Temporally Adaptive Sampling: A Case Study in Rare Species Survey Design with Marbled Salamanders (Ambystoma opacum)

Abstract

Improving detection rates for elusive species with clumped distributions is often accomplished through adaptive sampling designs. This approach can be extended to include species with temporally variable detection probabilities. By concentrating survey effort in years when the focal species are most abundant or visible, overall detection rates can be improved. This requires either long-term monitoring at a few locations where the species are known to occur or models capable of predicting population trends using climatic and demographic data. For marbled salamanders (Ambystoma opacum) in Massachusetts, we demonstrate that annual variation in detection probability of larvae is regionally correlated. In our data, the difference in survey success between years was far more important than the difference among the three survey methods we employed: diurnal surveys, nocturnal surveys, and dipnet surveys. Based on these data, we simulate future surveys to locate unknown populations under a temporally adaptive sampling framework. In the simulations, when pond dynamics are correlated over the focal region, the temporally adaptive design improved mean survey success by as much as 26% over a non-adaptive sampling design. Employing a temporally adaptive strategy costs very little, is simple, and has the potential to substantially improve the efficient use of scarce conservation funds.

Temporally adaptive acoustic sampling to maximize detection across a suite of focal wildlife species

“…This work contributes novel methodology to the adaptive sampling paradigm for monitoring wildlife. The bulk of research on adaptive sampling of wildlife is focused on sampling in the spatial dimension (e.g., Thompson, White, & Gowan, ; Thompson, ; Turk & Borkowski, ), while temporal adaptive sampling has not been explicitly explored in great depth (though see Charney, Kubel, & Eiseman, ; Dyo et al, ). Recent work on the optimization of survey effort over space and time (Moore & McCarthy, ), and when species detectability varies (Moore, McCarthy, Parris, & Moore, ), explicitly incorporates the opportunity cost incurred by researchers when traveling to a field site for sampling; conceptually, the travel cost parameter may be framed as an analog to the costs of wireless data plans in remote acoustic recording units.…”

“…Recent work on the optimization of survey effort over space and time (Moore & McCarthy, ), and when species detectability varies (Moore, McCarthy, Parris, & Moore, ), explicitly incorporates the opportunity cost incurred by researchers when traveling to a field site for sampling; conceptually, the travel cost parameter may be framed as an analog to the costs of wireless data plans in remote acoustic recording units. Additionally, although the notion of time‐sensitive sampling is present in wildlife surveys—for example, by surveying during seasonally appropriate occasions for breeding amphibians, or on spring mornings during the dawn chorus for breeding birds—such sampling is not adaptive in nature unless information from prior surveys is incorporated into future sampling efforts (Charney et al, ; Thompson & Seber, ).…”

“…For other circumstances, temporally adaptive sampling may enable monitoring that might otherwise have been impossible This work contributes novel methodology to the adaptive sampling paradigm for monitoring wildlife. The bulk of research on adaptive sampling of wildlife is focused on sampling in the spatial dimension (e.g., Thompson, White, & Gowan, 1998;Thompson, 2004;Turk & Borkowski, 2005), while temporal adaptive sampling has not been explicitly explored in great depth (though see Charney, Kubel, & Eiseman, 2015;Dyo et al, 2012). Recent work on the optimization of survey effort over space and time (Moore & McCarthy, 2016), and when species detectability varies (Moore, McCarthy,…”

“…Additionally, although the notion of time-sensitive sampling is present in wildlife surveys-for example, by surveying during seasonally appropriate occasions for breeding amphibians, or on spring mornings during the dawn chorus for breeding birds-such sampling is not adaptive in nature unless information from prior surveys is incorporated into future sampling efforts (Charney et al, 2015;Thompson & Seber, 1994).…”

Peer Review #1 of "Using historical dip net data to infer absence of flatwoods salamanders in stochastic environments (v0.1)"

“…In some cases, the repercussions of failing to detect an organism are considerably more severe than incorrectly documenting a presence, i.e., false negatives are more problematic than false positives (Hauser & McCarthy, 2009;Charney, Kubel & Eiseman, 2015;Veale & Russello, 2016). Conservation reintroductions are a useful example of the risk imbalance between type-1 and type-2 errors.…”