Online Marketplaces’ Anti‐Data Collection Policies Hinder Research on Biodiversity Conservation and Zoonotic Disease Prevention

International, legal trade in wildlife accounts for 220 billion annually, with illegal trade adding billions to tens of billions to that figure (Andersson et al. 2021; Tow et al. 2021). At its best, this trade provides financial benefit and food security to the world's poorest people and incentivizes sustainable use (Roe et al. 2020). International wildlife trade also drives species extinct (Hinsley et al. 2023), causes cascading harm to ecosystems (Hughes et al. 2023), introduces invasive species (García-Díaz et al. 2017; Souviron-Priego et al. 2018), and exposes people to zoonotic pathogens (Can et al. 2019; Nijman 2021; Shivaprakash et al. 2021). For better and for worse, this trade increasingly takes place online (Moloney et al. 2023; Stringham et al. 2021). Online wildlife trade often takes place on social media or on consumer-to-consumer websites, such as Etsy, eBay, and Amazon (Chakraborty et al. 2025; Coleman et al. 2024). Monitoring this trade is challenging, given its diffuse and ephemeral nature, the quantity of listings, and rapid changes in seller and buyer behavior (Cardoso et al. 2023; Gippet et al. 2023; Sung et al. 2021). Nevertheless, e-commerce data are an invaluable resource for understanding the species, patterns, and consumers of the legal wildlife trade because there is no global database of trade in unprotected species (Hughes et al. 2021; Janssen and Leupen 2019). Data from these platforms have been used to evaluate the sustainability of unregulated trade (Hunter et al. 2024; Su et al. 2024), detect illegal trade (Sung and Fong 2018; Xu et al. 2020), understand what drives consumption of wildlife (Coleman et al. 2024), predict future invasive species (Toomes et al. 2023), assess the risk of zoonotic disease exposure to consumers (Tarango et al. 2025), and develop demand-reduction strategies (Lavorgna and Sajeva 2021). Automated data collection can vastly expand these efforts. A recent study used automation to search 148 online marketplaces for mention of 13, 773 species for 15 weeks (Chakraborty et al. 2025). These numbers cannot be replicated by a reasonably sized team of human observers. The automated tool produced a pool of listings likely to contain wildlife products for sale, which were then manually vetted, ensuring accuracy and making the best use of limited researcher time. Not only did automation locate illegal online trade in sharks, Chakraborty et al. (2025) also identified 13 species in trade that had not been previously documented. Detecting online trade in non-CITES species is crucial for understanding how sustainable that trade is (Hughes et al. 2021), but this work is much harder to do manually than searching for a limited list of protected species. Recently, we encountered a roadblock to similar research when we set out to assess online trade in bats (Tarango et al. 2025). We planned to include Etsy in our investigation, as other surveys of wildlife on e-commerce platforms have done (Coleman et al. 2024; Hunter et al. 2024; Losey et al. 2022). Just prior to project execution, we discovered that they had adopted a policy that prohibited all data collection (Etsy 2025). Other major e-commerce and social media platforms that permit wildlife trade, like eBay, Facebook, and TikTok, have also implemented policies that limit or outright ban automated data collection (Table S1). These prohibitions serve a variety of reasonable goals, from protecting users’ data to thwarting unauthorized use by generative artificial intelligence (AI) platforms. Indeed, discourse on the ethics of web scraping represents an incipient but growing body of literature (Brown et al. 2025; Trezza 2023). Although most of the websites we reviewed indicate that an exemption to their ban on data collection is possible, none outlined the means for obtaining such an exemption in their terms of service (Table S1). This oversight may be due to the rapidity with which these well-intentioned policies have been needed and adopted, due to the recent AI boom. However, exemptions that are impractical or impossible to obtain mean that these bans have the unintended side-effect of chilling research on biodiversity and zoonotic risks. Selling illegal goods is against these sites’ terms of service, and some platforms have taken measures to prevent unsustainable wildlife trade (Coleman et al. 2025). We hope these websites will elaborate their policies to accommodate research that shares these goals. During our bat study, we sought permission from Etsy to collect data but were denied. We were lucky to receive any response—none of the websites we reviewed indicated their criteria for issuing an exemption, an expected response time, or an appeals process for denials. Stymying research into wildlife crime online enables traffickers to profit from e-commerce and runs counter to platforms’ efforts to remove illegal activity. Outright denials are burdensome, but so too is the prospect of applying for exemptions at every website of potential interest through opaque, discrete processes. Inconsistencies in permission will bias data, when some sites are regularly reviewed and others excluded. The practical lack of exemptions also creates an ethical quandary for researchers; if they comply with the rules, vulnerable species and consumers might suffer preventable harm. We further note that data scraping has been used to study online drug, human organ, and sex trafficking (Giommoni and Ikwu 2024; Li et al. 2022; Maybir and Chapman 2021) and that a broad range of investigations may be inadvertently compromised by prohibitive data collection policies. We encourage e-commerce platforms to develop a shared process for approving scientific applications for data use. A coalition of platforms could publish necessary criteria for exemption to data scraping bans, which should affirm guardrails for protecting users’ privacy, and review applications for exemption. This would save member platforms the time of individually reviewing applications, offer clarity and fairness to applicants, and reward researchers who adhere to ethical best practices. In summary, many e-commerce and social media platforms are taking justified measures to protect user data and copyrighted material from exploitation. However, sweeping anti-data collection policies without transparent, achievable exemptions for scientific research undermine efforts to prevent species extinctions and disease outbreaks. We encourage e-commerce platforms to adopt centralized and transparent policies for permitting ethical wildlife trade research. In a time of accelerating biodiversity loss and intensifying zoonotic threats, we need to understand the rapidly changing online wildlife trade more than ever. The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the US Fish and Wildlife Service. The data that supports the findings of this study are available in the supplementary material of this article. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.