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Global expansion of human activities is associated with the introduction of novel stimuli, such as anthropogenic noise, artificial lights and chemical agents. Progress in documenting the ecological effects of sensory pollutants is weakened by sparse knowledge of the mechanisms underlying these effects. This severely limits our capacity to devise mitigation measures. Here, we integrate knowledge of animal sensory ecology, physiology and life history to articulate three perceptual mechanisms—masking, distracting and misleading—that clearly explain how and why anthropogenic sensory pollutants impact organisms. We then link these three mechanisms to ecological consequences and discuss their implications for conservation. We argue that this framework can reveal the presence of ‘sensory danger zones’, hotspots of conservation concern where sensory pollutants overlap in space and time with an organism’s activity, and foster development of strategic interventions to mitigate the impact of sensory pollutants. Future research that applies this framework will provide critical insight to preserve the natural sensory world. Anthropogenic sensory pollutants, such as noise, light and chemicals, are affecting biodiversity. This Perspective uses an understanding of animal sensory ecology to explore how these impacts can be mitigated.

Habitat loss and fragmentation are the leading causes of species range contraction and extirpation, worldwide. Factors that predict sensitivity to fragmentation include high trophic level, large body size, and extensive spatial requirements. Pumas (Puma concolor) exemplify these qualities, making them particularly susceptible to fragmentation and subsequent reductions in demographic connectivity. The chaparral‐dominated ecosystems surrounding the greater San Francisco Bay Area encompass over 10,000 km2 of suitable puma habitat, but inland waterways, croplands, urban land uses, and extensive transportation infrastructure have resulted in widespread habitat fragmentation. Pumas in this region now exist as a metapopulation marked by loss of genetic diversity, collisions with vehicles, and extensive human–puma conflict. Given these trends, we conducted a photo survey from 2017 to 2021 across 19 patches of predicted habitat and compiled a dataset of >6584 puma images. We used a logistic regression analytical framework to evaluate the hypothesis that puma patch occupancy would exhibit a threshold response explained by patch size, isolation, and habitat quality. Contrary to predictions, only variables related to patch size demonstrated any power to explain occupancy. On average, occupied patches were 18× larger than those where they were not detected (825 ± 1238 vs. 46 ± 101 km2). Although we observed pumas in patches as small as 1 km2, logistic regression models indicated a threshold occupancy probability between 300 and 400 km2, which is remarkably close to the mean male puma home range size in coastal California (~381 km2). Puma populations dependent on habitats below this value may be susceptible to inbreeding depression and human–wildlife conflict, and therefore vulnerable to extirpation. For species conservation, we suggest conflicts might be ameliorated by identifying the largest, isolated patches for public education campaigns with respect to management of domestic animals, and remaining connective parcels be identified, mapped, and prioritized for targeted mitigation. This manuscript details efforts to estimate thresholds in habitat patch size predicting the occupancy of pumas (Puma concolor) in a highly fragmented ecosystem around the San Francisco Bay area. We argue that the empirical threshold identified herein corresponds to the mean male home range size of a puma, as measured in the chaparral‐dominated ecosystems of coastal California. Furthermore, this metric may be useful for identifying subpopulations at risk of extirpation. Because of the combined concern over human safety and species conservation the topic is of interest to policy makers and wildlife managers in California and other western jurisdictions.

The effect of climatically-driven plant phenology on mammalian reproduction is one key to predicting species-specific demographic responses to climate change. Large ungulates face their greatest energetic demands from the later stages of pregnancy through weaning, and so in seasonal environments parturition dates should match periods of high primary productivity. Interannual variation in weather influences the quality and timing of forage availability, which can influence neonatal survival. Here, we evaluated macro-scale patterns in reproductive performance of a widely distributed ungulate (mule deer, Odocoileus hemionus) across contrasting climatological regimes using satellite-derived indices of primary productivity and plant phenology over eight degrees of latitude (890 km) in the American Southwest. The dataset comprised > 180,000 animal observations taken from 54 populations over eight years (2004-2011). Regionally, both the start and peak of growing season (\"Start\" and \"Peak\", respectively) are negatively and significantly correlated with latitude, an unusual pattern stemming from a change in the dominance of spring snowmelt in the north to the influence of the North American Monsoon in the south. Corresponding to the timing and variation in both the Start and Peak, mule deer reproduction was latest, lowest, and most variable at lower latitudes where plant phenology is timed to the onset of monsoonal moisture. Parturition dates closely tracked the growing season across space, lagging behind the Start and preceding the Peak by 27 and 23 days, respectively. Mean juvenile production increased, and variation decreased, with increasing latitude. Temporally, juvenile production was best predicted by primary productivity during summer, which encompassed late pregnancy, parturition, and early lactation. Our findings offer a parsimonious explanation of two key reproductive parameters in ungulate demography, timing of parturition and mean annual production, across latitude and changing climatological regimes. Practically, this demonstrates the potential for broad-scale modeling of couplings between climate, plant phenology, and animal populations using space-borne observations.

