Received: 21 December 2020 Revised: 5 July 2021 Accepted: 12 July 2021 DOI: 10.1111/conl.12832 POLICY PERSPECTIVE Mischaracterizing wildlife trade and its impacts may mislead policy processes Daniel W.S. Challender1 Dan Brockington2 Amy Hinsley1 Michael Hoffmann3 Jonathan E. Kolby4,5 Francis Massé6 Daniel J.D. Natusch7 Thomasina E.E. Oldfield8 Willow Outhwaite8 Michael ’t Sas-Rolfes9 E.J. Milner-Gulland1 1 Department of Zoology, University of Oxford, Oxford, UK Abstract 2Sheffield Institute for International Overexploitation is a key driver of biodiversity loss but the relationship between Development, University of Sheffield, the use and trade of species and conservation outcomes is not always straightfor- Sheffield, UK 3 ward. Accurately characterizing wildlife trade and understanding the impact it Conservation and Policy, Zoological Society of London, London, UK has on wildlife populations are therefore critical to evaluating the potential threat 4IUCN SSC Amphibian Specialist Group, trade poses to species and informing local to international policy responses. How- Toronto, Canada ever, a review of recent research that uses wildlife and trade-related databases to 5 College of Public Health, Medical and investigate these topics highlights three relatively widespread issues: (1) mischar- Veterinary Sciences, James Cook University, Townsville, Australia acterization of the threat that trade poses to certain species or groups, (2) misin- 6 Department of Geography & terpretation of wildlife trade data (and illegal trade data in particular), resulting Environmental Sciences, Northumbria in the mischaracterization of trade, and (3) misrepresentation of international University, UK policy processes and instruments. This is concerning because these studies may 7 Department of Biological Sciences, Macquarie University, Sydney, New South unwittingly misinform policymaking to the detriment of conservation, for exam- Wales, Australia ple by undermining positive outcomes for species and people along wildlife sup- 8 TRAFFIC, Cambridge, UK ply chains. Moreover, these issues demonstrate flaws in the peer-review process. 9School of Geography and the As wildlife trade articles published in peer-reviewed journals can be highly influ- Environment, University of Oxford, ential, we propose ways for authors, journal editors, database managers, and pol- Oxford, UK icymakers to identify, understand, and avoid these issues as we all work towards Correspondence more sustainable futures. Daniel W.S. Challender, Department of Zoology, University of Oxford, Zoology KEYWORDS Research and Administration Building, 11a CITES, database, illegal trade, IUCN Red List, policy, social media, sustainable use, threat, Mansfield Road, Oxford, OX1 3SZ, UK. wildlife trade Email: dan.challender@zoo.ox.ac.uk This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2021 The Authors. Conservation Letters published by Wiley Periodicals LLC Conservation Letters. 2022;15:e12832. wileyonlinelibrary.com/journal/conl 1 of 10 https://doi.org/10.1111/conl.12832 1755263x, 2022, 1, Downloaded from https://conbio.onlinelibrary.wiley.com/doi/10.1111/conl.12832 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [26/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 2 of 10 CHALLENDER et al. 1 INTRODUCTION 2 MISCHARACTERIZATION OF THE THREAT WILDLIFE TRADE POSES TO Overexploitation is a key driver of biodiversity loss SPECIES (Maxwell et al., 2016) but the relationship between the use and trade of species and conservation outcomes is not Various studies have characterized the threat of wildlife always straightforward. While harvest and trade can some- trade to species (Table 1). However, these threats can be times benefit both wildlife populations and people, at other mischaracterized where data are misinterpreted, or results times it can drive biodiversity loss (Cooney et al., 2015; are overinterpreted by authors subjectively evaluating the Hutton & Leader-Williams, 2003). Accurate characteriza- impact of trade on wild populations without supporting tion of wildlife trade and an understanding of the impact it evidence. has on wildlife populations are therefore critical to eval- Misinterpretation of datasets can arise if researchers are uating the potential threat trade poses to species and to not aware of important limitations to the datasets they informing local to international policy responses. Large- are using. Regarding the Red List for instance, not all tax- scale databases are increasingly being used as tools to onomic groups have been comprehensively assessed, so guide international conservation policy. These include the there are biases in species taxonomic coverage. In addi- IUCN (International Union for Conservation of Nature) tion, not all species have complete data on scope and sever- Red List of Threatened Species (hereafter “Red List”) and ity of threats (making it difficult to distinguish the rela- the CITES (Convention on International Trade in Endan- tive impacts of different threats), and information on use gered Species of Wild Fauna and Flora) Trade Database. and trade of species is incomplete for many taxa because Similar databases focus on illegal wildlife trade (Support- it is not required documentation for Red List assessments ing Information S1). There is also an increasing body of (IUCN, 2013). Fukushima et al. (2020), for example, ana- research using datasets derived from monitoring of wildlife lyzed patterns of use and trade among species on the Red trade that takes place online (e.g., Hinsley et al., 2016). List without reference to inconsistencies in documenta- Studies using these data sources frequently offer policy rec- tion. They further estimated the proportion of “traded” ommendations to inform international policymaking (e.g., species among threatened species in different phyla but CITES, 2019a). present the results as the proportion of species “threatened Although many examples of wildlife trade research by trade,” an incorrect and highly misleading assump- using these datasets appropriately exist (e.g., Gale et al., tion. Using the Red List to determine if use and/or trade 2019), research studies that describe wildlife trade and is a threat to species requires interrogating the threats its impacts—and suggest policy interventions—sometimes classification scheme (particularly scheme 5 on Biologi- misunderstand or misinterpret the datasets used and/or cal Resource Use) and paying close attention to the asso- inappropriately interpret the results. As research has the ciated threat codings. Scheffers et al. (2019) constructed a potential to influence policymakers taking critical deci- list of “traded” species by combining data from the Red sions on the sustainability and regulation of wildlife trade, List with the species in the CITES Appendices and esti- this is problematic. These studies also demonstrate flaws in mated that trade affects 24% of terrestrial vertebrates glob- the peer-review process, and the problem is compounded ally. However, this mistakenly equates being in trade with when subsequent authors apply the same methodologies risk of extinction from trade and assumes that all species and make identical errors. listed in the CITES Appendices are in trade when they Here, we examine a non-random selection of recent (last are not (Challender, Broad et al., 2019). Many species are ∼5 years) research studies and discuss three key issues in included in CITES for precautionary purposes because wildlife trade research. These are (1) mischaracterization they resemble traded species (i.e., are “lookalikes”; CITES of the threat wildlife trade poses to species, (2) misinter- Res. Conf. 9.24, Rev. CoP17), or as part of taxonomic groups pretation of wildlife trade data, and illegal trade data in where the entire group is listed (higher taxon-listings; e.g., particular, and (3) misrepresentation of international pol- parrots [Psittaciformes spp.]). Additionally, listing species icy processes and instruments. We highlight a generic chal- in CITES Appendix I is intended to prevent commercial, lenge for researchers through to end-users, and propose international trade (rather than indicate that a species is ways authors, journal editors, database managers, and pol- in trade). A more appropriate analytical approach would icymakers can identify and address these issues. Our pur- have been to identify species known to be in trade using the pose is not to specifically critique the authors or their CITES trade data (for international trade in CITES-listed work. Rather, while recognizing that many of these stud- species) combined with data from the Red List and other ies present important methodological or other scientific sources. Table 1 summarizes these issues, together with the advances, we discuss these articles because they are con- consequences for the arguments made, and provides addi- temporary and illustrate the issues. tional examples. TA B L E 1 Issues, consequences for the arguments made by authors, and example articles Summary Issue Consequences for argument made Examples Mischaracterization Assuming use/trade constitutes a threat to species or is Mischaracterizes species as threatened by Auliya et al. (2016), Fukushima et al. of threat from trade detrimental to wild populations trade or assumes that trade is (2020), Harrington et al. (2019), Jensen detrimental to wild populations when et al. (2018), Luiselli et al. (2012), CHALLENDER et al. this may not necessarily be the case Marshall et al. (2020), Scheffers et al. (2019) Misinterpretation of Misinterpretation of CITES trade data: Assumes that differences in quantity Andersson and Gibson (2018), Berec et al. wildlife trade data Incorrectly comparing importer- and between importer- and (2018) exporter-reported data exporter-reported data reflect reporting issues, errors or “missing data” when they may result from legitimate differences (e.g., differences in source or purpose code) Incorrectly combining direct and indirect trade data May inflate trade volumes for items that Poole and Shepherd (2016) have been imported and (re-)exported several times by treating each export/re-export as a new item Misunderstanding the use of source and purpose codes† Mischaracterizes trade (e.g., conflates Nellemann et al. (2018) source of specimens/purpose of trade) Conflation in use of terms/units† Mischaracterizes trade volumes (e.g., Andersson and Gibson (2018) For example, misinterpreting blank units in trade inflating the number of individual records as missing data (and assuming trade involved animals or plants in trade) the recommended unit for specific derivatives e.g., kg) rather than “number of items” Assuming each row of data comprises a single Miscalculates transaction frequency since Berec et al. (2018), Can et al. (2019), shipment/incident‡ rows in a comparative tabulation D’Cruze and Macdonald (2015), output, for example, may contain Vall-Llosera and Su (2018) multiple records (see Pavitt et al. 2019) Assuming source code I refers to illegal trade Misrepresents illegal trade levels (e.g., D’Cruze and Macdonald (2015, 2016), number of individual animals or plants Ribeiro et al. (2019), Ye et al. (2020) involved) Misinterpretation of LEMIS data: Mistakenly inflates the number of Goyenechea and Indenbaum (2015), Treating each row of data as a single seizure event seizures and thereby the extent of Petrossian et al. (2016), Petrossian et al. illegal trade (2020), Sosnowski and Petrossian (2020) Misinterpretation of seizure data: Misrepresents illegal trade data and the C4ADS (2020), Hitchens and Blakeslee Failing to acknowledge and/or account for inherent “trends” derived are not meaningful (2020), Morcatty et al. (2020), Paudel biases in seizure data and describing illegal trade as et al. (2020), Siriwat and Nijman (2018), increasing or similar UNODC (2020), Wildlife Justice Commission (2020) (Continues) 3 of 10 1755263x, 2022, 1, Downloaded from https://conbio.onlinelibrary.wiley.com/doi/10.1111/conl.12832 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [26/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 1755263x, 2022, 1, Downloaded from https://conbio.onlinelibrary.wiley.com/doi/10.1111/conl.12832 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [26/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 4 of 10 CHALLENDER et al. Wildlife trade can positively or negatively affect pop- et al. (2016), Shepherd et al. (2018, 2019) Wilcove (2019), Marshall et al. (2020). ulations of wild species and sustainability depends on Altherr and Lameter (2020), Frank and Frank and Wilcove (2019), Harrington et al. (2019), Gomez (2021), Rowley Frank and Wilcove (2019), Gorobets appropriate governance of varying interactions between biological, economic, and social factors (Cooney et al., 2015; Hutton & Leader-Williams, 2003). Understanding the impact of trade-driven harvest on wild populations requires data on critical population parameters, including Scheffers et al. (2019) intertemporal harvest rates and their influence on density (Sutherland, 2001). However, various studies (Table 1) have bypassed such in-depth analyses and used trade Examples (2020) volumes subjectively to determine that trade is (or is likely Since 2019 shipment-level trade data (with anonymised permit numbers) has been made available as a static download from the CITES Trade Database, updated once a year. to be) detrimental to species populations and thus pre- scribed policy responses (e.g., include species in the CITES Appendices). Auliya et al. (2016) discussed the impact of trade on particular reptile taxa but concluded that trade in Misrepresents the CITES Appendices and processes for determining threat status Overlooks the fact that IUCN and CITES a broader range of species (whether legal or illegal) should, This assumption is misleading because negative for species and change over Consequences for argument made inflates the number of CITES-listed have not been evaluated in realistic Appendix I or II may be positive or difficult to determine because they by default, be considered detrimental to their survival. This the inclusion of species in CITES species considered to be in trade The utility of recommendations is have independent criteria and is problematic because in many cases whether trade-driven harvest is detrimental to populations remains an open question requiring further research. While some species may be threatened by modest levels of trade, others can be traded in large volumes without trade posing a threat to the survival of the species in the wild (e.g., reticulated python Malayopython reticulatus and American Alligator Alligator terms time mississippiensis; Joanen et al., 2021; Natusch et al., 2016). 