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Using encounter rates as surrogates for density estimates makes monitoring of heavily-traded grey parrots achievable across Africa

  • Stuart J. Marsden (a1), Emmanuel Loqueh (a2), Jean Michel Takuo (a3), John A. Hart (a4), Robert Abani (a5), Dibié Bernard Ahon (a6), Nathaniel N. D. Annorbah (a1), Robin Johnson (a7) and Simon Valle (a1)...
Abstract
Abstract

Estimating population sizes in the heavily traded grey parrots of West and Central Africa would provide insights into conservation status and sustainability of harvests. Ideally, density estimates would be derived from a standardized method such as distance sampling, but survey efforts are hampered by the extensive ranges, patchy distribution, variable abundance, cryptic habits and high mobility of the parrots as well as by logistical difficulties and limited resources. We carried out line transect distance sampling alongside a simpler encounter rate method at 10 sites across five West and Central African countries. Density estimates were variable across sites, from 0–0.5 individuals km−2 in Côte d'Ivoire and central Democratic Republic of the Congo to c. 30 km−2 in Cameroon and > 70 km−2 on the island of Príncipe. Most significantly, we identified the relationship between densities estimated from distance sampling and simple encounter rates, which has important applications in monitoring grey parrots: (1) to convert records of parrot groups encountered in a day's activities by anti-poaching patrols within protected areas into indicative density estimates, (2) to confirm low density in areas where parrots are so rare that distance sampling is not feasible, and (3) to provide a link between anecdotal records and local density estimates. Encounter rates of less than one parrot group per day of walking are a reality in most forests within the species’ ranges. Densities in these areas are expected to be one individual km−2 or lower, and local harvest should be disallowed on this basis.

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(Corresponding author) E-mail s.valle@mmu.ac.uk
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Oryx
  • ISSN: 0030-6053
  • EISSN: 1365-3008
  • URL: /core/journals/oryx
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