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Remote cameras are a common method for surveying wildlife and recently have been promoted for implementing large‐scale regional biodiversity monitoring programs. The use of camera‐trap data depends on the correct identification of animals captured in the photographs, yet misidentification rates can be high, especially when morphologically similar species co‐occur, and this can lead to faulty inferences and hinder conservation efforts. Correct identification is dependent on diagnosable taxonomic characters, photograph quality, and the experience and training of the observer. However, keys rooted in taxonomy are rarely used for the identification of camera‐trap images and error rates are rarely assessed, even when morphologically similar species are present in the study area. We tested a method for ensuring high identification accuracy using two sympatric and morphologically similar chipmunk (Neotamias) species as a case study. We hypothesized that the identification accuracy would improve with use of the identification key and with observer training, resulting in higher levels of observer confidence and higher levels of agreement among observers. We developed an identification key and tested identification accuracy based on photographs of verified museum specimens. Our results supported predictions for each of these hypotheses. In addition, we validated the method in the field by comparing remote‐camera data with live‐trapping data. We recommend use of these methods to evaluate error rates and to exclude ambiguous records in camera‐trap datasets. We urge that ensuring correct and scientifically defensible species identifications is incumbent on researchers and should be incorporated into the camera‐trap workflow. Misidentification of animals in camera‐trap data can be high even among experts, compromising its utility. We tested a method for ensuring high identification accuracy using two sympatric and morphologically similar chipmunk (Neotamias) species as a case study. We recommend use of these methods to evaluate error rates and to remove ambiguous records in camera‐trap datasets, and we urge that ensuring correct and scientifically defensible species identifications is incumbent on researchers and should be incorporated into the camera‐trap workflow.

Anthropogenic global change is impacting the evolutionary potential of biodiversity in ways that have been difficult to predict. Distinct evolutionary units within species may respond differently to the same environmental trends, reflecting unique geography, ecology, adaptation, or drift. Least shrews (Cryptotis parvus group) have a widespread distribution across North America, yet systematic relationships and ongoing evolutionary processes remain unresolved. Westernmost peripheral populations have been prioritized for conservation, but little is known of their evolutionary histories or population trajectories. The broad range of this group of species is coincident with many other temperate taxa, presenting a hypothesis that diversification of least shrews follows a repeated process through the Pleistocene, leading to regionally diagnosable conservation units. We use genomic data and niche modeling to delimit species and conservation units of least shrews. Our results show that least shrews warrant recognition as multiple distinct species, along with geographically discrete infraspecific lineages of C. parvus (sensu stricto). Western peripheral populations are evolutionarily distinct based on nuclear, but not mitochondrial data, possibly reflecting mitochondrial capture during the last glacial phase. This population represents a relict conservation unit, consistent with both an “adaptive unit” and “management unit” based on non‐neutral and neutral divergence, respectively. Hindcast niche modeling supports growing evidence for a shared process of diversification among co‐distributed biota, and forecast modeling suggests continued future loss of suitable environmental niche in peripheral regions. Given mito‐nuclear discordance among samples of parapatric lineages, future environmental perturbation may continue to impact the genomic integrity of important conservation units, making ecological and genomic monitoring a critical need. Least shrews, distributed widely across North America and Mesoamerica, remain an enigmatic group in terms of their evolutionary history, biogeography, and ongoing responses to environmental change. Under a phylogenomic framework using reduced representation genome data, we investigated these dynamics across multiple scales of analysis. We found that the current taxonomy is in need of revision and provide updated nomenclature, systematic relationships, and conservation implications. This group provides a clear demonstration of diagnosable diversification across this vast study area.

Hibernation is a key life history feature that can impact many other crucial aspects of a species' biology, such as its survival and reproduction. I examined the timing of hibernation and reproduction in the federally endangered New Mexico meadow jumping mouse (Zapus hudsonius luteus), which occurs across a broad range of latitudes and elevations in the American Southwest. Data from museum specimens and field studies supported predictions for later emergence and shorter active intervals in montane populations relative to lower elevation valley populations. A low-elevation population located at Bosque del Apache National Wildlife Refuge (BANWR) in the Rio Grande valley was most similar to other subspecies of Z. hudsonius: the first emergence date was in mid-May and there was an active interval of 162 days. In montane populations of Z. h. luteus, the date of first emergence was delayed until mid-June and the active interval was reduced to ca 124-135 days, similar to some populations of the western jumping mouse (Z. princeps). Last date of immergence into hibernation occurred at about the same time in all populations (mid to late October). In montane populations pregnant females are known from July to late August and evidence suggests that they have a single litter per year. At BANWR two peaks in reproduction were expected based on similarity of active season to Z. h. preblei. However, only one peak was clearly evident, possibly due to later first reproduction and possible torpor during late summer. At BANWR pregnant females are known from June and July. Due to the short activity season and geographic variation in phenology of key life history events of Z. h. luteus, recommendations are made for the appropriate timing for surveys for this endangered species.

