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At least 127 records · Page 7Linked to original sources
USGS2014

Water quality monitoring protocol for wadeable streams and rivers in the Northern Great Plains Network

Preserving the national parks unimpaired for the enjoyment of future generations is a fundamental purpose of the National Park Service (NPS). To address growing concerns regarding the overall physical, chemical, and biological elements and processes of park ecosystems, the NPS implemented science-based management through “Vital Signs” monitoring in 270 national parks (NPS 2007). The Northern Great Plains Network (NGPN) is among the 32 National Park Service Networks participating in this monitoring effort. The NGPN will develop protocols over the next several years to determine the overall health or condition of resources within 13 parks located in Nebraska, North Dakota, South Dakota, and Wyoming. The NGPN identified water resources as a Vital Sign to monitor because water quality and quantity are important aspects of ecological processes that operate across multiple temporal and spatial scales. In the semi-arid region of the Northern Great Plains, surface-water resources within the NGPN are ecologically important. The 13 parks within the NGPN are diverse and vary greatly in size, visitation, and water resources. For example, the measured surface area of the Badlands National Park is about 243,000 acres, which represents nearly one-half of the combined acreage of all 13 NGPN park units; however, water resources within the park are scarce and the majority of streams are intermittent. The Badlands National Park annually hosts nearly 860,000 visitors. Mount Rushmore National Memorial also has limited water resources but hosts nearly 3 million visitors per year within its 1,278 acres. The Missouri National Recreational River contains the greatest portion of waterbodies within the NGPN, consisting of 139 rivers and streams within an areal extent of about 69,000 acres. Although water resources and acreage of the NGPN parks are varied, unifying factors among the parks include the relatively low population density within the Great Plains area and the strong emphasis on agrarian land use throughout the region. To address the diverse water quality concerns, NGPN received input from park staff and conducted pilot studies in 2009 and 2010. These factors, in combination with the NGPN budget allocations, resulted in development of the NGPN’s water quality monitoring protocol. This protocol will provide a context to aid park resource managers in their day-to-day decisions and allow the assessment of the status (current conditions) and trends (directional changes across time) of streams/rivers within selected NGPN parks. Data collected from integrating water resource monitoring, in combination with the inventory of additional Vital Signs, can be used to assess resources and to aid in sound managerial decisions by the NGPN parks. As recommended by Oakley et al. (2003), this protocol provides a narrative and the rationale for selection of streams and rivers within the NGPN that will be measured for water quality, including dissolved oxygen, pH, specific conductivity, and temperature. Standard operating procedures (SOPs) that detail the steps to collect, manage, and disseminate the NGPN water quality data are in an accompanying document. The sampling design documented in this protocol may be updated as monitoring information is collected and interpreted, and as refinement of methodologies develop through time. In addition, evaluation of data and refinement of the program may necessitate potential changes of program objectives. Changes to the NGPN water quality protocols and SOPs will be carefully documented in a revision history log.

Colorado, Montana, Nebraska, North Dakota, South D↗
USGS2017

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

Sonoran Desert↗
USGS2019

Assessing the hydrologic impact of historical railroad embankments on wetland vegetation response in Canaan Valley, WV (USA): The value of high-resolution data

The recovery of natural ecological processes after disturbance is poorly understood. Some disturbances may be so severe as to set ecosystems onto a new trajectory. The Canaan Valley National Wildlife Refuge in West Virginia protects a unique high-altitude wetland that was heavily disturbed by logging 100 years BP and has since transitioned to a new ecological state (shrub wetland). Refuge managers interested in preserving and restoring ecosystem states expressed concerned about lingering impacts of previous disturbances (logging, railroads, beaver, deer, fire). Available data suggested hydrologic impacts from the remnant rail grade but managers had insufficient quantitative data to assess these impacts. We initiated a fine scale assessment of topography, vegetation distribution, and hydrology to assess impacts from the remnant rail grade using lidar data, vegetation surveys, and piezometers. We developed topographic models, hydrological models, and mapped vegetation distribution. We developed statistical models to assess relationships between vegetation communities, hydrology, and distance to the rail grade. Surprisingly, we found that hydrologic flow paths did not conform to expectation and were not restricted by remnant land use features. For the most part, vegetation communities are responding to topographic and environmental gradients that existed prior to disturbance. Use of highly detailed topographic data (lidar), field hydrology, and vegetation studies allowed us to more accurately assess hydrologic and vegetation regimes, eliminating the need for mitigation, saving significant resources.

