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Journal of Experimental Psychology: Animal Learning and Cognition

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Journal scope statement

The Journal of Experimental Psychology: Animal Learning and Cognition ® publishes experimental and theoretical studies concerning all aspects of animal behavior processes. Studies of associative, nonassociative, cognitive, perceptual, and motivational processes are welcome.

The journal emphasizes empirical reports but may include specialized reviews appropriate to the journal's content area. The journal also publishes brief communications, typically based on a single experiment that reports a significant new empirical or theoretical contribution, perhaps involving a novel technique or analytical approach.

Disclaimer: APA and the editors of the Journal of Experimental Psychology: Animal Learning and Cognition assume no responsibility for statements and opinions advanced by the authors of its articles.

Equity, diversity, and inclusion

Journal of Experimental Psychology: Animal Learning and Cognition supports equity, diversity, and inclusion (EDI) in its practices. More information on these initiatives is available under EDI Efforts .

Editor’s Choice

This journal’s content is highlighted in the APA Editor's Choice newsletter, a free, bi-weekly compilation of editor-recommended APA Journals articles. More information is available under the submission guidelines .

Open science

The APA Journals Program is committed to publishing transparent, rigorous research; improving reproducibility in science; and aiding research discovery. Open science practices vary per editor discretion. View the initiatives implemented by this journal .

Author and editor spotlights

Explore journal highlights : free article summaries, editor interviews and editorials, journal awards, mentorship opportunities, and more.

Prior to submission, please carefully read and follow the submission guidelines detailed below. Manuscripts that do not conform to the submission guidelines may be returned without review.

To submit to the editorial office of Andrew R. Delamater, please submit manuscripts electronically through the Manuscript Submission Portal in Microsoft Word (.docx) or LaTex (.tex) as a zip file with an accompanied Portable Document Format (.pdf) of the manuscript file.

Prepare manuscripts according to the Publication Manual of the American Psychological Association using the 7 th edition. Manuscripts may be copyedited for bias-free language (see Chapter 5 of the Publication Manual ). APA Style and Grammar Guidelines for the 7 th edition are available.

Submit Manuscript

Andrew R. Delamater City University of New York PhD Program in Psychology Brooklyn College – CUNY 2900 Bedford Ave Brooklyn, NY 11210

General correspondence may be directed to the editor's office .

Most of the articles published in the journal are reports of substantial empirical and theoretical studies and focused reviews of topics germane to the study of animal behavior processes.

The journal also publishes brief communications, typically based on a single experiment that reports a significant new empirical or theoretical contribution, perhaps involving a novel technique or analytic approach. In preparing a brief communication, authors should use 12-point Times Roman type and 1-inch margins. Length should not exceed 400 lines of text and references (exclusive of the title page, abstract, author note, footnotes, tables, and figures). There should be no more than two tables or figures.

Additional paper formats include the brief theoretical perspective and brief commentary. The perspective article provides the author an opportunity to concisely present a new theoretical framework regarding an especially controversial topic. The aim would be to stimulate further research on that topic from a new perspective. A commentary paper may be published that addresses a specific feature of another article published in the journal (e.g., a reanalysis or reinterpretation of the data), and would normally be accompanied by a rebuttal commentary by the authors of the original target article.

The Journal of Experimental Psychology: Animal Learning and Cognition ® will also publish direct replications. Submissions should include “A Replication of XX Study” in the subtitle of the manuscript as well as in the abstract. Such publications should be on a topic of critical importance in the field. Generally speaking, multi-experiment papers should have internal replications and extensions built into their experimental designs.

Journal of Experimental Psychology: Animal Learning and Cognition  is now using a software system to screen submitted content for similarity with other published content. The system compares the initial version of each submitted manuscript against a database of 40+ million scholarly documents, as well as content appearing on the open web. This allows APA to check submissions for potential overlap with material previously published in scholarly journals (e.g., lifted or republished material).

Each issue of the Journal of Experimental Psychology: Animal Learning & Cognition will highlight one manuscript with the designation as an “ Editor’s Choice ” paper. The paper will be broadly distributed by APA through a newsletter designed to stimulate interest in science. Once the paper appears in this newsletter it will be made freely accessible for 30 days. The editor’s selection will be based on the paper’s potential impact to the field, its integrative scope, and/or its identification of an important future theoretical or empirical direction for our discipline.

Masked review policy

Masked reviews are optional, and authors who wish masked reviews must specifically request them when submitting their manuscripts.

Each copy of a manuscript to be subjected to masked review should include a separate title page with authors' names and affiliations, and these should not appear anywhere else in the manuscript. Footnotes that identify the authors should be typed on a separate page. It is the authors' responsibility to see that the manuscript itself contains no clues to their identities, including grant numbers, names of institutions providing IRB approval, self-citations, and links to online repositories for data, materials, code, or preregistrations (e.g., Create a View-only Link for a Project ).

Related Journals of Experimental Psychology

For the other JEP journals, authors should submit manuscripts according to the manuscript submission guidelines for each individual journal:

• Journal of Experimental Psychology: General
• Journal of Experimental Psychology: Applied
• Journal of Experimental Psychology: Human Perception and Performance
• Journal of Experimental Psychology: Learning, Memory, and Cognition

When one of the editors believes a manuscript is clearly more appropriate for an alternative APA journal, the editor may redirect the manuscript with the approval of the author.

Manuscript preparation

Review APA's Journal Manuscript Preparation Guidelines before submitting your article.

Double-space all copy. Other formatting instructions, as well as instructions on preparing tables, figures, references, metrics, and abstracts, appear in the Manual . Additional guidance on APA Style is available on the APA Style website .

Below are additional instructions regarding the preparation of display equations, computer code, and tables.

Display equations

We strongly encourage you to use MathType (third-party software) or Equation Editor 3.0 (built into pre-2007 versions of Word) to construct your equations, rather than the equation support that is built into Word 2007 and Word 2010. Equations composed with the built-in Word 2007/Word 2010 equation support are converted to low-resolution graphics when they enter the production process and must be rekeyed by the typesetter, which may introduce errors.

To construct your equations with MathType or Equation Editor 3.0:

• Go to the Text section of the Insert tab and select Object.
• Select MathType or Equation Editor 3.0 in the drop-down menu.

If you have an equation that has already been produced using Microsoft Word 2007 or 2010 and you have access to the full version of MathType 6.5 or later, you can convert this equation to MathType by clicking on MathType Insert Equation. Copy the equation from Microsoft Word and paste it into the MathType box. Verify that your equation is correct, click File, and then click Update. Your equation has now been inserted into your Word file as a MathType Equation.

Use Equation Editor 3.0 or MathType only for equations or for formulas that cannot be produced as Word text using the Times or Symbol font.

Computer code

Because altering computer code in any way (e.g., indents, line spacing, line breaks, page breaks) during the typesetting process could alter its meaning, we treat computer code differently from the rest of your article in our production process. To that end, we request separate files for computer code.

In online supplemental material

We request that runnable source code be included as supplemental material to the article. For more information, visit Supplementing Your Article With Online Material .

In the text of the article

If you would like to include code in the text of your published manuscript, please submit a separate file with your code exactly as you want it to appear, using Courier New font with a type size of 8 points. We will make an image of each segment of code in your article that exceeds 40 characters in length. (Shorter snippets of code that appear in text will be typeset in Courier New and run in with the rest of the text.) If an appendix contains a mix of code and explanatory text, please submit a file that contains the entire appendix, with the code keyed in 8-point Courier New.

Use Word's insert table function when you create tables. Using spaces or tabs in your table will create problems when the table is typeset and may result in errors.

Academic writing and English language editing services

Authors who feel that their manuscript may benefit from additional academic writing or language editing support prior to submission are encouraged to seek out such services at their host institutions, engage with colleagues and subject matter experts, and/or consider several vendors that offer discounts to APA authors .

Please note that APA does not endorse or take responsibility for the service providers listed. It is strictly a referral service.

Use of such service is not mandatory for publication in an APA journal. Use of one or more of these services does not guarantee selection for peer review, manuscript acceptance, or preference for publication in any APA journal.

Submitting supplemental materials

APA can place supplemental materials online, available via the published article in the PsycArticles ® database. Please see Supplementing Your Article With Online Material for more details.

Abstract and keywords

All manuscripts must include an abstract containing a maximum of 250 words typed on a separate page. After the abstract, please supply up to five keywords or brief phrases.

List references in alphabetical order. Each listed reference should be cited in text, and each text citation should be listed in the references section.

Examples of basic reference formats:

Journal article

McCauley, S. M., & Christiansen, M. H. (2019). Language learning as language use: A cross-linguistic model of child language development. Psychological Review , 126 (1), 1–51. https://doi.org/10.1037/rev0000126

Authored book

Brown, L. S. (2018). Feminist therapy (2nd ed.). American Psychological Association. https://doi.org/10.1037/0000092-000

Chapter in an edited book

Balsam, K. F., Martell, C. R., Jones. K. P., & Safren, S. A. (2019). Affirmative cognitive behavior therapy with sexual and gender minority people. In G. Y. Iwamasa & P. A. Hays (Eds.), Culturally responsive cognitive behavior therapy: Practice and supervision (2nd ed., pp. 287–314). American Psychological Association. https://doi.org/10.1037/0000119-012

Data set citation

Alegria, M., Jackson, J. S., Kessler, R. C., & Takeuchi, D. (2016). Collaborative Psychiatric Epidemiology Surveys (CPES), 2001–2003 [Data set]. Inter-university Consortium for Political and Social Research. https://doi.org/10.3886/ICPSR20240.v8

Software/Code citation

Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package.  Journal of Statistical Software , 36(3), 1–48. https://www.jstatsoft.org/v36/i03/

Wickham, H. et al., (2019). Welcome to the tidyverse. Journal of Open Source Software, 4 (43), 1686, https://doi.org/10.21105/joss.01686

All data, program code, and other methods should be cited in the text and listed in the references section.

Preferred formats for graphics files are TIFF and JPG, and preferred format for vector-based files is EPS. Graphics downloaded or saved from web pages are not acceptable for publication. Multipanel figures (i.e., figures with parts labeled a, b, c, d, etc.) should be assembled into one file. When possible, please place symbol legends below the figure instead of to the side.

• All color line art and halftones: 300 DPI
• Black and white line tone and gray halftone images: 600 DPI

Line weights

• Color (RGB, CMYK) images: 2 pixels
• Grayscale images: 4 pixels
• Stroke weight: 0.5 points

APA offers authors the option to publish their figures online in color without the costs associated with print publication of color figures.

The same caption will appear on both the online (color) and print (black and white) versions. To ensure that the figure can be understood in both formats, authors should add alternative wording (e.g., “the red (dark gray) bars represent”) as needed.

For authors who prefer their figures to be published in color both in print and online, original color figures can be printed in color at the editor's and publisher's discretion provided the author agrees to pay:

• $900 for one figure
• An additional $600 for the second figure
• An additional $450 for each subsequent figure

Journal Article Reporting Standards

Authors should review the APA Style Journal Article Reporting Standards (JARS) for quantitative, qualitative, and mixed methods. The standards offer ways to improve transparency in reporting to ensure that readers have the information necessary to evaluate the quality of the research and to facilitate collaboration and replication.

The guidelines focus on transparency in methods reporting, recommending descriptions of how the researcher's own perspective affected the study, as well as the contexts in which the research and analysis took place. In particular, manuscripts should report: (1) how the sample size was determined, (2) specific criteria for all data exclusions, (3) all manipulations, and (4) all behavioral measures used in the study.

Equity, diversity, and inclusion statement

The Journal of Experimental Psychology: Animal Learning and Cognition is committed to equity, diversity, and inclusion (EDI) in science. Authors and readers of the journal come from highly diverse backgrounds and nationalities, and this has been one of its strengths. There are still a variety of ways in which EDI efforts can be increased and additional steps taken by the journal include the following.

• Research conducted with human participants is encouraged to use diverse samples. Specific participant demographic information should appear in methods sections and any potential limitations in the generality of the conclusions should be highlighted in the discussion section.
• The journal uses the CRediT taxonomy system to increase transparency and equity by specifying more concretely co-author contributions.
• The journal encourages a “Mentored Student Review” policy whereby faculty members are encouraged to co-review with their graduate students and/or post-doctoral fellows. However, it is expected that faculty members will work closely with their students to model a professional review standard and to promote a truly educational process.
• All reviewers are reminded to use only the most respectful language in their commentaries, and to avoid using any language that reflects biases of any kind or that may have discriminatory overtones. The journal has long been a strength in the discipline largely because of the highly constructive, yet critical, evaluations provided by peer reviewers. It is important to stress that such evaluations always must maintain a highly objective, bias-free, and civil level of communication.
• Authors are reminded that the journal offers a Masked Review option, should they feel more comfortable with that approach to peer review.
• The journal offers credit for conducting reviews through the ORCID system.
• Data sharing and openness in science is a high priority of the journal. All authors are encouraged to consider making their data, stimulus materials, and specialized code publicly available. Such practices help promote transparency in science, as well as providing more access to all groups of scientists.
• Authors are also reminded to include statements of justification for their chosen sample sizes. This helps to contextualize the research findings based on the statistical power supported by a particular experiment.
• Reviewers are encouraged to enter their demographic information in the editorial manager so that this can be monitored to equitably distribute reviews across highly diverse populations of scientists in our discipline.
• The editorial board for JEP:ALC consists of approximately 40% members from countries other than the United States and approximately 20% women. However, more efforts will go into ensuring an equitable distribution, particularly from underrepresented groups, that reflects our discipline.
• Finally, to maintain a consistent and clear approach to reporting our science, all authors are encouraged to follow APA style (7th ed). The importance of providing a clear description of research methods (including procedure and analytical approaches) cannot be emphasized enough. Authors should always include enough detail to enable replication of the research.

Equity, diversity, and inclusion in Journal of Experimental Psychology: Animal Learning and Cognition

The Journal of Experimental Psychology: Animal Learning and Cognition is committed to improving equity, diversity, and inclusion (EDI) in scientific research, in line with the  APA Publishing EDI framework and APA’s trio of 2021 resolutions to address systemic racism in psychology.

