About

Dr. Adrian Treves is a researcher focused on wildlife science, particularly the study and management of carnivores such as wolves. His work emphasizes scientific integrity, transparency, and the importance of open data in wildlife research and policy. Treves has contributed to debates on wolf management, critiquing the scientific methods and data transparency of Wisconsin Department of Natural Resources (WDNR) studies, and has highlighted issues related to research reproducibility, conflicts of interest, and ethical standards in scientific publishing. He has authored numerous articles and editorials addressing the ethics of peer review, the need for transparency in scientific research, and the importance of science-informed decision-making in wildlife policy. Treves advocates for rigorous scientific standards and open science practices to ensure credible, unbiased research that can effectively inform public policy and conservation efforts. His work also involves developing frameworks for understanding wildlife trusteeship and promoting the role of science in safeguarding ecological and public interests.

Research topics

• Political Science
• Sociology
• Biology
• Geography
• Ecology
• Law
• Environmental planning
• Criminology
• Psychology
• Environmental resource management
• Zoology
• History
• Law and economics
• Environmental ethics
• Public relations
• Economics
• Demography

Selected publications

• Hounds and Bystanders

  OSF Preprints (OSF Preprints) · 2026-02-11

  other1st authorCorresponding

  manuscript plus 3 SM files

  Publisher

• SM 1-3

  OSF Preprints (OSF Preprints) · 2026-02-11

  other1st authorCorresponding

  Supporting Materials 3 files

  Publisher

• Community Counting Carnivores: Discrepancies between volunteer and DNR winter gray wolf counts in Wisconsin 2003-2011 

  2026-03-10

  articleOpen accessSenior author

  Large carnivores are threatened globally, with most extant taxa having suffered significant historical range contractions. Due to this imperiled status, as well as increased scientific interest in top-down ecological processes, ecologists and conservationists have dedicated renewed efforts towards large carnivore preservation and management. As part of these efforts, reliable and transparent population monitoring is critical both to evaluating population dynamics as well as to detecting policy and management effects on large carnivore populations. Therefore, it is imperative to evaluate how methodological changes to monitoring regimes may affect the bias and uncertainty of estimates, especially with cryptic and politically contentious taxa like large carnivores. We describe methodological changes in Wisconsin gray wolf (Canis lupus) censusing techniques by the Wisconsin Department of Natural Resources (DNR), paying particular attention to a citizen science program where volunteers conducted winter wolf track surveys separately from DNR trackers. We hypothesize how changes to volunteer training and participation in winter wolf counts may have resulted in several methodologically distinct time series of wolf population estimates. To investigate this hypothesis, we use a Bayesian mixed effects model to analyze how volunteer and DNR trackers counted wolves during a relatively methodologically consistent period from 2003 to 2011 and find that volunteers counted 83% (95% CI: [74%-92%]) as many wolves as DNR trackers. Therefore, we conclude that changes in relative volunteer involvement before and after that period must necessarily affect the bias and precision of wolf population estimates. We hypothesize possible reasons for this discrepancy between volunteer and DNR trackers, including differences in tracking aptitude, potential biases among trackers, and differences in survey timing. We also simulate volunteer and DNR wolf counts as if both tracker types had surveyed all blocks across all years to compare our reproducible wolf count uncertainties to DNR-reported uncertainties. We end with recommendations for more transparent and reproducible wolf counting by the DNR and broader recommendations for ecological citizen science initiatives.