Species distribution models (SDMs) use presence records to determine the relationship between species occurrence and various environmental variables to create predictive maps describing the species' distribution. The Oscura Mountains Colorado chipmunk (Neotamias quadrivittatus oscuraensis) occurs in central New Mexico and is of conservation concern due to its relict distribution and threats to habitat. We previously created an occupancy model for this taxon, but were concerned that the model may not have adequately captured the ecological factors influencing the chipmunk's distribution because of the data hungry nature of occupancy modeling. MaxEnt is another SDM method that is particularly effective at testing large numbers of variables and handling small sample sizes. Our goal was to create a MaxEnt model for the Oscura Mountains Colorado chipmunk and to compare it with our previous occupancy model for this taxon, either to strengthen our original assessment of the relevant ecological factors or identify additional factors that were not captured by our occupancy model. We created MaxEnt models using occurrence records from baited camera traps and opportunistic surveys. We adjusted model complexity using a novel method for tuning both the regularization multiplier and feature class parameters while also performing variable selection. We compared the distribution maps and variables selected by MaxEnt to the results of our occupancy model for this taxon. The MaxEnt and occupancy models selected similar environmental variables and the overall spatial pattern of occurrence was similar for each model. Likelihood of occurrence was positively related to elevation, piñon woodland vegetation type, and topographic variables associated with escarpments. The overall similarities between the MaxEnt and occupancy models increased our confidence of the ecological factors influencing the distribution of the chipmunk. We conclude that MaxEnt offers advantages for predicting the distribution of rare species, which can help inform conservation actions.

Aim The Mexican long‐tongued bat (Choeronycteris mexicana), Mexican long‐nosed bat (Leptonycteris nivalis) and lesser long‐nosed bat (Leptonycteris yerbabuenae) (Phyllostomidae: Glossophaginae) undertake long‐distance migrations from south‐central Mexico to the south‐western United States. It is proposed that these bats migrate along a nectar corridor of columnar cacti and Agave species, but this has not been tested with independent data and the spatiotemporal nature of this relationship is poorly understood. Our goal was to test this nectar corridor hypothesis and determine the relative importance of food plant and abiotic variables to the distribution and seasonal movements of these migratory nectarivores. Location Mexico and the south‐western United States. Methods We generated species distribution models (SDMs) of documented food plants for these bats. We then created SDMs for each bat following a model selection approach, using food plant and abiotic predictor variables. We modelled migration pathways for C. mexicana and L. yerbabuenae using circuit theory and seasonal SDMs based on seasonally available food plants. Main conclusions Food plants were more important than climatic and topographic variables in shaping the distribution of these bats. The most important predictors of distribution were Agave, columnar cacti and species richness of food plants. Species richness of food plants was the most consistently important variable, but the components of this diversity varied by bat species: Choeronycteris mexicana was influenced by Agave and cacti; Leptonycteris nivalis was influenced solely by Agave; Leptonycteris yerbabuenae was influenced more generally by cacti, Agave and C3 plants. Migration models for C. mexicana and L. yerbabuenae provided independent support for the nectar corridor hypothesis and indicate shifts in relative importance of specific food plants throughout the year. These results suggest that conservation of these bats should focus more broadly on management for species richness of food plants, especially in tropical dry forests.

Habitat information for small mammals typically consists of anecdotal descriptions or infrequent analyses of habitat use, which often are reported erroneously as signifying habitat preference, requirements, or quality. Habitat preferences can be determined only by analysis of habitat selection, a behavioral process that results in the disproportionate use of one resource over other available resources and occurs in a hierarchical manner across different environmental scales. North American chipmunks (Neotamias and Tamias) are a prime example of the lack of studies on habitat selection for small mammal species. We used the Organ Mountains Colorado chipmunk (N. quadrivittatus australis) as a case study to determine whether previous descriptions of habitat in the literature were upheld in a multiscale habitat selection context. We tracked VHF radiocollared chipmunks and collected habitat information at used and available locations to analyze habitat selection at three scales: second order (i.e., home range), third order (i.e., within home range), and microhabitat scales. Mean home range was 2.55 ha ± 1.55 SD and did not differ between sexes. At the second and third order, N. q. australis avoided a coniferous forest land cover type and favored particular areas of arroyos (gullies) that were relatively steep-sided and greener and contained montane scrub land cover type. At the microhabitat scale, chipmunks selected areas that had greater woody plant diversity, rock ground cover, and ground cover of coarse woody debris. We concluded that habitat selection by N. q. australis fundamentally was different from descriptions of habitat in the literature that described N. quadrivittatus as primarily associated with coniferous forests. We suggest that arroyos, which are unique and rare on the landscape, function as climate refugia for these chipmunks because they create a cool, wet microclimate. Our findings demonstrate the importance of conducting multiscale habitat selection studies for small mammals to ensure that defensible and enduring habitat information is available to support appropriate conservation and management actions.

