A stochastic simulation model for assessing the masking effects of road noise for wildlife, outdoor recreation, and bioacoustic monitoring.

Traffic noise is one of the leading causes of reductions in animal abundances near roads. Acoustic masking of conspecific signals and adventitious cues is one mechanism that likely causes animals to abandon loud areas. However, masking effects can be difficult to document in situ and the effects of infrequent noise events may be impractical to study. Here, we present the Soundscapes model, a stochastic individual-based model that dynamically models the listening areas of animals searching for acoustic resources ("searchers"). The model also studies the masking effects of noise for human detections of the searchers. The model is set in a landscape adjacent to a road. Noise produced by vehicles traveling on that road is represented by calibrated spectra that vary with speed. Noise propagation is implemented using ISO-9613 procedures. We present demonstration simulations that quantify declines in searcher efficiency and human detection of searchers at relatively low traffic volumes, fewer than 50 vehicles per hour. Traffic noise is pervasive, and the Soundscapes model offers an extensible tool to study the effects of noise on bioacoustics monitoring, point-count surveys, the restorative value of natural soundscapes, and auditory performance in an ecological context.

Timing and technique impact the effectiveness of road-based, mobile acoustic surveys of bats.

Mobile acoustic surveys are a common method of surveying bat communities. However, there is a paucity of empirical studies exploring different methods for conducting mobile road surveys of bats. During 2013, we conducted acoustic mobile surveys on three routes in north-central Indiana, U.S.A., using (1) a standard road survey, (2) a road survey where the vehicle stopped for 1 min at every half mile of the survey route (called a "start-stop method"), and (3) a road survey with an individual using a bicycle. Linear mixed models with multiple comparison procedures revealed that when all bat passes were analyzed, using a bike to conduct mobile surveys detected significantly more bat passes per unit time compared to other methods. However, incorporating genus-level comparisons revealed no advantage to using a bike over vehicle-based methods. We also found that survey method had a significant effect when analyses were limited to those bat passes that could be identified to genus, with the start-stop method generally detecting more identifiable passes than the standard protocol or bike survey. Additionally, we found that significantly more identifiable bat passes (particularly those of the Eptesicus and Lasiurus genera) were detected in surveys conducted immediately following sunset. As governing agencies, particularly in North America, implement vehicle-based bat monitoring programs, it is important for researchers to understand how variations on protocols influence the inference that can be gained from different monitoring schemes.

Simulations reveal the power and peril of artificial breeding sites for monitoring and managing animals.

Despite common use, the efficacy of artificial breeding sites (e.g., nest boxes, bat houses, artificial burrows) as tools for monitoring and managing animals depends on the demography of target populations and availability of natural sites. Yet, the conditions enabling artificial breeding sites to be useful or informative have yet to be articulated. We use a stochastic simulation model to determine situations where artificial breeding sites are either useful or disadvantageous for monitoring and managing animals. Artificial breeding sites are a convenient tool for monitoring animals and therefore occupancy of artificial breeding sites is often used as an index of population levels. However, systematic changes in availability of sites that are not monitored might induce trends in occupancy of monitored sites, a situation rarely considered by monitoring programs. We therefore examine how systematic changes in unmonitored sites could bias inference from trends in the occupancy of monitored sites. Our model also allows us to examine effects on population levels if artificial breeding sites either increase or decrease population vital rates (survival and fecundity). We demonstrate that trends in occupancy of monitored sites are misleading if the number of unmonitored sites changes over time. Further, breeding site fidelity can cause an initial lag in occupancy of newly installed sites that could be misinterpreted as an increasing population, even when the population has been continuously declining. Importantly, provisioning of artificial breeding sites only benefits populations if breeding sites are limiting or if artificial sites increase vital rates. There are many situations where installation of artificial breeding sites, and their use in monitoring, can have unintended consequences. Managers should therefore not assume that provision of artificial breeding sites will necessarily benefit populations. Further, trends in occupancy of artificial breeding sites should be interpreted in light of potential changes in the availability of unmonitored sites and the potential of lags in occupancy owing to site fidelity.

SEARCH: Spatially Explicit Animal Response to Composition of Habitat.

Complex decisions dramatically affect animal dispersal and space use. Dispersing individuals respond to a combination of fine-scale environmental stimuli and internal attributes. Individual-based modeling offers a valuable approach for the investigation of such interactions because it combines the heterogeneity of animal behaviors with spatial detail. Most individual-based models (IBMs), however, vastly oversimplify animal behavior and such behavioral minimalism diminishes the value of these models. We present program SEARCH (Spatially Explicit Animal Response to Composition of Habitat), a spatially explicit, individual-based, population model of animal dispersal through realistic landscapes. SEARCH uses values in Geographic Information System (GIS) maps to apply rules that animals follow during dispersal, thus allowing virtual animals to respond to fine-scale features of the landscape and maintain a detailed memory of areas sensed during movement. SEARCH also incorporates temporally dynamic landscapes so that the environment to which virtual animals respond can change during the course of a simulation. Animals in SEARCH are behaviorally dynamic and able to respond to stimuli based upon their individual experiences. Therefore, SEARCH is able to model behavioral traits of dispersing animals at fine scales and with many dynamic aspects. Such added complexity allows investigation of unique ecological questions. To illustrate SEARCH's capabilities, we simulated case studies using three mammals. We examined the impact of seasonally variable food resources on the weight distribution of dispersing raccoons (Procyon lotor), the effect of temporally dynamic mortality pressure in combination with various levels of behavioral responsiveness in eastern chipmunks (Tamias striatus), and the impact of behavioral plasticity and home range selection on disperser mortality and weight change in virtual American martens (Martes americana). These simulations highlight the relevance of SEARCH for a variety of applications and illustrate benefits it can provide for conservation planning.