Format

Send to

Choose Destination
Proc Natl Acad Sci U S A. 2015 Jun 30;112(26):7948-53. doi: 10.1073/pnas.1500862112. Epub 2015 Jun 15.

Quantitative methods of identifying the key nodes in the illegal wildlife trade network.

Author information

1
Department of Clinical Studies-New Bolton Center, University of Pennsylvania School of Veterinary Medicine, Kennett Square, PA 19348; nikkitapatel@gmail.com.
2
Department of Clinical Studies-New Bolton Center, University of Pennsylvania School of Veterinary Medicine, Kennett Square, PA 19348;
3
Metabiota, San Francisco, CA 94104;
4
Department of Pediatrics, Harvard Medical School, Boston, MA 02215; Boston Children's Hospital, Boston, MA 02215;
5
Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA 19104.

Abstract

Innovative approaches are needed to combat the illegal trade in wildlife. Here, we used network analysis and a new database, HealthMap Wildlife Trade, to identify the key nodes (countries) that support the illegal wildlife trade. We identified key exporters and importers from the number of shipments a country sent and received and from the number of connections a country had to other countries over a given time period. We used flow betweenness centrality measurements to identify key intermediary countries. We found the set of nodes whose removal from the network would cause the maximum disruption to the network. Selecting six nodes would fragment 89.5% of the network for elephants, 92.3% for rhinoceros, and 98.1% for tigers. We then found sets of nodes that would best disseminate an educational message via direct connections through the network. We would need to select 18 nodes to reach 100% of the elephant trade network, 16 nodes for rhinoceros, and 10 for tigers. Although the choice of locations for interventions should be customized for the animal and the goal of the intervention, China was the most frequently selected country for network fragmentation and information dissemination. Identification of key countries will help strategize illegal wildlife trade interventions.

KEYWORDS:

elephant; key player; network analysis; rhinoceros; wildlife trade

PMID:
26080413
PMCID:
PMC4491747
DOI:
10.1073/pnas.1500862112
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for HighWire Icon for PubMed Central
Loading ...
Support Center