Abstract
1. Obtaining robust abundance or density estimates is problematic for many rare or cryptic species. We combine elements of capture-recapture and distance sampling, to develop a method called trapping point transects (TPT).
2. TPT requires two separate surveys to be held concurrently in space and time. In the main survey, the encounter rate (number of animals caught per trap per session) is measured. In the trial survey, animals whose locations are known prior to opening traps are used to estimate the detection function g(r) (the probability of capturing an animal given it is distance r from a trap when it is set), so the effective trapping area in the main survey can be estimated. It is assumed animals in the trial survey are a representative sample of all animals in the population. Individual heterogeneity in trappability is accommodated using random effects in g(r).
3. Performance of two TPT estimators was assessed by simulation. Generally, when underlying capture probabilities were high (g(0)=0.8) and between-individual variation was small, modest survey effort (360 trap nights in the trial survey) generated little bias in estimated abundance (c. 5%). Uncertainty and relative bias in population estimates increased with decreasing capture probabilities and increasing between-individual variation. Survey effort required to obtain unbiased estimates was also investigated.
4. Abundance of the endangered Key Largo woodrat (Neotoma floridana smalli) was estimated using TPT between 2008-2011, yielding annual estimates of the extant wild population of 693, 248, 78, and 256 animals, with CVs of 0.45, 0.55, 0.82 and 0.43, respectively.
5. TPT was found to be a cost-efficient monitoring method, and could be adapted to a range of species that are otherwise very difficult to monitor. For example, detection of animals at the sample point might rely on camera traps, or different lures (e.g., vocal-playback or baits). We anticipate that TPT surveys will see wide usage for estimating population abundance of cryptic but trappable species.
2. TPT requires two separate surveys to be held concurrently in space and time. In the main survey, the encounter rate (number of animals caught per trap per session) is measured. In the trial survey, animals whose locations are known prior to opening traps are used to estimate the detection function g(r) (the probability of capturing an animal given it is distance r from a trap when it is set), so the effective trapping area in the main survey can be estimated. It is assumed animals in the trial survey are a representative sample of all animals in the population. Individual heterogeneity in trappability is accommodated using random effects in g(r).
3. Performance of two TPT estimators was assessed by simulation. Generally, when underlying capture probabilities were high (g(0)=0.8) and between-individual variation was small, modest survey effort (360 trap nights in the trial survey) generated little bias in estimated abundance (c. 5%). Uncertainty and relative bias in population estimates increased with decreasing capture probabilities and increasing between-individual variation. Survey effort required to obtain unbiased estimates was also investigated.
4. Abundance of the endangered Key Largo woodrat (Neotoma floridana smalli) was estimated using TPT between 2008-2011, yielding annual estimates of the extant wild population of 693, 248, 78, and 256 animals, with CVs of 0.45, 0.55, 0.82 and 0.43, respectively.
5. TPT was found to be a cost-efficient monitoring method, and could be adapted to a range of species that are otherwise very difficult to monitor. For example, detection of animals at the sample point might rely on camera traps, or different lures (e.g., vocal-playback or baits). We anticipate that TPT surveys will see wide usage for estimating population abundance of cryptic but trappable species.
Original language | English |
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Pages (from-to) | 695-703 |
Journal | Methods in Ecology and Evolution |
Volume | 3 |
DOIs | |
Publication status | Published - 2012 |