We report the first observations of feeding behavior by free-ranging New Mexico meadow jumping mice (Zapus hudsonius luteus). We made observations during a radiotelemetry study of Z. h. luteus in the floodplain of the Rio Grande at Bosque del Apache National Wildlife Refuge, Socorro Co., New Mexico, in 2009 and 2010. We observed Z. h. luteus eat the achenes or seeds of the order Cyperales: common threesquare (Schoenoplectus pungens), spikerush (Eleocharis spp.), saltgrass (Distichlis spicata), foxtail barley (Hordeum jubatum), Saunder's wildrye (Elymus saundersii), Japanese brome (Bromus japonicus), slender wheatgrass (Elymus trachycaulus), and knotgrass (Paspalum distichum). Mice frequently foraged 0.5–1 m above the ground in the canopy of herbaceous vegetation. Seed heads for consumption were harvested in several ways.

The Oscura Mountains Colorado chipmunk (Neotamias quadrivittatus oscuraensis) is a rare subspecies of the Colorado chipmunk that is listed as threatened by the state of New Mexico, primarily because it is an endemic subspecies with a small, isolated habitat and the potential for continuing habitat loss. Knowledge about its ecology is limited, which has hindered the development of scientifically defensible management plans. Our goal was to better understand the ecological factors related to the distribution and habitat selection of this chipmunk. We deployed baited camera traps in the Oscura Mountains, New Mexico, USA, using an occupancy modeling framework to determine which ecological factors are associated with occupancy and detection probability. We collected microhabitat and landscape-level data for use as covariates in the occupancy models. We detected the Oscura Mountains chipmunk at 26 of the 137 survey sites. Occupancy probability was not influenced by the microhabitat characteristics measured and the final model contained only landscape-level covariates on occupancy. Probability of occupancy was positively associated with proximity to an escarpment, two-needle pinyon (Pinus edulis) woodland vegetation community type, and elevation. Detection probability was positively associated with the presence of mature two-needle pinyons at the site. Habitat loss is a major concern for this taxon, especially because climate change is expected to exacerbate threats to pinyon woodlands. Drought, wildfire, bark beetle (Ips confusus) outbreaks, and other diseases pose a large risk to conifer woodlands throughout the southwestern United States. Conserving the pinyon woodlands on the Oscura Mountains, particularly in areas near escarpments, will help maintain habitat that is important for the Oscura Mountains chipmunk.

Noninvasive survey methods may be necessary when studying rare species or when site conditions are likely to result in unintended mortalities during conventional live trapping. Traditional noninvasive methods based on visual and auditory observations, such as stationary point and roaming, time-constrained area surveys, may be prone to error. Remote cameras are primarily used with large mammals but have increasingly been applied to small mammals. We compared survey methods for a rare subspecies of the Colorado chipmunk (Neotamias quadrivittatus oscuraensis) occurring in a remote mountain range in New Mexico using stationary point surveys; roaming, time-constrained area surveys; and remote-camera survey methods. We detected chipmunks at substantially more locations using remote cameras (13%–23%) versus surveys using visual and auditory cues at stationary points (2.6%) or roaming within 2.7-ha plots (5.6%). In addition, remote cameras have additional strengths, such as reducing the risk of false positive and false negative results as well as providing verifiable and archivable evidence that can be used to corroborate study results.

Species distributions are usually inferred from occurrence records. However, these records are prone to errors in spatial precision and reliability. Although influence of spatial errors has been fairly well studied, there is little information on impacts of poor reliability. Reliability of an occurrence record can be influenced by characteristics of the species, conditions during the observation, and observer’s knowledge. Some studies have advocated use of anecdotal data, while others have advocated more stringent evidentiary standards such as only accepting records verified by physical evidence, at least for rare or elusive species. Our goal was to evaluate the influence of occurrence records with different reliability on species distribution models (SDMs) of a unique mammal, the white-nosed coati (Nasua narica) in the American Southwest. We compared SDMs developed using maximum entropy analysis of combined bioclimatic and biophysical variables and based on seven subsets of occurrence records that varied in reliability and spatial precision. We found that the predicted distribution of the coati based on datasets that included anecdotal occurrence records were similar to those based on datasets that only included physical evidence. Coati distribution in the American Southwest was predicted to occur in southwestern New Mexico and southeastern Arizona and was defined primarily by evenness of climate and Madrean woodland and chaparral land-cover types. Coati distribution patterns in this region suggest a good model for understanding the biogeographic structure of range margins. We concluded that occurrence datasets that include anecdotal records can be used to infer species distributions, providing such data are used only for easily-identifiable species and based on robust modeling methods such as maximum entropy. Use of a reliability rating system is critical for using anecdotal data.