3 MISINTERPRETATION OF WILDLIFE TRADE DATA Assuming all species included in the CITES Appendices changes to policy instruments (e.g., CITES) or trade Assuming the inclusion of species in CITES will be Failing to consider the feasibility of recommended Since 2010, ∼130 studies have used the CITES Trade international trade based on the Red List would Assuming species determined to be threatened by automatically qualify for inclusion in CITES Database to characterize international wildlife trade (UNEP-WCMC, unpubl. data); others have used the US Fish and Wildlife Service Law Enforcement Management Information System (LEMIS) data, or other databases positive for their conservation (Supporting Information S1). However, numerous studies have misinterpreted these databases, resulting in the mis- characterization of trade dynamics and volumes (Table 1). For example, a common error is treating each row of data in the “comparative tabulation” output from the CITES regulations Trade Database (which may comprise many shipments are traded aggregated into a single row) as a single trade transaction, which miscalculates transaction frequency (Table 1). Simi- Issue Based on Robinson and Sinovas (2018). lar misinterpretation applies to LEMIS data, which records trade in all wildlife species that cross US borders. Sos- nowski and Petrossian (2020) analyzed seizures of fashion- (Continued) related wildlife products in the United States but inflated international policy Misrepresentation of the number of seizures. They assumed each row of data processes and represented a single seizure, but whether a single seizure instruments is represented by one or more data rows varies. For exam- Summary TA B L E 1 ple, a single confiscated item derived from more than one wildlife species will appear as multiple rows of LEMIS data and should not be counted as multiple seizure events † ‡ 1755263x, 2022, 1, Downloaded from https://conbio.onlinelibrary.wiley.com/doi/10.1111/conl.12832 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [26/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License CHALLENDER et al. 5 of 10 (Natusch et al., 2021). Failure to correctly interpret the reflect known seizures, rather than absolute trade volumes number of seizures and/or items seized can erroneously or bias-adjusted trends or spatial patterns. inflate the extent of illegal trade. Another problem regarding CITES trade data is interpre- tation of source code “I,” which has been used to describe 4 MISREPRESENTATION OF illegal international trade dynamics (Table 1). This code INTERNATIONAL POLICY PROCESSES can refer to seizures made due to a lack of valid permits AND INSTRUMENTS accompanying specimens in trade, or international trade in specimens of species that have previously been seized The framing of research can result in misguided rec- or confiscated but are being legally exported in accor- ommendations, stemming in part from authors misun- dance with CITES Res. Conf. 17.8 paragraph 8 (e.g., repa- derstanding international policy processes and how pol- triation to the source country). Hence, the code may or icy instruments function. Frank and Wilcove (2019), for may not indicate illegal trade. Without verification from example, estimated that it takes approximately 10 years the relevant CITES Management Authorities that trade for species they determined to be threatened by interna- records do indeed refer to illegal trade it is not possible tional trade on the Red List to be included in CITES, and to accurately characterize illegal trade using these data. argued for a “near-automatic pathway by which unpro- Alternative illegal wildlife trade datasets exist (Supporting tected species identified by the IUCN as threatened by Information S1). international trade receive a vote for inclusion in CITES Analysis of seizure data is frequently used to understand Appendix I or II.” However, this seemingly simple, but ulti- illegal wildlife trade, but misinterpretation of these data mately far-reaching, recommendation discounts four main is commonplace (Table 1). While seizure data can be use- issues, three of which are characteristic of other studies. ful to gain insights into illegal trade dynamics, they suf- First, the Red List and CITES apply independent (albeit fer from inherent biases related to enforcement effort (e.g., related) criteria for determining threat status; the Red List resources committed), rates of seizure (proportion of illegal sets quantitative thresholds for species to be listed in a par- transactions seized) and reporting (proportion of seizures ticular Red List category, while the CITES listing criteria reported to focal database), which differ between countries only provide indicative, nonbinding guidelines on numer- (Underwood et al., 2013). Critically, these