Data from: Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance

It is common to use multiple field sampling methods when implementing
wildlife surveys to compare method efficacy or cost-efficiency, integrate
distinct pieces of information provided by separate methods, or evaluate
method-specific biases and misclassification error. Existing models that
combine information from multiple field methods or sampling devices permit
rigorous comparison of method-specific detection parameters, enable
estimation of additional parameters such as false-positive detection
probability, and improve occurrence or abundance estimates, but with the
assumption that the separate sampling methods produce detections
independently of one another. This assumption is tenuous if methods are
paired or deployed in close proximity simultaneously, a common practice
that reduces the additional effort required to implement multiple methods
and reduces the risk that differences between method-specific detection
parameters are confounded by other environmental factors. We develop
occupancy and spatial capture-recapture models that permit covariance
between the detections produced by different methods, use simulation to
compare estimator performance of the new models to models assuming
independence, and provide an empirical application based upon American
marten (Martes americana) surveys using paired remote cameras,
hair-catches, and snow tracking. Simulation results indicate existing
models that assume that methods independently detect organisms produce
biased parameter estimates and substantially understate estimate
uncertainty when this assumption is violated, while our reformulated
models are robust to either methodological independence or covariance.
Empirical results suggested that remote-cameras and snow-tracking had
comparable probability of detecting present martens, but that
snow-tracking also produced false-positive marten detections that could
potentially substantially bias distribution estimates if not corrected
for. Remote cameras detected marten individuals more readily than passive
hair-catches. Inability to photographically distinguish individual sex did
not appear to induce negative bias in camera density estimates; instead,
hair-catches appeared to produce detection competition between individuals
that may have been a source of negative bias. Our model reformulations
broaden the range of circumstances in which analyses incorporating
multiple sources of information can be robustly used, and our empirical
results demonstrate that using multiple field-methods can enhance
inferences regarding ecological parameters of interest and improve
understanding of how reliably survey methods sample these parameters.