Sarah Louise Carroll

Expanding human activities increasingly influence animal movement. Yet, conservation interventions often overlook intraspecific variation in how movement is structured across populations inhabiting distinct ecosystems. For wide‐ranging generalists such as African savanna elephants ( Loxodonta africana ), understanding how responses to resource availability and anthropogenic pressure vary across populations is critical for effective conservation planning. Here, we analyze long‐term GPS tracking data from 175 African elephants to contrast how movement is structured across mesic (Mara–Serengeti) and xeric (Samburu–Laikipia) savannas in East Africa. We delineate the landscape of elephant movement (a “movescape”), using a network‐based approach that integrates movement path, use intensity, and connectivity metrics to describe how animals use discrete locations for different functions. We focused on identifying highly used areas and movement corridors, then used mixed‐effects spatial regressions to evaluate how environmental context influenced the occurrence of these areas within and across ecosystems. All analyses in Mara–Serengeti represent a new application of this framework and are compared with previously published results from Samburu–Laikipia. Elephant movement structure differed between ecosystems. In the Mara–Serengeti, movement networks were dense and clustered, with more locations used repeatedly and connected by redundant pathways. Movement in Samburu–Laikipia was more spatially dispersed. Most locations were used by elephants with low intensity, and connectivity was concentrated in fewer corridors. Across both ecosystems, core‐use areas comprised a small proportion of the landscape, highlighting locations where conservation efforts could be targeted in unprotected areas. In the Mara–Serengeti, elephants concentrated use in areas with low boma density and away from villages. In Samburu–Laikipia, core areas and corridors were strongly associated with permanent water and consistent vegetation productivity, likely reflecting more ecological constraints on movement. Conservation planning in the Mara–Serengeti could prioritize riparian woodlands and bush thickets on hillsides to protect connectivity between core elephant areas. In Samburu–Laikipia, protecting existing limited corridors that provide access to seasonally productive forage and access to permanent natural water sources could be effective. Our combined delineation of core‐use areas and the corridors that link them provides a framework for prioritizing both core habitat patches and the movement pathways that sustain landscape‐scale connectivity.

Translocations have been widely used to restore and conserve bighorn sheep ( Ovis canadensis ) populations in North America. Some translocations have been successful, but many populations remain small and genetically isolated. Population structure can influence the viability and long‐term success of reintroductions. Social ungulates often function as interconnected subpopulations (metapopulations); however, few studies evaluate subpopulation sizes, connectivity, and genetic diversity within metapopulations. To address this gap, we conducted a comprehensive study of a reintroduced Rocky Mountain bighorn sheep ( Ovis canadensis canadensis ) population in Dinosaur National Monument in Colorado and Utah, USA, between 2006–2020. We analyzed global positioning system (GPS) radio‐collar data, genetic samples, and results of health testing to evaluate abundance, distribution, genetic structure and diversity, habitat use, movement and connectivity, and presence of or exposure to respiratory pathogens. We integrated these analyses to evaluate the outcomes of a reintroduction effort that began in 1952, over 70 years ago, and to inform management decisions in Dinosaur National Monument. We also provide a framework for evaluating metapopulation processes, including a non‐invasive approach that links genetic structure with Bayesian spatial capture‐recapture analyses to estimate subpopulation sizes. Despite models indicating continuous suitable habitat, we found a spatially structured population with at least 4 subpopulations with constrained connectivity. Evidence from step selection and density analyses suggested that movement among subpopulations may be limited by semi‐permeable barriers including rivers and human disturbance, which could contribute to maintenance of spatial structure over time. In 2006, antibody to Mycoplasma ovipneumoniae was detected in all geographically and genetically distinct subpopulations. Widespread clinical signs of disease and a confirmed exposure to M. ovipneumoniae in 2019 indicate a long‐term disease challenge. Proximity to domestic sheep creates repeated opportunities for introduction of new M. ovipneumoniae strains. We estimated abundance in 2019 at 109 (95% CrI = 87–133), composed of subpopulations ranging from 18–39 animals (95% CrIs from 11–50). Genetic diversity was relatively high compared to other reintroduced and native Rocky Mountain bighorn sheep populations, which is likely a consequence of multiple translocations from different sources. Three of 4 subpopulation centers generally aligned with the locations of original translocation release sites. Persistence in the presence of pathogens may be facilitated by metapopulation structure and moderately high genetic diversity. Conversely, metapopulation structure can also facilitate pathogen persistence. Our approach offers a path to advance understanding of the population ecology of reintroduced bighorn sheep and can inform effective conservation and management of their populations.

