Bryan S. McLean’s research while affiliated with University of North Carolina at Greensboro and other places

Understanding animal movement is at the core of ecology, evolution and conservation science. Big data approaches for animal tracking have facilitated impactful synthesis research on spatial biology and behavior in ecologically important and human-impacted regions. Similarly, databases of animal traits (e.g. body size, limb length, locomotion method, lifespan) have been used for a wide range of comparative questions, with emerging data being shared at the level of individuals and populations. Here, we argue that the proliferation of both types of publicly available data creates exciting opportunities to unlock new avenues of research, such as spatial planning and ecological forecasting. We assessed the feasibility of combining animal tracking and trait databases to develop and test hypotheses across geographic, temporal and biological allometric scales. We identified multiple research questions addressing performance and distribution constraints that could be answered by integrating trait and tracking data. For example, how do physiological (e.g. metabolic rates) and biomechanical traits (e.g. limb length, locomotion form) influence migration distances? We illustrate the potential of our framework with three case studies that effectively integrate trait and tracking data for comparative research. An important challenge ahead is the lack of taxonomic and spatial overlap in trait and tracking databases. We identify critical next steps for future integration of tracking and trait databases, with the most impactful being open and interlinked individual-level data. Coordinated efforts to combine trait and tracking databases will accelerate global ecological and evolutionary insights and inform conservation and management decisions in our changing world.

Amid global challenges like climate change, extinctions, and disease epidemics, science and society require nuanced, international solutions that are grounded in robust, interdisciplinary perspectives and datasets that span deep time. Natural history collections, from modern biological specimens to the archaeological and fossil records, are crucial tools for understanding cultural and biological processes that shape our modern world. At the same time, natural history collections in low and middle-income countries are at-risk and underresourced, imperiling efforts to build the infrastructure and scientific capacity necessary to tackle critical challenges. The case of Mongolia exemplifies the unique challenges of preserving natural history collections in a country with limited financial resources under the thumb of scientific colonialism. Specifically, the lack of biorepository infrastructure throughout Mongolia stymies efforts to study or respond to large-scale environmental changes of the modern era. Investment in museum capacity and training to develop locally-accessible collections that characterize natural communities over time and space must be a key priority for a future where understanding climate scenarios, predicting, and responding to zoonotic disease, making informed conservation choices, or adapting to agricultural challenges, will be all but impossible without relevant and accessible collections.

The “small-eared” species group of Urocitellus ground squirrels (Sciuridae: Xerinae: Marmotini) is endemic to the Great Basin, United States, and surrounding cold desert ecosystems. Most specific and subspecific lineages in this group occupy narrow geographic ranges, and some are of significant conservation concern; despite this, current taxonomy remains largely based on karyotypic or subtle pelage and morphological characteristics. Here, we leverage 2 multilocus DNA sequence data sets and apply formal species delimitation tests alongside morphometric comparisons to demonstrate that the most widespread small-eared species (U. mollis Kennicott, 1863 sensu lato; Piute Ground Squirrel) is comprised of 2 nonsister and deeply divergent lineages. The 2 lineages are geographically separated by the east-west flowing Snake River in southern Idaho, with no sites of sympatry currently known. Based on robust support across the nuclear genome, we elevate populations previously attributed to U. mollis from north of the Snake River to species status under the name Urocitellus idahoensis (Merriam 1913) and propose the common name “Snake River Plains Ground Squirrel” for this taxon. We delimit 2 subspecies within U. idahoensis; U. i. idahoensis (Merriam 1913) in western Idaho and U. i. artemesiae (Merriam 1913) in eastern Idaho. Urocitellus idahoensis is endemic to Idaho and has a maximal range area of roughly 29,700 km2 spanning 22 counties but occurs discontinuously across this area. Our work substantially expands knowledge of ground squirrel diversity in the northern Great Basin and Columbia Plateau and highlights the difficulty in delimiting aridland mammals whose morphological attributes are highly conserved.