While the journal focuses on investigations of basic learning and cognitive processes in non-human animals, the journal also publishes relevant research performed with human participants. In those cases, the journal welcomes submissions that utilize heterogeneous participant samples as well as those that feature Black, Indigenous, and People of Color (BIPOC) and other historically marginalized sample populations. Studies focused exclusively on BIPOC and other historically excluded populations are also welcome.

To promote a more equitable research and publication process, the Journal of Experimental Psychology: Animal Learning and Cognition has adopted the following standards for inclusive research reporting.

Author contribution statements using CRediT 

The  APA Publication Manual ( 7th ed. ) stipulates that "authorship encompasses…not only persons who do the writing but also those who have made substantial scientific contributions to a study." In the spirit of transparency and openness, the Journal of Experimental Psychology: Animal Learning and Cognition has adopted the Contributor Roles Taxonomy (CRediT) to describe each author's individual contributions to the work. CRediT offers authors the opportunity to share an accurate and detailed description of their diverse contributions to a manuscript. 

Submitting authors must identify the contributions of all authors at initial submission according to the CRediT taxonomy. If the manuscript is accepted for publication, the CRediT designations will be published as an author contributions statement in the author note of the final article. All authors should have reviewed and agreed to their individual contribution(s) before submission. 

Authors can claim credit for more than one contributor role, and the same role can be attributed to more than one author. Not all roles will be applicable to a particular scholarly work. 

Participant description, sample justification, and informed consent

For investigations using human participants, authors are encouraged to include a detailed description of the study participants in the Method section of each empirical report, including (but not limited to) the following: 

• racial identity 
• nativity or immigration history 
• socioeconomic status 
• clinical diagnoses and comorbidities (as appropriate) 
• any other relevant demographics (e.g., disability status; sexual orientation) 

In both the abstract and in the discussion section of the manuscript, authors are encouraged to discuss the diversity of their study samples and the generalizability of their findings (see also the constraints on generality section below) especially as they relate to relevant studies conducted with non-human species as well as other participant populations. 

Authors are also encouraged to justify their sample demographics and describe their sample inclusion efforts in the Method section (see  Roberts, et al., 2020  for more information on justifying sample demographics). 

For human studies, the Method section also must include a statement describing how informed consent was obtained from the participants (or their parents/guardians), including for secondary use of data if applicable, and indicate that the study was conducted in compliance with an appropriate Internal Review Board. 

Constraints on generality

Authors are encouraged to consider including a subsection of the discussion section titled "Constraints on generality," in which they include a detailed discussion of the limits on generality of their findings (see Simons, Shoda, & Lindsay, 2017). In this section, authors should detail grounds for concluding why the results may or may not be specific to the characteristics of the specific animal species or human participant population studied. Since the journal emphasizes basic learning and cognitive processes in non-human as well as human animal species, some consideration should be given to whether the findings reflect the operation of some general or highly specialized learning or cognitive process. Authors should address limits on generality not only for their choice of study species or participants but for their materials and procedures as well.

Transparency and openness

APA endorses the Transparency and Openness Promotion (TOP) Guidelines by a community working group in conjunction with the Center for Open Science ( Nosek et al. 2015 ). Empirical research, including meta-analyses, submitted to the  Journal of Experimental Psychology: Animal Learning and Cognition  must meet the “disclosure” level for all eight aspects of research planning and reporting.

Authors should include a subsection in the method section titled “Transparency and Openness.” This subsection should detail the efforts the authors have made to comply with the TOP guidelines with a 21-word statement addressing that TOP standards have been met. Moreover, links to publicly available data, code, and stimulus materials, if applicable, should be provided here.

For example:

• We report how we determined our sample size, all data exclusions (if any), all manipulations, and all measures in the study.
• All data, analysis code, and research materials are available at [stable link to repository].
• Data were analyzed using R, version 4.0.0 (R Core Team, 2020) and the package ggplot , version 3.2.1 (Wickham, 2016). This study’s design and its analysis were not pre-registered.

Policy on data, materials, and code

Authors must state whether data, code, and study materials are available and, if so, how to access them. Recommended repositories include APA’s repository on the Open Science Framework (OSF), or authors can access a full list of other recommended repositories . Trusted repositories adhere to policies that make data discoverable, accessible, usable, and preserved for the long term. Trusted repositories also assign unique and persistent identifiers.

As noted above, in a subsection titled "Transparency and Openness" at the end of the method section, specify whether and where the data and material will be available or include a statement noting that they are not available. For submissions with quantitative or simulation analytic methods, state whether the study analysis code is posted to a trusted repository, and, if so, how to access it.

• All data have been made publicly available at the [trusted repository name] and can be accessed at [persistent URL or DOI].
• Materials and analysis code for this study are available by emailing the corresponding author.
• Materials and analysis code for this study are not available.
• The code behind this analysis/simulation has been made publicly available at the [trusted repository name] and can be accessed at [persistent URL or DOI].

Preregistration of studies and analysis plans

Preregistration of studies and specific hypotheses can be a useful tool for making strong theoretical claims. Likewise, preregistration of analysis plans can be useful for distinguishing confirmatory and exploratory analyses. Investigators who wish to preregister their studies and analysis plans prior to conducting the research are invited to do so via a publicly accessible registry system (e.g., OSF , ClinicalTrials.gov, or other trial registries in the WHO Registry Network).

There are many available templates; for example, APA, the British Psychological Society, and the German Psychological Society partnered with the Leibniz Institute for Psychology and Center for Open Science to create Preregistration Standards for Quantitative Research in Psychology (Bosnjak et al., 2022).

Articles must state whether or not any work was preregistered and, if so, where to access the preregistration. If any aspect of the study is preregistered, include the registry link in the method section (transparency and openness subsection).

• This study’s design was preregistered prospectively, before data were collected; see [STABLE LINK OR DOI].
• This study’s design and hypotheses were preregistered after data had been collected but before analyses were undertaken; see [STABLE LINK OR DOI].
• This study’s analysis plan was preregistered; see [STABLE LINK OR DOI].
• This study was not preregistered.

Permissions

Authors of accepted papers must obtain and provide to the editor on final acceptance all necessary permissions to reproduce in print and electronic form any copyrighted work, including test materials (or portions thereof), photographs, and other graphic images (including those used as stimuli in experiments).

On advice of counsel, APA may decline to publish any image whose copyright status is unknown.

• Download Permissions Alert Form (PDF, 13KB)

Publication policies

For full details on publication policies, including use of Artificial Intelligence tools, please see APA Publishing Policies .

APA policy prohibits an author from submitting the same manuscript for concurrent consideration by two or more publications.

See also APA Journals ® Internet Posting Guidelines .

APA requires authors to reveal any possible conflict of interest in the conduct and reporting of research (e.g., financial interests in a test or procedure, funding by pharmaceutical companies for drug research).

• Download Full Disclosure of Interests Form (PDF, 41KB)

In light of changing patterns of scientific knowledge dissemination, APA requires authors to provide information on prior dissemination of the data and narrative interpretations of the data/research appearing in the manuscript (e.g., if some or all were presented at a conference or meeting, posted on a listserv, shared on a website, including academic social networks like ResearchGate, etc.). This information (2–4 sentences) must be provided as part of the author note.

Ethical Principles

It is a violation of APA Ethical Principles to publish "as original data, data that have been previously published" (Standard 8.13).

In addition, APA Ethical Principles specify that "after research results are published, psychologists do not withhold the data on which their conclusions are based from other competent professionals who seek to verify the substantive claims through reanalysis and who intend to use such data only for that purpose, provided that the confidentiality of the participants can be protected and unless legal rights concerning proprietary data preclude their release" (Standard 8.14).

APA expects authors to adhere to these standards. Specifically, APA expects authors to have their data available throughout the editorial review process and for at least 5 years after the date of publication.

Authors are required to state in writing that they have complied with APA ethical standards in the treatment of their sample, human or animal, or to describe the details of treatment.

• Download Certification of Compliance With APA Ethical Principles Form (PDF, 26KB)

The APA Ethics Office provides the full Ethical Principles of Psychologists and Code of Conduct electronically on its website in HTML, PDF, and Word format. You may also request a copy by emailing or calling the APA Ethics Office (202-336-5930). You may also read "Ethical Principles," December 1992, American Psychologist , Vol. 47, pp. 1597–1611.

Other information

See APA’s Publishing Policies page for more information on publication policies, including information on author contributorship and responsibilities of authors, author name changes after publication, the use of generative artificial intelligence, funder information and conflict-of-interest disclosures, duplicate publication, data publication and reuse, and preprints.

Visit the Journals Publishing Resource Center for more resources for writing, reviewing, and editing articles for publishing in APA journals.

Andrew R. Delamater Brooklyn College-CUNY

Consulting editors

Bernard W. Balleine University of New South Wales

Peter D. Balsam Barnard College and Columbia University

Tom Beckers Katholieke Universiteit Leuven

Michael Beran Georgia State University

Aaron P. Blaisdell UCLA

Mark Bouton University of Vermont

Charlotte Bonardi University of Nottingham

Ken Cheng Macquarie University

Robert Cook Tufts University

Jonathan D. Crystal Indiana University

Dominic Dwyer Cardiff University

David George University of Hull

Geoffrey Hall University of York

Justin Harris University of Sydney

Nathan Holmes University of New South Wales

Robert C. Honey Cardiff University

Mihaela D. Iordanova Concordia University

Kimberly Kirkpatrick Kansas State University

Matthew Lattal Oregon Health & Science University

Mike Le Pelley University of New South Wales, Sydney

Armando D. B. Machado University of Minho

Ian P. L. McLaren University of Exeter

Robin A. Murphy Oxford University

James Byron Nelson University of the Basque Country, Spain

Amy Odum Utah State University

John M. Pearce Cardiff University

Federico Sanabria Arizona State University

Geoffrey Schoenbaum NIDA

Ed Wasserman University of Iowa

Kate M. Wassum UCLA

Gabrielle Weidemann Western Sydney University

Thomas R. Zentall University of Kentucky

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Special issue of APA's Journal of Experimental Psychology: Animal Learning and Cognition, Vol. 48, No. 4, October 2022. This special issue considers some of the many ways in which Rescorla’s empirical and theoretical contributions impacted learning theory over his almost 50-year career.

Special issue of APA’s Journal of Experimental Psychology: Animal Learning and Cognition, Vol. 47, No. 3, July 2021. This special issue represents a collection of 14 papers that help to display some of the diversity of ideas and approaches within this flourishing research area of comparative cognition.

Transparency and Openness Promotion

APA endorses the Transparency and Openness Promotion (TOP) Guidelines by a community working group in conjunction with the Center for Open Science ( Nosek et al. 2015 ). The TOP Guidelines cover eight fundamental aspects of research planning and reporting that can be followed by journals and authors at three levels of compliance.

• Level 1: Disclosure—The article must disclose whether or not the materials are posted to a trusted repository.
• Level 2: Requirement—The article must share materials via a trusted repository when legally and ethically permitted (or disclose the legal and/or ethical restriction when not permitted).
• Level 3: Verification—A third party must verify that the standard is met.

Empirical research, including meta-analyses, submitted to the  Journal of Experimental Psychology: Animal Learning and Cognition  must, at a minimum, meet Level 1 (Disclosure) for all eight aspects of research planning and reporting. Authors should include a subsection in their methods description titled “Transparency and openness.” This subsection should detail the efforts the authors have made to comply with the TOP guidelines.

The list below summarizes the minimal TOP requirements of the journal. Please refer to the Center for Open Science TOP guidelines for details, and contact the editor (Andrew R. Delamater, PhD) with any further questions. APA recommends sharing data, materials, and code via  trusted repositories (e.g.,  APA’s repository  on the Open Science Framework (OSF)). Trusted repositories adhere to policies that make data discoverable, accessible, usable, and preserved for the long term. Trusted repositories also assign unique and persistent identifiers.

We encourage investigators to preregister their studies and to share protocols and analysis plans prior to conducting the research. There are many available preregistration forms (e.g., the APA Preregistration for Quantitative Research in Psychology template, ClininalTrials.gov , or other preregistration templates available via OSF ). Completed preregistration forms should be posted on a publicly accessible registry system (e.g., OSF , ClinicalTrials.gov, or other trial registries in the WHO Registry Network).

A list of participating journals is also available from APA.

The following list presents the eight fundamental aspects of research planning and reporting, the TOP level required by the  Journal of Experimental Psychology: Animal Learning and Cognition,  and a brief description of the journal's policy.

• Citation: Level 1, Disclosure—All data, program code, and other methods developed by others should be cited in the text and listed in the references section.
• Data Transparency: Level 1, Disclosure—Article states whether the raw and/or processed data on which study conclusions are based are posted to a trusted repository and, if so, how to access them.
• Analytic Methods (Code) Transparency: Level 1, Disclosure—Article states whether computer code or syntax needed to reproduce analyses in an article is posted to a trusted repository and, if so, how to access it.
• Research Materials Transparency: Level 1, Disclosure—Article states whether materials described in the method section are posted to a trusted repository and, if so, how to access them.
• Design and Analysis Transparency (Reporting Standards): Level 1, Disclosure—The journal encourages the use of APA Style Journal Article Reporting Standards (JARS-Quant, JARS-Qual, and/or MARS). Manuscripts should report (1) how the sample size was determined, (2) specific criteria for all data exclusions, (3) all manipulations, and (4) all behavioral measures used in the study.
• Study Preregistration: Level 1, Disclosure—Article states whether the study design and (if applicable) hypotheses of any of the work reported was preregistered and, if so, how to access it. Authors may submit a masked copy via stable link or supplemental material or may provide a link after acceptance.
• Analysis Plan Preregistration: Level 1, Disclosure—Article states whether any of the work reported preregistered an analysis plan and, if so, how to access it. Authors may submit a masked copy via stable link or supplemental material or may provide a link after acceptance.
• Replication: Level 1, Disclosure—The journal publishes replications.

