Reliable evidence of trends in the illegal ivory trade is important for informing decision making for elephants but it is difficult to obtain due to the covert nature of the trade. The Elephant Trade Information System, a global database of reported seizures of illegal ivory, holds the only extensive information on illicit trade available. However inherent biases in seizure data make it difficult to infer trends; countries differ in their ability to make and report seizures and these differences cannot be directly measured. We developed a new modelling framework to provide quantitative evidence on trends in the illegal ivory trade from seizures data. The framework used Bayesian hierarchical latent variable models to reduce bias in seizures data by identifying proxy variables that describe the variability in seizure and reporting rates between countries and over time. Models produced bias-adjusted smoothed estimates of relative trends in illegal ivory activity for raw and worked ivory in three weight classes. Activity is represented by two indicators describing the number of illegal ivory transactions – Transactions Index – and the total weight of illegal ivory transactions – Weights Index – at global, regional or national levels. Globally, activity was found to be rapidly increasing and at its highest level for 16 years, more than doubling from 2007 to 2011 and tripling from 1998 to 2011. Over 70% of the Transactions Index is from shipments of worked ivory weighing less than 10 kg and the rapid increase since 2007 is mainly due to increased consumption in China. Over 70% of the Weights Index is from shipments of raw ivory weighing at least 100 kg mainly moving from Central and East Africa to Southeast and East Asia. The results tie together recent findings on trends in poaching rates, declining populations and consumption and provide detailed evidence to inform international decision making on elephants.

Introduction

The illegal ivory trade remains a major threat to elephant populations. There is evidence of increased poaching of elephants for their ivory, from the global monitoring program MIKE (Monitoring the Illegal Killing of Elephants) [1], [2] and from regional, national and site level case studies [3]–[5]. Furthermore, there is evidence of declining populations of elephants in some regions [6], [7] and countries [1], [8], [9]. These studies identify major sources of ivory but do not identify what happens to the ivory once it has been poached. Evidence of global trends in the illegal ivory trade, and the identification of trade route patterns from source to destination are required to provide a better understanding of the trade and to assist in decision making for elephants.

The covert nature of the illegal ivory trade is a serious obstacle to quantitative study of the process. The trade typically has been studied by describing the extent of domestic ivory markets in specific countries [10]–[13] or by focussing on economic models [14], [15], or other approaches [16] which correlate national populations of elephants before and after the 1989 ban on ivory trade, with variables describing various aspects of the illegal trade. However, none of this research provides a global picture or quantitative evidence of global trends in the trade. We show that, using Bayesian statistical modelling, data on seizures of illegal ivory can produce trends and reveal underlying dynamics of the illegal ivory trade.

The Elephant Trade Information System (ETIS) was mandated by CITES (Convention for International Trade in Endangered Species of Wild Fauna and Flora) in 1997 to track the illegal ivory trade globally; it is the sister programme to MIKE. CITES Parties (countries that are members of CITES) are requested to report all illegal ivory seizures to ETIS within 90 days. We use over 11,000 ETIS records from 1996 to 2011 to provide quantitative evidence on trends in the illegal ivory trade, in particular global trends in the total weight and number of illegal ivory transactions. We also identify regions and countries and their roles in the trade.

Using Seizures Data to Understand the Illegal Ivory Trade The use of seizures data to provide a reliable picture of illegal ivory trade activity has often been dismissed, [17] for example, because of the obvious biases inherent in the data. However, it is intuitively clear that seizures data hold some information about the illegal trade, so rather than ignoring the data altogether, we attempt to identify the sources of bias and account for them in the data analysis. Because ETIS contains reported records of illegal ivory seizures, bias arises from two principal sources (Figure 1A). First, not all illegal ivory transactions within a country are seized; the proportion that is seized, the seizure rate, is unknown. Second, not all seizures made by law enforcement bodies are reported to ETIS; the proportion that is reported, the reporting rate, is unknown. PPT PowerPoint slide