West Virginia↗
USGS2022

Spatial and temporal patterns in Arctic mosquito abundance

Organisms that undergo a shift in ontogeny and habitat type often change their spatial distribution throughout their life cycle, but how this affects population dynamics remains poorly understood. We examined spatial and temporal patterns in Aedes nigripes abundance, a widespread univoltine Arctic mosquito species (Diptera: Culicidae), hypothesizing that the spatial distribution of adults would be closely tied to aquatic habitat. We tracked adult densities of A. nigripes near Kangerlussuaq, Greenland using emergence traps, CO 2 -baited traps, and sweep-nets. In back-to-back years of sampling (2017 and 2018) we found two-fold variation in overall abundance. Adults were spatially patchy when first emerging from aquatic habitats but within a week, mean capture rates for host-seeking adult females were similar across locations, even in places far from larval habitat. Daily variation in mosquito captures was primarily explained by weather, with virtually no mosquito activity when temperatures averaged less than 8°C or wind speeds exceeded 6 m/s. Gravid females (3% of resting adults) were spatially patchy on the landscape, but not always in the same places where most adults emerged. The spatial distribution of adults is quickly uncoupled from the spatial distribution of larvae because A. nigripes females may disperse far from their natal habitats in search of a blood-meal and high-quality oviposition habitat. 8. This research highlights the value of studying ecological processes that act at disparate life stages for understanding the population biology of organisms with complex life cycles.

Ecological Applications↗
USGS2023

Evaluation of threatened, endangered, and rare fish species and communities of the St. Lawrence River and its tributaries in the United States

Biodiversity is responsible for important ecological processes like productivity and ecosystem stability, and rare species are a major component of biodiversity. Rarity increases a species' vulnerability to disturbances and also makes them difficult to study. Globally, species of freshwater systems are some of the most threatened, and evaluation of rare freshwater species and their habitats is needed to help preserve natural flexibility and ecological function. We conducted an analysis of full fish communities of the upper St. Lawrence River and its major US tributaries, with the goals of determining species locations and abundances, associated environmental conditions, the distribution of distinct fish assemblages across the landscape (with emphasis on communities supporting rare species), and potential threats. From 2009 to 2015, the US Geological Survey (USGS) and Saint Regis Mohawk Tribe (SRMT) worked together using standardized methods to collect community samples within 4 different aquatic realms (shallow and deep lentic, and small and large lotic systems) and determine species-specific fish abundances, frequencies of occurrence, and associated habitat signatures and spatial distributions. Distinct fish assemblages and associated habitat conditions were objectively identified by multivariate and hypothesis-testing methods. We used a geographic information system (GIS) to spatially associate habitat, biotic, and landscape attributes within each stream reach throughout the study area, facilitating quantification of distribution patterns. Comparisons with historical data provided estimates of loss or gain of threatened and endangered species (T&E) colonies. We developed a disturbance index to highlight potential threats to aquatic species. More than 140,000 fishes of 87 species were collected from a total of 1140 sample sites, covering 278 stream reaches, including the endangered Notropis anogenus (Pugnose Shiner), and threatened Hiodon tergisus (Mooneye), Etheostoma pellucidum (Eastern Sand Darter), and Acipenser fulvescens (Lake Sturgeon). We identified 50 distinct fish assemblages differing in species composition, abundance, and/or diversity, but only 13 of those assemblages included a T&E species. The rareness, extent, and patchiness of fish assemblages created a mosaic of fish communities across the landscape, from headwaters to the mainstem of the St. Lawrence River. Comparisons with historic surveys (1978–2008) showed a stable number of T&E species colonies or an increase for some species. The geographic distribution of multimetric disturbance index values showed where combinations of disturbances to fish habitats might affect rare fish species and aquatic communities in the region. The species–habitat associations and fish assemblage distributions can be used for evaluation of species, communities, or habitats that may need protection or restoration.