Journal equity, diversity, and inclusion statement

The Journal of Experimental Psychology: Animal Learning and Cognition is committed to equity, diversity, and inclusion (EDI) in science. Authors and readers of the journal come from highly diverse backgrounds and nationalities, and this has been one of its strengths.  There are still a variety of ways in which EDI efforts can be increased and additional steps taken by the journal include the following.

Inclusive study designs

• Diverse samples

Definitions and further details on inclusive study designs are available on the Journals EDI homepage .

Inclusive reporting standards

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Behavioral ecology: New technology enables a more holistic view of complex animal behavior

* E-mail: [email protected]

Affiliation Department of Evolution and Ecology, University of California, Davis, California, United States of America

• Gail L. Patricelli

Published: August 24, 2023

• https://doi.org/10.1371/journal.pbio.3002264
• Reader Comments

As any animal observer will tell you, behavior is complex. A more holistic view of this complexity is emerging as technological advances enable the study of spatiotemporal variability and expand the focus from single components to behavioral systems.

Citation: Patricelli GL (2023) Behavioral ecology: New technology enables a more holistic view of complex animal behavior. PLoS Biol 21(8): e3002264. https://doi.org/10.1371/journal.pbio.3002264

Copyright: © 2023 Gail L. Patricelli. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The author received no specific funding for this work.

Competing interests: The author has declared that no competing interests exist.

This article is part of the PLOS Biology 20th Anniversary Collection.

Behavior is more than just a suite of traits; it is the crux where the inside of the organism meets and interacts with the external environment. On the inside of the organism, behavior emerges through an interaction of genetic, physiological, cognitive, and developmental processes, which can be affected, in turn, by that organism’s behavior and experience. Behavior is also how organisms respond to—and influence—the biotic and physical environment, which includes potential mates, rivals, offspring, group members, predators, prey, and pathogens—all with their own behaviors—interacting amidst changing seasons and climates. And behaviors may manifest at multiple scales, from individuals to swarms. For the past 20 years and going forward, many of the exciting frontiers in the study of animal behavior involve grappling with this complexity in a more holistic way, examining the causes and functions of variability in behavior over space and time, and scaling up from components to systems, examining interaction networks that function as a whole.

Many breakthroughs on key aspects of animal behavior (social behavior, mate choice, communication, predator–prey dynamics, foraging ecology, and migration) have been enabled by advances in technology that allow us to collect detailed and simultaneous data from many components of complex systems ( Box 1 ). These tools are made possible by increased computing power, rapid advances in machine learning, and the development of smaller, cheaper, and more powerful hardware. Such tools are pushing the study of behavior, like other fields of science, into the “big data” era.

Box 1. Technology allowing a more holistic view of animal behavior.

Advances in both hardware for collecting data and machine learning software to analyze those data are expanding the detail and the scale at which we can study behavior.

• Animal-borne telemetry tags, which collect or transmit data about movements and other measures, can be miniaturized to much less than a gram and provide precise locations with onboard GPS or data from sensors (e.g., accelerometers, physiological monitors, microphones, or light-level monitors). Tags may store or transmit data to other tags, land-based receiver arrays, or satellites (e.g., ICARUS or MOTUS). These tags reveal aspects of animal lives that were previously unobservable, helping to identify critical resources and habitats for protection (e.g., migration corridors and refueling sites), exposure and response to stressors (e.g., human activity, noise and light pollution), and cryptic behaviors (e.g., nocturnal movements, quiet communication, and visits to potential mates).
• Other key hardware includes synchronized microphone arrays to triangulate animal positions from the arrival time of their vocalizations [ 1 ], drones with imaging tools, terrestrial laser scanning (ground-based LiDAR) for detailed habitat measures, and Passive Integrated Transponders (PIT tags).

Machine learning

• Supervised machine learning, trained on human-annotated data sets, is automating tedious tasks and making detailed analysis of large datasets more feasible.
• Unsupervised machine learning can identify new patterns in movement tracks and other behavioral data, providing insights less limited by human biases and reducing (not eliminating) subjective decisions about which characteristics to measure.
• On videos, freely available software [ 2 ] uses machine learning to track position and orientation on multiple individuals, enabling the study of social networks and swarm dynamics. Machine learning can also be used for pose estimation by tracking the relative position of multiple body parts for biomechanical studies of behaviors (e.g., DEEPLabCut [ 3 ]).
• On audio recordings, machine learning is automating detection and identification of sounds from birds, bats, and other vocal animals, enabling acoustic monitoring over time, in remote locations, and at night [ 4 ] and increasing the feasibility of using synchronized microphone arrays to study vocal behavior and movements [ 1 ].

Spatiotemporal variability is a ubiquitous feature of animal behavior. By necessity, behaviors are often measured by choosing a few key characteristics that can be scored accurately and repeatably, often averaging multiple measures from consistent conditions. This allows behaviorists to examine, for example, the relationship between courtship rate and mating success, or dominance hierarchies in social groups. While important, there is increasing awareness that fascinating biology is being averaged away, such as differences among individuals in the ability to execute behaviors consistently or adapt to changing social and environmental situations, or variation among groups in the stability of social networks [ 5 – 7 ]. The past few decades have seen frameworks for understanding aspects of this behavioral variation, such as consistent individual differences (CIDs) and personality, behavioral reaction norms, and dynamic social network analyses, but the difficulty of collecting data has limited the scope of empirical work.

To capture and analyze variability itself, we need enough snapshots to make a movie, multiple measures of behaviors within and among individuals or groups, across time and context, so the patterns of change can be examined. New hardware and machine learning algorithms for tracking movements and recognizing patterns are opening exciting new opportunities for collecting such data [ 2 , 4 , 8 ].

For example, using GPS telemetry tags in the wild or overhead video in captive enclosures, it is increasingly feasible to study the causes and consequences of CIDs in behavior, such as activity level or aggressiveness, by tracking multiple individuals throughout development or among contexts. Patterns of behavioral variation can then be examined relative to genotype, epigenetics, experience, adult behavior (of the focal animal, their parents, and their offspring), and social group dynamics. In fish, for example, tracking has revealed that CIDs in behavior among clonal mollies raised in identical conditions are present from birth and strengthen over time [ 9 ] and that CIDs among sticklebacks in sociability and boldness can affect the movement and foraging performance of entire shoals [ 10 ].

Similar machine learning algorithms can track the position of body parts for pose estimation, automating frame-by frame analysis of biomechanics during courting, fighting, prey capture, locomotion, and other behaviors [ 3 , 8 ]. This can save time, expand the number of traits measured on focal or interacting individuals, and reduce subjectivity in analyses ( Box 1 ). These opportunities for high-resolution data collection will (I hope) inspire further development of theory in neglected areas, such as optimal tactics during courtship and other dynamic behavioral interactions [ 5 ].

New tracking tools are also helping us to scale up from spatiotemporal analyses of behavioral components to a systems-level view of the whole. The systems approach focuses on structure–function relationships, moving from cause-and-effect thinking to synergistic thinking, by emphasizing interactions, linkages, and integrated phenotypes [ 5 , 11 ].

For example, a hot topic of research for more than 20 years has been why sexual selection frequently favors complex courtship displays with components in different sensory modalities, combining songs, dances, colors, scents, and vibrations [ 5 , 6 , 11 ]. A recent comparative analysis of the famously complex and spectacular displays of 40 species of birds-of-paradise utilized video and audio recordings, as well as color patterns from museum skins, finding positive relationships instead of trade-offs between complexity in the acoustic, color, and behavioral display components [ 12 ]. The authors argued that integrated suites of traits evolve as a courtship phenotype, with functional overlap and interdependency providing robustness and promoting diversification. Further research is needed to determine whether similar patterns emerge in the complex courtship displays of other clades of birds, as well as clades of reptiles, amphibians, fishes, insects, and spiders. With machine learning tools for automated data collection, such broad comparative analyses are becoming possible with growing online databases, such as libraries of audio and video recordings and 3D scans of museum specimens. Ultimately, to understand the evolution of complex courtship phenotypes, as in birds-of-paradise, we must also understand how male display components interact to stimulate the females’ sensory, cognitive, and motivational systems to influence their mate choice. In other words, a holistic approach is also required to understand the aesthetic experiences and complex preferences of the females these courtship displays evolved to impress. This interface between behavioral ecology and neuroethology promises exciting discoveries about the evolution of some of nature’s most beautiful spectacles.

Systems-level analyses of multicomponent social groups have been similarly insightful. Tracking of large groups of birds is revealing surprisingly complex, multilevel social systems, from families, to cohesive groups of unrelated individuals, to fission–fusion dynamics among groups, to structured flocks of interacting species [ 13 ]. Tracking is also allowing the detailed examination of collective behaviors [ 10 , 14 ], exploring how behavioral rules followed by individuals scale into emergent properties of groups, such as swarming behavior of locusts. For example, by modelling how group size and spacing affect individuals’ views through the crowd, researchers are learning how geometry affects swarm dynamics and collective decisions.

Along with benefits of new technology, come challenges. To name a few, minimizing the impacts of our technology on animal bearers, finding meaningful biology in the output of black box algorithms, and not letting data volume and high statistical power substitute for thoughtful experimental design and biologically relevant effect sizes. Downloading data from satellites is no substitute for time in the field or lab learning about natural history and carefully observing behaviors, which is essential to inspire creativity and anchor us to the real world. At its best, new technology complements existing methods and helps to reveal hidden dimensions of behavior. Moving into the big data era, animal behavior, like other fields, can minimize pitfalls by increasing transparency, standardization, and sharing of data, algorithms, and statistical code.

As the pace of urbanization, habitat loss, climate change, and other human impacts increase, behavior will often be the first response, either allowing animals to adjust to change, or not. Behavioral changes are often the first signs scientists can measure as evidence of human impacts. Behavior is also what often inspires public fascination and concern about wildlife. Therefore, in addition to addressing basic questions about behavioral evolution, new technology and a more holistic view of animal behavior is key to understanding, predicting, and mitigating human impacts on wildlife. For example, behaviorists are revealing how noise and light pollution impact social behaviors, improving methods for population monitoring and restoration, and reducing human–wildlife conflict. The next 20 years will bring increased opportunity and increased necessity for animal behaviorists to engage actively with conservationists, policy makers, stakeholders, and the public to find solutions to these complex problems.

Acknowledgments

The author apologizes to the hundreds of authors and ideas in the field of animal behavior that there was insufficient space to credit here.

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Strengthening the research–practice loop in applied animal behavior: Introduction to the special issue

Christina alligood.

1 The Chicago School of Professional Psychology

2 Disney's Animals, Science, and Environment

3 Behavior Works, LLC

Timothy Edwards

4 University of Waikato

Amanda Mahoney

Though operant learning has been applied to socially significant animal behavior for many years, connections between these practical applications and the basic science that supports them have weakened over time. There is a need for replications and extensions of technologies derived from basic research to applied animal settings, and for practical questions to be taken back to the lab where they can be modeled and studied under controlled conditions before incorporating the results in applied behavior‐change research and practice. This special issue highlights ways that behavior analysis can contribute to and support the development of evidence‐based applications with animals. Articles in this issue provide context for the relationship between basic research and practice in animal behavior, apply basic principles to animal behavior practice, and investigate practical problems using basic research techniques. Each of these is important for a robust interchange between basic science and practice. Here we comment on the contributions of each article to the literature and identify directions for future research.

The history of the application of operant learning to socially significant animal behavior is long and has resulted in tremendously effective technologies benefiting both animals and humans in many different practical settings (Alligood et al.,  2017 ; Edwards & Poling,  2011 ; Mahoney et al.,  2012 ). Over the past several decades, there has been a weakening of some of the connections between practical applications of operant learning with animals and the basic science that supports those applications, to the detriment of the continued development of effective technologies (Alligood & Friedman,  2022 ; Kalafut & Freestone, this issue; Kurland & St. Peter, this issue). Given our focus on measuring behavior change in individuals over time, behavior analysis has much to offer to applied animal work in various settings. Indeed, multiple authors have called for increased use of behavior‐analytic principles and methodologies in animal care (e.g., Alligood & Leighty,  2015 ; Alligood et al.  2017 ; Bloomsmith et al.,  2007 ; Friedman,  2005 ; Friedman,  2009 ; Maple,  2007 ).

The purpose of this special issue is to highlight ways that behavior analysis can contribute to and support the development of evidence‐based applications with animals from multiple positions on the spectrum (Kyonka & Subramaniam,  2018 ) from the experimental analysis of behavior (EAB) to practice. There is a need for replications and extensions of technologies derived from basic research to applied animal settings. Concurrently, there is a need for practical questions to be taken back to the lab where they can be modeled and studied under controlled conditions before incorporating the results in applied behavior‐change research and practice. In this issue, we are pleased to introduce a series of articles that provide context for the relationship between basic research and practice in animal behavior (Lattal & Fernandez; Kalafut & Freestone; Kodak, Bergmann, & Waite; Kurland & St. Peter, this issue), apply basic principles to animal behavior practice (Davidson & Rosales‐Ruiz; Nishimuta, Rosales‐Ruiz, Will, & Hunter; Rosales‐Ruiz & Katz, this issue) and investigate practical problems using basic research techniques (Bizo, Moser, & Brown; Cameron, Begum‐Diamond, & Neuhauser; Platzer & Feuerbacher; Rosales‐Ruiz & Peiris; Salzer & Reed, this issue). Each of these is important for a robust interchange between basic science and practice.

Relationship Between Basic Research and Practice in Animal Behavior

Lattal and Fernandez (this issue) provide an expert view of the contributions of EAB to applied animal behavior (AAB). Organized around four of the pillars of EAB described by Lattal ( 2013 ), their paper highlights pertinent experimental data from studies on reinforcement, extinction and punishment, stimuli correlated with reinforcement and punishment, and stimulus control. Readers of the special issue will find guidelines and useful references for common issues in AAB including the selection of step sizes in shaping procedures, potential side effects of procedures used in target training (e.g., baiting), and adaptations to consider in clicker training (e.g. the use of second‐order schedules). This article also points out for readers some conceptual divergences between EAB and AAB, such as descriptions in AAB that do not carry technical definitions stemming from procedures in EAB but may be accounted for on a process level by EAB (e.g. marking, bridging) and the classification of certain procedures and processes (e.g. the classification of extinction as an aversive procedure and the implications of making distinctions between positive and negative reinforcement).

