Towards accurate and precise estimates of lion density
Reliable estimates of animal density are fundamental to our understanding of ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation biology since wildlife authorities rely on these figures to make decisions. However, it is notoriously difficult to accurate...
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| Format: | Journal article |
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Wiley
2017
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| _version_ | 1826294767251619840 |
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| author | Elliot, N Gopalaswamy, A |
| author_facet | Elliot, N Gopalaswamy, A |
| author_sort | Elliot, N |
| collection | OXFORD |
| description | Reliable estimates of animal density are fundamental to our understanding of ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation biology since wildlife authorities rely on these figures to make decisions. However, it is notoriously difficult to accurately estimate density for wide-ranging species such as carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores. African lions (Panthera leo) provide an excellent example as although abundance indices have been shown to produce poor inferences, they continue to be used to estimate lion density and inform management and policy. In this study we adapt a Bayesian spatially explicit capture-recapture model to estimate lion density in the Maasai Mara National Reserve (MMNR) and surrounding conservancies in Kenya. We utilize sightings data from a three-month survey period to produce statistically rigorous spatial density estimates. Overall posterior mean lion density was estimated to be 16.85 (posterior standard deviation = 1.30) lions over one year of age per 100km2 with a sex ratio of 2.2♀:1♂. We argue that such methods should be developed, improved and favored over less reliable methods such as track and call-up surveys. We caution against trend analyses based on surveys of differing reliability and call for a unified framework to assess lion numbers across their range in order for better informed management and policy decisions to be made. |
| first_indexed | 2024-03-07T03:50:45Z |
| format | Journal article |
| id | oxford-uuid:c12bc236-cd97-473d-8776-1d5e1b1e8a75 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T03:50:45Z |
| publishDate | 2017 |
| publisher | Wiley |
| record_format | dspace |
| spelling | oxford-uuid:c12bc236-cd97-473d-8776-1d5e1b1e8a752022-03-27T05:59:31ZTowards accurate and precise estimates of lion densityJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:c12bc236-cd97-473d-8776-1d5e1b1e8a75Symplectic Elements at OxfordWiley2017Elliot, NGopalaswamy, AReliable estimates of animal density are fundamental to our understanding of ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation biology since wildlife authorities rely on these figures to make decisions. However, it is notoriously difficult to accurately estimate density for wide-ranging species such as carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores. African lions (Panthera leo) provide an excellent example as although abundance indices have been shown to produce poor inferences, they continue to be used to estimate lion density and inform management and policy. In this study we adapt a Bayesian spatially explicit capture-recapture model to estimate lion density in the Maasai Mara National Reserve (MMNR) and surrounding conservancies in Kenya. We utilize sightings data from a three-month survey period to produce statistically rigorous spatial density estimates. Overall posterior mean lion density was estimated to be 16.85 (posterior standard deviation = 1.30) lions over one year of age per 100km2 with a sex ratio of 2.2♀:1♂. We argue that such methods should be developed, improved and favored over less reliable methods such as track and call-up surveys. We caution against trend analyses based on surveys of differing reliability and call for a unified framework to assess lion numbers across their range in order for better informed management and policy decisions to be made. |
| spellingShingle | Elliot, N Gopalaswamy, A Towards accurate and precise estimates of lion density |
| title | Towards accurate and precise estimates of lion density |
| title_full | Towards accurate and precise estimates of lion density |
| title_fullStr | Towards accurate and precise estimates of lion density |
| title_full_unstemmed | Towards accurate and precise estimates of lion density |
| title_short | Towards accurate and precise estimates of lion density |
| title_sort | towards accurate and precise estimates of lion density |
| work_keys_str_mv | AT elliotn towardsaccurateandpreciseestimatesofliondensity AT gopalaswamya towardsaccurateandpreciseestimatesofliondensity |