This post introduces and summarizes research published in the journal Conservation Biology. Click here for the full publication.
1. Introduction and Context
Sustainable, well-regulated wildlife trade helps support biodiversity, provides livelihoods around the world and is crucial for food security, especially for communities that might have limited access to other protein sources 1. Sustainable wildlife trade is then key for moving towards the Sustainable Development Goals, particularly in developing countries. But many of the benefits of sustainable wildlife trade start to break apart when illegality and non-compliance become widespread 2,3. Therefore, studying and measuring illegal wildlife trade is critical to ensure that the benefits of sustainable trade are realized. Of course, it’s easier said than done.
As part of my PhD thesis at the University of Oxford I’ve devoted many hours to thinking on ways to investigate and study why people engage in illegal trade of wildlife. I’ve tried a variety of methods and approaches, such as specialized survey techniques, simulations, and encounter data modelling4,5, which uses data from encounters between enforcers and non-complying resource extractors to predict overall rates of non-compliance. After a few years of careful research and involvement with fishing communities, we are starting to grasp how illegality in a specific fishery in Chile – the common hake – operates, and what incentivizes the behaviour of those who participate in it 6–8. Our greater understanding of the complexities of the illegal hake fishery in Chile is underscoring the challenges and need for developing possible solutions for improved compliance.
The common hake fishery is an emblematic fishery in Chile. It not only provides livelihoods for thousands of small-scale fishers, but there is also a key social and cultural connection between Chileans and this fishery. This is because common hake is by far the most widespread local fish eaten in the country and plays an important part in festivities such as easter9. Unfortunately, it is not only emblematic because of its socio-economic and cultural importance: in the last decade it has been the focus of a campaign by the government to stop rampant levels of illegal fishing, which has kept the stock moving between states of over-exploitation and depletion7.
A fisher pulling the nets in the hope of a good catch (photo credit: Rodrigo Oyanedel)
With this backdrop, we developed a mathematical simulation model that can be used to calculate quantities of legal and illegal trading9. This approach is especially helpful when only some of the data needed to describe a process are available (which is common in cases where there is illegality). We, however, focused on understanding traders’ economic incentives to trade legal or illegal products (rather than fishers’) to estimate how much illegal fish was being traded. With a tested model, we then set out to understand what policy levers might reduce illegal trade.
2. Key Findings
Our findings, unfortunately, indicated that illegal fish are the norm, with around 77% of the products being traded coming from illegal fishing activities (unreported catch over the quota). This is keeping the stock in an overexploited state, as fishing happens at higher levels than the regenerative capacity of the stock. Moreover, we found that changing this situation and improving sustainability won’t be easy. Using the model, we assessed how much illegal fishing would be reduced by testing different potential policy levers. For instance, we simulated changes in fishing levels with increases in enforcement by the government and increases in the “price premium” traders get for legal products. What we found, however, was that only very significant levels (>200%) of increases in the policy levers would reduce illegal fishing considerably (>30%).
3. Research Implications
Our work shows that it is indeed possible to use mathematical models to assess the extent and drivers of illegal wildlife trade, using the Chilean hake fishery as a case study: our mathematical approach helped disentangle this usually cryptic illegal trade. Focusing on traders (rather than fishers) proved to be a useful new angle to understand this problem and potential solutions. More work is needed, though, to adapt this model and approach to other contexts and species.
Our results on the common hake fishery pose a daunting challenge, as findings suggest that illegality dominates the market, and addressing illegality is a steep hill to climb (at least from the policy perspective we analysed). This has negative consequences for an already overexploited stock, undermining the capacity of this fishery to provide its potential benefits. Our results indicate just how important it is to actively assess ways to incentivize legal over illegal trade.
While our results paint a bleak picture, they also shed light on how crucial it is to understand legal and illegal trade dynamics, and ways to prevent socio-ecological systems getting to a situation where non-compliance is common and hard to reverse, as in the Chilean hake fishery. The difficulty of reducing illegal trade of wildlife might be significantly lower in cases where the problem is identified early on: time plays a key part here, so researchers, practitioners and governments need to be alert and ready to intervene.
Illegal trade is a serious threat to wildlife, communities and economies, and global efforts must be mobilized to address it. Building more solid and sustainable legal trade markets is possible if novel approaches are used in a timely fashion, considering the incentives that people have for trading legal or illegal products.
I want to thank my supervisors (Professor EJ Milner-Gulland and Professor Stefan Gelcich), and Emile Mathieu for their constant support through this project. I also sincerely thank the key informants who consented to being interviewed.
This work was supported by The Walton Family Foundation, FONDECYT 1190109, Financiamiento ANID PIA/Basal FB0002, Millennium Science Initiative Program—ICN 2019_015, ANID-Becas Chile, and the Marine Stewardship Council’s Scholarship Program. S.G. and E.J.M.G. were supported by Pew Marine Fellowships. E.J.M.G. acknowledges funding from the UK Research and Innovation’s Global Challenges Research Fund (UKRI GCRF) through the Trade, Development and the Environment Hub project (project number ES/S008160/1). E.M. acknowledges the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007- 2013) ERC grant agreement no. 617071, Microsoft Research, and EPSRC for funding his studentship.
- Andersson, A. A. et al. CITES and beyond: Illuminating 20 years of global, legal wildlife trade. Global Ecology and Conservation 26, e01455 (2021).
2. t Sas-Rolfes, M., Challender, D. W. S., Hinsley, A., Veríssimo, D. & Milner-Gulland, E. J. Illegal Wildlife Trade: Scale, Processes, and Governance. Annual Review of Environment and Resources 44, 201–228 (2019).
3. Phelps, J., Biggs, D. & Webb, E. L. Tools and terms for understanding illegal wildlife trade. Frontiers in Ecology and the Environment 14, 479–489 (2016).
4. Oyanedel, R., Keim, A., Castilla, J. C. & Gelcich, S. Illegal fishing and territorial user rights in Chile. Conservation Biology 32, 619–627 (2018).
5. Keane, Jones, J. P. G. & Milner-Gulland, E. J. Encounter data in resource management and ecology: Pitfalls and possibilities. Journal of Applied Ecology 48, 1164–1173 (2011).
6. Oyanedel, R., Gelcich, S. & Milner-Gulland, E. J. A framework for assessing and intervening in markets driving unsustainable wildlife use. Science of The Total Environment 792, 148328 (2021).
7. Oyanedel, R., Gelcich, S. & Milner-Gulland, E. J. Motivations for (non-)compliance with conservation rules by small-scale resource users. Conservation Letters 13, 1–9 (2020).
8. Oyanedel, R., Gelcich, S. & Milner-Gulland, E. J. A synthesis of (non-)compliance theories with applications to small-scale fisheries research and practice. Fish and Fisheries 1120–1134 (2020) doi:10.1111/faf.12490.
9. Beaumont, M. A. Approximate Bayesian Computation in Evolution and Ecology. Annual Review of Ecology, Evolution, and Systematics 41, 379–406 (2010).