-
DATA IDENTIFICATION
-
-
Name
-
Proportion of detected trade in wildlife and wildlife products that is illegal (SDG 15.7.2)
-
Indicator purpose
-
Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss.
-
Abstract
-
There are over 35,000 species under international protection, so it is impossible to monitor all poaching. Illegal trade, however, is an indirect indicator of poaching. Wildlife seizures represent concrete instances of illegal trade, but the share of overall wildlife crime they represent is unknown and variable. In addition, the number of species under international protection continues to grow. Legal international trade in protected species, by definition, is 100% captured in the CITES Trade Database, which now contains over 16 million records of trade in CITES-listed species. To ground the illegal trade data in a complete indicator, the ratio of aggregated seizures to total trade is estimated. An increase in the share of total wildlife trade that is illegal would be interpreted as a negative indicator, and a decrease as a positive one.
-
Data source
-
Forest Department
-
DATA CHARACTERISTICS
-
-
Contact organization person
-
Forest Department
-
Date last updated
-
08-NOV-2019
-
Periodicity
-
-
-
Unit of measure
-
Percentage (%)
-
Other characteristics
-
Levels of access to protected areas vary among the protected area management categories. Some areas, such as scientific reserves, are maintained in their natural state and closed to any other use. Others are used for recreation or tourism, or even open for the sustainable extraction of natural resources. In addition to protecting biodiversity, protected areas have high social and economic value: supporting local livelihoods; protecting watersheds from erosion; harbouring an untold wealth of genetic resources; supporting thriving recreation and tourism industries; providing for science, research and education; and forming a basis for cultural and other non-material values. Because the illegal wildlife trade represents thousands of distinct products, a means of aggregation is necessary. The legal trade value does not represent the true black-market value of the items seized, nor the true value of the legal shipments, because it is derived from a single market source (US LEMIS). It does, however, present a logical and consistent means of aggregating unlike products.
-
DATA CONCEPTS and CLASSIFICATIONS
-
-
Classification used
-
To take urgent action to end poaching and trafficking of protected species of flora and fauna and address both demand and supply of illegal wildlife products.
-
Disaggregation
-
Where source data are available, the data could be disaggregated to the national level. As a form of trade data, issues of gender, age, and disability status are not applicable.
-
Key statistical concepts
-
The value of a species-product unit is derived from the weighted average of prices declared for legal imports of analogous species product units, as acquired from United States Law Enforcement Monitoring and Information System of the Fish and Wildlife Service. The value of legal trade is the sum of all species-product units documented in CITES export permits as reported in the CITES Annual Reports times the species-product unit prices as specified above. The value of illegal trade is the sum of all species-product units documented in the World WISE seizure database times the species-product unit prices as specified above. The indicator is value of illegal trade / (value of legal trade + value of illegal trade).
-
Formula
-
-
-
OTHER ASPECTS
-
-
Recommended uses
-
The indicator is used to measure the proportion of traded wildlife that was poached or illicitly trafficked.
-
Limitations
-
Seizures are an incomplete indicator of trafficking, and subject to considerable volatility. Universal coverage is not presently available, although 120 countries are represented in the present database. Since the indicator looks at the relationship between two values, changes in the relationship could be due to changes in either value.
-
Other comments
-
-