St. Lawrence River study area↗
USGS2010

Models for inference in dynamic metacommunity systems

A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species‐ and location‐specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species‐specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity.

Ecology↗
USGS2019

Assessing plant production responses to climate across water-limited regions using Google Earth Engine

(Munson) Climate variability and change acting at broad scales can lead to divergent changes in plant production at local scales. Quantifying how production responds to variation in climate at local scales is essential to understand underlying ecological processes and inform land management decision-making, but has historically been limited in spatiotemporal scale based on the use of discrete ground-based measurements or coarse resolution satellite observations. With the advent of cloud-based computing through Google Earth Engine (GEE), production responses to climate can be evaluated across broad landscapes though time at a resolution useful for ecological and land management applications. Here, GEE was employed to synthesize a multi-platform Landsat time series (1988 – 2014) and evaluate relationships between the soil-adjusted vegetation index (a proxy for plant production) and climate across deserts and plant communities of the southwestern U.S. A “climate pivot point” approach was adopted in GEE to assess the trade-off between production responses to increasing wetness and resistances to drought at 30-m resolution. Consistent with a long-term seasonal climate gradient, production was most related to climate variance during the cool-season in the western deserts, during the warm-season in the eastern deserts, and equally related to both seasons within several desert areas. Communities dominated by grasses and deciduous trees displayed large production responses to an increase in wetness and low resistances to water deficit, while shrublands and evergreen woodlands had variable responses and high drought resistances. Production in plant communities that spanned multiple deserts responded differently to seasonal climate variability in each desert. Defining these plant production sensitivities to climate at 30-m resolution in GEE advances forecasts of how long-term climate trajectories may affect carbon storage, wildlife habitat, and the vulnerability of water-limited ecosystems.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2020

Bioclimatic modeling of potential vegetation types as an alternative to species distribution models for projecting plant species shifts under changing climates

Land managers need new tools for planning novel futures due to climate change. Species distribution modeling (SDM) has been used extensively to predict future distributions of species under different climates, but their map products are often too coarse for fine-scale operational use. In this study we developed a flexible, efficient, and robust method for mapping current and future distributions and abundances of vegetation species and communities at the fine spatial resolutions that are germane to land management. First, we mapped Potential Vegetation Types (PVTs) using conventional statistical modeling techniques (Random Forests) that used bioclimatic ecosystem process and climate variables as predictors. We obtained over 50% accuracy across 13 mapped PVTs for our study area. We then applied future climate projections as climate input to the Random Forest model to generate future PVT maps, and used field data describing the occurrence of tree and non-tree species in each PVT category to model and map species distribution for current and future climate. These maps were then compared to two previous SDM mapping efforts with over 80% agreement and equivalent accuracy. Because PVTs represent the biophysical potential of the landscape to support vegetation communities as opposed to the vegetation that currently exists, they can be readily linked to climate forecasts and correlated with other, climate-sensitive ecological processes significant in land management, such as fire regimes and site productivity.

Montana↗
USGS2013

Assessing impacts of roads: application of a standard assessment protocol

Adaptive management of road networks depends on timely data that accurately reflect the impacts those systems are having on ecosystem processes and associated services. In the absence of reliable data, land managers are left with little more than observations and perceptions to support management decisions of road-associated disturbances. Roads can negatively impact the soil, hydrologic, plant, and animal processes on which virtually all ecosystem services depend. The Interpreting Indicators of Rangeland Health (IIRH) protocol is a qualitative method that has been demonstrated to be effective in characterizing impacts of roads. The goal of this study were to develop, describe, and test an approach for using IIRH to systematically evaluate road impacts across large, diverse arid and semiarid landscapes. We developed a stratified random sampling approach to plot selection based on ecological potential, road inventory data, and image interpretation of road impacts. The test application on a semiarid landscape in southern New Mexico, United States, demonstrates that the approach developed is sensitive to road impacts across a broad range of ecological sites but that not all the types of stratification were useful. Ecological site and road inventory strata accounted for significant variability in the functioning of ecological processes but stratification based on apparent impact did not. Analysis of the repeatability of IIRH applied to road plots indicates that the method is repeatable but consensus evaluations based on multiple observers should be used to minimize risk of bias. Landscape-scale analysis of impacts by roads of contrasting designs (maintained dirt or gravel roads vs. non- or infrequently maintained roads) suggests that future travel management plans for the study area should consider concentrating traffic on fewer roads that are well designed and maintained. Application of the approach by land managers will likely provide important insights into minimizing impacts of road networks on key ecosystem services.

Rangeland Ecology and Management↗
USGS2017

Multiscale guidance and tools for implementing a landscape approach to resource management in the Bureau of Land Management

The Bureau of Land Management (BLM) is implementing a landscape approach to resource management (hereafter, landscape approach) to more effectively work with partners and understand the effects of management decisions. A landscape approach is a set of concepts and principles used to guide resource management when multiple stakeholders are involved and goals include diverse and sustainable social, environmental, and economic outcomes. Core principles of a landscape approach include seeking meaningful participation of diverse stakeholders, considering diverse resource values in multifunctional landscapes, acknowledging the tradeoffs needed to meet diverse objectives in the context of sustainable resource management, and addressing the complexity of social and ecological processes by embracing interdisciplinarity and considering multiple and broad spatial and temporal perspectives. In chapter 1, we outline the overall goal of this report: to provide a conceptual foundation and framework for implementing a landscape approach to resource management in the BLM, focusing on the role of multiscale natural resource monitoring and assessment information. In chapter 2, we describe a landscape approach to resource management. BLM actions taken to implement a landscape approach include a major effort to compile broad-scale data on natural resource status and condition across much of the west. These broadscale data now provide a regional context for interpreting monitoring data collected at individual sites and informing decisions made for local projects. We also illustrate the utility of using multiscale data to understand potential effects of different resource management decisions, define relevant terms in landscape ecology, and identify spatial scales at which planning and management decisions may be evaluated. In chapter 3, we describe how the BLM Rapid Ecoregional Assessment program and Assessment, Inventory and Monitoring program may be integrated to provide the multiscale monitoring data needed to inform a landscape approach. We propose six core, broad-scale indicators of natural resource status and condition: the amount, spatial distribution, patch size and connectivity of ecosystems and wildlife habitats, and the pattern of existing development across the landscape. Additional supplemental broad-scale indicators may include fire return intervals, distributions of invasive species, and vulnerability of ecosystems to a changing climate. Landscape intactness is an additional derived indicator that is calculated from one or more of the core and supplemental broad-scale indicators. We then outline a process for assessing broad-scale indicators that is consistent with the overall BLM Assessment, Inventory, and Monitoring process, facilitating development of a multiscale natural resource monitoring program. Finally, we describe how broad-scale indicators of natural resource status and condition may guide field monitoring implemented through the BLM Assessment, Inventory and Monitoring program and help address complex management questions. In chapter 4, we consider the specific question of assessing the ecological integrity of rangelands across the western United States. We first define ecological integrity and its relation to land health. We then suggest that a combination of six local-scale indicators collected through field sampling at individual sites and five complementary broad-scale indicators together provide information on the composition, structure, and function of rangelands. The terrestrial monitoring indicators collected at the level of individual field sites are the amount of bare ground, vegetation composition (including invasive plants and plants of management concern), vegetation height, and the proportion of the soil surface in large intercanopy gaps. The broad-scale indicators are vegetation amount, distribution, patch size, connectivity, and productivity, along with the pattern of terrestrial development. Our suggested approach to quantifying ecological integrity focuses specifically on informing management of public lands for multiple resource uses, and illustrates how existing data collected through BLM monitoring and assessment programs may be used together to provide multiscale information on land condition across broad extents. In chapter 5, we develop a method for quantifying landscape intactness and apply this method to the western United States. Our multiscale index of landscape intactness is designed to be defensible, decomposable, and easy to understand. The foundation of the multiscale index of landscape intactness is the surface disturbance footprint of anthropogenic development, including energy and urban development, roads and railroads, cultivated croplands, surface mines and quarries, and energy transmission lines and pipelines. The index represents a gradient of anthropogenic influence as represented by development summarized at two spatial scales of analysis: 2.5 and 20 kilometers. We provide several example applications of the index, illustrating how these data may inform natural resource decisions at the spatial extent of BLM field and district offices, states, ecoregions, and the western United States. We find that 19.2 percent of lands managed by the BLM across the 17 western states of the conterminous United States had the highest landscape intactness. The largest intact areas occur on public lands at high elevations or in the Great Basin. We believe the frameworks, processes, and analyses provided in this report will improve the ability of the BLM to identify and evaluate potential direct and indirect effects of management actions (such as habitat restoration and renewable energy development), and assist the BLM in further implementing a landscape approach to resource management.

Open-File Report↗
USGS2020

Review of trap-and-haul for managing Pacific salmonids (Oncorhynchus spp.) in impounded river systems

High-head dams are migration barriers for Pacific salmon Oncorhynchus spp. in many river systems and recovery measures for impacted stocks are limited. Trap-and-haul has been widely used in attempts to facilitate recovery but information from existing programs has not been synthesized to inform improvements to aid recovery of salmonids in systems with high-head dams. We reviewed 17 trap-and-haul programs regarding Pacific salmon to: (1) summarize information about facility design, operation and biological effects; (2) identify critical knowledge gaps; and (3) evaluate trap-and-haul as a current and future management tool. Existing programs are operated to address a range of management goals including restoring access to historical habitats, temporarily reducing exposure to dangerous in-river conditions, and reintroducing ecological processes upstream from dams. Information gathered from decades of operation on facility design criteria and fish handling protocols, and robust literature on fish collection and passage are available. While many aspects of trap-and-haul have been evaluated, effects on population productivity and sustainability remain poorly understood. Long-term and systematic studies of trap-and-haul outcomes are rare, and assessments can be confounded by concurrent management actions and broad ecological and climatic effects. Existing data suggest that performance and effectiveness vary among programs and over various time scales within programs. Although critical information gaps exist, trap-and-haul is an important management and conservation tool for providing Pacific salmonids access to historical habitats. Successful application of trap-and-haul programs requires long-term commitment and an adaptive management approach by dam owners and stakeholders, and careful planning of new programs.

California, Idaho, Oregon, Washington↗
USGS2018

Modulators of mercury risk to wildlife and humans in the context of rapid global change

Environmental mercury (Hg) contamination is an urgent global health threat. The complexity of Hg in the environment can hinder accurate determination of ecological and human health risks, particularly within the context of the rapid global changes that are altering many ecological processes, socioeconomic patterns, and other factors like infectious disease incidence, which can affect Hg exposures and health outcomes. However, the success of global Hg-reduction efforts depends on accurate assessments of their effectiveness in reducing health risks. In this paper, we examine the role that key extrinsic and intrinsic drivers play on several aspects of Hg risk to humans and organisms in the environment. We do so within three key domains of ecological and human health risk. First, we examine how extrinsic global change drivers influence pathways of Hg bioaccumulation and biomagnification through food webs. Next, we describe how extrinsic socioeconomic drivers at a global scale, and intrinsic individual-level drivers, influence human Hg exposure. Finally, we address how the adverse health effects of Hg in humans and wildlife are modulated by a range of extrinsic and intrinsic drivers within the context of rapid global change. Incorporating components of these three domains into research and monitoring will facilitate a more holistic understanding of how ecological and societal drivers interact to influence Hg health risks.

Ambio↗
USGS2017

A Bayesian method for assessing multiscalespecies-habitat relationships

Context Scientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multi-scale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large. Objectives Our objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance. Methods We introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA. Results Our method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%. Conclusions Given the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships.

Nebraska↗
USGS2017

Geomorphology and sediment regimes of intermittent rivers and ephemeral streams

The geomorphology and sediment regimes of intermittent rivers and ephemeral streams (IRES) are extremely diverse, owing in large part to the substantial spatiotemporal variability of the associated hydrological regimes. We describe the geomorphological character and sediment transport processes along IRES within the context of four geomorphological zones—upland, piedmont, lowland, and floodout—to illustrate the underpinning longitudinal trends of sediment production, transfer, and deposition that exist at the landscape scale. Many geomorphological features of IRES tend to be spatially discontinuous as a result of extended no or low-flow conditions that are punctuated by high-magnitude flood events. Diversity of geomorphology and sediment regimes both within and between the four geomorphological zones therefore promotes ecological processes and patterns in IRES that can be very distinct from perennial river systems.

Book chapter↗
USGS2022

Modeling spatiotemporal abundance and movement dynamics using an integrated spatial capture–recapture movement model

Animal movement is a fundamental ecological process affecting the survival and reproduction of individuals, the structure of populations, and the dynamics of communities. Methods to quantify animal movement and spatiotemporal abundances, however, are generally separate and therefore omit linkages between individual-level and population-level processes. We describe an integrated spatial capture–recapture (SCR) movement model to jointly estimate (1) the number and distribution of individuals in a defined spatial region and (2) movement of those individuals through time. We applied our model to a study of polar bears ( Ursus maritimus ) in a 28,125 km 2 survey area of the eastern Chukchi Sea, USA in 2015 that incorporated capture–recapture and telemetry data. In simulation studies, the model provided unbiased estimates of movement, abundance, and detection parameters using a bivariate normal random walk and correlated random walk movement process. Our case study provided detailed evidence of directional movement persistence for both male and female bears, where individuals regularly traversed areas larger than the survey area during the 36-day study period. Scaling from individual- to population-level inferences, we found that densities varied from <0.75 bears/625 km 2 grid cell/day in nearshore cells to 1.6–2.5 bears/grid cell/day for cells surrounded by sea ice. Daily abundance estimates ranged from 53 to 69 bears, with no trend across days. The cumulative number of unique bears that used the survey area increased through time due to movements into and out of the area, resulting in an estimated 171 individuals using the survey area during the study (95% credible interval 124–250). Abundance estimates were similar to a previous multiyear integrated population model using capture–recapture and telemetry data (2008–2016; Regehr et al., Scientific Reports 8:16780, 2018). Overall, the SCR–movement model successfully quantified both individual- and population-level space use, including the effects of landscape characteristics on movement, abundance, and detection, while linking the movement and abundance processes to directly estimate density within a prescribed spatial region and temporal period. Integrated SCR–movement models provide a generalizable approach to incorporate greater movement realism into population dynamics and link movement to emergent properties including spatiotemporal densities and abundances.

eastern Chukchi Sea↗
USGS2025

Evaluation of the gap intercept method to measure rangeland connectivity

Characterizing the connectivity of materials, organisms, and energy on rangelands is critical to understanding and managing ecosystem response to disturbances. For over twenty years, scientists and rangeland managers have used the gap intercept method to monitor connectivity. However, using gap intercept measurements to infer ecosystem processes or inform management actions and conservation practices on rangelands has been limited because there are few tools and syntheses to help managers pragmatically interpret gap measurements. In this synthesis, we review the different ways the gap intercept method is conducted and highlight considerations when collecting and using gap intercept data. We discuss what is known about how gap intercept data can be used to assess wind and water erosion, biocrust abundance and composition, soil fertility, plant community dynamics, wildlife habitat characteristics, and fuel connectivity and fire behavior. Finally, we identify emerging opportunities regarding the collection and use of gap intercept data to assess rangeland connectivity, ecosystem function, and ecological processes. Through this synthesis we demonstrate the value of the gap intercept method, particularly “all-plant” (i.e., whole-community) canopy gap, in supporting assessments of rangeland condition and vulnerability, and in planning future management actions.

Rangeland Ecology & Management↗
USGS2025

A model for regional-scale oak savanna management: The roles of fire, canopy, and soils for understory plant diversity

Predicting the outcomes of land management on biodiversity is difficult without a mechanistic understanding of how management approaches, ecosystem structure, environmental conditions, and biodiversity interact. Management effects may be direct or indirect, context- or scale-dependent, or obscured by local environmental conditions. Resolving these relationships at the regional scale may be difficult, given heterogeneity in local environmental conditions, yet understanding broad-scale patterns can elucidate context dependencies and improve restoration outcomes. We confronted these challenges within globally rare oak savannas in the midwestern United States, which have been altered by fire exclusion and resulting woody encroachment. By modeling direct and indirect pathways by which management influences diversity, we test a general framework for savanna restoration. Across 100 oak savannas spanning five US states, management by prescribed fire and mechanical thinning of woody vegetation affected groundlayer plant species richness through changes to ecosystem structure (canopy openness and litter depth), and these effects were both context- and scale-dependent. Frequent prescribed fires and canopy thinning promoted greater canopy openness, which in turn increased richness at small (1 m 2 ), but not larger (1000 m 2 ) scales. Frequent fire additionally increased richness at small and larger scales through effects independent of ecosystem structure. While management effects were large relative to the influence of local edaphic conditions, soil productivity had two largely offsetting effects on small-scale richness, increasing richness directly but decreasing richness indirectly by promoting closed canopy structure. These results suggest using a combination of fire and canopy thinning to reverse the effects of decades of fire exclusion. However, management effects were also context-dependent, emphasizing that management outcomes vary regionally. Here, 1-m 2 plant species richness increased with both fire frequency and canopy thinning under low, but not high, productivity soil conditions. By demonstrating how specific management practices influence savanna structure and biodiversity by manipulating ecological processes across broad geographic and edaphic gradients, our findings provide a framework for understanding management outcomes at short and medium intervals (e.g., within and between decades, respectively), in the form of a model that can be refined by testing additional hypotheses to better predict savanna restoration outcomes.

Illinois, Indiana, Michigan, Ohio, Wisconsin↗
USGS2023

Estimating fat content in barred owls (Strix varia) with predictive models developed from direct measures of proximate body composition

Body condition indices and related metrics can help assess habitat quality and other ecological processes, and ideally, these metrics are based on measures of lipids directly extracted from the species of interest. In recent decades, barred owls ( Strix varia ) have become a species of conservation concern as they invaded older forests of the US Pacific Northwest, and caused population declines of the closely related and federally threatened northern spotted owl ( Strix occidentalis caurina ). A simple and effective measure of barred owl body condition could help to understand how habitat quality varies within their new range, which in turn can inform their management and other aspects of their ecology. Using 77 barred owl carcasses collected during experimental removals in Washington and Oregon, USA, we measured the amount of lipid in each specimen with proximate body composition analysis. We then fit and compared (with adjusted R 2 values) alternative linear regression models to estimate the percent lipids in dry mass of the owls based on morphometric body condition indices, a qualitative fat score of subcutaneous breast fat, sex and the time of year females were collected (relative to egg production). Adjusted R 2 values for all models ranged from 0.49 to 0.87, with the best model including mass divided by foot-pad length, fat score, sex and the time of year a female was collected. Most models generated comparable estimates of percent lipids at a population level and we provided correction factors to apply these models when used with live barred owls, allowing for site-specific comparisons of body condition among individuals inhabiting a diversity of environmental conditions.

Conservation Physiology↗