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larger image TIFF original image Download: Figure 1. Conceptual models of the illegal ivory trade and seizures data. (A) In each county, in each year an unknown proportion (seizure rate) of illegal ivory transactions (see Figure 1B for examples) is seized. Of these seizures an unknown proportion (reporting rate) are reported to ETIS. We identify potential predictors that discriminate different countries ability to make and report seizures so that we can obtain relative estimates of seizure and reporting rates and the numbers of illegal ivory transactions. Figure S1 shows the predictors of seizure and reporting rate identified by the modelling exercise described in this paper. (B) Flow of ivory from source to point of sale representing different types of illegal ivory transactions. Circles represent individual countries along the trade chain. Raw ivory obtained from illegally killed elephants (or stolen from stockpiles of ivory) is put together into a shipment – this ivory may be sourced from several countries. Shipments might pass through a number of countries before arriving at ivory processing plants. Once the ivory is processed into worked ivory it is put into a shipment (again this ivory may come from several ivory processing plants in different countries and from stockpiles) and could pass through several countries before arriving at wholesale or retail places. Once there, it will likely be sold to individuals, locals or tourists, and could pass through several more countries before reaching its final destination. Seizures can occur all along this trade chain and seized ivory should pass to the ivory stockpiles which also includes ivory from natural elephant mortality in range States. There is evidence that ivory sometimes re-enters the trade chain from unsecured ivory stockpiles [45]. The whole, or parts, of the trade chain for any single piece of ivory could occur in one country, one region or across the globe. https://doi.org/10.1371/journal.pone.0076539.g001 If it could be assumed that the seizure rate and reporting rate were the same for all countries and were constant over time, then simple summaries of the ETIS records would be sufficient to describe trends over time, make comparisons between countries and identify those that play a major role in the trade. This would hold even though the actual seizure and reporting rates were unknown. However, there is no a priori evidence to justify this assumption, and we proceeded by considering variable rates and the underlying reasons for this variability between countries and over time. Variation in reporting rate arises from differences both in resources and in the degree of commitment between countries. Each country’s CITES Management Authority (CMA) is the responsible body for reporting to CITES, including the reporting of ivory seizures to ETIS. Some countries have automated systems through which they regularly report to ETIS on all ivory seizure records that were made by their law enforcement agencies. In such cases one might expect that most of the seizures a country makes are reported to ETIS, and the reporting rate to be high. For other countries, reporting to CITES may not be a priority and information on illegal ivory seizures may not come from the CMA, but from NGOs or other sources. Under such circumstances a complete record of all seizures made in that country is unlikely, and the reporting rate is considered low. Similarly a country’s seizure rate may vary depending on the resources committed to law enforcement. The number of personnel, equipment, training and knowledge of staff would all affect enforcement effort and, in particular, the ability to make ivory seizures. Furthermore, the effectiveness of this enforcement effort may depend on the levels of corruption and governance within the country [18]–[20]. We do not necessarily expect seizure and reporting rate to be related as different agencies are involved in making seizures and reporting these seizures; in general, law enforcement agencies make seizures and CITES authorities report seizures to ETIS. Depending on the degree of inter-agency collaboration, which varies from country to country, two countries with very similar seizure rates may have very different reporting rates. To capture the variability in reporting and seizure rates, we constructed a statistical model, represented conceptually by Figure 1A. We modelled the seizure and reporting rates in terms of predictor variables representing the causes of variation between countries and over time as described above. Direct observation of the predictors was impossible, so country-specific, time-based candidate proxy variables were sought instead (as listed in Table 1), and those that provided the best fit to the data were identified. Using the best proxy variables the model produced relative bias-adjusted and smoothed estimates of illegal ivory trade activity. The candidate proxy variables, statistical modelling and model selection process are described in the Materials and Methods Section. PPT PowerPoint slide

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larger image TIFF original image Download: Table 1. Candidate variables for predictors of seizure and reporting rates. https://doi.org/10.1371/journal.pone.0076539.t001