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Author (up) Durbach, I., Borchers, D., Sutherland, C., Sharma, K. url 
  Title Fast, flexible alternatives to regular grid designs for spatial capture–recapture. Type Research Article
  Year 2020 Publication Methods in Ecology and Evolution Abbreviated Journal  
  Volume Issue Pages 1-13  
  Keywords camera trap, population ecology,sampling, spatial capture-recapture, surveys  
  Abstract Spatial capture–recapture (SCR) methods use the location of

detectors (camera traps, hair snares and live-capture traps) and the

locations at which animals were detected (their spatial capture

histories) to estimate animal density. Despite the often large expense

and effort involved in placing detectors in a landscape, there has been

relatively little work on how detectors should be located. A natural

criterion is to place traps so as to maximize the precision of density

estimators, but the lack of a closed-form expression for precision has

made optimizing this criterion computationally demanding. 2. Recent

results by Efford and Boulanger (2019) show that precision can be well

approximated by a function of the expected number of detected

individuals and expected number of recapture events, both of which can

be evaluated at low computational cost. We use these results to develop

a method for obtaining survey designs that optimize this approximate

precision for SCR studies using count or binary proximity detectors, or

multi-catch traps. 3. We show how the basic design protocol can be

extended to incorporate spatially varying distributions of activity

centres and animal detectability. We illustrate our approach by

simulating from a camera trap study of snow leopards in Mongolia and

comparing estimates from our designs to those generated by regular or

optimized grid designs. Optimizing detector placement increased the

number of detected individuals and recaptures, but this did not always

lead to more precise density estimators due to less precise estimation

of the effective sampling area. In most cases, the precision of density

estimators was comparable to that obtained with grid designs, with

improvement in some scenarios where approximate CV(¬D) < 20% and density

varied spatially. 4. Designs generated using our approach are

transparent and statistically grounded. They can be produced for survey

regions of any shape, adapt to known information about animal density

and detectability, and are potentially easier and less costly to

implement. We recommend their use as good, flexible candidate designs

for SCR surveys when reasonable knowledge of model parameters exists. We

provide software for researchers to construct their own designs, in the

form of updates to design functions in the r package oSCR.
 
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  Area Expedition Conference  
  Notes Approved no  
  Call Number Serial 1618  
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