doi: 10.1038/s41467-021-23228-3

Mitchell R. J., Irwin R. E., Flanagan R. J., Karron J. D. (2009). Ecology and evolution of plant-pollinator interactions. Ann. Bot. 103, 1355–1363. doi: 10.1093/aob/mcp122

Murren C. (2002). Effects of habitat fragmentation on pollination: pollinators, pollinia viability and reproductive success. J. Ecol. 90, 100–107. doi: 10.1046/j.0022-0477.2001.00638.x

Osorio-Beristain M., Domínguez C. A., Eguiarte L. E., Benrey B. (1997). Pollination efficiency of native and invading Africanized bees in the tropical dry forest annual plant, Kallstroemia grandiflora Torr ex Gray. Apidologie. 28, 11–16. doi: 10.1051/apido:19970102

Pérez Irungaray G. E., Rosito Monzón J. C., Maas Ibarra R. E., Gándara Cabrera G. A. (2018) Ecosistemas de Guatemala basado en el Sistema de Clasificación de Zonas de Vida (IARNA-URL, Ed.) . Available at: http://www.infoiarna.org.gt/wp-content/uploads/2019/02/Ecosistemas-de-Guatemala-final.pdf .

Quesada M., Rosas F., Lopezaraiza-Mikel M., Aguilar R., Ashworth L., Rosas-Guerrero, et al. (2012). “Ecología y conservación biológica de sistemas de polinización en plantas tropicales”, Ecología y evolución las interacciones bióticas . Eds. Val Del E., Boege K. (México: Ediciones Científicas Universitarias, UNAM), 76–101.

Redhead J. W., Powney G. D., Woodcock B. A., Pywell R. F. (2020). Effects of future agricultural change scenarios on beneficial insects. J. Environ. Manage. 265, 110550. doi: 10.1016/j.jenvman.2020.110550

Ricketts T. H., Daily G. C., Ehrlich P. R., Michener C. D. (2004). Economic value of tropical forest to coffee production. Proc. Natl. Acad. Sci. U.S.A. 101, 12579–12582. doi: 10.1073/pnas.0405147101

Roubik D. W. (1983). Nest and Colony Characteristics of Stingless Bees from Panamá (Hymenoptera: Apidae). J. Kans. Entomol. Soc . 56, 327–355. Available at: https://www.jstor.org/stable/25084419 .

Samejima H., Marzuki M., Nagamitsu T., Nakasizuka T. (2004). The effects of human disturbance on a stingless bee community in a tropical rainforest. Biol. Conserv. 120, 577–587. doi: 10.1016/J.BIOCON.2004.03.030

SAS Institute Inc (2012). JMP®, Version 10.0.0 (Cary, North Carolina, USA).

Sharma D., Abrol D. P. (2014). “Role of pollinators in sustainable farming and livelihood security,” in Beekeeping for poverty alleviation and livelihood security . Eds. Gupta R. K., Reybroeck W., Veen van J., Gupta A. (Springer Nature), 379–411.

Shepherd M., Buchmann S. L., Vaughan M., Hoffman Black S. (2003). Pollinator conservation handbook . (Portland, Oregon, USA: The Xerces Society for Invertebrate Conservation), 145.

Sobotka R., Sáková L., Curn V. (2000). Molecular mechanisms of self-incompatibility in Brassica. Curr. Issues. Mol. Biol. 2, 103–112.

PubMed Abstract | Google Scholar

Standley P. C., Steyermark J. A. (1946). Flora of Guatemala . (Fieldiana: Botany, part IV, Chicago Ilinois, USA, Chicago Natural History Museum), 356–357.

Steckel J. (2013). Effects of landscape heterogeneity and land use on interacting groups of solitary bees, wasps and their flying and ground-dwelling antagonists . Doctoral Disertation, Julius-Maximilians-Universität Würzburg, Germany.