biases need to ical values (see Annex 5 of Res. Conf. 9.24, [Rev. CoP17]). be appropriately accounted for in order to derive mean- Consequently, a species determined to be threatened by ingful temporal trade trends or spatial patterns. Under- international trade according to the Red List may, or may wood et al. (2013) used Bayesian hierarchical latent vari- not, qualify for inclusion in CITES (Challender, Hoffmann able modeling to account for biases and produce relative et al., 2019). Other articles have also made this assumption trends in illegal international trade in elephant ivory using (e.g., Gorobets, 2020). Second, Frank and Wilcove (2019) ETIS (Elephant Trade Information System) data. Similar focus on Appendix I and II only, overlooking Appendix analyses have not been completed for other species, in part III. Parties to CITES may unilaterally include species in because of the large and comprehensive datasets needed Appendix III without the lengthy process that would be (ETIS holds > 29,000 seizure records; TRAFFIC, 2019). required for proposing species be included in Appendices I Yet researchers commonly fail to recognize (or account and II, which would reduce the time-lags identified by the for) these biases explicitly and/or incorrectly describe ille- authors. gal trade trends from the raw data in qualitative terms Third, the establishment of a “near-automatic pathway” (e.g., illegal trade is increasing) without the necessary would require fundamental changes to the Convention, caveats. These “trends” are not meaningful. For example, probably including amendment of the Convention text, an apparent increase in seizures may reflect greater law requiring the agreement of the Parties. However, the fea- enforcement effort or discovery of a previously unknown sibility and political palatability of the proposal were not smuggling method rather than an increase in illegal considered by the authors. This is non-trivial because even trade. suggestions agreed by the Parties can take many years to Seizure data can be used to: (i) estimate the minimum take effect. The Gaborone amendment allowing regional number of individual animals or plants in illegal trade, economic integration organizations to accede to CITES (ii) estimate minimum volumes or quantities of derivatives took 30 years to enter into force following its adoption over a defined period, and (iii) characterize spatial traffick- (CITES, 2013). Other studies apply a similar approach ing patterns (e.g., countries of origin, export, transit, and to suggested reforms to wildlife trade regulation (Mar- destination) based on reported seizures. However, stud- shall et al., 2020), including the “reverse listing” model ies using seizure data for these purposes should explicitly (Altherr & Lameter, 2020), whereby all international trade acknowledge the inherent biases and the fact that the data would be prohibited unless it could be demonstrated to be 1755263x, 2022, 1, Downloaded from https://conbio.onlinelibrary.wiley.com/doi/10.1111/conl.12832 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [26/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 6 of 10 CHALLENDER et al. sustainable. Scientific research should be used to inform Second, the articles discussed demonstrate certain flaws potential wildlife trade policy reforms, but such studies in the peer-review process. Researchers may publish should consider the realities of the policy frameworks responses, but rebuttals seldom alter scientific or public discussed. perceptions of original articles (Banobi et al., 2011), and Fourth, Frank and Wilcove (2019) suggest that includ- readers of an article are rarely made aware that a response ing species in CITES Appendix I or II may help to avoid has been published. Even where they do exist, responses the extinction of species, but they fail to acknowledge that are typically limited in terms of space, especially in high- such measures may at times do more harm than good. impact journals, meaning it is not always possible to fully Although designed to restrict trade and reduce unsus- address the problems identified. Once published, the orig- tainable harvesting, such listings may signal scarcity to inal articles continue to be cited (Cosentino & Veríssimo, speculative collectors, stockpilers, and organized crime 2016) and influence the conservation agenda, to the poten- groups, and at least in theory could lead to scarcity-driven tial detriment of the science-policy interface. price increases that in turn raise incentives for accelerated To avoid the issues discussed in future research, we pro- wild harvest (e.g., Asian arowana Scleropages formosus; pose the following measures for researchers, journal edi- Bergstrom, 1990; Courchamp et al., 2006; Crockett, 2021). tors, database managers, and policymakers. The assumption that including species in CITES is