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At least 1,369 records · Page 76Linked to original sources
USGS2025

Spatiotemporal interactions facilitate sympatry in a diverse mammalian community

Understanding mechanisms underlying coexistence among potential competitors, and between predators and prey, is a persistent challenge in community ecology. Using 6 years (2013–2018) of camera-trapping data and species interaction models, we investigated the spatiotemporal patterns of inter- and intra-guild interspecific interactions in a diverse terrestrial mammalian community in Pakke Wildlife Sanctuary and Tiger Reserve (PTR), Northeast India. We found no evidence of spatial interaction among apex predators (tiger Panthera tigris , leopard Panthera pardus , and dhole Cuon alpinus ). However, dholes temporally separated themselves from tigers and leopards. Among small carnivores, marbled cat ( Pardofelis marmorata ) and leopard cat ( Prionailurus bengalensis ) exhibited temporal separation, whereas leopard cat overlapped spatially and temporally with other small carnivores. Herbivores exhibited neither spatial nor temporal separation with each other. All apex predators exhibited diel activity and space-use patterns to overlap with their preferred prey. Our results suggest that the assembly of the diverse mammalian community of PTR is a complex process, and coexistence among potential competitors, and predators and prey is likely facilitated by several mechanisms including spatial and temporal segregation, and potentially dietary separation.

Arunachal Pradesh↗
USGS2015

Western juniper management: assessing strategies for improving greater sage-grouse habitat and rangeland productivity

Western juniper ( Juniperus occidentalis subsp. occidentalis ) range expansion into sagebrush steppe ecosystems has affected both native wildlife and economic livelihoods across western North America. The potential listing of the greater sage-grouse ( Centrocercus urophasianus ) under the U.S. Endangered Species Act has spurred a decade of juniper removal efforts, yet limited research has evaluated program effectiveness. We used a multi-objective spatially explicit model to identify optimal juniper removal sites in Northeastern California across weighted goals for ecological (sage-grouse habitat) and economic (cattle forage production) benefits. We also extended the analysis through alternative case scenarios that tested the effects of coordination among federal agencies, budgetary constraints, and the use of fire as a juniper treatment method. We found that sage-grouse conservation and forage production goals are somewhat complementary, but the extent of complementary benefits strongly depends on spatial factors and management approaches. Certain management actions substantially increase achievable benefits, including agency coordination and the use of prescribed burns to remove juniper. Critically, our results indicate that juniper management strategies designed to increase cattle forage do not necessarily achieve measurable sage-grouse benefits, underscoring the need for program evaluation and monitoring.

California, Oregon, Nevada↗
USGS2016

Bayesian analysis of Jolly-Seber type models

We propose the use of finite mixtures of continuous distributions in modelling the process by which new individuals, that arrive in groups, become part of a wildlife population. We demonstrate this approach using a data set of migrating semipalmated sandpipers ( Calidris pussila ) for which we extend existing stopover models to allow for individuals to have different behaviour in terms of their stopover duration at the site. We demonstrate the use of reversible jump MCMC methods to derive posterior distributions for the model parameters and the models, simultaneously. The algorithm moves between models with different numbers of arrival groups as well as between models with different numbers of behavioural groups. The approach is shown to provide new ecological insights about the stopover behaviour of semipalmated sandpipers but is generally applicable to any population in which animals arrive in groups and potentially exhibit heterogeneity in terms of one or more other processes.

Environmental and Ecological Statistics↗
USGS2010

A general science-based framework for dynamical spatio-temporal models

Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic nonlinearity and demonstrate that it accommodates many different classes of scientific-based parameterizations as special cases. The model is presented in a hierarchical Bayesian framework and is illustrated with examples from ecology and oceanography. ?? 2010 Sociedad de Estad??stica e Investigaci??n Operativa.

Test↗
USGS2018

The use of remote camera trapping to study cheetahs

Remote camera trapping is an efficient noninvasive technique for monitoring rare and elusive species, such as cheetahs. The unique pelage pattern of cheetahs allows for identification of individuals from photographs, providing detection histories that are naturally suited for abundance estimation using capture–recapture methods. Furthermore, the spatial location of photographic detections allows for the use of spatial capture–recapture models, which provide estimates of density. In this chapter, we describe aspects of cheetah ecology that should be considered when designing camera trapping surveys (e.g., social structure, natural densities, and home range size) to estimate cheetah density and provide guidance for future camera trap sampling and analysis.