Community-based conservation (CBC) initiatives aim to reconcile biodiversity protection with local livelihoods, yet their effectiveness in protecting wildlife remains uncertain, often hinging on local management ^1,2 . We evaluated a globally significant CBC model in Kenya’s Greater Maasai Mara Ecosystem (GME), where conservancies, run jointly by Maasai landowners and the tourism sector, employ rotational cattle grazing to support both wildlife and pastoralism ^3,4 . Using a ∼1200 km ² grid of 180 camera traps across gradients of livestock pressure in Maasai Mara National Reserve and three conservancies in 2018, we collected and analysed over 2 million images with a customised AI-powered pipeline. We found a positive impact of observed cattle pressure on mammal community occupancy and species richness, except for at the highest levels of cattle grazing. However, sheep and goat grazing and proximity to infrastructure had a negative impact. These results provide evidence that wildlife and pastoralism can coexist under community-led stewardship ⁵ , but only with active management and targeted control of emerging threats. AI tools such as our image classifier may contribute to more adaptive community-led management of these areas ⁶ . As conservation policy shifts beyond formal protected areas, our findings support CBC as a scalable model for conserving biodiversity within working landscapes, offering a pathway to meet global targets while maintaining local livelihoods ⁷ .

Conservation plans that explicitly account for the social landscape where people and wildlife co‐occur can yield more effective and equitable conservation practices and outcomes. Yet, social data remain underutilized, often because social data are treated as aspatial or are analyzed with approaches that do not quantify uncertainty or address bias in self‐reported data. We conducted a survey (questionnaires) of 177 households in a multiuse landscape in the Kenya–Tanzania borderlands. In a mixed‐methods approach, we used Bayesian hierarchical models to quantify and map local attitudes toward African elephant ( Loxodonta africana ) conservation while accounting for response bias and then combined inference from attitude models with thematic analysis of open‐ended responses and cointerpretation of results with local communities to gain deeper understanding of what explains attitudes of people living with wildlife. Model estimates showed that believing elephants have sociocultural value increased the probability of respondents holding positive attitudes toward elephant conservation in general (mean increase = 0.31 [95% credible interval, CrI, 0.02–0.67]), but experiencing negative impacts from any wildlife species lowered the probability of respondents holding a positive attitude toward local elephant conservation (mean decrease = −0.20 [95% CrI −0.42 to 0.03]). Qualitative data revealed that safety and well‐being concerns related to the perceived threats that elephants pose to human lives and livelihoods, and limited incentives to support conservation on community and private lands lowered positive local attitude probabilities and contributed to negative perceptions of human–elephant coexistence. Our spatially explicit modeling approach revealed fine‐scale variation in drivers of conservation attitudes that can inform targeted conservation planning. Our results suggest that approaches focused on sustaining existing sociocultural values and relationships with wildlife, investing in well‐being, and implementing species‐agnostic approaches to wildlife impact mitigation could improve conservation outcomes in shared landscapes.

