Using power analysis and spatial prioritization to evaluate the design of a forest bird monitoring programme
Biodiversity monitoring programmes should be designed with sufficient statistical power to detect population change. Here we evaluated the statistical power of monitoring to detect declines in the occupancy of forest birds on Christmas Island, Australia. We fitted zero-inflated binomial models to 3...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Cambridge University Press
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| Online Access: | https://www.cambridge.org/core/product/identifier/S0030605323001382/type/journal_article |
| _version_ | 1797336270677999616 |
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| author | Darren M. Southwell Adam Smart Samuel D. Merson Katherine E. Selwood Nicholas A. Macgregor |
| author_facet | Darren M. Southwell Adam Smart Samuel D. Merson Katherine E. Selwood Nicholas A. Macgregor |
| author_sort | Darren M. Southwell |
| collection | DOAJ |
| description | Biodiversity monitoring programmes should be designed with sufficient statistical power to detect population change. Here we evaluated the statistical power of monitoring to detect declines in the occupancy of forest birds on Christmas Island, Australia. We fitted zero-inflated binomial models to 3 years of repeat detection data (2011, 2013 and 2015) to estimate single-visit detection probabilities for four species of concern: the Christmas Island imperial pigeon Ducula whartoni, Christmas Island white-eye Zosterops natalis, Christmas Island thrush Turdus poliocephalus erythropleurus and Christmas Island emerald dove Chalcophaps indica natalis. We combined detection probabilities with maps of occupancy to simulate data collected over the next 10 years for alternative monitoring designs and for different declines in occupancy (10–50%). Specifically, we explored how the number of sites (60, 128, 300, 500), the interval between surveys (1–5 years), the number of repeat visits (2–4 visits) and the location of sites influenced power. Power was high (> 80%) for the imperial pigeon, white-eye and thrush for most scenarios, except for when only 60 sites were surveyed or a 10% decline in occupancy was simulated over 10 years. For the emerald dove, which is the rarest of the four species and has a patchy distribution, power was low in almost all scenarios tested. Prioritizing monitoring towards core habitat for this species only slightly improved power to detect declines. Our study demonstrates how data collected during the early stages of monitoring can be analysed in simulation tools to fine-tune future survey design decisions. |
| first_indexed | 2024-03-08T08:51:50Z |
| format | Article |
| id | doaj.art-f2dce6a39b40410f802725efa15f6a11 |
| institution | Directory Open Access Journal |
| issn | 0030-6053 1365-3008 |
| language | English |
| last_indexed | 2024-03-08T08:51:50Z |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Oryx |
| spelling | doaj.art-f2dce6a39b40410f802725efa15f6a112024-02-01T10:12:10ZengCambridge University PressOryx0030-60531365-300811010.1017/S0030605323001382Using power analysis and spatial prioritization to evaluate the design of a forest bird monitoring programmeDarren M. Southwell0https://orcid.org/0000-0002-8767-9014Adam Smart1https://orcid.org/0000-0002-9739-3204Samuel D. Merson2Katherine E. Selwood3https://orcid.org/0000-0003-1145-9039Nicholas A. Macgregor4https://orcid.org/0000-0002-7995-0230School of Environmental and Life Science, University of Newcastle, Callaghan, Australia School of BioSciences, University of Melbourne, Parkville, AustraliaSchool of BioSciences, University of Melbourne, Parkville, AustraliaParks Australia, Canberra, AustraliaSchool of BioSciences, University of Melbourne, Parkville, Australia Wildlife Conservation and Science, Zoos Victoria, Parkville, AustraliaParks Australia, Canberra, Australia Durrell Institute of Conservation and Ecology (DICE), School of Anthropology and Conservation, University of Kent, Canterbury, UKBiodiversity monitoring programmes should be designed with sufficient statistical power to detect population change. Here we evaluated the statistical power of monitoring to detect declines in the occupancy of forest birds on Christmas Island, Australia. We fitted zero-inflated binomial models to 3 years of repeat detection data (2011, 2013 and 2015) to estimate single-visit detection probabilities for four species of concern: the Christmas Island imperial pigeon Ducula whartoni, Christmas Island white-eye Zosterops natalis, Christmas Island thrush Turdus poliocephalus erythropleurus and Christmas Island emerald dove Chalcophaps indica natalis. We combined detection probabilities with maps of occupancy to simulate data collected over the next 10 years for alternative monitoring designs and for different declines in occupancy (10–50%). Specifically, we explored how the number of sites (60, 128, 300, 500), the interval between surveys (1–5 years), the number of repeat visits (2–4 visits) and the location of sites influenced power. Power was high (> 80%) for the imperial pigeon, white-eye and thrush for most scenarios, except for when only 60 sites were surveyed or a 10% decline in occupancy was simulated over 10 years. For the emerald dove, which is the rarest of the four species and has a patchy distribution, power was low in almost all scenarios tested. Prioritizing monitoring towards core habitat for this species only slightly improved power to detect declines. Our study demonstrates how data collected during the early stages of monitoring can be analysed in simulation tools to fine-tune future survey design decisions.https://www.cambridge.org/core/product/identifier/S0030605323001382/type/journal_articleChristmas Islanddetectabilityforest birdsmonitoringoccupancy modelssimulationstatistical powersurvey design |
| spellingShingle | Darren M. Southwell Adam Smart Samuel D. Merson Katherine E. Selwood Nicholas A. Macgregor Using power analysis and spatial prioritization to evaluate the design of a forest bird monitoring programme Oryx Christmas Island detectability forest birds monitoring occupancy models simulation statistical power survey design |
| title | Using power analysis and spatial prioritization to evaluate the design of a forest bird monitoring programme |
| title_full | Using power analysis and spatial prioritization to evaluate the design of a forest bird monitoring programme |
| title_fullStr | Using power analysis and spatial prioritization to evaluate the design of a forest bird monitoring programme |
| title_full_unstemmed | Using power analysis and spatial prioritization to evaluate the design of a forest bird monitoring programme |
| title_short | Using power analysis and spatial prioritization to evaluate the design of a forest bird monitoring programme |
| title_sort | using power analysis and spatial prioritization to evaluate the design of a forest bird monitoring programme |
| topic | Christmas Island detectability forest birds monitoring occupancy models simulation statistical power survey design |
| url | https://www.cambridge.org/core/product/identifier/S0030605323001382/type/journal_article |
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