Dispersal is a complex series of movements before an individual establishes a home range. Animals must travel and forage in unfamiliar landscapes that include anthropogenic risks such as road crossings, harvest, and urban landscapes. We compare dispersal behavior of juvenile mountain lions (Puma concolor) from two geographically distinct populations in California and Nevada, USA. These two sites are ecologically similar but have different management practices; hunting is permitted in Nevada, whereas mountain lions are protected in California. We used GPS‐collar data and net‐squared displacement analysis to identify three dispersal states: exploratory, departure, and transient home range. We then compared each dispersal state of the two mountain lion populations using an integrated step selection analysis (iSSA). The model included explanatory variables hypothesized to influence one or more dispersal states, including distance to forest, shrub, water, hay and crop, developed lands, and four‐wheel drive roads, as well as elevation and terrain ruggedness. Results revealed consistent habitat selection between sites across most landscape variables, with one notable exception: anthropogenic covariates, including distance to developed land, distance to hay and crop, and distance to four‐wheeled drive roads, were only statistically significant on modeled habitat selection during dispersal in the population subject to hunting (i.e., Nevada). Results suggest that hunting (pursuit with hounds resulting in harvest) and non‐lethal pursuit (pursuit with hounds but no harvest allowed) increase avoidance of anthropogenic landscapes during dispersal for juvenile mountain lions. By comparing populations, we provided valuable insights into the role of management in shaping dispersal behavior. We compare dispersal behavior of juvenile mountain lions (Puma concolor) from two geographically distinct populations in California and Nevada, USA. Mountain lions selected anthropogenic landscape features differently, suggesting that hunting and non‐lethal pursuit increase avoidance of anthropogenic landscapes during dispersal for juvenile mountain lions.

Non‐native species can affect ecosystems by influencing native predator‐prey dynamics. Therefore, management interventions designed to remove non‐natives may inadvertently lead to increased predation on native species. Feral horses are widely distributed throughout the arid parts of western North America. A growing body of research indicates that horses can be an important prey species to mountain lions in ecosystems where they overlap. In December 2020, the Bureau of Land Management removed 455 horses from the Delamar Mountains, Nevada, USA. We leveraged this management intervention to implement a before–after–control–impact study to test hypotheses about predation on horses and native ungulates. We predicted (1) that horses would comprise an important part of the diet in this mixed‐prey community, (2) following removal, the proportion of horses in the diet would decrease and native ungulates would increase, and (3) mountain lion home ranges overlapping the treatment areas would increase in response to decreased prey availability. From 2018 to 2022, we investigated 1360 clusters from 29 GPS‐collared lions and identified 1056 prey items. To model the probability of a predation event (a kill), we fit a mixed‐effects logistic regression model for ungulate prey as a function of lion sex, treatment area (in/out), and treatment period (pre‐/post‐removal). We used a log‐linear regression model to evaluate changes in home range size. The most common prey were mule deer (55%), feral horses (32%), and coyotes (4%). Twenty‐two of 29 lions consumed horses, although the rate of horse consumption was highly variable across individuals. Horses of both sexes and all age classes were predated. In contrast to predictions, our models detected no effect of removals on diet composition (βinteraction = 0.30 ± 1.1), nor did the removal influence home range size (βinteraction = 0.02 ± 0.02). Despite a 46% reduction in horse abundance, we found no evidence for prey‐switching following the horse removal treatment. Removal magnitude, rapid horse immigration, and/or behavioral specialization of individual mountain lions may help explain these results. Our findings have important implications for mountain lion and feral horse management in arid environments characterized by high prey diversity, but low prey abundance.