Kalafut and Freestone (this issue) advocate the blending of EAB and AAB expertise to solve practical problems. The authors provide several examples of situations in which EAB expertise was brought to bear on practical problems with nonhuman animals. Their discussion follows in the tradition of Sidman ( 2011 , p. 973):

Before entering the worlds of applied research and practice, I spent approximately 10 years intensively involved in basic behavioral research in the laboratory, mostly with nonhumans as subjects. Then, almost as soon as I started to work with people who had suffered strokes or who displayed severe learning and other behavioral deficiencies, I realized that the preceding 10 years had constituted a period of apprenticeship for me. It turned out to have been an effective apprenticeship. By applying principles and investigative techniques I had learned in the laboratory, I found that I could communicate nonverbally with people who could not speak, that I could teach the supposedly unteachable, and that I could often successfully revise ineffective therapeutic procedures.

Kalafut and Freestone's (this issue) examples illustrate the utility of an understanding of basic research methodology and technological tools, as well as basic behavior principles, in collecting data for practical purposes in animal care settings. They end with several recommendations that will be helpful for behavior analysts interested in establishing collaborations focused on applied animal behavior.

To ensure internal validity in research experiments and promote treatment adherence in practice, behavior analysts must measure procedural fidelity, or the extent to which procedures are implemented as designed. While procedural fidelity has been increasingly investigated and discussed in the behavioral analysis literature over the past several decades (e.g., DiGenarro Reed & Codding,  2014 ; Falakfarsa et al.,  2022 ; Fallon et al.,  2020 ), the topic has received little attention in applied animal behavior research and practice. Kodak et al. (this issue) review the behavior‐analytic procedural fidelity literature, including basic and applied studies with human participants, and draw clear connections to applied animal behavior research and practice. Readers will find suggestions for future research directions, as well as an analysis of procedural fidelity measures best suited to AAB research and practice.

In AAB practice, some commonly used terms and related procedures have largely unrecognized connections to the experimental analysis of behavior (Alligood & Friedman, 2022; Lattal & Fernandez, this issue). Kurland and St. Peter (this issue) discuss behavior‐analytic conceptualizations and research around the term “loopy training”, identifying points of correspondence and research questions to be explored. In addition, they provide several excellent suggestions for improving the “loops” between animal trainers and behavior analysts.

Applications of Basic Principles to Animal Behavior Practice

The special issue showcases several studies that engaged the basic principles of behavior to produce socially significant behavior change in nonhuman animals. Davidson and Rosales‐Ruiz (this issue) modified two classes of maladaptive behavior (specifically, mouthing and jumping) by differentially reinforcing those response classes in the presence of a novel SD (which mimicked the original SD but added an additional auditory component with which the dog had no history) and withholding the reinforcer for all other response classes. They simultaneously implemented the contingencies in reverse for the original SD (putting the undesirable response classes on extinction while reinforcing any other behavior). This paper demonstrates a practical amelioration of a pet owner's circumstances without the use of punishment and modeled an intervention for behaviors that need not be eliminated across all contexts.

Lattal and Fernandez (this issue) point out that conjugate schedules, which they define as reinforcement schedules in which “some property of the reinforcer varies with some property of responding”, may prove useful in strengthening response classes of interest in AAB. Nishimuta et al. (this issue) incorporated a conjugate schedule into a differential reinforcement procedure by delivering higher quality tactile interactions contingent upon behaviors other than pushing, nibbling, biting, or walking away. Tactile interaction was also used as a reinforcer to shape “stay” and “come” behaviors across a prescribed 29‐step shaping program to train the horses to stay on cue and a prescribed 11‐step shaping procedure for training the horses to come on cue. One of the interesting implications of this is that tactile stimulation may yield positive training outcomes without the need to incorporate phylogenetically important events (PIEs) such as food.

There is a growing literature on interventions to increase “adoptability” in shelter‐housed animals by increasing behaviors that are positively correlated with likelihood of adoption and decreasing behaviors that are negatively correlated (Protopopova & Gunter,  2017 ). Behaviors labeled as “fearful” have been negatively correlated with likelihood of adoption and often targeted for reduction using desensitization and counterconditioning (DSCC) interventions. Rosales‐Ruiz and Katz (this issue) employed an alternative to DSCC in which behaviors classified as fearful were treated as operants, and more preferable alternative (“friendly”) behaviors were reinforced with reduced proximity to a novel person. They were able to very efficiently teach preferred behaviors and concurrently reduce fearful behaviors in all three dogs participating in the study, and all three dogs were subsequently adopted. Rosales‐Ruiz and Katz describe this intervention as “constructional” because it builds upon the animal's existing repertoire to increase preferred behaviors, and nonpreferred behaviors decrease without being explicitly targeted in the procedures. This paper provides an example of the use of behavior‐analytic principles to solve a practical problem in a way that is beneficial to both the dogs (through increased “friendly” behavior) and to the shelter (through effective and efficient training). This demonstrates a critical feature of sustainable solutions in the shelter environment: prioritizing organizational needs. A fruitful direction for future analyses might be a comparison of this procedure to others in the behavior‐analytic literature and a discussion of the necessary and sufficient conditions for use of the label “constructional”.

Investigations of Practical Animal Behavior Problems Using Basic Research Techniques

This issue also presents several articles describing investigations of practical animal behavior problems using basic research techniques. For example, to maximize the effectiveness and efficiency of applications of behavior analysis with animals, it is important to identify reinforcers for individual animals. For pets, enriching the environment with safe opportunities for exercise is critical for good health. Cameron et al. (this issue) used basic research techniques to investigate both of these practical problems in guinea pigs. Demand testing has been used in the laboratory and in applied settings to assess reinforcer value (Hursh et al.  2013 ; Rasmussen et al.,  2020 ). Cameron et al. titrated demand by adjusting the slope of a ramp the guinea pigs climbed to reach food items, determining demand based on maximum slope climbed for an item. They were also able to use this metric to identify safe and accessible ramp slopes for habitat enrichment.

Platzer and Feuerbacher (this issue) evaluated the reinforcer efficacy of six different grains for horses, considering factors such as nonstructural carbohydrate content and texture. All grains in the study functioned as effective reinforcers, with few differences in efficacy between grain types, an important finding for horse trainers and researchers alike. Similar results were obtained when the authors evaluated reinforcer efficacy as a function of unit price per kilocalorie. Exploring the extant literature and considering the conditions in effect for the horses in their study, the authors identified important factors that may influence the reinforcer efficacy of grain and other types of food for horses. One such factor is the type of food that horses receive as part of their normal daily rations. With the increasing popularity of horse training using positive reinforcement, clarifying the role of qualitative food characteristics in determining reinforcer efficacy is valuable. This study represents a useful contribution that can inform practice and future research on this topic.

Bizo et al. (this issue) describe the first evaluation of a habituation–dishabituation test for determining the olfactory detection threshold for n‐amyl acetate, an organic compound with a banana‐like scent, in dogs. To do so, in the experimental condition they presented a mineral‐oil filled vial for three trials followed by five trials of increasing concentrations of the target compound for the dogs to explore. Upon achieving mixed results across 35 dogs, they concluded that discrimination testing remains best practice.

Salzer and Reed (this issue) evaluated the utility of the Ideal Free Distribution model in describing the distribution of domestic dogs between resource sites in a dog day‐care setting. Automated feeders distributed food according to variable time schedules in two sites and, as predicted by the model, the number of dogs in each site was proportional to the frequency of food delivery in each site. This study is the first to evaluate the Ideal Free Distribution under controlled conditions with domestic dogs. The authors employed methods that can be readily applied by other researchers. For example, the automated apparatus, which the authors thoroughly tested prior to conducting this research, is available commercially, and dog day‐care setting are accessible to many researchers. Using similar methods, this line of research with domestic dogs could be extended to explore the relationship between individual behavior (i.e., matching) and the distribution of individuals between resource sites, as discussed by the authors. Given the close relationship between humans and dogs, enhancing our understanding of the factors that determine where dogs spend time is important.

Many animal trainers use a clicker or other stimulus (e.g., a whistle) to “bridge” the gap between a correct response and the delivery of a reinforcer. It is difficult to overstate the controversy in the animal training community surrounding whether it is advantageous to pair each occurrence of the bridging stimulus with the delivery of a reinforcer (see Dorey & Cox,  2018 for a review of common clicker training terminology compared with basic research terminology). The issue has previously been addressed in conceptual analyses (e.g., Alligood et al.,  2020 ; Martin & Friedman,  2011 ). Rosales‐Ruiz and Peiris (this issue) conducted an empirical investigation in two dogs, comparing the behavioral effects of always following a click with food versus only sometimes following a click with food. Their results support what previous conceptual analyses have speculated: Performance of trained behaviors was stronger, and disruptions minimized, when each click was paired with food. The authors provide a sound conceptual analysis of these results that is worthwhile reading for anyone hoping to better understand these issues.

Conclusions

In summary, the articles in this issue provide an excellent foundation for forging connections between basic behavior‐analytic research and applications of behavior analysis with animals. The present authors have found our basic research training tremendously helpful in designing analyses and interventions to address practical problems in this area. By the same token, we have found our connections with the settings in which these applications are implemented to be useful in understanding which research questions relevant to these settings might be usefully addressed in the laboratory. We hope that these articles spark readers' interest in this important area of study, and lead to further progress.

This issue is dedicated to the memory of David P. (Dave) Jarmolowicz. Dave's philosophy was an ideal representation of the goals of this special issue, as reflected by his insistence on being led by data: “As Dave branched into various pursuits, he retained the core value that you never let expertise with behavior principles seduce you into circumventing an empirical analysis.” (Reed et al., this issue). Although he did not formally work in applied animal behavior, Dave took an interest in this area both as an important extension of behavior science and as a means of informing the care of the animals in his laboratory. When one of the present authors discussed this special issue with him, he expressed excitement about the prospect of strengthened connections between basic science and practice in applied animal behavior, emphasizing that the best behavior‐analytic solutions to practical problems come from returning to basic principles to better understand the problem, eventually allowing the creation of specialized solutions that apply directly to the challenge at hand.

Editor‐in‐Chief: Mark Galizio

Associate Editor: Mark Galizio

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Article Contents

Why the gap, should animal behavior scientists concern themselves with animal ethics, how can animal behavior scientists engage with philosophy and animal ethics, conclusions, acknowledgments, references cited.

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Animal Ethics and Behavioral Science: An Overdue Discussion

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Christine E Webb, Peter Woodford, Elise Huchard, Animal Ethics and Behavioral Science: An Overdue Discussion, BioScience , Volume 69, Issue 10, October 2019, Pages 778–788, https://doi.org/10.1093/biosci/biz082

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Animal ethics—the field of philosophy concerned with the moral status of animals—is experiencing a momentum unprecedented in its history. Surprisingly, animal behavior science remains on the sidelines, despite producing critical evidence on which many arguments in animal ethics rest. In the present article, we explore the origins of the divide between animal behavior science and animal ethics before considering whether behavioral scientists should concern themselves with it. We finally envision tangible steps that could be taken to bridge the gap, encouraging scientists to be aware of, and to more actively engage with, an ethical revolution that is partly fueled by the evidence they generate.

The moral status of animals is a longstanding question dating back at least to Aristotelian philosophy (see Regan and Singer 1989 for an overview of historical and contemporary writings on the topic). However, it has been brought into especially acute focus in recent decades. The modern development of the animal ethics debate is fueled by many factors—among them, novel scientific insights into the complexities of animal minds and emotions (Bekoff and Pierce 2017 ); the ever-increasing scale of industrial farming (Harrison 2013 ); and the Anthropocene, an era heralded by unprecedented human-induced changes to the Earth's climate, environments, and resident wildlife (Ceballos et al. 2015 ). The cumulative impact of these trends has raised the urgency of moral concerns over the nature of human–animal relationships, particularly in the context of our use, overuse, and misuse of animals. The exploitation of animals for food and other products represents just part of the prevailing narrative: A major shift is taking place in how people view the role of animals in research, entertainment, and even companionship. This turn was detectable in early publications such as Ryder's ( 1975 ) Victims of Science and Singer's ( 1975 ) seminal Animal Liberation , and later built on by those of other, scholars (e.g., Regan 1983 , Rollin 1992 , Francione 1995 , Jamieson 2002 , Donaldson and Kymlicka 2011 , Korsgaard 2018 , Nussbaum 2018 ; see also Armstrong and Botzler 2017 for a comprehensive anthology of readings on animal ethics). The last two decades have witnessed an exponential increase in literature and journals focusing on animal ethics—the field of philosophy concerned with the moral status of animals (figure 1 ).

Web-based search results (the grey bars correspond to total number of hits) for the search terms (a) animal ethics as well as (b) human-animal relations in academic articles, and (c ) animal rights in US state or federal case law. The ratio of the total number of hits for each search term to the total number of hits for the (control) search term animal during the same decade is illustrated by black lines (see the secondary y -axis) to account for growth in scientific knowledge over time. All information was obtained from Google Scholar on 17 May 2019.

This transition in ethical thinking about animals has been, at least in part, driven forward by evolutionary theory and discoveries made in the behavioral sciences. Darwin's theory of evolution by natural selection offered a new and powerful challenge to the anthropocentric assumption that humans are the pinnacle of creation—an assumption central to many historically and presently influential theological conceptions of the world (Rachels 1990 ). As the earlier scientific revolution guiding human understanding of the natural order showed that the Earth is not the center of the cosmos, this revolution more dramatically leveled human ontological status by insisting that humans are one of a countless variety of other animals. The disintegration of our pre-Darwinian understanding of nature, coupled today with the extent of anthropogenic changes faced by the environment and animals in the industrial world, has revealed deep-seated incompatibilities between dominant frameworks of value (still rooted in a pervasive sense of human superiority) and the current state of knowledge regarding the capacities of other species and their vulnerability to human actions (e.g., Rachels 1990 , Jones 2013 , Bekoff and Pierce 2017 ).

