Understanding what drives the pet trade can help anticipate conservation, biosecurity, and welfare risks. We used South Australia’s native wildlife permit reporting system as a data-rich example of a live vertebrate pet market. We used piecewise structural equation modelling (SEM) to test the influence of 11 a priori variables relating to pets (e.g., species traits), pet owners (e.g., socioeconomic metrics), and regulatory systems (e.g., permit requirements) on the quantities of bird and reptile captive keeping, breeding, trading, and escapes into the wild. We found that species traits are a strong determinant of pet trade dynamics, yet permit systems also play a key role in de-incentivising undesirable trade practices. While our research highlights the potential of trade regulatory systems, we recommend that consistent permit category criteria are established to reduce trade in threatened species, as well as alien species of high biosecurity risk.
Illegal or unsustainable wildlife trade (IUWT) currently presents one of the most high-profile conservation challenges. There is no “one-size-fits-all” strategy, and a variety of disciplines and actors are needed for any counteractive approach to work effectively. Here, we detail common challenges faced when tackling IUWT, and we describe some available tools and technologies to curb and track IUWT (e.g. bans, quotas, protected areas, certification, captive-breeding and propagation, education and awareness). We discuss gaps to be filled in regulation, enforcement, engagement and knowledge about wildlife trade, and propose practical solutions to regulate and curb IUWT, paving the road for immediate action.
Illegal or unsustainable wildlife trade is growing at a global level, threatening the traded species and coexisting biota, and promoting the spread of invasive species. From the loss of ecosystem services to diseases transmitted from wildlife to humans, or connections with major organized crime networks and disruption of local to global economies, its ramifications are pervading our daily lives and perniciously affecting our well-being. Here we build on the manifesto ‘World Scientists’ Warning to Humanity, issued by the Alliance of World Scientists. As a group of researchers deeply concerned about the consequences of illegal or unsustainable wildlife trade, we review and highlight how these can negatively impact species, ecosystems, and society. We appeal for urgent action to close key knowledge gaps and regulate wildlife trade more stringently.
We compiled a dataset consisting of all the species involved in the illegal wildlife trade along with the reason (i.e., use-type) they were being traded. In total, the dataset includes c. 4.9k distinct taxa representing c. 3.3k species and contains c. 11k taxa-use combinations from 110 unique use-types. Our dataset can be used to conduct large-scale broad searches of the Internet to find illegally traded wildlife.
We found a pattern between US reptile trade and smuggling of live reptiles to Australia. Almost all species smuggled to Aus are legal in US trade and are popular We compared illegal smuggling of reptiles into Australia to the legal pet trade of reptiles in the US. We provide the first empirical risk watch-list for desirable reptile species being trafficked into Australia. Our findings give insight into the drivers of illegal wildlife trade and our approach provides a framework for anticipating future trends in wildlife smuggling.
The Internet can be vast source of data for the wildlife trade. However, data collected from the Internet is often numerous and messy, making data cleaning a task the requires a lot time and effort. Here, we tested if text classification can be used to speed up the process of data cleaning in relation to online data collected on the wildlife trade. We found that text classification models can predict with great accuracy relaxant advertisements, including the taxonomy of relevant species, using the text found in online advertisements. We recommend using text classification as a method to make data cleaning more efficient. Future efforts should try to pair text classification with image classification for improved efficiency.
Australian reptiles face serious conservation threats from illegal poaching fuelled by international demand and the exotic pet trade. We investigated the extent of illegal trade in a charismatic Australian lizard: the shingleback, also known as the bobtail or sleepy lizard. Using government records, media reports, and online advertisements, we found clear evidence that many shinglebacks have been illegally poached from the wild and are smuggled overseas to be traded as pets. Not only are our findings concerning from a conservation and animal welfare perspective, but they also highlight a major legal loophole. Once shinglebacks are illegally smuggled out of Australia, there are no legal actions available to prevent or regulate overseas trade. To address this, we recommend using an existing and under-utilised legislative tool (Appendix III of CITES, an international treaty) to protect Australian shinglebacks and help to curtail global trade.
The international trade in exotic vertebrate pets provides key social and economic benefits but also drives associated ecological, ethical, and human health impacts. Here, we represent and review the structure of the pet trade as a network composed of different market actors (nodes) and trade flows (links). As a case study of how data-informed networks can realize this goal, we quantified spatial and temporal patterns in pets imported to the United States. Our framework and case study illustrate how network approaches can help to inform and manage the effects of the growing demand for exotic pets.
Keeping propagule pressure low can reduce the probability a non-native species will establish in a new location. Here we develop a mathematical framework that can determine the required reduction in levels for propagule size and number (representative of management actions) to maintain a target establishment probability. Our tool can serve to guide the development of new invasive species management plans in a transparent and quantitative manner. Together with information on the costs associated with approaches to reducing propagule pressure, our tool can be used to identify the most cost‐effective approach to prevent invasive species establishments.
The internet is a vast source of wildlife trade data. Here, we present an accessible guide for Internet‐based wildlife trade surveillance, which uses a repeatable and systematic method to automate data collection from relevant websites. Our guide is adaptable to the multitude of trade‐based contexts including different focal taxa or derived parts, and locations of interest.
The live pet trade is a major pathways for invasive species. Australia imposes tough regulations against the trade of non-native animals as pets. However, there exists an illegal trade of these animals in Australia that threatens biosecurity. Here, we used government records of enquiries from the general public to assess the characteristics of species that are likely desired as pets. We found that desired species are more likely to invasive species elsewhere or at risk of extinction due to trade. Our findings suggest that in absence of strict laws, an unregulated pet trade would threaten Australian biosecurity and global conservation efforts.
The exotic pet trade is a multi-billion dollar industry involving thousands of animal species. Research has historically focused only the conservation and disease risks, however the risk of pets becoming invasive species has been overlooked. We show this trade is now the leading contributor of non-native establishments and invasions worldwide among vertebrates. We highlight areas of future research/policy changes needed to avoid more invasive pets in the future.
The trade of non-native animals as pets the main pathway for new invasive species if they become released into the wild. Here, we examined the trade in non-native reptiles and amphibians as pets in the United States. We found c. 1,700 species traded in the past two decades of which 126 species have been recorded as released in the wild. Using machine learning models, we show that larger-bodied, longer-lived species, who sold for cheaper prices were more likely to have been released. We propose policies and education focused on species with these characteristics in order to curb the impacts of new invasive species that originated as pets.
White-nose syndrome (WNS) has caused catastrophic declines in some bat species, while others appear less impacted. We conducted a mark–recapture study of federally endangered Indiana bats (Myotis sodalis) during 2011–2016 and found survival had decreased by around 4 percentage points. We ran population models based on new survival data and results suggested there will be future population declines for the Indiana bat.
Mathematical models that inform conservation efforts always have underlying uncertainty. We show that in many applied cases, this uncertainty results in a non-trivial probability that management action will have no benefit to conservation. We encourage future use of population viability analysis (PVA) to explicitly account for this uncertainty when considering whether or not to implement management actions.
Endangered species face many threats, including from invasive predators. Here, we developed a modelling method to compare different management options for controlling predators. We then applied this method to compared management options for the endangered shorebird, the piping plover, which faces predation threats from the red fox along New Jersey beaches.