Steckel J., Westphal C., Peters M. K., Bellach M., Rothenwöhrer C., Erasmi S., et al. (2014). Landscape composition and configuration differently affect trap-nesting bees, wasps and their antagonists. Biol. Conserv. 172, 56–64. doi: 10.1016/j.biocon.2014.02.015

Sun S. G., Huang S. Q., Gu Y. H. (2013). Pollinator shift to managed honeybees enhances reproductive output in a bumblebee-pollinated plant. Plant Sys.t Evol. 299, 139–150. doi: 10.1007/s00606-012-0711-8

Tscharntke T., Klein A. M., Kruess A., Steffan-Dewenter I., Thies C. (2005). Landscape perspectives on agricultural intensification and biodiversity - Ecosystem service management. Ecol. Lett. 8, 857–874. doi: 10.1111/j.1461-0248.2005.00782.x

Valido A., Rodríguez-Rodríguez M. C., Jordano P. (2019). Honeybees disrupt the structure and functionality of plant-pollinator networks. Sci. Rep. 9, 4711. doi: 10.1038/s41598-019-41271-5

Vides-Borrell E., Porter-Bolland L., Fergunson, Gasselin P., Vaca R., Valle-Mora J., et al. (2019). Polyculture, pastures and monocultures: Effects of land use intensity on wild bee diversity in tropical landscapes of southeastern Mexico. Biol. Conserv. 236, 269–280. doi: 10.1016/j.biocon.2019.04.025

Volenec Z. M., Dobson A. P. (2020). Conservation value of small reserves. Conserv. Biol. 34, 66–79. doi: 10.1111/cobi.13308

Vranckx G., Jacquemyn H., Muys B., Honnay O. (2012). Meta-analysis of susceptibility of woody plants to loss of genetic diversity through habitat fragmentation. Conserv. Biol. 26, 228–237. doi: 10.1111/j.1523-1739.2011.01778.x

Wang R., Yang C., Zhao G., Yang J. (2005). Fragmentation effects on diversity of wasp community and its impact on fig/fig wasp interaction in Ficus racemosa L. J. Integr. Plant Biol. 47, 20–26. doi: 10.1111/j.1744-7909.2005.00003.x

Watts S., Sapir Y., Segal B., Dafni A. (2013). The endangered Iris atropurpurea (Iridaceae) in Israel: Honey-bees, night-sheltering male bees and female solitary bees as pollinators. Ann. Bot. 111, 395–407. doi: 10.1093/aob/mcs292

Westerkamp C. (1991). Honeybees are poor pollinators — why? Plant Syst. Evol. 177, 71–75. Available at: http://www.jstor.org/stable/23674659 .

Wilson P., Thomson J. D. (1991). Heterogeneity among floral visitors leads to discordance between removal and deposition of pollen. Ecology 72, 1503–1507. doi: 10.2307/1941124

Wolf S., Moritz R. F. A. (2008). Foraging distance in Bombus terrestris L. (Hymenoptera: Apidae). Apidologie 39, 419–427.

Zuur A., Ieno E. N., Walker N., Saveliev A. A., Smith G. M. (2009). Mixed effects models and extensions in ecology with R (Springer New York, NY). doi: 10.1007/978-0-387-87458-6

Keywords: fruit set, Guatemala, landscape disturbance, land use, native bees

Citation: Escobedo-Kenefic N, Cardona E, Arizmendi MdC and Domínguez CA (2024) Do forest reserves help maintain pollinator diversity and pollination services in tropical agricultural highlands? A case study using Brassica rapa as a model. Front. Bee Sci. 2:1393431. doi: 10.3389/frbee.2024.1393431

Received: 29 February 2024; Accepted: 02 July 2024; Published: 26 July 2024.

Reviewed by:

Copyright © 2024 Escobedo-Kenefic, Cardona, Arizmendi and Domínguez. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: César A. Domínguez, [email protected] ; Natalia Escobedo-Kenefic, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

share this!

July 17, 2024

This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:

fact-checked

trusted source

written by researcher(s)

Biodiversity loss impacts societies and economies: How can Europe confront the spread of invasive species?

by Núria Roura-Pascual, The Conversation

Biological invasions are the main cause of biodiversity loss, but they can also have serious social and economic repercussions. In Europe, over 13,000 non-native (or "alien") species have an established presence, around 1,500 of which are invasive species that have a negative impact on their surroundings. Species of particular concern are the brown rat, raccoon, red swamp crayfish, tiger mosquito, varroa mite, ragweed, and ailanthus, among many others .