Recent progress in scientific research on animal behavior has provided evidence used in animal ethics by documenting previously unknown aspects of animal life that have fundamental ethical implications. Studies on the cognitive, emotional, and social capacities of other species have discredited long-held assumptions about capacities thought to be unique to humans. Nonexclusively, this list includes the design and use of tools (Sanz et al. 2013 ); the prevalence of animal cultures (Laland and Bennett 2009 ) and the capacity to innovate (Reader et al. 2016 ); the complexity and efficiency of animal vocal communication, including symbolic communication (Seyfarth et al. 1980 ) and forms of protosyntaxes (Ouattara et al. 2009 ); the capacity for self-awareness (Gallup et al. 2002 ), mental time-travel (Raby et al. 2007 ), and a wide range of emotional experiences, including joy and grief (de Waal 2019 ); reports of complex forms of consciousness, such as empathy (de Waal and Preston 2017 ), and of social intelligence, such as the formation of reciprocal alliances and the active management of long-term social relationships (Cheney and Seyfarth 2007 ), systems of conflict resolution (Aureli and de Waal 2000 ), and the ability to impute mental states to others (Call and Tomasello 2008 ), including the strategic adjustment of one's own knowledge of what others know (Emery and Clayton 2001 ). These findings have all blurred traditional divisions structuring historical discussions of human uniqueness—including the opposition between nature and culture, between animal objects and human subjects, and between instinctive and rational actions—consequently casting doubt on the anthropocentrism that has largely dominated the history of ethics as a field of philosophical inquiry.

Alternative systems of ethical values developed in contemporary animal ethics often rely on empirical evidence to demonstrate the possession (or lack thereof) by a nonhuman individual of the relevant attribute conferring moral consideration (Allen 2006 ). The main theories in animal ethics are pathocentric (i.e., centered on sentience and the capacity to suffer) and therefore hinge on empirical knowledge documenting the sentience of animals—such as recent work demonstrating that fish feel pain (Brown 2015 ). In addition, perceptions of animals as subjects-of-a-life are central to the deontological approach to animal ethics developed by Tom Regan that has also formed a critical part of the legal case for animal rights (Regan 1983 ). Studies revealing the existence of personalities (Sih et al. 2004 ), episodic memory (Clayton et al. 2001 ), intentionality (Allen and Bekoff 1995 ), and rationality (Hurley and Nudds 2006 ) have been instrumental in revealing that animals have a subjective life, personal history, interests, and goal-oriented agency (Jones 2013 ). Taken together, this constellation of results from scientific research on animals has paved the way to changed (and changing) perspectives on the moral status of animals.

Despite these critical contributions to animal ethics, animal behavior sciences such as ethology, behavioral ecology, and comparative psychology have played a rather passive role in the progression and expansion of this movement. In other words, although animal behavior scientists’ work has been integral, it is nonscientists who have primarily pioneered the integration of science and ethics. In the present article, we advance the argument that if the ethics of human–animal relationships are to be redefined, then more active participation on the part of animal behavior scientists has great potential—not just for moving animal ethics debates forward but for scientists themselves. To be clear, in attempting to bridge the study of animal behavior and animal ethics, we are not just referring to the ethics of using animals in behavioral sciences—which have already been the focus of thorough reviews (see box 1 ). Furthermore, although the scientific literature has recently highlighted how animal behavioral sciences can inform animal conservation (e.g., Caro 2007 , Greggor et al. 2016 ) and animal welfare science (e.g., Fraser 1999 , Dawkins 2006 ), it has not yet extended to engage with the full realm of issues debated in animal ethics, which include questions about the fundamental ground of moral status. Our primary purpose in this article is to make that extension by addressing three key questions: What are the primary reasons for a gap between animal behavior science and animal ethics? Should behavioral scientists feel concerned about this growing disconnect? And how could they more actively contribute to the development of animal ethics?

In this article, we emphasize potential interactions between the philosophical field of animal ethics and behavioral sciences. Ethical issues raised by research in behavioral sciences are a related but different and narrower issue. On top of legal requirements, professional organizations have taken further practical steps to ensure that ethical issues related to animal welfare are an integral part of the design of the research being conducted by setting up their own standards (see the Association for the Study of Animal Behaviour's 2012 Guidelines for the Treatment of Animals in Behavioural Research and Teaching, and the American Psychological Association's 2010 Guidelines for Ethical Conduct in the Care and Use of Nonhuman Animals in Research). The main scientific journals in psychology and behavioral ecology require that these standards be met to publish a paper. It certainly does not mean that all ethical issues associated with animal behavior sciences have been thoroughly resolved, and future work should strive to keep ethics questions central to its interests. Empirical work attempting to measure the stress, pain, and mortality caused by study protocols is an emerging field of research (e.g., Le Maho et al. 2011 , Hämäläinen et al. 2014 ), and several recent reviews have been dedicated to these and other ethical issues (Mackinnon and Riley 2010 , Costello et al. 2016 , Field et al. 2019 ).

A primary reason for a frequent lack of communication between animal ethicists and behavioral scientists may reflect traditional difficulties in crossing disciplinary boundaries. Contemporary scientific culture remains largely disconnected from philosophy, which—unfortunately, in our view—is not part of the regular academic training received by scientists; as a result, scientists may not be motivated or prepared to engage in broad ethical discussions that directly pertain to their scientific practice or results. The persistence of a gap is exacerbated institutionally by a lack of educational and career development opportunities that cross-over between behavioral science and philosophy. But it is also caused by fundamentally different theoretical and methodological orientations. Science aims to discover causal relationships between states of affairs and phenomena in the physical world, whereas ethics is an explicitly value-laden, normative field of inquiry that aims to defend our best judgments as to what we ought to do. We are not in the present article proposing a solution to the fact–value relationship or to the problem of whether there are normative facts and how they might fit into nature but, rather, proposing that differences in the basic questions and methods of scientists and ethicists underlie a prevalent, but divisive attitude that science is rigorous and objective, whereas ethical theorizing is more subjective. Acquainting scientists with rigorous debate in normative ethics and ethical theory about basic moral principles and their implications, as well as pointing them to the ways in which scientific research can be enmeshed within the values of the particular times and places in which it is carried out (Kincaid et al. 2007 ), may help emphasize the benefits of interdisciplinary dialogue and research into the complex historical and logical relationship between science and ethics. Greater awareness of the various conceptual and normative assumptions that may come along with different explanatory frameworks can only improve the quality of scientific thinking (Laplane et al. 2019 ).

Although scientists should all be aware of the spectrum of ethical discussions related to their daily scientific practice, they may sometimes fail to see that animal ethics is a broad and fast-growing area of philosophical inquiry and normative debate concerning the nature of human–animal relationships that is built on rational argumentation. It is important to realize that philosophers working on animal ethics may adopt a diversity of nuanced positions, and do not uniformly defend specific political or policy agendas. Scientists may sometimes lump the term animal ethics with other domains, in particular with the set of ethical regulations that rule their research activities (box 1 ), with the emergence of animal welfare or conservation as scientific fields using research to assess and improve the animal condition, or even with the activism incited by animal rights associations. Conversely, although ethicists may be more aware of scientists’ work than the reverse, they may not be up to date with the most current research and debates in the field. Nor do ethicists necessarily have experience rigorously observing animal behavior. Disciplinary segregations between animal welfare scientists, conservation biologists, and (some) animal ethicists are particularly telling examples of the oddity that the divide between these so-called two cultures persists even in the context of obviously shared ethical concerns (Fraser 1999 ). Although the integration of normative and empirical approaches to animal welfare and conservation sciences has eventually gained advocates (e.g., welfare: Fraser 1999 , Dawkins 2006 , Würbel 2009 ; conservation: Ramp and Bekoff 2015 ), scientific discussions of ethical issues have focused on a rather specific set of questions with limited attention to foundational reflection on ethical frameworks and on how normative and empirical approaches relate (Dawkins 2006 ).

The gap between ethicists and behavioral scientists has further been maintained by mutual defiance and skepticism. If and how animals should be used in science has been a core question of animal ethics since its inception, and behavioral research has immediately been the focus of severe criticism for conducting painful and unnecessary experiments (Ryder 1975 , Singer 1975 ). Ethicists subsequently became suspicious toward, or dismissive of, any scientific procedure involving animals to study their behavior (Fraser 1999 ). Meanwhile, animal behavior scientists naturally feared condemnation surrounding their research, and may have perceived the gradual development of ethical regulations on the use of animals in research (box 1 ) as an extra source of constraints and bureaucracy in their work. This divide has likely been furthered by several aspects of the predominant disciplinary culture of animal behavior. Many animal behavior researchers have traditionally adopted the attitude of stifling empathy toward their study subjects in the interest of preserving scientific objectivity and avoiding behavioral interferences with the study subject (Kennedy 1992 ). Such detachment in the name of objectivity may have contributed to the notion that an ethical sensibility toward subjects of research is “unscientific” and “subjective” and may still prevent many researchers from perceiving open engagement with current debates in animal ethics as an integral part of—or at least as compatible with—scientific thinking and practice.

New points of tension have arisen in the course of contemporary discussions in animal ethics, which have for the most part been dominated by two competing approaches: Utilitarian welfare-based and deontological rights-based approaches. Whereas both approaches share the idea that animal welfare is worthy of protection for its own sake and not for the sake of humans, the welfare approach insists that moral duties related to the humane treatment of animals come from animals’ capacity to feel pain and pleasure. It stems from a utilitarian and consequentialist approach to animal ethics, according to which the aggregate benefits of any intervention into animal lives must exceed any harmful costs (Singer 1975 ). In contrast, theories of animal rights are based in deontological ethics, pursuant to which duties to animals come from the respect that they deserve as agents with their own unique interests, aims, and goals. Theorists in this school consider animals’ lives to be intrinsically valuable and propose to grant them basic rights—such as the right to life, freedom, and not to be tortured—to prevent them from being treated as mere means, such that their interests are sacrificed to human interests (Regan 1983 , Francione 1995 , Donaldson and Kymlicka 2011 ). This generates a critical tension with welfare approaches, according to which animals retain an instrumental value in situations in which benefits (to the human community) might outweigh harm (to the animals). It is clear that when animal scientists do engage with ethical debates, the prevailing utilitarian, welfare-based approach is often adopted by default, probably due—at least in part—to the use of animals in scientific research. However, many ethicists have instead favored theories of animal rights (Donaldson and Kymlicka 2011 ), although they have not uniformly condemned the use of animals in research within this framework. Therefore, although the practical implications of such divergences in underlying ethical theory may be profound, rights-based theories do not necessarily exclude the possibility of research on animals. For example, just as human volunteers can participate in scientific experiments, it may be possible to envision a research protocol that respects the dissent of a nonhuman subject (e.g., Fenton 2014 ), especially in behavioral research where experiments can be designed in which animals are free to participate.

A greater integration between animal ethics and the animal behavior scientific community is desirable for ethical and pragmatic reasons. Foremost, there is an ethical reason in that scientists fulfill a social responsibility when they engage with and help others understand the ethical implications of research. However, there are also pragmatic benefits for science, including helping scientists examine sources of historical and cultural bias that may limit scientific questions and approaches, and so further enrich and broaden scientific understanding. Some of these benefits may admittedly arise from interactions with philosophical discussions about the nature of animals that are broader than animal ethics, for example philosophical work on animal minds, perception and representation, social learning and culture, altruism and cooperation, and rationality (Andrews 2015 , Andrews and Beck 2018 ). Nonetheless, the recent renewal of the philosophy of animals as a subfield within the philosophy of science has played and continues to play a major role in the expansion of animal ethics insofar as it has also challenged anthropocentric approaches that have dominated classical philosophy. Although the recognition of animal consciousness and subjectivity is growing, it is not unanimous in philosophy (cf., e.g., Carruthers 2000 , Tye 2016 ). These important debates that are relevant to animal ethics, but are also broader, draw on and require science and should, therefore, be inspiring to animal scientists as well.

Fulfilling a social responsibility

Many scientists are naturally interested in how their results inform and inspire societal debates—one obvious reason for animal behavioral scientists to engage with the literature on animal ethics. In addition to this natural curiosity, and despite commonly holding the view that scientific findings have no intrinsic normative value, scientists still usually support ideas of moral progress that follow from scientific progress in our rational understanding of the natural world. For example, where progress in understanding the neurologic development of infants uncovered the capacity for pain (Anand and Hickey 1987 ), it became an ethical duty for scientists to advocate against neonatal surgeries without anesthesia. The parallels to our understanding of animal pain are obvious, and scientists could play an important role in advocating against farming or research practices that involve suffering in the form of pain as well. More generally, ethics makes a claim on scientists to engage with public debates on ethical issues that are related to their scientific activities (and sometimes even raised by their results; Siekevitz 1970 , Pain 2013 ). At a time when researchers in science and technology are often consulted to set the direction and values of society, and often occupy leadership roles on decision-making bodies, this obligation must increasingly be emphasized. For example, a communication from Mark S. Frankel, director of the Scientific Responsibility, Human Rights, and Law Program at the American Association for the Advancement of Science (AAAS), argues that students and scientists should put less emphasis on their internal responsibility regarding how research should be conducted, and more on their external responsibility by being “vitally concerned” with the influence that their work and knowledge can have on society (Pain 2013 ). Scientists are increasingly required to justify the benefits of their research to society—this is notably the case for individual applications to research positions or funding, as well as for research evaluations at the institutional level—and growing debates on animal moral status spark public interest in animal behavior science. In this context, active engagement with animal ethics could translate to a new and promising applied dimension of scientists’ work—one that is both instrumentally beneficial and aligned with social responsibilities.