Road networks pose many well‐documented threats to wildlife, from fragmenting habitats and restricting movement to causing mortality through vehicle collisions. For large, wide‐ranging mammals, home range requirements and seasonal migrations often necessitate road crossings, posing threats to human safety, property, and animal survival. Artificial nightlight, emanating from light posts and urban sky glow, is ubiquitous on and around road networks worldwide; however, its effects on road crossing behavior and the associated mortality risk for wildlife are not well understood. By integrating the latest NASA nightlight products with GPS collar data collected from 67 mule deer (Odocoileus hemionus) over a 7‐year period (2012–2018), we used a resource‐selection framework to assess factors influencing seasonal crossing behavior and road mortality in Salt Lake City, Utah, an expanding metropolitan area in the United States. We found deer preferred to cross the road where surrounding artificial nightlight was lower in both summer and winter seasons, especially during crepuscular and nighttime periods. However, lower nightlight levels also increased the risk of road mortality. Areas with more shrub cover and lower speed limits increased the likelihood of crossing as well as lowered the risk of road mortality. There were five times as many mortality events in winter as in summer, likely because of the combination of deer preference for dark roads mixed with proximity to both higher speed roads and increased human activity. Better understanding how a pervasive and expanding environmental pollutant like artificial nightlight may attract or repel human‐tolerant wildlife species from roadways presents an opportunity to mitigate collision risk while improving population management strategies for this abundant, generalist herbivore and many other economically and ecologically important species.

The “green wave” hypothesis posits that during spring consumers track spatial gradients in emergent vegetation and associated foraging opportunities. This idea has largely been invoked to explain animal migration patterns, yet the general phenomenon underlies trends in vertebrate reproductive chronology as well. We evaluated the utility of this hypothesis for predicting spatial variation in nest initiation of greater sage‐grouse (Centrocerus urophasianus), a species of conservation concern in western North America. We used the Normalized Difference Vegetation Index (NDVI) to map the green wave across elevation and then compiled dates and locations of >450 sage‐grouse nests from 20 study sites (2000–2014) to model nest initiation as a function of the start of the growing season (SOS), defined here as the maximum daily rate of increase in NDVI. Individual sites were drawn from three ecoregions, distributed over 4.5° latitude, and spanning 2,300 m in elevation, which captured the climatic, edaphic, and floristic diversity of sagebrush ecosystems in the southern half of current sage‐grouse range. As predicted, SOS displayed a significant, positive relationship with elevation, occurring 1.3 days later for each 100 m increase in elevation. In turn, sage‐grouse nest initiation followed SOS by 22 ± 10 days (r2 = .57), with hatch dates falling on or just prior to the peak of the growing season. By timing nesting to the green wave, sage‐grouse chicks hatched when the abundance of protein‐rich invertebrate biomass is hypothesized to be nearing a seasonal high. This adaptation likely represents a strategy for maximizing reproductive success in the arid, variable environments that define sagebrush ecosystems. Given projected changes in climate and land use, these results can be used to predict periods of relative sensitivity to habitat disturbance for sage‐grouse. Moreover, the near real‐time availability of satellite imagery offers a heretofore underutilized means of mapping the green wave, planning habitat restoration, and monitoring range conditions. We tested the hypothesis that sage‐grouse nesting chronology would correspond to the “green wave.” Sage‐grouse nest initiation tracked the start of the growing season (the “green wave”) by 22 ± 10 days, with hatch dates falling on or just prior to the peak of the growing season. This adaptation likely represents a strategy for maximizing reproductive success in the arid and variable environments that define sagebrush ecosystems.

Artificial nightlight is increasingly recognized as an important environmental disturbance that influences the habitats and fitness of numerous species. However, its effects on wide‐ranging vertebrates and their interactions remain unclear. Light pollution has the potential to amplify land‐use change, and as such, answering the question of how this sensory stimulant affects behavior and habitat use of species valued for their ecological roles and economic impacts is critical for conservation and land‐use planning. Here, we combined satellite‐derived estimates of light pollution, with GPS‐data from cougars Puma concolor (n = 56), mule deer Odocoileus hemionus (n = 263) and locations of cougar‐killed deer (n = 1562 carcasses), to assess the effects of light exposure on mammal behavior and predator–prey relationships across wildland–urban gradients in the southwestern United States. Our results indicate that deer used the anthropogenic environments to access forage and were more active at night than their wildland conspecifics. Despite higher nightlight levels, cougars killed deer at the wildland–urban interface, but hunted them in the relatively darkest locations. Light had the greatest effect of all covariates on where cougars killed deer at the wildland–urban interface. Both species exhibited functional responses to light pollution at fine scales; individual cougars and deer with less light exposure increasingly avoided illuminated areas when exposed to greater radiance, whereas deer living in the wildland–urban interface selected elevated light levels. We conclude that integrating estimates of light pollution into ecological studies provides crucial insights into how the dynamic human footprint can alter animal behavior and ecosystem function across spatial scales.