  PublisherDOI

• A code of ethics for peer reviewers

  Frontiers in Ecology and the Environment · 2026-02-18

  articleOpen access1st authorCorresponding

  Peer review of research findings has changed repeatedly since 1832, when the Royal Society formalized written refereeing by experts (Hist J 2018). Calls for the reform of peer review have changed the system, including calls from researchers concerned with their peers’ impartiality or ability to catch errors or fraud. Here, we address a narrow set of issues relating to the conduct of peer reviewers toward not only their editors but also the authors whose work they are reviewing. An explicit code of ethics may be needed for the vast and far-flung research community, given the logistical impossibility of convening all members to discuss conduct and given the confidentiality of single- and double-blind reviews. Ethics seem particularly important; if overlooked during review, misconduct can corrupt the research-based evidence demanded by public policy and threaten the entire research endeavor. The problem may be even more acute now, given the global rise in anti-intellectualism, including mistrust of experts. Because high-quality independent review is essential to advance knowledge, our recommendations for a code of ethics for reviewers follow the hallmark principles of good science—transparency, independence, falsifiability, and reproducibility—as well as recent calls for greater diversity in the scientific community. Transparency in peer review is fundamental to each step. Transparency about independence should enhance confidence that the review was not distorted by rivalries, collaborations, or other competing interests. Just as most statistical tests require independence of samples, the reliability of findings requires independence between peers during review. Hence, reviewers should disclose all financial and non-financial potentially competing interests related to the authors (if identifiable), methods, or findings of articles they review. We cannot be the judges of our own partiality. Non-financial interests that compete with our ability to fairly and scientifically evaluate findings are especially hard for us to see in ourselves, because they relate to ideology, personal rivalry/friendship, unconscious bias, etc. Transparency also requires reviewers to disclose when they are unqualified to address any portion of a manuscript or would like a specialist to examine the relevant passages. Likewise, a reviewer who challenges a claim made by authors must have (and reveal) the evidence behind their challenge. The challenge must be falsifiable (open to disproof) and the evidence must be reproducible. A common breach of this ethical code is for reviewers to subtly undermine the authors’ credibility not with evidence but rather with assertions such as “In my experience…” and vague citations to unspecified or non-peer-reviewed sources. Such assertions and citations are unscientific because they cannot be falsified. The need for falsifiable, reproducible evidence in reviews extends to the use of generative artificial intelligence (GenAI), including large language models (LLMs), which draws from others’ work untraceably. If one uses GenAI applications in limited circumstances, including translation or simple online searches, one must disclose how and specify the tool by name (see transparency above). At first glance, diversity in the scientific community might appear to be unrelated to peer review. As Oreskes, in her 2019 book “Why Trust Science?” (Princeton, NJ: Princeton University Press) argued, the scientific endeavor advances more quickly when the research community approaches evidence from diverse viewpoints with open-minded scrutiny of all claims. Homogeneity of thought or experiences may impede thoroughgoing scrutiny of the assumptions or methods in a manuscript. Differences of opinion and clashes of values are not scientific disagreements and, thus, not a basis for judging methods or findings. Who conducted the work or how you feel about the results muddles facts and values. All of us have bemoaned when the lay public decides that they dislike a finding and consequently ignore its implications; so why do we do it to peers? Even when confronting methods, peers should suspect themselves of being partial to the assumptions, hypotheses, and procedures with which we are familiar or fond. Chamberlin's early insight (Science 1965) cautions us against “the dangers of parental affection for a favorite theory”. Business as usual does not seem to satisfy anyone. Although imperfect, peer review is arguably the best model available to evaluate research findings. Therefore, a strong code of ethics may now be needed to increase trust in science.

  PublisherOA PDFDOI

• Irreproducible research and a typology of replication efforts

  2026-01-26

  articleOpen access1st authorCorresponding

  The scholarly and scientific literature does not automatically correct itself. Erroneous findings may persist without correction or retraction. Following prior definitions of zombie articles that are retracted but continue to be cited affirmatively, we add another category of ‘undead’ articles. We define ‘vampire’ articles by two necessary conditions. The first condition is irreproducibility, demonstrated by one or more failed efforts at replication or conditions that make replication impossible. We offer a novel typology of four categories of replication efforts. We propose a rule of thumb for how many failed efforts at replication might be required for each type of replication effort before the original finding is deemed irreproducible. The second condition for a putative vampire article is that it is cited affirmatively in public policy, the scholarly literature, or private communications, after the first condition is met. We discuss rules of thumb for how many such affirmative citations might lead qualified researchers in that subfield to propose correction, retraction, or editorial note of concern for the article in question. Our first case concerns aerial shooting at coyotes and the second case predicts over-fishing. We discuss the damaging effects of vampire articles and why the metaphor has heuristic value and utility. We also discuss lessons from the communication sciences about how to remedy misinformation, offering recommendations to researchers, publishers and editors, concerned with correcting their literatures and public trust in science generally.