Various studies have predicted that by 2050, the number of non-native species in Europe will grow by as much as 64%. This estimate assumes that current trends will continue unchanged. However, the number and repercussions of invasive species depend on a range of environmental and socioeconomic factors that will evolve in ways that are hard to predict.

Four possible future scenarios

Researchers, managers and policymakers from various countries have developed four qualitative scenarios on the future of biological invasions up to 2050 . This was done as part of the AlienScenarios and InvasiBES projects.

The scenarios are not predictions as such—they are narrative descriptions and accounts of what could happen in the future under a range of different circumstances.

In particular, our scenarios take into account the socio-ecological developments that are critical for invasive species, and they are more biodiversity-focused than other global change scenarios, such as the shared socioeconomic pathways (SSPs) used by many climate change reports. The scenarios are as follows:

Big Tech rules Europe : Distrust of governments leads to companies having increased power, while populations concentrate in cities and suffer economic hardship. An increase in invasive species and a reduction in their coordinated management .

Technological (pseudo-)panacea : Rapid technological development, large trade volumes and high biosecurity. European societies concentrate in "smart cities." The rate of invasive species spreading and becoming established is low due to solid, strict biosecurity measures.

Green local governance : Local governments acquire more influence. By adopting degrowth, society begins to value locally produced goods, and spreads from urban centers to rural areas. Reduced trade limits the spread of invasive species, but inefficient coordination is an obstacle to management and biosecurity.

• Lost (in) Europe : Reduced international cooperation and increased social inequality. Pollution, climate change and biodiversity loss become worse. There are fewer invasive species due to reduced trade, but they are barely controlled or managed.

Going beyond direct management

We have used these scenarios to develop a strategy for the management of biological invasions .

The strategy was built around the vision that "by 2050, the harmful impacts of invasive species in Europe (EU member states and non-EU states) are substantially reduced compared to today," and that we can adapt to the uncertainties arising from the scenarios mentioned above.

This management strategy covers 19 different objectives, grouped into four categories:

Political : improving political competence on the issue, increasing funding, scanning the horizon for future alien species, prioritization of invasive species, invaded areas and pathways for management.

Research : establishing research networks, detecting gaps in data and knowledge regarding invasive species, and developing critical tools to record and control their spread.

Public awareness : setting up communication strategies , funding to raise awareness, and enhancing public engagement.

Biosecurity : an increase in international and European cooperation, creating a monitoring system and developing systems for rapid response, control, eradication and restoration.

This range of goals highlights the complexity of managing invasive species, and the need to consider actions beyond direct management, such as prevention, eradication and control.

Several of these objectives have been identified by other studies, but the AlienScenarios and InvasiBES projects expand on them, integrating existing knowledge into a comprehensive framework. This framework will guide actions on invasive species in different future scenarios, and help to design a long-term management strategy for biological invasions in Europe.

Main recommendations

Based on the relationship between our goals and the main elements of the management strategy, we have four main recommendations for managing invasive species in Europe :

• Establish a dedicated European agency, or an intergovernmental agreement, that has the mandate and resources to regulate and oversee activities related to the management of invasive species.
• Establish a cross-sectoral communication strategy on invasive species (including a dedicated curriculum for schools) and a centralized, multilingual communication platform at the European level.
• Adopt standard protocols to gather and provide access to data on invasive species, with the aim of guiding management decisions.
• Set up a monitoring system to assess biological invasions on a European and national level.

None of these recommendations will be sufficient on their own, but they are the pillars of a long-term strategy for managing biological invasions at the European level. It is time to shift the focus towards a more holistic perspective, one that accounts for the unique situations of different sectors and countries, and that explicitly considers plausible future scenarios.