Chiggers are larval mites that pose a significant health risk globally via the spread of scrub typhus. However, fundamental studies into the bacterial microbiome in North America have never been considered. In this investigation, chiggers were collected in the wild from two locally common rodent host species (i.e., Sigmodon hispidus and Peromyscus leucopus) in three different ecoregions of North Carolina (NC), United States to investigate the composition of their bacterial communities, including potential pathogens. DNA was extracted from the chiggers, and the V3-V4 regions of the bacterial 16S rRNA gene were sequenced using next-generation sequencing (NGS). Alpha diversity metrics revealed significant differences in bacterial diversity among different collection counties. Beta diversity metrics also revealed that bacterial communities across counties were significantly different, suggesting changes in the microbiome as the environment changed. Specifically, we saw that the two western NC collection counties had similar bacterial composition as did the two eastern collection counties. In addition, we found that the chigger microbiome bacterial diversity and composition differed between rodent host species. The 16S rRNA sequence reads were assigned to 64 phyla, 106 orders, 199 families, and 359 genera. The major bacterial phylum was Actinobacteria. The most abundant species were in the genera Corynebacterium, Propionibacterium, class ZB2, and Methylobacterium. Sequences derived from potential pathogens within the genera Orientia and Rickettsia were also detected. Our findings provide the first insights into the ecology of chigger microbiomes in the US. Further research is required to determine if the potential pathogens found detected in chiggers are a threat to humans and wildlife.

The availability and quality of food resources can alter the intensity of competition and predation pressure within communities. Understanding species capacity to respond to global change‐driven shifts in resource distribution is therefore crucial for biodiversity conservation. Small mammal communities are often structured by competition for food resources, but understanding and monitoring these processes are currently hindered by lack of functional dietary trait information in these hard‐to‐sample systems. In this study, we collected a comprehensive suite of gastrointestinal (GI) measurements from 26 small mammal species (including some never reported), compared them with more traditional craniodental traits in predicting dietary guild, and used them in a novel way to understand how diet structures 22 small mammal communities across the Appalachian Mountains of eastern North America. As predicted, we found GI traits to be effective dietary trait proxies; they were equally or more accurate than craniodental proportions in predicting the dietary guild of individual species. Furthermore, at the community level, we found that both the mean and functional dispersion of GI length were positively correlated with latitude and measures of temperature seasonality. Our results indicate that small mammal communities in more seasonal environments are filtered to include species with longer GI tracts (on average) as well as those that can partition food resources more finely, as expected based on the lower productivity of these regions. Conversely, communities in less seasonal environments display functional redundancy from the addition of species with short to intermediate GI lengths. Proportions of the GI tract represent novel dietary traits that can illuminate community assembly processes across regional environmental gradients and in the face of changing timing and availability of resources.

Understanding animal movement is at the core of ecology, evolution, and conservation science. Big data approaches for animal tracking have facilitated impactful synthesis research on spatial biology and behavior in ecologically important and human-impacted regions. Similarly, databases of animal traits (e.g., body size, limb length, locomotion method, lifespan) have been used for a wide range of comparative questions, with emerging data being shared at the levels of individuals and populations. Here, we argue that the proliferation of both types of publicly available data creates exciting opportunities to unlock new avenues of research, such as spatial planning and ecological forecasting, across a diverse range of species. We assessed the feasibility of combining animal tracking and trait databases to develop and test hypotheses across geographic, temporal, and biological allometric scales. We identified multiple research questions addressing performance and distribution constraints that could be answered by integrating trait and tracking data. For example, how do physiological (e.g., metabolic rates) and biomechanical traits (e.g., limb length, locomotion form) influence migration distances? How does habitat type influence movement metrics such as speed and energetic cost? We illustrate the potential of our framework with three case studies that effectively integrate trait and tracking data for comparative research. An important challenge ahead is the lack of taxonomic and spatial overlap in trait and tracking databases. We identify critical next steps for future integration of tracking and trait databases, with the most impactful being open and interlinked individual-level data. Coordinated efforts to combine trait and tracking databases will accelerate global ecological and evolutionary insights and inform conservation and management decisions in our changing world.