Opening the black box of animal minds

Following the vast accumulation of knowledge on animal behavior, scientists are faced with new questions about the nature of animal minds, a crucial topic also at the center of philosophical debate today (Lurz 2009 , Andrews 2015 , Andrews and Beck 2018 ). Nonetheless, the lingering conviction that animal mental states are unknowable—a black box that is inaccessible to science—or irrelevant to the explanation of behavior (e.g., Dawkins 2015 ) has limited scientifically-informed ethical reasoning about animals. For example, Griffin's ( 1998 ) call to bring the study of consciousness to the fore of ethology nearly two decades ago is continually met with considerable resistance (for a historical overview on cognitive ethology, see Allen and Bekoff 2007 ), and some contemporary scientists deny that documenting the degree of animal consciousness is useful in the science of comparative cognition (Shettleworth 2010 ). In addition to this fundamental debate on whether animal consciousness can and should be studied by scientists, some leading approaches in animal behavior science downplay the explanatory significance of animal mental and emotional lives. In particular, behavioral ecologists are traditionally trained to focus on the adaptive value of a trait, favoring ultimate over proximate explanations for behavior. As one example, infanticide is often framed exclusively in terms of evolutionary costs and benefits rather than any underlying emotion or proximate motivation (e.g., see van Schaik and Janson 2009 ). Although these functional evolutionary explanations are valuable in their own right, they offer only a very limited view of animal emotions, capabilities, and agency, and little to no insight into perceptions, intentionality, rationality, or consciousness residing in animal minds. This poses a deeper, more fundamental epistemological problem in the sense that building a whole field of scientific inquiry around what is currently a black box inherently hampers ultimate explanatory and predictive efforts. This shortcoming in turn reveals how explanatory frameworks in the behavioral sciences can quickly overlook or render invisible the very object of moral concern—the organism itself as a potentially sentient entity that can be benefited or harmed—or, at the very least, relegate the organism to secondary status (Walsh 2015 ).

The language that animal behavior scientists habitually employ reflects this deeply entrenched practice (Crist 1999 ). Reducing animal behavior to mechanistic, causal descriptions has reinforced the view of animals as mere objects or vehicles of their genes and environment, preempting any inferences to their mental life or agency (it is noteworthy that in the writings of early naturalists such as Darwin, animals were commonly portrayed as individuals with an array of meaningful subjective experiences and aims). For example, scientists have traditionally used terms such as innate releasing mechanism while habitually relegating complex behavioral phenomena—usually those linked with cognitive or affective capacities—to more parsimonious explanations, further distancing themselves from the animals they study. However, this presupposes that such technical, parsimonious descriptions are also unbiased, and it would behoove scientists to realize that the theoretical language they employ is built on an inherently skeptical bias toward animal subjective and agential traits. The animal ethics literature, which puts animal subjectivity and agency at the heart of its argumentation, places an ethical urgency and burden of proof on mechanistic views of animal behavior in the behavioral sciences to show that animals are not sentient (Birch, 2017 , 2018 ), and to develop more solid inferences about the existence and character of animal subjectivity (e.g., see Smuts 2001 , Godfrey-Smith 2016 ).

Questioning the anthropocentric legacy of behavioral studies

The slow development of cognitive ethology is not merely a consequence of empirical limitations in accessing animal minds or a predominant focus on ultimate explanation in studies of animal behavior. The avoidance of attributing—or even studying—morally-relevant traits such as agency, interests, or motivations and goals to nonhuman animals reflects a more pervasive bias, namely the perceived dangers of anthropomorphism (e.g., Wynne 2004 ). In addition to shaping research questions, experimental settings and interpretations of results traditionally tend to disfavor anthropomorphic hypotheses, according to which similar mechanisms underlie the behavioral similarities observed between humans and nonhumans. This occurs even when studying species that are closely related to us, a revelatory context regarding such a bias, referred to as anthropodenial by de Waal ( 1999 ). According to basic evolutionary principles, the most parsimonious explanation in such cases is the one assuming that similar processes in closely related species emerge from common ancestry (phylogenetic parsimony). A scenario in which the evolution of distinct cognitive processes generates similar behavioral manifestations in closely related species is, in fact, improbable. It is also revealing to note that simple mechanistic explanations are generally favored over phylogenetic parsimony when discussing cognitive capacities, as opposed to physiological or anatomical traits, for which scientists have no problem invoking human–animal similarity (de Waal 1999 ). This bias appears to be a direct, pervasive legacy of the famous Morgan's Canon proposed at the end of the 19th century, which states that “In no case may we interpret an action as the outcome of the exercise of a higher psychical faculty, if it can be interpreted as the outcome of the exercise of one which stands lower in the psychological scale” (Morgan 1894 , p. 53). A large philosophical literature has recently accumulated around the notion of parsimony and related methodological issues (Keeley 2004 , Fitzpatrick 2008 , Sober 2012 , Mikhalevich 2014 , Halina 2015 , Buckner 2017 ), and scientists can benefit from deeper reflection on any bias toward simplicity that is motivated by worries about the dangers of anthropomorphism.

Another upshot of this approach is that the threshold of evidence needed to provide support for a particular cognitive or emotional faculty in other species is much higher than in our own. For example, the definition of animal teaching initially proposed by Caro and Hauser ( 1992 ) has proven so strict that it would exclude many occurrences of human teaching as employed in common parlance (Laland and Hoppitt 2003 ). This anthropocentric perspective has also figured prominently in debates about animal emotions (Bekoff 2009 , de Waal 2019 ); it is not just a remnant of the behaviorist era but still alive today in the form of categorical rejections of anthropomorphism and anecdote. However, when the animal's perspective is carefully considered, anthropomorphic and anecdotal accounts have an important role to play in informing and inspiring rigorous science (Burghardt 1991 , de Waal 1999 , Bates and Byrne 2007 , Godfrey-Smith 2016 ), particularly when it comes to animal mental capacities and emotions (Bekoff 2009 ). Although this form of anthropocentric reductionism is very entrenched in the Western scientific culture in animal behavior, an independent academic tradition emerged in Japan, where anecdotes were valued and where anthropomorphism was not considered a threat (Asquith 1996 , de Waal 2003 ). Despite intense criticisms by Western scientists, Japanese primatologists used individually-based observations—which are now the standard in ethological studies—and made fundamental discoveries in socioecology, such as the existence of tight family bonds structuring animal societies, and the diffusion of socially-learned behaviors throughout animal groups, long before these questions crystallized interest in Western research (Asquith 1996 , de Waal 2003 ). This example illustrates the potential benefits of raising scientists’ awareness of the cultural and cognitive biases that may hamper progress in their discipline. And even though the fear of anthropomorphism may be less present in today's scientific culture than it used to be, the critical stance adopted by thinkers in animal ethics regarding anthropocentric values, combined with their fresh and attentive eye toward animal minds and subjectivity, encourages behavioral scientists who have not already done so to inspect the deeply entrenched sources of biases that inevitably affect their discipline.

Enriching scientific practices

A greater consideration of animal interests and subjectivity may be beneficial pragmatically by changing the way scientists ask questions, design protocols, and interpret animal reactions to experimental conditions. Integrating information about the first-person perspective of the animal is increasingly recognized as important in evolutionary modeling of the effects of natural selection on behavior (e.g., Akçay et al. 2009 ). When designing experiments, careful attention to the animal's perspective on a proposed task can reduce some biases—such as experimenter effects (Despret 2015 ). For example, laboratory mice perceive gender of the experimenter and may consequently modify their behavioral response in an experiment, with male experimenters eliciting a greater stress response than females (Sorge et al. 2014 ). Along similar lines, earlier scholars appreciated that animals live in meaningful and complex worlds, and that adopting the animal's sensory perspective was a necessary precondition for the successful study of behavior (von Uexküll 1992 ). In contrast, subsequent behavioral studies have sometimes failed to adopt such a perspective by designing studies linked to species-specific daily environmental challenges, and so are at risk of making erroneous inferences about animal capacities. For example, dogs were once thought to lack self-awareness because of their failure to pass the mirror self-recognition task, which is strongly biased toward visual species, but they were subsequently found to succeed in passing an olfactory mirror test (e.g., Gatti 2016 ). The role of perspective-taking in animal behavior research is also central to the influential work of philosopher Merleau-Ponty ( 1998 ), who first established a link between animal behavior and phenomenology—which can arguably make a major contribution to both animal ethics (Painter and Lotz 2007 ) and scientific research on animal behavior (Ruonakoski 2007 ) by offering additional insights into animal subjectivity. When it comes to studying animal behavior, Merleau-Ponty ( 1998 ) questions the behaviorist way of interpreting the scientist's role, requiring the scientist's detachment from the study subject. Rather than rejecting anthropomorphism and denying their own sensitivity toward the behavior of study subjects, scientists could acknowledge that human experience, careful observation, and even engaged interaction with animals are the only possible starting points for their investigations, because absolute detachment is impossible in practice (e.g., see Smuts 2001 , Ruonakoski 2007 , Candea 2010 ).

An interdisciplinary dialogue between philosophers, ethicists, and scientists may promote changes in paradigms that could usefully complement traditional approaches and open productive, more holistic avenues to study and understand animal behavior without compromising scientific rigor. In particular, research in cognitive ethology on concepts rooted in classical, anthropocentric philosophy (e.g., self-awareness, empathy, free will, or culture) would benefit from such discussions, which may facilitate the establishment of more inclusive definitions (i.e., applicable to studying nonhuman animals) that retain theoretical and empirical traction. It would further encourage reflection on the most efficient research approaches and the criteria that would provide supporting evidence for the existence of such phenomena in other species. As one example, some philosophers reexamined the state of knowledge regarding behaviors long thought to be unique to humans, such as the capacity to commit suicide (e.g., Peña-Guzmán 2017 ), by lending more weight to animal subjectivity than many scientists traditionally have. These exercises illustrate the potential power of such interdisciplinary dialogues for enriching the perspectives of scientists working on animal behavior while making them more aware of the fact that a collection of scientific observations can lead to divergent interpretative frameworks.

In summary, interactions between the science of animal behavior and animal ethics could have a greater and mutually beneficial scope, addressing questions about what animals are, how we should treat them, and how to envision potential futures for human–animal interactions. The possibility of such a productive exchange between science and philosophy has a strong precedent in the relationship between the science of ecology and environmental philosophy. By generating new scientific knowledge on the interconnectedness and dependence among various forms of life, the field of ecology has also influenced ethical thought. Although it is not uniformly defended by ethicists, ecology has led to calls to regard supraindividual processes, such as ecosystems themselves, as intrinsically valuable and as objects of ethical concern—particularly concerning planetary health criteria grounded in the capacity to sustain and generate biodiversity. Just as in the case of animal behavior science and animal ethics, ecology too has been a source for combating anthropocentrism and generating a more balanced, indeed scientifically-informed, worldview regarding the place of humans as one species embedded within deeply interconnected, interdependent ­living systems (Callicott 1990 ).

In turn, animal behavior scientists can contribute to animal ethics in various ways. Their potential contributions to animal ethics span the full spectrum of scientific ­activities—not only in offering original evidence that fuels theoretical progress in animal ethics, but shaping its practical applications, lending pertinent expertise, and communicating ­effectively with the wider public. There are, however, boundary conditions to what they can offer to ethicists; one prerequisite is that some research involving animals is tolerated—itself a source of disagreement even within the animal ethics community—provided that its costs are minimal and outweighed by clear benefits. As a result, behavioral scientists should carefully take ethical considerations into account when designing their research (box 1 ).

Foster productive interdisciplinary exchanges

An essential first step in this integration could be for behavioral scientists to familiarize themselves with the field of animal ethics (Armstrong and Botzler 2017 provided a comprehensive anthology of readings on animal ethics), which will also cultivate mutual respect and awareness across fields. However, at least to our knowledge, animal ethics, and philosophy more generally, are often absent from animal behavior educational programs and curricula. Reciprocally, academic departments in animal studies are typically housed in social science or humanities faculties, and often lack scientists. This structural separation limits cross-disciplinary exchanges, which could be encouraged by the development of joint teaching, reading groups, research programs, and conferences. Mutual engagement and integrative theory-building could be further fostered by hosting philosophers and ethicists in scientific labs and research groups. Furthermore, several interdisciplinary journals now provide a forum wherein scholars across these disparate fields can comment on topics of mutual interest ranging from animal emotions to the most sound approaches to animal protection legislation (e.g., see Birch 2017 along with associated commentaries).

On gaining meaningful exposure to the basic purview of animal ethics, scientists of animal behavior can further update some of their conceptual frameworks and research practices (as elaborated in the previous section), which may simultaneously foster the endorsement of their findings by nonscientists pursuing related questions. Among the most notable successes in this regard is pioneering work in the area of compassionate conservation, which attempts to appease tensions between scientists who conventionally focus on species and populations and ethicists who typically focus on individuals (Ramp and Bekoff 2015 ).

Produce relevant original evidence

As highlighted above, original evidence stemming from the natural course of animal behavior science has already played a role in inspiring important developments in animal philosophy. Of course, although detailed knowledge concerning the cognitive, affective, and social lives of animals can contribute to our understanding of what is painful to an animal, its degree of sentience and consciousness, the optimal environments in which it thrives, and so on, it certainly cannot tell us what is right or wrong—the central concepts that structure ethical theory and practice. Nevertheless, biological knowledge on the natural behavior of different species, in relation to their phylogenetic position and ecology, can help in setting species-specific criteria for animal ethics agendas. It also has a hand in proposing modes of interactions with animals that are respectful of their physiology and psychology, consistent with a new theory of animal rights that borrows concepts from political philosophy (including citizenship or sovereignty) to envision a new legal frame applicable to the complexity and diversity of animal–human relationships (Donaldson and Kymlicka 2011 ).

In addition, as has already occurred in conservation practice, there is growing pressure for policy decisions concerning animal ethics to be evidence-based, and animal behavior scientists are positioned to contribute data and knowledge that can, at a minimum, inform political decisions regarding the assignment of diverse taxonomic groupings to particular moral categories (Jones 2013 ). The diversity of species that animal behavior scientists study—many of which are beneath the radar of philosophers in favor of a focus on higher vertebrates (with notable exceptions, e.g., Godfrey-Smith 2016 , Tye 2016 )—can raise new ethical concerns and priorities. For example, combined with novel insights on behavioral and cognitive complexity, accumulating scientific evidence that fish feel pain has supported the argument that they be granted similar legal protections to other vertebrates (Brown 2015 ). Similarly, legal personhood campaigns, generally devised to grant legal protections to large mammals, are contingent on evidence concerning capacities such as self-awareness and autonomy (Wise 2000 , Andrews et al. 2018 ). Thompson ( 2019 ) recently outlined how scientists’ work could better position lawyers to build personhood cases, citing four domains—innovativeness, altruism, self-control, and defiance—that would more demonstrably provide evidence for autonomy to the court system. Despite philosophical disagreement over the personhood defense of animal rights (e.g., see Korsgaard 2018 , Nussbaum 2018 ), such communications are important given that scientists do not naturally design their research in light of legal principles and questions.

