Assessing the global prevalence of wild birds in trade

Author:

Donald Paul F.12ORCID,Fernando Eresha13,Brown Lauren4,Busana Michela1,Butchart Stuart H. M.12,Chng Serene5ORCID,de la Colina Alicia6,Ferreira Juliana Machado7,Jain Anuj8ORCID,Jones Victoria R.1,Lapido Rocio9,Malsch Kelly10,McDougall Amy1,Muccio Colum11,Nguyen Dao12,Outhwaite Willow4,Petrovan Silviu O.2ORCID,Stafford Ciara10,Sutherland William J.2,Tallowin Oliver3,Safford Roger1

Affiliation:

1. BirdLife International Cambridge UK

2. Department of Zoology University of Cambridge Cambridge UK

3. IUCN Cambridge UK

4. TRAFFIC Cambridge UK

5. TRAFFIC Kelana Jaya Malaysia

6. Fundación Temaikèn Belén de Escobar Argentina

7. Freeland Brazil São Paulo Brazil

8. BirdLife International Singapore Singapore

9. Aves Argentinas, Asociación Ornitológica del Plata Buenos Aires Argentina

10. UN Environment Programme World Conservation Monitoring Centre Cambridge UK

11. ARCAS Gautemala San Lucas Sacatepéquez Guatemala

12. IUCN Gland Switzerland

Abstract

AbstractTrade represents a significant threat to many wild species and is often clandestine and poorly monitored. Information on which species are most prevalent in trade and potentially threatened by it therefore remains fragmentary. We used 7 global data sets on birds in trade to identify species or groups of species at particular risk and assessed the extent to which they were congruent in terms of the species recorded in trade. We used the frequency with which species were recorded in the data sets as the basis for a trade prevalence score that was applied to all bird species globally. Literature searches and questionnaire surveys were used to develop a list of species known to be heavily traded to validate the trade prevalence score. The score was modeled to identify significant predictors of trade. Although the data sets sampled different parts of the broad trade spectrum, congruence among them was statistically strong in all comparisons. Furthermore, the frequency with which species were recorded within data sets was positively correlated with their occurrence across data sets, indicating that the trade prevalence score captured information on trade volume. The trade prevalence score discriminated well between species identified from semi‐independent assessments as heavily or unsustainably traded and all other species. Globally, 45.1% of all bird species and 36.7% of globally threatened bird species had trade prevalence scores ≥1. Species listed in Appendices I or II of CITES, species with large geographical distributions, and nonpasserines tended to have high trade prevalence scores. Speciose orders with high mean trade prevalence scores included Falconiformes, Psittaciformes, Accipitriformes, Anseriformes, Bucerotiformes, and Strigiformes. Despite their low mean prevalence score, Passeriformes accounted for the highest overall number of traded species of any order but had low representation in CITES appendices. Geographical hotspots where large numbers of traded species co‐occur differed among passerines (Southeast Asia and Eurasia) and nonpasserines (central South America, sub‐Saharan Africa, and India). This first attempt to quantify and map the relative prevalence in trade of all bird species globally can be used to identify species and groups of species that may be at particular risk of harm from trade and can inform conservation and policy interventions to reduce its adverse impacts.

Publisher

Wiley

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