The digitization and open availability of life history traits measured directly from individuals provide a key means of linking organismal function to environmental and ecological contexts at fine resolution. These linkages play a critical role in understanding trait‐mediated response to global change, with particular need to resolve them for taxa that are secretive and hard to monitor, like most mammals. In this study, we use digitized museum specimen and census data to document how climate and body size each shape a key life history trait – litter size – in 39 small mammals across North America. We employ mixed models to test associations between litter size, climate and body size, with a focus on joint estimation of inter‐ and intraspecific trends. Among species, no single climate predictor explained a large amount of litter size variation. Instead, interactions between temperature‐related (continentality, solar irradiation) and moisture‐related (annual precipitation, relative humidity) indices, along with body size, exert a stronger influence on litter size. We observed maximal litter sizes for species inhabiting seasonal or xeric regions under conditions of increased moisture availability, or conversely, mesic or aseasonal regions under conditions of reduced moisture availability. These patterns are consistent with primary productivity as a mechanistic driver of litter size. At the intraspecific level, litter size responds to continentality and temperature‐related indices experienced by populations, but is most strongly shaped by body size of individual females. We also find evidence of phylogenetic covariation in these intraspecific trends. Our study demonstrates how life history traits assembled from individual‐level biodiversity records improve precision and granularity of ecological studies, help to parse among‐ and within‐species trends, and foster improved understanding of tradeoffs between energetic supply and demand (e.g. reproduction) in wild mammals.

Functional traits are phenotypic characteristics that contribute to fitness of individuals in dynamic and changing environments. In mammals, both categorical and continuous (e.g., quantitative) functional traits have been extensively utilized as proxies for diet, locomotion, and other aspects of species ecology, but there has been less focus on form and function of soft tissues. This is particularly true for the digestive system, which varies in size and complexity across Class Mammalia and plays a major role in the energetics of species. To guide more effective utilization of gastrointestinal (GI) morphology as a functional proxy in small mammal ecology, we examined how GI tracts (lengths and masses of four GI sections) varied within a population of deer mice (Peromyscus maniculatus) in the Southern Appalachian Mountains of North Carolina, United States. We collected samples of adult P. maniculatus monthly for 1 year and measured GI tracts to quantify variation with respect to seasonality and trophic level, providing insight into plasticity in this soft tissue trait over time. We found that season had a significant effect on the total length and wet mass of the GI tract, with January mice having the longest GI tracts and lengths being shortest in the summer. The relative shortening of the GI tract in summer corresponded with a partial trophic increase detected by stable isotope signatures. GI length and wet mass also were affected by reproduction, but males and females responded in sex-specific ways to demands of reproduction, with reproductively active males having shorter and lighter GI tracts than nonreproductively active males. Our study provides proof-of-concept for understanding population-level plasticity in a rarely collected soft tissue trait, which may also be complementary to standard craniodental measurements as a functional dietary proxy to understand mammalian ecology and community assembly.

Effects of global climate change on population persistence are often mediated by life‐history traits of individuals, especially the timing of somatic growth, reproductive development, and reproduction itself. These traits can vary among age groups and between the sexes, a result of differential life‐history tactics and levels of lifetime reproductive investment. Unfortunately, the trait data necessary for revealing sex‐specific breeding behaviors and use of breeding cues over reasonably large geographic areas remain sparse for most taxa. In this study, we assembled and analyzed a new reproductive trait base for the North American deer mouse (Peromyscus maniculatus) from digitized natural history specimens and field censuses. We used the data to reconstruct sex‐specific breeding phenologies and their drivers within and among North American ecoregions. Male and female phenologies varied across the geographic range of this species, with discordance in timing and intensity being highest in regions of lower seasonality (and longer breeding seasons). Reliance on environmental variables as breeding cues also appeared to vary in a sex‐specific manner, being most similar for photoperiod and least similar for temperature (positive male response and negative female response); in addition, model validation indicated that phenological models generalized better for males than for females. Finally, our individual‐level trait data also show that male reproductive investment (quantified as relative testis size) varies across the vastly different abiotic and social (i.e., female breeding) contexts studied here. By harmonizing across a broad set of digital data resources, we demonstrate the potential to uncover drivers of phenological variation within species and inform global change predictions at multiple scales of biological organization.