Investigating illegal wildlife trade: innovative approaches to inform global conservation policy

Project Details

Description

The illegal wildlife trade is considered the largest illegitimate business after narcotics and is threatening the persistence of thousands of species globally. Currently, there is a global spotlight on combatting illegal wildlife trade. A paucity of data on the scale and extent of the problem has thus far limited progress toward assessing the real impact illegal wildlife trade is having on biodiversity. In this project, I will address this limitation by using new data made available by project collaborators and data mined from social media platforms. Specifically, I will use this data to develop innovative analyses to expose the supply chain of the illegal wildlife trade in order to inform global conservation policy. First, I plan to identify areas globally where pressures on species threatened by illegal wildlife trade are the highest and resources for counteracting illegal activities are the lowest. Second, I intend to assess the relationships between the legal (allowed by international conventions) and illegal wildlife trade in order to assess the extent to which legal trade patterns reflect those of illegal trade. Third, I will use new data mined from social media platforms, which have become one of the main venues where to trade illegal wildlife products, to unveil social networks of traders and users of illegal wildlife products and potential shipping routes. Fourth, I will develop biodiversity indicators that can be used by decision-makers to assess the impact illegal wildlife trade is having on biodiversity and monitor the success of conservation interventions over time. As this study is developed in collaboration with the most influential organizations promoting biodiversity conservation globally, the impact of the project will be maximized by feeding the results of this project directly into key policy-making processes at United Nations Environmental Programme, Convention of International Trade in Endangered Species of Wild Fauna and Flora, the Convention of Biological Diversity and other decision-making fora.
Short titleWildlife trade
StatusFinished
Effective start/end date01/09/201631/05/2020

Funding

  • Helsinki Institute of Sustainability Science (HELSUS): €118,000.00
  • Valtion perusrahoitus/hankkeet

Fields of Science

  • 1181 Ecology, evolutionary biology
  • conservation biology
  • 113 Computer and information sciences
  • Artificial Intelligence
  • machine learning
  • 112 Statistics and probability
  • 1171 Geosciences

Research Output

A framework for investigating illegal wildlife trade on social media with machine learning

Di Minin, E., Fink, C., Hiippala, T. & Tenkanen, H., Feb 2019, In : Conservation Biology. 33, 1, p. 210-213 4 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
File

python-webis: Python wrapper for the webis Twitter sentiment evaluation ensemble

Fink, C. A., 23 Jan 2019

Research output: Non-textual formSoftwareScientific

Open Access

Machine learning for tracking illegal wildlife trade on social media

Di Minin, E., Fink, C., Tenkanen, H. & Hiippala, T., Mar 2018, In : Nature Ecology & Evolution. 2, 3, p. 406-407 2 p.

Research output: Contribution to journalLetterScientific

Activities

  • 1 Organisation and participation in conferences, workshops, courses, seminars
  • 1 Invited talk

Non detriment finding for white and black rhinoceros

Enrico Di Minin (Attendee)

31 Jan 20181 Feb 2018

Activity: Participating in or organising an event typesOrganisation and participation in conferences, workshops, courses, seminars

Machine learning for tracking illegal wildlife trade on social media

Enrico Di Minin (Speaker)

29 Jan 2018

Activity: Talk or presentation typesInvited talk