Provided by The Conversation

Explore further

Feedback to editors

Saturday Citations: E-bike accident spike; epigenetics in memory formation; Komodo dragons now scarier

2 hours ago

Spacecraft to swing by Earth, moon on path to Jupiter

5 hours ago

New process uses light and enzymes to create greener chemicals

Outsourcing conservation in Africa: NGO management reduces poaching and boosts tourism, but raises risks for civilians

Two shark species documented in Puget Sound for first time

6 hours ago

New study disputes Hunga Tonga volcano's role in 2023–24 global warm-up

20 hours ago

New self-powered electrostatic tweezer enhances object manipulation and microfluidics

21 hours ago

Climate is most important factor in where mammals choose to live, study finds

Team develops novel hybrid scheme for compressible flow computations

Twisted carbon nanotubes could achieve significantly better energy storage than advanced lithium-ion batteries

22 hours ago

Relevant PhysicsForums posts

The predictive brain (stimulus-specific error prediction neurons).

Jul 21, 2024

Contradictory statements made by two different professors

The cass report (uk).

Jul 19, 2024

Understanding COVID Quarantine Guidance

Innovative ideas and technologies to help folks with disabilities.

Jul 18, 2024

New and Interesting Publications Relevant to the Origin of Life

Jul 15, 2024

More from Biology and Medical

Related Stories

Less affluent countries found to be more prone to damage caused by biological invasions despite lower trade volume

Mar 28, 2024

Team of international experts call for urgent action against increasing threat from invasive species

Jun 3, 2024

Invasive species risk a biodiversity disaster—but there is still time to stop it

Sep 6, 2023

New study reveals alarmingly massive economic costs of biological invasions to the European Union

Jun 13, 2023

Climate change to bring invasive weeds to mid-Atlantic and northeastern US states: Study

Feb 9, 2024

Political geography key to assessing economic costs of invasive pests on islands

Dec 1, 2022

Recommended for you

New clam species discovered in South Africa's kelp forest

New understanding of fly behavior has potential application in robotics, public safety

Jul 26, 2024

Increased demand for metals and minerals needed for clean energy transition puts 4,000+ species at risk, finds study

Let us know if there is a problem with our content.

Use this form if you have come across a typo, inaccuracy or would like to send an edit request for the content on this page. For general inquiries, please use our contact form . For general feedback, use the public comments section below (please adhere to guidelines ).

Please select the most appropriate category to facilitate processing of your request

Thank you for taking time to provide your feedback to the editors.

Your feedback is important to us. However, we do not guarantee individual replies due to the high volume of messages.

E-mail the story

Your email address is used only to let the recipient know who sent the email. Neither your address nor the recipient's address will be used for any other purpose. The information you enter will appear in your e-mail message and is not retained by Phys.org in any form.

Newsletter sign up

Get weekly and/or daily updates delivered to your inbox. You can unsubscribe at any time and we'll never share your details to third parties.

More information Privacy policy

Donate and enjoy an ad-free experience

We keep our content available to everyone. Consider supporting Science X's mission by getting a premium account.

E-mail newsletter

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Recommended Articles
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

Spatiotemporal evolution and drivers of carbon storage from a sustainable development perspective: a case study of the region along the middle and lower yellow river, china, share and cite.

An, S.; Duan, Y.; Chen, D.; Wu, X. Spatiotemporal Evolution and Drivers of Carbon Storage from a Sustainable Development Perspective: A Case Study of the Region along the Middle and Lower Yellow River, China. Sustainability 2024 , 16 , 6409. https://doi.org/10.3390/su16156409

An S, Duan Y, Chen D, Wu X. Spatiotemporal Evolution and Drivers of Carbon Storage from a Sustainable Development Perspective: A Case Study of the Region along the Middle and Lower Yellow River, China. Sustainability . 2024; 16(15):6409. https://doi.org/10.3390/su16156409

An, Shu, Yifang Duan, Dengshuai Chen, and Xiaoman Wu. 2024. "Spatiotemporal Evolution and Drivers of Carbon Storage from a Sustainable Development Perspective: A Case Study of the Region along the Middle and Lower Yellow River, China" Sustainability 16, no. 15: 6409. https://doi.org/10.3390/su16156409

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals