Geology topics

Erin K. Buchholtz

Publications and source records attributed to Erin K. Buchholtz.

10 recordsLinked to original sources

USGS2026

Developing a low-cost drone-based method for deploying and retrieving autonomous recording units in inaccessible areas

Autonomous Recording Units (ARUs) are increasingly used in research to support passive acoustic monitoring, but deployment in remote or inaccessible locations remains logistically challenging. Traditional manual placement is labor-intensive, time-consuming, potentially hazardous, and often limited to habitat edges, creating sampling biases and restricting spatial coverage. To address placement limitations in wetland systems, we developed and field-tested a low-cost, lightweight floating platform paired with a drone-based deployment and retrieval system. The drone-deployable ARU platform, constructed from inexpensive, off-the-shelf materials (~US $21 per unit), weighed ~560 g and was mounted with an ARU (AudioMoth) at ~1.2 m above water. The platform was designed for stability, portability, and compliance with Federal Aviation Administration Part 107 regulations. Field trials were conducted across 50 operations in various types of historical rice-field impoundments along the South Carolina coast, which provide critical habitat for secretive marsh birds such as rails (e.g ., Rallus, Laterallus , and Porzana ) and bitterns (e.g ., Botaurus and Ixobrychus ). All 50 deployments and retrievals were successful, demonstrating the robustness of the method under diverse hydrologic and vegetative conditions. Deployment times were significantly shorter than retrieval times (median 6 vs. 9 min), with retrieval requiring greater precision for hook engagement. Operation times scaled predictably with distance: deployment increased by 0.93 min/100 m (R 2 = 0.94) and retrieval by 1.17 min/100 m (R 2 = 0.95). No platform damage or displacement was observed, as emergent vegetation was likely providing natural anchoring. Our approach offers an affordable and effective solution for expanding ARU coverage in large, inaccessible wetlands, reducing sampling bias and enhancing biodiversity monitoring. With continued advances in drone payload capacity, battery endurance, and beyond-visual-line-of-sight flight regulations, our workflow could be adapted for deploying multi-sensor platforms (e.g., ARUs, eDNA samplers, water and air quality sensors, plant sample collectors, insect traps, and trail cameras) to support integrated biodiversity monitoring in challenging landscapes worldwide.

South Carollina↗

USGS2026

Resilience thinking for human-wildlife coexistence: Bridging dynamic systems, archetypes, and transformations

As human activities and wildlife increasingly overlap in the Anthropocene, conventional conservation paradigms focused on land-sparing are shifting toward strategies that support human–wildlife coexistence. However, achieving sustainable coexistence is often hindered by a limited understanding of the dynamic social–ecological processes that drive integrated human–wildlife systems. This Special Issue explores “resilience thinking” as a scientific framework to address these knowledge gaps. By bridging sustainability and wildlife sciences, we examine how concepts such as adaptive capacity, feedback loops, system archetypes, and tipping points can illuminate the conditions that facilitate stable coexistence or lead to persistent conflict. Through diverse global case studies ranging from carnivore management in Europe to primate interactions in Indonesia, contributions highlight how societal perceptions, governance, and co-adaptation shape system trajectories. Ultimately, we argue that fostering durable coexistence requires moving beyond incremental adaptation toward transformative governance that centers on equity, relationality, and proactive management.

Ambio↗

USGS2025

Invasive wild pig movement and space use in a mixed-use forest landscape, South Carolina

Invasive wild pigs ( Sus scrofa ) pose considerable ecological and economic challenges across their introduced range, and understanding their spatial ecology is critical for management. This research and accompanying dataset represents adult wild pig movement in South Carolina, United States based on 16 individuals collared in 2023-2024. Using hourly GPS collar data for 6 males and 5 females, we calculated autocorrelated kernel density estimates (AKDEs) and monthly kernel density estimates (KDEs) to characterize space use. Individual pigs had an average hourly step length of 83 m and average net displacement of 930 m. On average, pigs used 2.32 km 2 monthly, while they used 2.95 km 2 over their entire tracked period (mean = 111 days). This work aims to support management actions and future research on invasive wild pigs.

South Carolina↗

USGS2025

Different data for different goals: Exploring trade-offs and synergies in the use of spatial data inputs to optimize conservation action in sagebrush ecosystems

Ecosystems worldwide continue to experience rapid rates of habitat and species loss. Management actions to conserve and restore functional habitats are needed to reduce these declines, but funding and resources for such actions are limited. Spatial conservation prioritization (SCP) can facilitate strategic decision-making for targeted conservation planning and delivery, but complexities arise when management objectives include multiple wildlife species and ecological or management constraints, all of which can be further complicated by data uncertainty and existing conservation plans. The Prioritizing Restoration of Sagebrush Ecosystems Tool (PReSET), an R package-based decision-support tool, supports strategic ecosystem management planning across the sagebrush biome by using SCP. We adapted PReSET to better address the needs of multiple wildlife species, evaluate the effects of different ecological or management constraints on conservation outcomes, assess the influence of data uncertainty, and integrate existing conservation plans. Specifically, we developed optimization problems to identify priority sagebrush protection and restoration across the state of Wyoming, USA, and evaluated the efficacy and trade-offs of various approaches to problem design. We evaluated trade-offs in targeting multiple species compared to a single species, including using greater sage-grouse as a potential umbrella species to benefit other sagebrush-dependent wildlife. We then evaluated multi-species protection and restoration problems aimed at minimizing the risks of inadequate connectivity, climate change, and restoration failure, and accounted for data uncertainty to assess relationships between risk aversion of managers and conservation outcomes. We also developed optimization problems within conservation areas identified by an existing sagebrush conservation plan to evaluate the efficacy of guiding local-scale conservation delivery within more broadly defined conservation areas. Our results demonstrate how SCP methods can leverage novel spatial data to develop targeted decision-support resources that can facilitate landscape conservation planning and improve management outcomes across a wide array of systems and species.

Wyoming↗

USGS2025

The American black bear (Ursus americanus) as an apex predator: Investigating the ecological role of the world’s most abundant large carnivore

Introduction American black bears ( Ursus americanus ) have been documented to have top-down effects, both consumptive (through predation) and nonconsumptive (through fear effects). However, their behavioural and dietary adaptability has led to uncertainty about the conditions under which these may occur. Objectives We aimed to (1) investigate when, where, and how often black bears influence lower trophic levels, and (2) critically assess the experimental design of such studies to determine trends and biases. Methods We conducted a systematic literature search and used linear mixed-effects models to assess the relationships among prey age class, the presence of other large carnivores, and the percentage of ungulate mortality due to black bears. We also summarised the measured effects of black bears on other carnivores and the results of any experimental studies. Results We found a strong negative relationship between puma presence and the percentage of ungulate mortality due to black bears, but only in areas with at least one other large carnivore (e.g., wolves). Among 16 studies of black bears' impacts on other carnivores, most documented negative behavioural effects. While only 5% of studies had strong experimental design, bear removal consistently increased juvenile ungulate survival. Discussion and Synthesis Our findings highlight black bears' strong top-down effects, resembling or exceeding those of other large carnivores. These effects were greatest when no other large carnivores were present, but as highly effective kleptoparasites, black bears can alter the feeding habits of other large carnivores. Thus, we argue that ‘apex’ is a conditional state, not a species-wide status.

Mammal Review↗

USGS2024

Ecological trade-offs associated with fuel breaks in the sagebrush ecosystem

Background Unprecedented wildfire frequency, fueled by invasive annual grasses, threatens sagebrush ecosystems. To suppress wildfire and conserve sagebrush, land management agencies have installed fuel breaks across the sagebrush biome. However, despite the potential reduction in wildfire, fuel breaks may have ecological costs. Determining an acceptable balance between risks and benefits of fuel breaks is needed to avoid accelerating sagebrush loss, annual grass invasion, and habitat degradation. To evaluate the potential for ecological trade-offs to occur, we characterized the contexts in which known fuel breaks currently exist. We synthesized spatial data on all known fuel breaks and a suite of variables that may contribute to fuel break risks and benefits, including burn probabilities, predicted fuel break effectiveness, linear infrastructure, invasive annual grass cover, soil moisture conditions that confer resistance to invasion and resilience to disturbance, and priority wildlife habitats across the sagebrush biome. Results We found that within the sagebrush biome, fuel breaks are generally located in areas with high burn probability and are thus positioned well to intercept potential wildfires. However, fuel breaks are also frequently positioned in areas with lower predicted fuel break effectiveness relative to the sagebrush biome overall. Fuel breaks also are spatially associated with high invasive grass cover, indicating the need to better understand the causal relationship between fuel breaks and annual invasive grasses. We also show that the fuel break network is dense within priority wildlife habitats. Dense fuel breaks within wildlife habitats may trade off wildfire protection for decreased integrity of such habitats. Conclusions Our analyses describe the potential for fuel breaks to invoke ecological trade-offs and show that the balance of risks and benefits differs across sagebrush ecosystems. Strategic research and actions are needed to evaluate which factors tip the balance towards maximizing wildfire suppression while minimizing risk to sensitive ecological resources.

Arizona, California, Colorado, Idaho, Montana, Nev↗

USGS2023

Temporal patterns of structural sagebrush connectivity from 1985 to 2020

The sagebrush biome within the western United States has been reshaped by disturbances, management, and changing environmental conditions. As a result, sagebrush cover and configuration have varied over space and time, influencing processes and species that rely on contiguous, connected sagebrush. Previous studies have documented changes in sagebrush cover, but we know little about how the connectivity of sagebrush has changed over time and across the sagebrush biome. We investigated temporal connectivity patterns for sagebrush using a time series (1985–2020) of fractional sagebrush cover and used an omnidirectional circuit algorithm to assess the density of connections among areas with abundant sagebrush. By comparing connectivity patterns over time, we found that most of the biome experienced moderate change; the amount and type of change varied spatially, indicating that areas differ in the trend direction and magnitude of change. Two different types of designated areas of conservation and management interest had relatively high proportions of stable, high-connectivity patterns over time and stable connectivity trends on average. These results provide ecological information on sagebrush connectivity persistence across spatial and temporal scales that can support targeted actions to address changing structural connectivity and to maintain functioning, connected ecosystems.

Western United States↗

USGS2023

Assessing large landscape patterns of potential fire connectivity using circuit methods

Context Minimizing negative impacts of wildfire is a major societal objective in fire-prone landscapes. Models of fire connectivity can aid in understanding and managing wildfires by analyzing potential fire spread and conductance patterns. We define ‘fire connectivity’ as the landscape’s capacity to facilitate fire transmission from one point on the landscape to another. Objectives Our objective was to develop an approach for modeling fire connectivity patterns representing potential fire spread and relative flow across a broad landscape extent, particularly in the management-relevant context of fuel breaks. Methods We applied an omnidirectional circuit theory algorithm to model fire connectivity in the Great Basin of the western United States. We used predicted rates of fire spread to approximate conductance and calculated current densities to identify connections among areas with high spread rates. We compared existing and planned fuel breaks with fire connectivity patterns. Results Fire connectivity and relative flow outputs were characterized by spatial heterogeneity in the landscape’s capacity to transmit fire. We found that existing fuel break networks were denser in areas with relatively diffuse and impeded flow patterns, rather than in locations with channelized flow. Conclusions This approach could be paired with traditional fire behavior and risk analyses to better understand wildfire spread as well as direct strategic placement of individual fuel breaks within larger networks to constrain fire spread. Thus, our findings may offer local- to landscape-level support for management actions that aim to disrupt fire spread and mitigate the costs of fire on the landscape.

California, Idaho, Nevada, Oregon, Utah↗

USGS2023

Landscape and connectivity metrics as a spatial tool to support invasive annual grass management decisions

The spatial patterns and context of invasions are increasingly recognized as important for successful and efficient management actions. Beyond mapping occurrence or percent cover in pixels, spatial summary information that describes the size and arrangement of patches in the context of a larger landscape (e.g., infested regions, connected patch networks) can add a depth of information for managing invasive grasses that threaten native ecosystems. Few invasive annual grass analyses have explored the use of landscape and circuit-based connectivity metrics to characterize and compare spatial patterns of invasion. To assess the transferability and applicability of these landscape ecology analyses, we calculated landscape metrics (4 area-based, 3 configuration) and a connectivity metric (circuit-based centrality), using a weighted-average map of invasive annual grass cover in the Great Basin, USA. We calculated metrics at local and regional scales, allowing invasion statistics to be compared across the landscape and illustrating varying patterns of invasion extent and connectedness. We found the metrics provided additional, complementary information at the sampled local and regional scales beyond abundance measures alone. We also illustrated how key metrics could be used to categorize and map areas needing different management strategies, for example, where strategies could proactively protect uninvaded cores, disconnect fine fuel patches, or contain established invasions. The landscape and connectivity metric approach can be applied across scales to spatially target patches locally, provide broader context within a single region, as well as to compare metrics and spatial variation in patterns among different regions.

Biological Invasions↗

USGS2022

Potential cheatgrass abundance within lightly invaded areas of the Great Basin

Context Anticipating where an invasive species could become abundant can help guide prevention and control efforts aimed at reducing invasion impacts. Information on potential abundance can be combined with information on the current status of an invasion to guide management towards currently uninvaded locations where the threat of invasion is high. Objectives We aimed to support management by developing predictive maps of potential cover for cheatgrass ( Bromus tectorum ), a problematic invader that can transform plant communities. We integrated our predictions of potential abundance with mapped estimates of current cover to quantify invasion potential within lightly invaded areas. Methods We used quantile regression to model cheatgrass abundance as a function of climate, weather, and disturbance, treating outputs as low to high invasion scenarios. We developed a species-specific set of covariates and validated model performance using spatially and temporally independent data. Results Potential cheatgrass abundance was higher in areas that had burned, at low elevations, and when fall germination conditions were more favorable. Our results highlight the extensive areas across the Great Basin where cheatgrass abundance could increase to levels that can alter fire behavior and cause other ecological impacts. Conclusions We predict potential cheatgrass abundance to quantify relative invasion risk. Our model results provide high and low scenarios of cheatgrass abundance to guide resource allocation and planning efforts across shrubland ecosystems of the Great Basin that remain relatively uninvaded. Combining information on an invasive species’ current and potential abundance can yield spatial predictions to guide resource allocation and management action.

California, Idaho, Nevada, Oregon, Utah↗