Background: Improved understanding of wildlife population connectivity among protected area networks can support effective planning for the persistence of wildlife populations in the face of land use and climate change. Common approaches to estimating connectivity often rely on small samples of individuals without considering the spatial structure of populations, leading to limited understanding of how individual movement links to demography and population connectivity. Recently developed spatial capture-recapture (SCR) models provide a framework to formally connect inference about individual movement, connectivity, and population density, but few studies have applied this approach to empirical data to support connectivity planning. Methods: We used mark-recapture data collected from 924 genetic detections of 598 American black bears (Ursus americanus) in 2004 with SCR ecological distance models to simultaneously estimate density, landscape resistance to movement, and population connectivity in Glacier National Park northwest Montana, USA. We estimated density and movement parameters separately for males and females and used model estimates to calculate predicted density-weighted connectivity surfaces. Results: Model results indicated that landscape structure influences black bear density and space use in Glacier. The mean density estimate was 16.08 bears/100 km² (95% CI 12.52–20.6) for females and 9.27 bears/100 km² (95% CI 7.70–11.14) for males. Density increased with forest cover for both sexes. For male black bears, density decreased at higher grizzly bear (Ursus arctos) densities. Drainages, valley bottoms, and riparian vegetation decreased estimates of landscape resistance to movement for male and female bears. For males, forest cover also decreased estimated resistance to movement, but a transportation corridor bisecting the study area strongly increased resistance to movement presenting a barrier to connectivity. Conclusions: Density-weighed connectivity surfaces highlighted areas important for population connectivity that were distinct from areas with high potential connectivity. For black bears in Glacier and surrounding landscapes, consideration of both vegetation and valley topography could inform the placement of underpasses along the transportation corridor in areas characterized by both high population density and potential connectivity. Our study demonstrates that the SCR ecological distance model can provide biologically realistic, spatially explicit predictions to support movement connectivity planning across large landscapes.

Sexual harassment within academic institutions has profound impacts that may lead to the attrition of groups historically excluded from the biological sciences and related disciplines. To understand sexual harassment's effects on vulnerable communities within academia, we examined graduate student experiences with sexual harassment. In a survey of ecology and evolutionary biology programs across the United States, we found that 38% of the graduate student respondents were sexually harassed during their time in these programs. Sexual harassment disproportionately affected graduate students with multiple intersecting marginalized identities, and these experiences led to delays in completing graduate programs and shifts away from their desired careers. Our research highlights the need for academic institutions, and science more broadly, to make widespread changes to sexual harassment policies, including treating sexual harassment as scientific misconduct and creating resources for individuals within students’ informal support networks, in tandem with efforts to dismantle barriers to advancing diversity, equity, and inclusion.

Spatial capture–recapture (SCR) models are powerful analytical tools that have become the standard for estimating abundance and density of wild animal populations. When sampling populations to implement SCR, the number of unique individuals detected, total recaptures, and unique spatial relocations can be highly variable. These sample sizes influence the precision and accuracy of model parameter estimates. Testing the performance of SCR models with sparse empirical data sets typical of low‐density, wide‐ranging species can inform the threshold at which a more integrated modeling approach with additional data sources or additional years of monitoring may be required to achieve reliable, precise parameter estimates. Using a multi‐site, multi‐year Utah black bear (Ursus americanus) capture–recapture data set, we evaluated factors influencing the uncertainty of SCR structural parameter estimates, specifically density, detection, and the spatial scale parameter, sigma. We also provided some of the first SCR density estimates for Utah black bear populations, which ranged from 3.85 to 74.33 bears/100 km². Increasing total detections decreased the uncertainty of density estimates, whereas an increasing number of total recaptures and individuals with recaptures decreased the uncertainty of detection and sigma estimates, respectively. In most cases, multiple years of data were required for precise density estimates (<0.2 coefficient of variation [CV]). Across study areas there was an average decline in CV of 0.07 with the addition of another year of data. One sampled population with very high estimated bear density had an atypically low number of spatial recaptures relative to total recaptures, apparently inflating density estimates. A complementary simulation study used to assess estimate bias suggested that when 3 times the simulated density. Additional research could evaluate these requirements for other density scenarios. Large numbers of individuals detected, numbers of spatial recaptures, and precision alone may not be sufficient indicators of parameter estimate reliability. We provide an evaluation of simple summary statistics of capture–recapture data sets that can provide an early signal of the need to alter sampling design or collect auxiliary data before model implementation to improve estimate precision and accuracy.