The need for evidence-based animal ethics frameworks is not to overlook the veritable limits of scientific knowledge. It is important to note that the pace and reach of scientific progress is not always compatible with more immediate ethical decisions, necessitating guidance on what to do in the absence of convincing scientific evidence for aspects of animal sentience (e.g., see Birch 2017 ). Furthermore, burden of proof frameworks must weigh the relative consequences of under- versus overattributing particular mental states to animals, as such estimations can immediately affect welfare and related policy decisions—in particular, the implications of our systematic use of skepticism as the default position should be carefully evaluated (Birch, 2017 , 2018 ). It is also important to acknowledge the diversity of ethical stances toward the weight of scientific evidence—not merely in terms of what is accepted or tolerated, but what is encouraged as the optimal way to understand the complexity of the world around us. There are important philosophical discussions about the sources of our judgment as to whether or not animals have minds and mental lives, with some defending noninferential approaches on the basis of direct experience (see Jamieson 2012 ; see also Bekoff 2009 for an interesting discussion of scientific versus common-sense approaches, which are likely best considered in tandem when it comes to animal ethics).

Regardless of one's position, many scientists in the field of animal behavior spend considerable time observing animals and, therefore, have a wealth of direct, real-world experiences in this regard. A deep understanding of evolutionary theory, allied with the intimate experiences that people who work extensively with animals have, can translate to a unique perspective on animals and human–­animal relationships that ethical debate should capitalize on (see Smuts 2001 , Godfrey-Smith 2016 for pertinent examples). Phenomenologists are particularly interested in such perspectives given their potential to elucidate new realms of being and experience, challenging traditional philosophical views on animal natures and intersubjectivity (Merleau-Ponty 1998 ).

Provide scientific expertise

Scientists’ ability to synthesize and scrutinize academic knowledge has the potential to further guide the public and policymakers in their interpretation of scientific evidence. For example, The Cambridge Declaration on Consciousness (Low et al. 2012 )—prompted by the accumulation of data revealing that humans are not unique in possessing the neurological substrates that generate consciousness—was written by a group of neuroscientists to challenge previously held standards. Animal behavior scientists could similarly consider synthesizing information about species’ intellectual, emotional, and social lives in a format that can be used by decision-makers when drafting or updating ethics policies and legislation, preferably through quantitative meta-analyses and systematic reviews. Conservation and animal behavior scientists recently convened to identify research priorities in animal behavior that promote progress in applied conservation (Greggor et al. 2016 ); a similar exercise could benefit the translation of animal ethics into practical actions. Court cases on animal legal personhood are arising in a growing number of countries, providing a new context in which animal behavior scientists may be expected to act as experts. However, unlike scientists who regularly intervene in court cases and are well aware of the legal culture, such as criminologists or psychiatrists, animal behavioral scientists are generally unprepared for such an exercise. At a smaller scale (and if not already the case), behavioral scientists can join ethics committees to ensure independent representation of animal interests in other scientific fields, and ascertain that ethical concerns are carefully weighed when reviewing articles and grant applications in their own field.

Add a scientific credit to animal ethics in outreach efforts

inally, scientists are often perceived as the authorities on animal behavior, and therefore have the opportunity to inform and engage the public about animal interests. Although it is commonplace for animal behavior scientists to emphasize the conservation implications of their work, other broader impacts related to the moral standing of animals are emphasized relatively less in their public outreach. Increasingly, research on animal behavior has mass public appeal, which opens the door for animal behavior scientists to more actively engage with contemporary animal ethical or philosophical debates and discussions—following the recent tracks of some behavioral scientists (Smuts 2001 , Balcombe 2006 , Bekoff 2009 , Brown 2015 ).

Animal behavioral scientists have much to gain from their academic community's engagement with animal ethics. By jumping into the discussion, scientists also engage more directly with a revolution that has been in part stimulated by their work. Given the rapid rise and foreseeable progress of debates around animal ethics, it is certain that the current generation of animal behavior scientists will have to confront the questions that it raises in the coming decade(s), both as scientists and as citizens. Developing a stronger, more informed and engaged stance that aims to build consensus surrounding questions raised in animal ethics becomes critical to ensure the long-term importance and contribution of their scientific field, to fulfill their moral obligations, and to meet societal expectations by taking part in debates that they are well-positioned to inform. We hope that the present article will encourage this pressing and overdue discussion.

We would like to extend our thanks to many colleagues for insightful comments at various stages of this manuscript's preparation, especially Alice Baniel, Alecia Carter, Marie Charpentier, Becca Franks, Jennifer Jacquet, Alex Lee, and Harry Marshall. We are further grateful to several anonymous reviewers, who provided thorough and constructive feedback, as well as Marc Bekoff for his advice and encouragement. Finally, we would like to express our gratitude to the nonhuman animals with whom we have worked over the years. Those experiences inspired the present article and, most importantly, cultivated a deep personal and professional concern for animal ethics. Contribution ISEM 2019–114.

Author Biographical

Christine E. Webb ( [email protected] ) is an animal behavior scientist in the Department of Human Evolutionary Biology at Harvard University in Cambridge, Massachusetts. Peter Woodford is an assistant professor in religious studies and philosophy at Union College in Schenectady, New York. Elise Huchard is a behavioral ecologist at the Institut des Sciences de l’Evolution de Montpellier, Centre National de la Recherche Scientifique, Université de Montpellier, France.

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Editorial: recent advances in animal cognition and ethology.

1. Introduction

2. advances in ethology and cognition, 3. the role of cutting-edge technologies, 4. advances in animal research ethics, 5. conclusions, conflicts of interest.

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Sueur, C.; Pelé, M. Editorial: Recent Advances in Animal Cognition and Ethology. Animals 2023 , 13 , 2890. https://doi.org/10.3390/ani13182890

Sueur C, Pelé M. Editorial: Recent Advances in Animal Cognition and Ethology. Animals . 2023; 13(18):2890. https://doi.org/10.3390/ani13182890

Sueur, Cédric, and Marie Pelé. 2023. "Editorial: Recent Advances in Animal Cognition and Ethology" Animals 13, no. 18: 2890. https://doi.org/10.3390/ani13182890

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SPECIALTY GRAND CHALLENGE article

The science of animal behavior and welfare: challenges, opportunities, and global perspective.

• United States Department of Agriculture – Agricultural Research Service, Livestock Behavior Research Unit, West Lafayette, IN, USA

Animal welfare science is a relatively new scientific discipline, evolving mostly from within veterinary medicine over the latter half of the twentieth century into an independent specialty in its own right. Originally, the field of study was heavily focused on animal behavior (ethology), but it has emerged into a truly multi- and inter-disciplinary science, encompassing such sciences as behavior, physiology, pathology, health, immunology, endocrinology, and neuroscience, and influenced by personal and societal ethics. The first academic organization devoted to the scientific study of animal welfare was established in 1966 as the society for veterinary ethology (SVE), demonstrating its veterinary roots by being then affiliated with the British Veterinary Association. The world’s first Professor of Animal Welfare was appointed 20 years later at the University of Cambridge’s Department of Clinical Veterinary Medicine, and in 1991, the SVE became the International Society for Applied Ethology, in recognition of its geographical spread and its evolution from veterinary medicine. Over the last quarter of a century, there has been further expansion of the field and now animal welfare science is represented in many universities’ veterinary medicine and animal science departments across the world. Animal welfare science has become part of the core curriculum for many veterinary degrees, is a recognized specialty qualification within the veterinary professions of Europe, USA, and Australia and courses in animal welfare science as a stand-alone discipline are offered worldwide at Bachelor’s, Master’s, and Doctorate degree levels. Within research, there have been similar patterns of expansion and a spread from a heavy focus on farm animal welfare to the welfare of zoo, laboratory, and companion animals and the impacts of humans on wildlife. There continue to be studies that compare the welfare of populations within systems, but there is also more attention given to gaining in-depth knowledge of the welfare of individual animals, knowing that populations are not homogenous and that individuals within the same system may be experiencing quite different welfare states. We not only continue to use “traditional” welfare indicators but also work to develop novel indicators for use in experimental settings or in the field. As our fundamental knowledge base increases, we look for increasing application and we respond to challenges that arise from our own research questions and findings and from societal needs. In this paper, I will focus on a number of the areas that I see represent Grand Challenges within our discipline.

Animal Welfare Science in Focus

What I hope to address under this title are the challenges that define how the science of animal welfare may progress over the next few years. I will present my views of the challenges and opportunities that welfare assessment presents and how we adapt and adopt methodologies within animal welfare science to obtain greater understanding, quantification, and qualification of an animal’s welfare state. Historically, animal welfare has been defined under one of three over-arching, and intersecting, themes or approaches. These are biological functioning, “naturalness,” and feelings. The biological functioning theme of animal welfare enables us to focus on discreet measurable parameters, such as health indicators, production measures, measures of physiological functioning, and incidence of behaviors, and combine multiple measures to draw an overall picture of the welfare of the given animal at the time, or prior to, when the measures are taken. The “naturalness” theme focuses on the extent to which the animal is leading, or can lead, a life in which it is free to express its natural behavioral repertoire, with the idea that an animal being able to experience or fulfill its inherent nature, will have good welfare. The third theme concerns the feelings, emotions, or affective states of the animal, with the broad idea that for an animal to be experiencing good welfare, it should not only be devoid of negative emotions, such as anxiety or fear, but should also be experiencing positive emotions, such as pleasure or happiness. As I said above, these themes or approaches do not each exist in isolation and it is commonly acknowledged that there is a degree of overlap between them, and that in attempting to best establish the welfare state of an individual, there should be elements drawn from all three approaches ( 1 ).

Animal Welfare and Emotional States

The emotional states of animals in our care have been increasingly important in research terms, over the last few years. A Web of Science search combining the terms “animal welfare” with a number of different terms of emotionality shows a rapid increase in both publications and citations in the last 10 years (Figure 1 ). Out of a total of nearly 1350 publications, 130 focus on positive emotional states, whereas over 1200 address negative emotional states and the most cited paper (which includes open commentary from 45 other academics) concerns animal suffering ( 2 ).

Figure 1. Number of publications and citations of studies that include animal welfare and emotions over the time period 1985–2014 (Web of Science) .

However, the more recent trend is an increasing interest in positive rather than negative emotional states and a recent review article on measuring positive emotions in animals in relation to welfare is topping the table in terms of citations per year ( 3 ). In terms of recent experimental work, the most influential studies have been those using cognitive bias to assess emotional state ( 4 , 5 ). Other work in this area has included the use of functional near infrared spectroscopy to assess changes in cortical perfusion and neuronal activity in the study of mood and emotional reactions ( 6 ). There is no doubt that further adaptation of methods used within cognitive science and behavioral neuroscience will yield new fundamental insight into animal emotions, and thus its welfare. An example could be further development of electroencephalogram (EEG), which although currently used in sleep ( 7 ) and euthanasia/slaughter studies ( 8 ), may also yield insight into emotional state ( 9 ).

Animal Welfare and Quality of Life

A more recent term and concept that has been used within the companion animal welfare field is that of quality of life (QoL). The term “Quality of Life” originated within the human sociological/geographical/medical fields in 1950s and 1960s and within the human field, depending on context, is taken to encompass such measures as wealth, physical and social environment, health, and biological functioning. Critically, within the human medical field, it also incorporates the psychological well-being of the individual and health-related QoL (HRQoL) is defined as being “subjective and multidimensional, encompassing physical and occupational function, psychological state, social interaction, and somatic sensation” ( 10 ) and invariably includes self-reporting. Certainly, the emphasis of human QoL is on affective states in general and positive affective states, in particular. From an animal perspective, this of course presents problems. QoL for animals has been defined as encompassing animal welfare and the subjective feelings of the animal regarding its life, but that it can only be inferred from behavioral, physiological, and other measures ( 11 ). So it would seem that for many animal welfare scientists, there is a large degree of synonymy between their own working definition of “animal welfare” and that of “animal QoL,” but there is also some confusion ( 12 ).

Although there has been recent use and assessment of QoL in animals – mostly companion animals – there is certainly a degree of resistance within the broader animal welfare field to use of the term, either because of the perceived time-span limitations of its coverage or because of the anthropomorphism and subjectivity associated with a definition that includes assessment of an animal’s psychological state by indirect methods. However, there is increasing research focus within our field on indicators of positive welfare, rather than negative welfare, and on measures of the animal’s affective state, meaning that as our methods and measures evolve and refine, we may see a shift toward a concept of animal welfare that is more in line with definitions of QoL than our current definitions of animal welfare.

Animal Welfare Assessment in the Field

Increasing our fundamental knowledge about an animal’s welfare is part of our remit as animal welfare scientists. We also have to seek to apply that new-found knowledge to improve the welfare of animals under our care ( 13 ). When assessing animal welfare within an experimental setting, there is greater focus on the individual animal and more options in terms of the parameters that can be measured. Out in the “field,” be it within a farm, zoo, or lab animal facility or with companion animals in homes, stables, or shelters, there are many more limitations on the types of data that can be collected and where large facility populations are concerned, there will be focus on the group rather than on individuals within the group.

