Darkweb rhino horn

Framework 1: methods for characterising online trade

This framework is aimed at characterising online trade in wildlife products, producing tools that can track changes in this trade as traders and consumers respond to technological advances and increased online enforcement.

The internet presents a new frontier for all forms of trade, both legal and illegal. The rise of more legitimate online auction and trading sites, such as eBay and Alibaba, has been mirrored by markets for illegal goods, particularly drugs, such as the Silk Road online marketplace. Illegal online markets make use either of state-of-the-art technologies such as Tor’s hidden services to allow websites to function without being traceable by law enforcement, or alternatively may rely simply on the complexities of legal enforcement across jurisdictions as protection (Brown et al., 2013).

The few studies carried out to date on the illegal online wildlife trade (e.g. IFAW’s 2013 study of ivory sales on ebay) suggest that it is substantial, and that it occurs primarily on the public web (e.g. on online auction sites such as e-bay, on social media platforms like Facebook, and directly via the websites of traders). The ongoing demand for such products, the continual evolution of online communities and technologies, and increasing attempts to curtail this trade are likely to mean that the online wildlife trade will both grow and become more dispersed and challenging to monitor in the next few years. This makes monitoring of both the dark web and the public web necessary in order to understand how the modern trade in wildlife products will develop, and predict and preempt attempts to circumvent enforcement.

This Framework has three main focal activities:

  • Developing new, generic, tools that can be used proactively to monitor, track, and report online sales in wildlife. This will target existing online auction and sales sites and emerging platforms for trade, such as social media sites and Instagram. More significantly, this will require the development of means to monitor elements of the dark web, a significant proportion of which is not publicly linked or searchable through traditional means.
  • Developing approaches to identify and describe shifting patterns of use in the online trade of wildlife products. This work will involve analysis of the links between actors in technical, social, and trade networks; developments in the technologies that are used as the basis for these markets; and changes in this usage in response to exogenous factors such as activities of law enforcement.
  • Carrying out the online component of the research for the case studies, producing new information on specific products and species. This focus on concrete problems will inform and support the methodological developments under 1 and 2, and provide opportunities for direct and short-term impact for this element of the programme.

Researchers: Dr Joss Wright, Dr Dave Roberts, Dr Julio-Hernandez-Castro
Collaborating organisations: Saiga Conservation Alliance

Framework 2: methods for intervening effectively

We use the Medical Research Council’s revised framework for developing and evaluating complex public health interventions to guide approaches to intervention design, implementation and evaluation.

The importance of theory-based design and evaluation of interventions is well established (Chen & Rossi, 1983; Michie et al., 2005; Rogers & Weiss, 2007; Weiss, 1997). Key to this is an explicit programme theory or theory of change; a description of the causal chain of activities intended to produce a positive intervention outcome (Fraser et al., 2009). The benefits of such theories include more effective interventions, a better understanding of why they are effective, and improved implementation (Bonell et al., 2015; Cooksy et al., 2001; Kinmoth et al., 2008). Researchers commonly specify theories of interventions with the help of stakeholders, using formal consensus processes such as the Delphi and nominal group techniques (Julian, 1997; Van Urk et al., 2015).

Conservation has suffered from a lack of proper design and evaluation, resulting in an ineffective use of resources and impacts that cannot be measured (Salafsky et al., 2002, Crees et al., 2016). Without an adequate evidence base, projects can be implemented based on wishful thinking (Margoluis et al 2013). Well-designed projects are based on clear objectives, explicit theories of change, supported by research, with built-in monitoring and evaluation, thus allowing evaluation of outcomes, lesson learning and adaptive management to take place (Stem et al., 2005, Margolouis et al., 2009, Sweeney, 2011). However, examples of conservation interventions that fulfil these design criteria are still limited (Pullin & Knight, 2001, Ferraro & Pattanayak, 2006, Crees et al., 2016). Many project management tools are now available to conservationists [e.g. Miradi (CMP, Sitka, 2016), Foundations of Success (FOS, 2016) & CCF Framework (Kapos et al., 2008)], but few studies have evaluated whether projects are actually following the basic criteria for good design and evaluation (Ewen et al., 2014). 

Researcher: Dr Diogo Veríssimo

Framework 3: methods for gaining a predictive understanding

Here, we use scenario analysis and participatory modelling to better understand the likely responses of consumers and markets to potential interventions, and hence plan effectively for future actions.

New large-scale policy interventions, technological advances and social change take us into unknown territory in terms of how demand will respond. A predictive approach is required to understand how these external drivers will impact on the outcomes of interventions. Currently there is very little emphasis on predictive conservation science pertaining to people’s responses to interventions and external events; this is something our team has highlighted (Milner-Gulland, 2012, Nicholson et al., 2009), and has been touched on by other researchers (e.g. Polasky, 2005, Oliver et al., 2015). Within economics, predictive modelling, both theoretical and empirically-based, is much more standard (e.g. Giglio et al., 2016 on predicting macroeconomic shocks). Similarly, much climate science is about prediction (e.g. Allen & Ingram, 2002). Conservation can learn a lot from these subject areas about how best to predict changes in conditions and their effects on market and consumer behaviour, and develop interventions that are robust to these changes.

Framework 3 draws together our research in the case studies to consider the potential outcomes of policy interventions. It demonstrates also the potential of participatory model- building, with the development of a theoretical model for particularly contentious policy issues. This will enable us to explore how external change and interventions may interact to drive wildlife markets, and hence the impact of the illegal wildlife trade on biodiversity. Importantly, it will also highlight the remaining critical uncertainties in determining outcomes and emerging issues, which will shape our future research agenda.

The three main strands within this framework are to:

  • Draw empirical evidence from the programme’s case studies to develop predictive understanding of the likely potential impacts of a range of interventions, in the light of external conditions, using a scenario planning approach.
  • Adapt theoretical modelling through participatory approaches, to highlight uncertainties and clarify the basis for conflicting viewpoints on policy options; specifically to understand the potential effects of two additional case studies, on particularly contentious policy issues: 1) Variable quota setting for the lion bone trade, and 2) Synthetic and legal horn trades on illegal rhino horn markets.
  • Utilise horizon scanning as a technique for systematically identifying emerging challenges and opportunities that are not yet widely recognised as important, but which have a high probability of societal impact (Amanatidou et al., 2012, Konnola et al., 2012). Their early warning function reduces the unpredictability of these impacts, and gives time for technological progress or policy change to take place to address the issue. Sutherland et al. (2015) have carried out horizon scans for a range of conservation and environmental issues – this expertise will be drawn upon to structure and implement our horizon scan specific to the illegal wildlife trade.

Researchers: Michael ‘t Sas Rolfes, Nafeesa Esmail
Collaborating organisations: South African National Biodiversity Institute (SANBI), University of the Witwatersrand

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