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      Detecting illegal wildlife trafficking via real time tomography 3D X-ray imaging and automated algorithms

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          Abstract

          Wildlife trafficking is a global problem involving the deliberate and illegal transport of wildlife across international borders. Animals are either removed directly from their natural environment or bred specifically to fuel demand driven by activities such as the illegal pet trade or for purported medicinal reasons. In Australia, wildlife trafficking poses a serious environmental and biosecurity risk through the removal of native species and the introduction of exotic invasive wildlife. This has the potential to impact the natural ecosystem and Australia’s multibillion-dollar agricultural industry. To help detect and restrict this activity, innovative technologies such as 3D X-ray CT technology using Real Time Tomography has been trialed to create wildlife detection algorithms for deployment across Australian mail/traveller luggage pathways. Known species of trafficked Australian wildlife and additional model species of exotics were scanned to create an image reference library for algorithm detection. A total of 294 scans from 13 species of lizards, birds and fish were used to develop initial wildlife algorithms with a detection rate of 82% with a false alarm rate at 1.6%. In combination with human and biosecurity dog detection, this innovative technology is a promising complementary platform for wildlife detection at Australian international borders, with potential worldwide applications.

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          Scikit-learn: machine learning in Python

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            Global wildlife trade across the tree of life

            Wildlife trade is a multibillion dollar industry that is driving species toward extinction. Of >31,500 terrestrial bird, mammal, amphibian, and squamate reptile species, ~18% ( N = 5579) are traded globally. Trade is strongly phylogenetically conserved, and the hotspots of this trade are concentrated in the biologically diverse tropics. Using different assessment approaches, we predict that, owing to their phylogenetic replacement and trait similarity to currently traded species, future trade will affect up to 3196 additional species—totaling 8775 species at risk of extinction from trade. Our assessment underscores the need for a strategic plan to combat trade with policies that are proactive rather than reactive, which is especially important because species can quickly transition from being safe to being endangered as humans continue to harvest and trade across the tree of life.
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              Summarizing the Evidence on the International Trade in Illegal Wildlife

              The global trade in illegal wildlife is a multi-billion dollar industry that threatens biodiversity and acts as a potential avenue for invasive species and disease spread. Despite the broad-sweeping implications of illegal wildlife sales, scientists have yet to describe the scope and scale of the trade. Here, we provide the most thorough and current description of the illegal wildlife trade using 12 years of seizure records compiled by TRAFFIC, the wildlife trade monitoring network. These records comprise 967 seizures including massive quantities of ivory, tiger skins, live reptiles, and other endangered wildlife and wildlife products. Most seizures originate in Southeast Asia, a recently identified hotspot for future emerging infectious diseases. To date, regulation and enforcement have been insufficient to effectively control the global trade in illegal wildlife at national and international scales. Effective control will require a multi-pronged approach including community-scale education and empowering local people to value wildlife, coordinated international regulation, and a greater allocation of national resources to on-the-ground enforcement.
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                Author and article information

                Journal
                Frontiers in Conservation Science
                Front. Conserv. Sci.
                Frontiers Media SA
                2673-611X
                September 22 2022
                September 22 2022
                : 3
                Article
                10.3389/fcosc.2022.757950
                51c427ef-c7b0-4a4b-8748-4a54e2b9bc78
                © 2022

                Free to read

                https://creativecommons.org/licenses/by/4.0/

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