The reasons for assessing welfare in the field will differ depending on the setting and the species. For farm animals, ensuring a certain welfare standard may be tied to improving productivity and also to marketing of the end product, based on consumer or retailer demand ( 14 ), as seen by the many auditing or quality assurance schemes that exist for farm animal production. For laboratory animals, there is again a societal demand for a minimum welfare standard to be met, and there is sound argument that testing is carried out on animals devoid of poor welfare and altered biological function ( 15 ). For zoo animals, it may be relevant again to the “consumer” – i.e., the zoo-going public – and enforced by legislation ( 16 ), but also to better serve the biological needs of the animals to facilitate reproduction in those species subject to conservation efforts and because it is an ethical obligation. The Association of Zoos and Aquariums has a stated policy that “Animal and human health, safety, and welfare are never compromised” ( 17 ). Welfare assessment among companion animals is less developed and is more focused on environments where populations are being housed – e.g., humane shelters – rather than home settings with few individuals. Within shelters, there is an increasing understanding that physical and social environments that improve welfare also improve long-term adoptability ( 18 ).

The majority of field welfare assessment protocols for farm animals are heavily weighted in terms of environmental assessment – that is they gather much information on such things as the physical housing, the management techniques, the health and production records, and relatively less information on measures that are taken on the animals themselves. On large farms, there is a trade-off between time and the number of animals that can be assessed, and thus assessment has to be carried out on a representative sample, that will give an indication of the overall, or “population average” welfare rather than the welfare of individuals within the population. Also, the animal-based measures that are taken are often more concerned with direct measures of health and disease, or indirect measures of behavior, such as skin lesions, rather than the behavior itself. There has been some good progress in farm animal assessment recently ( 19 ), but more animal-centered methods and, in particular, methods that give quantifiable insight into the psychological lives of animals are needed, together with the development and validation of new indicators, such as tear-staining ( 20 , 21 ) that are relatively easily discernable to the observer, that may enable more objective assessment of individuals within a given population. For laboratory animals, even in a large facility, there should be greater attention to the individual than seen with on-farm assessment ( 22 ). Welfare assessment should comprise components that describe or quantify physical, physiological/biochemical, and psychological states, and may include scoring scales for such things as body weight, coat condition, respiration rates, ocular discharge, feces condition, and provoked behavioral response. With well-defined scoring scales, the overall assessment of an individual’s welfare can be objectively quantified and intervention carried out if a threshold total score is reached ( 22 ). Zoo animals are mostly housed in limited numbers and welfare assessment at an individual level is commonplace. Zoo keepers often have many years of experience with particular species and individual animals and are thus well-placed to assess welfare through sometimes quite subtle changes in appearance or activity, which can be objectively recorded and reported over time, using available tools such as WelfareTrack ® ( 23 ). Superimposed upon individual-level assessment, there are also increasing numbers of projects within the zoo community that seek to combine multi-institutional data and information to identify patterns in welfare issues for particular species, that may be previously unidentified without such collaboration ( 24 ).

Animal Welfare and the “Big Picture”

Animal welfare is an important societal concern and as a scientific field of study, animal welfare is one of the branches of specialized science that is most accessible and inherently interesting to the majority of the general public. This is a good thing, as public importance and relevance opens minds and doors to expansion and application of our science. As I touched on above, the original concept of QoL from a human point of view was to encompass aspects of the physical and social environment. For a great many people, their relationships or interactions with animals constitutes a large part of their daily life, and the quality of that life, be it with animals owned as companions or as a source of income, or with free-living animals within their ecosystem. As the global population continues to grow, there are a number of societal “Big Picture” challenges that are being, and will continue to need to be addressed, and with which animal welfare is intrinsically tied. Thus, as animal welfare scientists, it is more essential than ever that we do not live wholly within the bubble of animal welfare science and that we expand our horizons outside a relatively narrow scientific discipline to interact with, inform and learn from others working on global issues, which themselves are interconnected.

Animal Welfare, Population Growth, Global Food Security, and Sustainability

Food security is access by all people at all times to enough food for an active, healthy life ( 25 ) and it means having a reliable source of food and sufficient resources to purchase it. A family is considered food secure when its members do not live in hunger or fear of starvation. For those of us working in animal agriculture, we are constantly reminded of projected global population growth over the next 35 years, with an expected increase in global population from the current 7.2 billion up to 9.6 billion by 2050. Concomitant with this increase in overall population is a projected increase in overall food demand and a projected per capita increase in demand for food from animal sources, especially in developing countries. At present, more than 1 billion people are food insecure. As the global population increases, the number of people with an insecure food supply will also dramatically increase unless there is an increase in food production, and improvements in food distribution and storage. Given the sizeable stress that this demand for animal and crop production will place on planetary resources, it is not surprising that “sustainability” has become a keyword within agriculture as a whole. The main emphasis is on economic and environmental or ecological sustainability, but there is also the critical element of ethical or social sustainability ( 26 ). The projected increase in animal production will be achieved by increases in animal numbers and further increases in productivity – output per unit input. However, although current projections do show an increase in animal production, it is also probable that the actual increase will be buffered by a shift in diet away from animal products to foods from crop sources, either through concerns about animal welfare or sustainability/land-use efficiency or through perceived health benefits associated with a vegetarian/vegan diet. Twenty-five years ago, reasons for not eating animal products were mostly due to animal welfare (66%) and health reasons (26%) rather than environmental/ecological reasons (1%) ( 27 ). Five years ago, a much larger survey found that reasons for dietary animal-product avoidance were now shifted toward health (40.1%) and environmental/ecological (38.1%) reasons and away from animal welfare reasons (16.5%) ( 28 ). Although these studies are not directly comparable, they do highlight that consumers are also looking more at the “big picture” and identifying the relationship between animal production and sustainability.

Although over the last few decades, livestock farming in developed countries has been characterized by decreasing farm numbers, increasing farm size, and increased intensification, its ethical acceptability has been increasingly questioned. There will still be increasing intensification in newly industrialized and developing countries to meet the growing food demand, albeit not completely unquestioned. Fully industrialized economies, however, will continue to see mounting vociferous opposition to farming systems that do not meet society’s demand for production that is ecologically, environmentally, and ethically acceptable. Within the ethical acceptability boundary is the notion that animal farming systems must meet or exceed standards of animal welfare deemed acceptable by the given society, and this should not be overlooked ( 29 ). Even though a system may be environmentally and economically sustainable, if the animals kept within it are subject to housing conditions or production demands deemed unacceptable in terms of animal welfare, then consumer acceptance will evaporate, demand for the product will decrease and the system of production will ultimately become unsustainable – as seen in confinement housing systems such as veal crates, battery cages for laying hens, and gestation crates for sows. Alternatively, public antipathy may reach such a level that rather than a gradual decline in consumer demand forcing change, legislation may be enacted that outlaws the production system, either within a localized legislative framework (e.g., single state or country) or a more broader one (e.g., federal body). Examples of such housing systems include battery cages for laying hens, crates for veal calves, and crates for gestating sows.

However, it is not only housing systems being questioned. The public is also concerned with the animal’s own biological functioning and whether continued “improvements” in parameters such as litter size, growth rates, egg or milk production can be supported if the animal’s welfare is negatively impacted in combination. Another animal welfare concern is the potential impact of increased food production on wildlife, with decreasing natural habitats as land is converted to crop or animal farming and the culling of predators or wildlife that may consume crops or compete with farmed animals for resources. The issue of animal welfare as a component of sustainability and food security is important as we implement or adapt current systems for use in developing countries, and design new systems for use in a dynamic, economically interconnected world. Although the integration of an animal welfare emphasis into livestock and crop production systems in developing countries can also result in higher biodiversity, restoring habitat, reversing the impact of traditional production systems ( 30 ), and improving QoL, the standards of acceptable animal welfare are greatly changed by the level of food security and those of us living in food secure households must be aware that our own baseline of acceptability may be quite different from those struggling to feed themselves regularly.

Finally, another often overlooked aspect of growth in global population and wealth is a concomitant increase in the global population of companion animals, particularly in those countries with developing economies. For example, India has seen a 90% increase in cat and dog population between 2002 and 2012 ( 31 ), and even the U.S. cat and dog population has increased 15% in that time. In terms of big picture implications, this rapidly expanding population also puts further pressure on food supply and hence food security and sustainability. Increasing feral populations of companion animal species can also impact wildlife and animal and human health.

Animal Welfare and Climate Change

Scientific consensus is that the world’s climate is undergoing change ( 32 ). Temperatures and sea levels are rising and extreme climatic events are increasing in number. Much of this is attributed to an increase in greenhouse gases as a result of human activities, including some from animal production ( 33 ). Climate change will impact wildlife welfare in many ways, such as affecting habitat and food sources, decreasing water availability and shifts in ranges of disease vectors ( 34 ) to the extent that many species will ultimately be at threat of extinction ( 35 ). Companion and zoo animals may likewise be subjected to vector-borne diseases in new geographical areas and challenged by changes in thermal environment. Climate change will also present potential challenges in crop and animal production at a time when, as noted above, overall demand will be increasing. The projected further changes over the twenty-first century are variable, depending on the projection model used, but the general implications include further increases, and perhaps fluctuations in temperature and greater variability in precipitation, resulting in reduced or modified availability of water for agricultural purposes.

So far, there have been very few studies that have tried to quantify the impact of real-life climate change over the last few decades on livestock production, and those that have been carried out are focused on modeling projected impacts of future climate change, or models of disease transmission given the increased range of disease vectors. However, under experimental conditions, it is well known that heat and cold have very obvious effects on productivity, and indeed on welfare. Heat stress reduces appetite, reduces growth, affects reproduction, decreases milk and egg production and, at critical levels, can lead to heat stroke and death ( 36 ). Shifts in both maximum and minimum temperatures may result in more animals being exposed to both heat and cold stress events, thereby impacting their welfare.

Changing precipitation patterns may result in current pastoral-based systems having to adapt either in response to moving away from drought-susceptible areas or having to surrender high-quality pastureland over to crop production, and moving to reduced quality areas, with breeds of livestock that are not so well suited for the new, harsher environment. The changes in climate may also impact disease transmission with disease vectors, such as insects, becoming established in previously unrecorded areas.

Animal Welfare, Animal Health, and Food Safety

A recent study estimated that each year in the U.S., about 3% of the population suffers from an illness due to 1 of 31 known foodborne pathogens. According to these data, there are approximately 9.4 million illnesses, of which 56,000 require hospitalization, resulting in 1350 deaths ( 37 ). The U.S. Centers for Disease Control and Prevention estimate much higher figures. They not only include the above data set but also include data due to “unspecified agents” causing the symptoms of acute gastroenteritis. Combined, there are 48 million illnesses, 128,000 hospitalizations, and 3000 deaths ( 38 ). These are not all animal-product related, and further estimates within the U.S. put animal-related foodborne illness as a cause of 42% of illnesses, 46% of hospitalizations, and 43% of deaths, with major illness-causing agents identified as Listeria , Salmonella , Campylobacter spp., and Norovirus ( 39 ). Expand these estimates to a global population and the impact of unsafe food, especially in areas with limited access to medical treatment is great. The World Health Organization estimate 1.9 million children die each year from diarrheal illnesses and there is a major WHO initiative underway to estimate the “global burden of foodborne diseases,” which will report in 2015.

How does food safety fit with animal welfare? There is plenty of evidence of a direct link between animal welfare and animal health. Animals under stress are often immune-compromised and are more susceptible to disease. Higher levels of disease within an animal population can result in an increased risk of bacterial or viral contamination within food products and there is also a risk of medication residues in food products if withdrawal protocols are not stringently followed. Although the public often consider extensive production systems as being high welfare and high health, the reality is that decreased biosecurity in extensive systems may, in fact, increase exposure to, and incidence of certain diseases ( 40 ). There remains a greater need to consider the “farm-to-fork” chain as a whole and not focus on individual stages of the chain in isolation. Only with a foundation of high welfare/low stress/high health production systems can we begin to make real advances in the safety of the final products. Again, this “big picture” theme is intrinsically linked to the others.

Originally, animal welfare science was heavily behavior-based. As a scientific discipline in its own right, animal behavior has perhaps been unfairly thought of as a “soft” science and is still subject to misapplication by non-ethologists assuming they can study behavior without adequate expertise or training. Done right, behavior is valid and precise but it has taken the integration of perceived “harder” sciences such as physiology, immunology, and pathology for animal welfare science to evolve independence and specialty status. There is also the irony that as we now strive to develop and incorporate measures that will identify and quantify emotional state, we are perhaps returning to our ethological roots and becoming more reliant on behavior as a key component of our science.

As I hope I have illustrated above, there are real opportunities for animal welfare science to continue to expand our fundamental knowledge of many facets of biological functioning of the animals with which we interact, and enable us to apply our new-found knowledge to continue to improve our animals’ lives. A major advantage for our discipline is its relative accessibility to the general public and to scientists working in other fields. Animal welfare science is therefore positioned to play a role in some of the big issues confronting our global society and the opportunities afforded by inter-disciplinary collaboration should be embraced.

Conflict of Interest Statement

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

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Keywords: animal welfare, behavior, ethology, emotions, welfare assessment, ethics

Citation: Marchant-Forde JN (2015) The science of animal behavior and welfare: challenges, opportunities, and global perspective. Front. Vet. Sci. 2:16. doi: 10.3389/fvets.2015.00016

Received: 16 March 2015; Accepted: 14 May 2015; Published: 28 May 2015

Reviewed by:

Copyright: © 2015 Marchant-Forde. 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) or licensor 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: Jeremy N. Marchant-Forde, jeremy.marchant-forde@ars.usda.gov

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.

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• 15 June 2020

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Christian Rutz is a professor in the School of Biology, University of St Andrews, UK, and worked on this article while he was the 2019–2020 Grass Fellow at the Radcliffe Institute for Advanced Study, Harvard University, Cambridge, Massachusetts, USA.

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Ten years ago this week, researchers pointed out that many important findings in human experimental psychology cannot be generalized because study participants are predominantly drawn from a small, unrepresentative subset of the world’s population: societies that are Western, Educated, Industrialized, Rich and Democratic (WEIRD) 1 . Mounting evidence suggests that there could be similar sampling problems in research on animals. Behavioural studies of a wide range of species — from insects to primates — could be affected, with researchers testing individuals that are not fully representative of the wider populations they seek to understand. For example, certain sampling protocols are likely to trap the boldest animals, potentially skewing experimental results 2 .

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