Accounting for detectability improves estimates of species richness in tropical bat surveys

Testing the effectiveness of surveying techniques in determining bat community composition within woodland

Context Determining the biodiversity of an area is essential for making targeted conservation decisions. Undertaking surveys to confirm species presence or to estimate population sizes can be difficult, particularly for elusive species. Bats are able to detect and avoid traps, making it difficult to quantify abundance. Although acoustic surveys using bat detectors are often used as a surrogate for relative abundance, the implicit assumption that there is a positive correlation between activity levels and abundance is rarely tested. Aims We assessed the effectiveness of surveying techniques (i.e. trapping and acoustic monitoring) for detecting species presence and tested the strength of collinearity among methods. In addition, we tested whether the use of an acoustic lure (a bat-call synthesiser) increased bat-capture rate and therefore species detectability. Methods Surveying was carried out over 3 years in central Scotland (UK), in 68 woodlands within predominantly agricultural or urban landscapes. Key results There was a significant positive relationship between bat activity recorded on ultrasonic detectors and the relative abundance of Pipistrellus pygmaeus and P. pipistrellus, but not those in the genus Myotis. In general, acoustic monitoring was more effective than trapping at determining species presence; however, to ensure rarer or quiet species are recorded, a complementary approach is required. Broadcasting four different types of echolocation call resulted in a 2–12-fold increase in trapping success across four species of insectivorous bat found in the study region. Whereas lure effectiveness remained unchanged for female P. pygmaeus over time, there was a marked increase in the number of males captured using the lure throughout the summer (May to September). Conclusions In the present study, we have demonstrated a variety of ways to increase surveying efficiency, which can maximise the knowledge of diversity in an area, minimise wildlife disturbance, and enhance surveying effectiveness. Implications Increasing surveying efficiency can improve the accuracy of targeted conservation decisions.

Assessing the status and trend of bat populations across broad geographic regions with dynamic distribution models

Bats face unprecedented threats from habitat loss, climate change, disease, and wind power development, and populations of many species are in decline. A better ability to quantify bat population status and trend is urgently needed in order to develop effective conservation strategies. We used a Bayesian autoregressive approach to develop dynamic distribution models for Myotis lucifugus, the little brown bat, across a large portion of northwestern USA, using a four-year detection history matrix obtained from a regional monitoring program. This widespread and abundant species has experienced precipitous local population declines in northeastern USA resulting from the novel disease white-nose syndrome, and is facing likely range-wide declines. Our models were temporally dynamic and accounted for imperfect detection. Drawing on species-energy theory, we included measures of net primary productivity (NPP) and forest cover in models, predicting that M. lucifugus occurrence probabilities would covary positively along those gradients. Despite its common status, M. lucifugus was only detected during -50% of the surveys in occupied sample units. The overall naive estimate for the proportion of the study region occupied by the species was 0.69, but after accounting for imperfect detection, this increased to -0.90. Our models provide evidence of an association between NPP and forest cover and M. lucifugus distribution, with implications for the projected effects of accelerated climate change in the region, which include net aridification as snowpack and stream flows decline. Annual turnover, the probability that an occupied sample unit was a newly occupied one, was estimated to be low (-0.04-0.14), resulting in flat trend estimated with relatively high precision (SD = 0.04). We mapped the variation in predicted occurrence probabilities and corresponding prediction uncertainty along the productivity gradient. Our results provide a much needed baseline against which future anticipated declines in M. lucifugus occurrence can be measured. The dynamic distribution modeling approach has broad applicability to regional bat monitoring efforts now underway in several countries and we suggest ways to improve and expand our grid-based monitoring program to gain robust insights into bat population status and trend across large portions of North America.