Capacity of large-scale, long-term biodiversity monitoring programmes to detect trends in species prevalence
There is a critical need for monitoring programmes to assess change or trends in species status to inform conservation. A key aspect in developing such programmes is evaluating their statistical power--the ability to detect a real change. Here we examine the capacity of a broad-scale biodiversity mo...
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Veröffentlicht in: | Biodiversity and conservation 2009-10, Vol.18 (11), p.2961-2978 |
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creator | Nielsen, Scott E Haughland, Diane L Bayne, Erin Schieck, Jim |
description | There is a critical need for monitoring programmes to assess change or trends in species status to inform conservation. A key aspect in developing such programmes is evaluating their statistical power--the ability to detect a real change. Here we examine the capacity of a broad-scale biodiversity monitoring programme in Alberta, Canada to measure changes in species prevalence. Using observed variation in detectability and prevalence for 252 species monitored at 85 sites, we simulated 3% annual declines and evaluated sample size (6 different sizes) and length of monitoring (5 different durations) necessary to detect change with a 90% certainty (power) at an α of 0.1. Our results suggest that after four monitoring cycles (e.g., 20 years for a 5-year cycle) a power of 90% can be expected for 99% of species when monitoring 1,625 sites, 65% of species for 300 sites, 27% of species for 75 sites, and 8% of species for 25 sites. We found that 66% detectability and 50% prevalence were needed to ensure that 3% annual change is detected at 50 sites over a 20-year period. Our results demonstrate that broad-scale monitoring programmes cannot effectively detect trends in all species at all spatial scales. The time period and spatial scale necessary to detect a real change at a specified level needs to be provided to stakeholders to ensure the short-term success of biodiversity monitoring programmes and to ensure that the most robust indicators of biodiversity are selected. |
doi_str_mv | 10.1007/s10531-009-9619-1 |
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A key aspect in developing such programmes is evaluating their statistical power--the ability to detect a real change. Here we examine the capacity of a broad-scale biodiversity monitoring programme in Alberta, Canada to measure changes in species prevalence. Using observed variation in detectability and prevalence for 252 species monitored at 85 sites, we simulated 3% annual declines and evaluated sample size (6 different sizes) and length of monitoring (5 different durations) necessary to detect change with a 90% certainty (power) at an α of 0.1. Our results suggest that after four monitoring cycles (e.g., 20 years for a 5-year cycle) a power of 90% can be expected for 99% of species when monitoring 1,625 sites, 65% of species for 300 sites, 27% of species for 75 sites, and 8% of species for 25 sites. We found that 66% detectability and 50% prevalence were needed to ensure that 3% annual change is detected at 50 sites over a 20-year period. Our results demonstrate that broad-scale monitoring programmes cannot effectively detect trends in all species at all spatial scales. 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A key aspect in developing such programmes is evaluating their statistical power--the ability to detect a real change. Here we examine the capacity of a broad-scale biodiversity monitoring programme in Alberta, Canada to measure changes in species prevalence. Using observed variation in detectability and prevalence for 252 species monitored at 85 sites, we simulated 3% annual declines and evaluated sample size (6 different sizes) and length of monitoring (5 different durations) necessary to detect change with a 90% certainty (power) at an α of 0.1. Our results suggest that after four monitoring cycles (e.g., 20 years for a 5-year cycle) a power of 90% can be expected for 99% of species when monitoring 1,625 sites, 65% of species for 300 sites, 27% of species for 75 sites, and 8% of species for 25 sites. We found that 66% detectability and 50% prevalence were needed to ensure that 3% annual change is detected at 50 sites over a 20-year period. Our results demonstrate that broad-scale monitoring programmes cannot effectively detect trends in all species at all spatial scales. 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A key aspect in developing such programmes is evaluating their statistical power--the ability to detect a real change. Here we examine the capacity of a broad-scale biodiversity monitoring programme in Alberta, Canada to measure changes in species prevalence. Using observed variation in detectability and prevalence for 252 species monitored at 85 sites, we simulated 3% annual declines and evaluated sample size (6 different sizes) and length of monitoring (5 different durations) necessary to detect change with a 90% certainty (power) at an α of 0.1. Our results suggest that after four monitoring cycles (e.g., 20 years for a 5-year cycle) a power of 90% can be expected for 99% of species when monitoring 1,625 sites, 65% of species for 300 sites, 27% of species for 75 sites, and 8% of species for 25 sites. We found that 66% detectability and 50% prevalence were needed to ensure that 3% annual change is detected at 50 sites over a 20-year period. Our results demonstrate that broad-scale monitoring programmes cannot effectively detect trends in all species at all spatial scales. The time period and spatial scale necessary to detect a real change at a specified level needs to be provided to stakeholders to ensure the short-term success of biodiversity monitoring programmes and to ensure that the most robust indicators of biodiversity are selected.</abstract><cop>Dordrecht</cop><pub>Dordrecht : Springer Netherlands</pub><doi>10.1007/s10531-009-9619-1</doi><tpages>18</tpages></addata></record> |
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subjects | Biodiversity Biological diversity Biomedical and Life Sciences Climate Change/Climate Change Impacts Conservation Conservation Biology/Ecology Ecology Endangered & extinct species Life Sciences Monitoring Original Paper spatial distribution stakeholders Statistics Wildlife conservation |
title | Capacity of large-scale, long-term biodiversity monitoring programmes to detect trends in species prevalence |
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