  PublisherDOI

• Toward a Synthetic Theory of Tolerance for Carnivores: Learning from a Half-Century of Research on Attitudes Toward Wolves

  Conservation · 2026-04-02

  articleOpen accessSenior author

  Human intolerance is a critical factor limiting both the distributions and populations of large carnivores. Using gray wolves as a case study, we synthesize a half-century of scholarship with the aims of clarifying the conceptual foundations of “tolerance” and integrating insights from across the social sciences. Specifically, we review longitudinal studies of attitudes toward wolves and show how trends vary across the populations examined. We then identify and discuss three complementary theories that help explain variation in tolerance across individuals, social groups, and societies: (1) Risk–benefit theories illuminate how perceptions of risks, benefits, and controllability shape individuals’ tolerance of carnivores; (2) Modernization theory explains societal shifts in values and shows how reduced threats from carnivores impact tolerance at the societal level; and (3) Social Identity Theory highlights how identification with interest groups (e.g., hunters, environmentalists) shape beliefs in a manner that serves to exacerbate inter-group conflicts. Linking these theoretical perspectives provides a more holistic framework for understanding why tolerance can change within populations, and why inter-group conflicts persist even as societal attitudes have become more favorable. We conclude by outlining research priorities aimed at improving our understanding of tolerance and the conditions that allow for human–carnivore coexistence.

  PublisherOA PDFDOI

• Mexican wolf management needs transparency in methods and data to support policy decisions

  Journal of Applied Ecology · 2025-12-09

  articleOpen accessSenior author

  Abstract Mexican wolves ( Canis lupus baileyi) , an endangered subspecies of grey wolves, were extirpated in the Southwest United States by the 1970s. Since 1998, reintroduced Mexican wolves have been listed as an endangered species under the U.S. Endangered Species Act. A recent analysis by Breck and others of the factors affecting Mexican wolf recovery, searched for correlates of population growth rate, mortality and illegal killing and concluded that releases of captive‐bred adult wolves should be minimized. This policy recommendation is compromised by several shortcomings including: (i) the use of time periods not consistent with policy implementation and termination dates, (ii) the authors' choice to include, or exclude, data in their analyses that do not align with publicly available agency data, (iii) unclear or unexplained methodological decisions and (iv) a failure to consider the genetic consequences their recommendations can have on long‐term recovery. Synthesis and applications : These methodological shortcomings (omissions in the interpretation of policy periods, lack of clarity on data inclusion and exclusion, and unclear use of and changes to a referenced model, as well as an insufficient consideration of Mexican wolves' genetic diversity) raise questions about the validity of the resulting management recommendations. While democratic, participatory and transparent processes are needed for fostering coexistence between Mexican wolves and people, recommending reductions in approaches that enhance genetic diversity in this endangered population seems premature without stronger supporting evidence.

  PublisherOA PDFDOI

• Robust inference and errors in studies of wildlife control

  Scientific Reports · 2025-09-26

  articleOpen access1st authorCorresponding

  Randomized, controlled trials (RCT) are seen as the strongest basis for causal inference, but their strengths of inference and error rates relative to other study designs have never been quantified for interventions designed to prevent wildlife damage to property and game. We simulate common study designs from simple correlation to RCT with crossover design. We report rates of false positive, false negative, and over-estimation of treatment effects for five common study designs under various confounding interactions and effect sizes. We find non-randomized study designs mostly unreliable and that randomized designs with suitable safeguards against biases have much lower error rates. One implication is that virtually all studies of lethal interventions against predatory wildlife appear unreliable. Generally, applied fields can benefit from more robust designs against the common confounding effects we simulated.

  PublisherOA PDFDOI

• Robust inference and errors in studies of wildlife control

  Research Square · 2025-07-18

  preprintOpen access1st authorCorresponding
  PublisherOA PDFDOI

• Removing wolves did not reliably prevent domestic animal losses.

  2025-05-15

  preprintOpen access1st authorCorresponding
  PublisherDOI

Frequent coauthors

• Chris T. Darimont

  Raincoast Conservation Foundation

  41 shared

• Guillaume Chapron

  Swedish University of Agricultural Sciences

  36 shared

• José Vicente López‐Bao

  Universidad de Oviedo

  35 shared

• Jeremy T. Bruskotter

  The Ohio State University

  33 shared

• Roșie Woodroffe

  Zoological Society of London

  31 shared

• Lisa Naughton‐Treves

  University of Wisconsin–Madison

  29 shared

• Thomas M. Newsome

  University of Sydney

  29 shared

• Luke Hunter

  Wildlife Conservation Society

  27 shared

Labs

• Carnivore Coexistence LabPI

  Research on the ecology, law, and human dimensions of ecosystems where crop and livestock ownership overlaps the habitat of large carnivores.