posi- For researchers: Researchers should familiarize them- tive for their conservation is common in the wildlife trade selves with the datasets they will use before starting their literature. This includes articles which recommend that research, to avoid misinterpretation and so they are aware species be included in the Appendices but fail to evaluate of important limitations and biases. Guidance accompa- realistically whether it would be positive for those species nies various online databases including the CITES Trade and how this may change over time (e.g., Shepherd et al., Database (CITES, 2019b; UNEP-WCMC, 2013; and see 2019; Table 1). Evaluating the potential conservation ben- Robinson & Sinovas, 2018) and IUCN maintains protocols efits and risks to including species in CITES requires an and guidance documents pertaining to Red List data (e.g., in-depth understanding of the social-ecological system in IUCN, 2013). There are also resources on interpretation which harvest, trade, and consumption of species occur of illegal trade data (e.g., TRAFFIC, 2019). Uncertainties (e.g., using theories of change; Cooney et al., 2021). Future concerning the extraction, download, use, and/or interpre- research which considers CITES as a conservation tool tation of such datasets should be clarified with database should explicitly evaluate both the potential conservation providers and managers, and/or with other academics and benefits and risks of including species in the Convention. CITES Management Authorities (e.g., for CITES source codes). Researchers should report limitations in the data accu- 5 ADDRESSING THE rately and any associated caveats, as well as manipulations MISCHARACTERIZATION OF WILDLIFE of the raw data they have made, when presenting analysis TRADE or interpretation. Researchers should consider the biolog- ical significance of their results and whether use and/or The publication and dissemination of research that mis- trade represents a risk for species conservation or not, or if characterizes wildlife trade and its impact, and/or mis- there is insufficient evidence to objectively determine the presents policy processes and instruments is concerning risk. Language is also important, and we urge care in its for two main reasons. First, this research may unwittingly use. For example, a species being used for subsistence pur- misinform or misdirect wildlife trade policy and associ- poses does not equate to a species being in trade unless ated action by government agencies and conservation prac- it is purchased/bartered for; being in trade does not mean titioners (at local to international scales), including the that trade crosses international borders (though note that misallocation of resources. Such research may be inter- “trade” within CITES does refer to international trade); preted uncritically by policymakers and practitioners who and a species in use or trade is not automatically threat- may not have the time or expertise to critically evaluate ened by this use/trade. More evidence-based interpretation the methodologies used. This could lead to policy that and reporting around use and trade will help to ensure undermines positive outcomes for species and associated that policy deliberations are well-targeted and that man- benefits for people along wildlife supply chains, thereby agement interventions work for species conservation. hampering achievement of the Sustainable Development If making policy recommendations, authors should Goals (Booth et al., 2021). More broadly, this research may acquaint themselves with the treaties and institutions not contribute towards improved public understanding involved, and with the broader policy and regulatory because the associated press coverage can repeat errors landscape, to avoid misrepresenting policy processes and made in publications (e.g., Dunphy, 2019). instruments. This could be achieved by dialogue with 1755263x, 2022, 1, Downloaded from https://conbio.onlinelibrary.wiley.com/doi/10.1111/conl.12832 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [26/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License CHALLENDER et al. 7 of 10 experts in relevant institutions (e.g., IUCN, CITES, and There is broad research interest in the use and trade UNEP-WCMC). Critically, researchers should evaluate of wildlife species. The intention behind this article is whether their recommendations (and implementation not to discourage or criticize much-needed independent thereof) would in fact contribute to the conservation of research in this field. We strongly support ongoing inno- species, or not, and explicitly consider areas of uncertainty vative and exploratory research but emphasize the need and any associated risks (e.g., of CITES listings). If sug- for care and caution in analysis, interpretation, and dis- gesting broader policy reforms (e.g., to treaties) researchers cussion of results, and in making policy recommenda- should also offer evaluation of how realistic their recom- tions. Specifically, we want to highlight that using datasets mendations are; considering, for example, timelines, feasi- in this space (especially those that are publicly avail- bility, and expected impact. This would hopefully result in able) may require specialist analysis (Dobson et al., 2020). more robust and informed recommendations. Researchers should be encouraged to take advantage of For journal editors: Journal editors can best ensure the these datasets, but they should do this with due considera- correct use and analysis of wildlife trade datasets by select- tion, aware of the broader policy context and of the poten- ing peer-reviewers with in-depth knowledge of particular tial pitfalls of using secondary data. More effective com- databases and/or methods used, or the policy instruments munication between data generators, analysts, and users involved. These could include individuals with particular would lead to more pertinent, more meaningful, and ulti- expertise (e.g., database managers), many of whom already mately more impactful science that is better positioned to sit on journal editorial boards, and could therefore be con- make a positive contribution to conservation. sulted on appropriate uses of data and possible reviewers. Conflicts of interest could be managed to ensure these indi- AC K N OW L E D G E M E N T S viduals do not unduly influence the publishing process. We thank Thea Carroll, Kelly Malsch, Tom De Meule- While we are not suggesting that the articles we use as naer, Sofie Flensborg, Haruko Okusu, Johan A. Oldekop, examples should be retracted, where wildlife trade articles and Aly Pavitt for helpful comments on an earlier ver- are published in the future and post-publication review sion of this manuscript. DC and EJMG acknowledge fund- highlights very serious errors in the methods or data anal- ing from the Oxford Martin Programme on Wildlife Trade yses which materially and fundamentally affect the key and the UK Research and Innovation’s Global Challenges results and/or conclusions, journals could consider retrac- Research Fund (UKRI GCRF) through the Trade, Devel- tions as an option, as is done in other disciplines (e.g., opment, and the Environment Hub project (project num- medicine) to prevent perpetuation of the harmful errors. ber ES/S008160/1). AH is funded by a Kadas Fellowship at Responses which highlight key analytical issues should be Worcester College, Oxford. FM was supported by an ERC presented alongside original articles and made available Advanced Investigator Grant (number 694995). under open access terms. For database managers: To facilitate accurate and robust CONFLICT OF INTEREST analysis of data on wildlife trade, database managers The authors declare no conflict of interest. should provide accessible, up-to-date guidance on the use and misuse of the data they manage, including exam- AU T H O R CO N T R I B U T I O N S ples of best practice. Where feasible (e.g., subject to All authors contributed to the conception, writing, editing resources) data managers and/or compilers should engage and reviewing of the manuscript. with researchers to develop methodologically sound anal- yses and support correct interpretation of the data. E T H I C S S TAT E M E N T For policymakers and civil society organizations: It is No primary data were collected for this manuscript and an important to critically evaluate research before taking a ethical review process was not undertaken. position on an issue, in order to identify methodological errors, especially where these may materially influence DATA AC C E S S I B I L I T Y S TAT E M E N T the results and conclusions. It is worth checking if any No primary data were collected for this manuscript. responses to specific articles have been posted online that refute or invalidate the research findings, or if articles have ORCID been retracted. If in doubt, and where important policy Daniel W.S. Challender https://orcid.org/0000-0002- decisions are being made, policymakers should seek assur- 0606-1715 ances from the authors and independent experts, including Amy Hinsley https://orcid.org/0000-0002-5590-7617 the managers of the datasets in question, on the validity of Michael ’t Sas-Rolfes https://orcid.org/0000-0002-2220- the results. 6072 1755263x, 2022, 1, Downloaded from https://conbio.onlinelibrary.wiley.com/doi/10.1111/conl.12832 by Spanish Cochrane National Provision (Ministerio de Sanidad), Wiley Online Library on [26/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 8 of 10 CHALLENDER et al. REFERENCES Cooney, R., Challender, D. W. S., Broad, S., Roe, D., & Natusch, D. J. Altherr, S., & Lameter, K. (2020). The rush for the rare: Reptiles and D. (2021). 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