Prey species adjust their behavior along human‐use gradients by balancing risks from predators and humans. During hunting seasons, prey often exhibit strong antipredator responses to humans but may develop tolerance in suburban areas to exploit human‐mediated resources. Additionally, areas with high human activity may offer reduced predation risk if apex predators avoid such locations. This study examined mule deer Odocoileus hemionus behavioral responses to risks from humans and their primary predators, cougars Puma concolor, contextualized by differences in risk levels between study sites, individual risk exposure, and human habituation. We framed our investigation using three non‐mutually exclusive hypotheses: (H1) neutral impact, (H2) human shielding (human tolerance driven by cougar avoidance), and (H3) super‐additive risk (human avoidance dominating behavior). We controlled for deer phenology and diel period, recognizing that deer behavior varies with these temporal dynamics. Spatiotemporal cougar encounter risk was quantified using GPS collar data, while spatiotemporal human encounter risk and use intensity were quantified using GPS smartphone data. Our results supported H2 and H3, emphasizing the significance of site‐ and individual‐level variation in risk exposure and human use intensity. Deer managed cougar risk adaptively, but humans emerged as the dominant perceived risk, varying by study site. At the site with higher cougar density and lower human hunting pressure, deer exhibited antipredator responses to humans based on individual exposure to human activity, except during hunting season, when tolerance for cougars increased. Conversely, humans were the dominant risk at the site with lower cougar density and greater human hunting pressure. Deer behavior varied significantly across a gradient of human use, influenced by nuanced human presence and predation risks, which were discernible using human smartphone data.

Free-roaming equids (i.e., feral horses [Equus caballus] and burros [Equus asinus]) are widely distributed and locally abundant across the rangelands of the western United States. The 1971 Wild Free Roaming Horse and Burro Act (WFRHBA) gave the Bureau of Land Management (BLM) and United States Forest Service (USFS) the legal authority to manage these animals on designated public lands. To fulfill this responsibility, federal agencies established an Appropriate Management Level (AML), defined as the number of horses or burros that can be sustained on a given management unit under prevailing environmental conditions and land uses. Although the WFRHBA specifies that feral equids must be managed in ecological balance with other land uses, including conservation of native wildlife, population control measures such as gathers, contraception, and adoptions have failed to keep pace with intrinsic growth rates. Over 80% of federally managed herds currently exceed prescribed population levels, making the potential for competition between native ungulates and feral equids a growing concern among state wildlife agencies. Mule deer (Odocoileus hemionus), pronghorn (Antilocapra americana), elk (Cervus canadensis), and bighorn sheep (Ovis canadensis) are of ecological and economic value to the states where they occur, and all exhibit some degree of distributional, habitat, or dietary overlap with horses or burros. Notwithstanding the scale of the problem, to date there have been no range-wide assessments of competition potential among native and feral ungulates for space, forage, or water. To address this need, we compiled demographic, jurisdictional, and species occurrence data collected from 2010–2019 by federal and state agencies. We used these data to map the distributions of 4 native ungulate species across federal equid management units (FEMUS) in 10 western states (n=174). We then made within-state rankings of the 50 units that were ≥2 times over AML and encompassed ≥3 native ungulates. Collectively, FEMUs covered approximately 225,000 km², representing 18% of all BLM and USFS lands in affected states. Each FEMU supported ≥1 native ungulate and 14% contained all 4. The degree of overlap between native and feral species varied by state, ranging from 1% for mule deer in Montana, to 40% for bighorn sheep in Nevada. Oregon had the largest proportion of units that supported all 4 native ungulates (58%), whereas Montana and New Mexico had the fewest equids, but all populations were over target densities. Despite the perception that the problem of equid abundance is limited to the Great Basin states, high intrinsic growth rates and social constraints on management practices suggest all affected states should monitor range conditions and native ungulate demography in areas where forage and water resources are limited and expanding equid populations are a concern.