Book chapter↗
USGS2013

Fire regimes of quaking aspen in the Mountain West

Quaking aspen (Populus tremuloides Michx.) is the most widespread tree species in North America, and it is found throughout much of the Mountain West (MW) across a broad range of bioclimatic regions. Aspen typically regenerates asexually and prolifically after fire, and due to its seral status in many western conifer forests, aspen is often considered dependent upon disturbance for persistence. In many landscapes, historical evidence for post-fire aspen establishment is clear, and following extended fire-free periods senescing or declining aspen overstories sometimes lack adequate regeneration and are succeeding to conifers. However, aspen also forms relatively stable stands that contain little or no evidence of historical fire. In fact, aspen woodlands range from highly fire-dependent, seral communities to relatively stable, self-replacing, non-seral communities that do not require fire for persistence. Given the broad geographic distribution of aspen, fire regimes in these forests likely co-vary spatially with changing community composition, landscape setting, and climate, and temporally with land use and climate – but relatively few studies have explicitly focused on these important spatiotemporal variations. Here we reviewed the literature to summarize aspen fire regimes in the western US and highlight knowledge gaps. We found that only about one-fourth of the 46 research papers assessed for this review could be considered fire history studies (in which mean fire intervals were calculated), and all but one of these were based primarily on data from fire-scarred conifers. Nearly half of the studies reported at least some evidence of persistent aspen in the absence of fire. We also found that large portions of the MW have had little or no aspen fire history research. As a result of this review, we put forth a classification framework for aspen that is defined by key fire regime parameters (fire severity and probability), and that reflects underlying biophysical settings and correlated aspen functional types. We propose the following aspen fire regime types: (1) fire-independent, stable aspen; (2) fire-influenced, stable aspen; (3) fire-dependent, seral, conifer-aspen mix; (4) fire-dependent, seral, montane aspen-conifer; and (5) fire-dependent, seral, subalpine aspen-conifer. Closing research gaps and validating our proposed aspen fire regime classification will likely require additional site-specific research, enhanced dendrochronology techniques, charcoal and pollen record analysis, spatially-explicit modeling, and other techniques. We hope to encourage development of site-appropriate disturbance ecology characterizations, in order to aid efforts to manage and restore aspen communities and to diagnose key factors contributing to changes in aspen.

Forest Ecology and Management↗
USGS2007

Mercury speciation in piscivorous fish from mining-impacted reservoirs

Guadalupe Reservoir (GUA), California, and Lahontan Reservoir (LAH), Nevada, U.S. are both affected either directly or indirectly by the legacy of gold and silver mining in the Sierra Nevada during the nineteenth century. Analysis of total mercury in fish from these lentic systems consistently indicate elevated concentrations (>1 μg·g-1 wet weight; hereinafter, all concentrations are reported as wet weight unless indicated otherwise) well above the U.S. Environmenal Protection Agency's human consumption advisory level for fish (<0.3 μg·g-1). Replicate X-ray absorption near edge structure (XANES) analyses on largemouth bass and hybrid striped bass from GUA and LAH were performed to determine predominant chemical species of mercury accumulated by these high-trophic-level piscivores that are exposed to elevated mercury through trophic transfer in mining-impacted lentic systems. Despite distinct differences in mercury source, the proximity of the source, and concentrations of complexing ligands, results of XANES analysis clearly indicated that mercury accumulated in these individual fish from the two reservoirs were dominated by methylmercury cysteine complexes. These findings are consistent with results from commercial fish species inhabiting marine environments which are presumed to include differing mercury sources (e.g., atmospheric, hydrothermal, or benthic). The dominance of methylmercury cysteine complexes in muscle tissues of fish obtained from such contrasting environments and exposure conditions suggests that a generic toxicological model for the consumption of fish could be applicable over a wide range of ecologic settings.

Environmental Science & Technology↗
USGS2014

Occupancy of yellow-billed and Pacific loons: evidence for interspecific competition and habitat mediated co-occurrence

Interspecific competition is an important process structuring ecological communities, however, it is difficult to observe in nature. We used an occupancy modelling approach to evaluate evidence of competition between yellow-billed ( Gavia adamsii ) and Pacific ( G. pacifica ) loons for nesting lakes on the Arctic Coastal Plain of Alaska. With multiple years of data and survey platforms, we estimated dynamic occupancy states (e.g. rates of colonization or extinction from individual lakes) and controlled for detection differences among aircraft platforms and ground survey crews. Results indicated that yellow-billed loons were strong competitors and negatively influenced the occupancy of Pacific loons by excluding them from potential breeding lakes. Pacific loon occupancy was conditional on the presence of yellow-billed loons, with Pacific loons having almost a tenfold decrease in occupancy probability when yellow-billed loons were present and a threefold decrease in colonization probability when yellow-billed loons were present in the current or previous year. Yellow-billed and Pacific loons co-occurred less than expected by chance except on very large lakes or lakes with convoluted shorelines; variables which may decrease the cost of maintaining a territory in the presence of the other species. These results imply the existence of interspecific competition between yellow-billed and Pacific loons for nesting lakes; however, habitat characteristics which facilitate visual and spatial separation of territories can reduce competitive interactions and promote species co-occurrence.

Alaska↗
USGS2024

Wildfire probability estimated from recent climate and fine fuels across the big sagebrush region

Background Wildfire is a major proximate cause of historical and ongoing losses of intact big sagebrush ( Artemisia tridentata Nutt.) plant communities and declines in sagebrush obligate wildlife species. In recent decades, fire return intervals have shortened and area burned has increased in some areas, and habitat degradation is occurring where post-fire re-establishment of sagebrush is hindered by invasive annual grasses. In coming decades, the changing climate may accelerate these wildfire and invasive feedbacks, although projecting future wildfire dynamics requires a better understanding of long-term wildfire drivers across the big sagebrush region. Here, we integrated wildfire observations with climate and vegetation data to derive a statistical model for the entire big sagebrush region that represents how annual wildfire probability is influenced by climate and fine fuel characteristics. Results Wildfire frequency varied significantly across the sagebrush region, and our statistical model represented much of that variation. Biomass of annual and perennial grasses and forbs, which we used as proxies for fine fuels, influenced wildfire probability. Wildfire probability was highest in areas with high annual forb and grass biomass, which is consistent with the well-documented phenomenon of increased wildfire following annual grass invasion. The effects of annuals on wildfire probability were strongest in places with dry summers. Wildfire probability varied with the biomass of perennial grasses and forbs and was highest at intermediate biomass levels. Climate, which varies substantially across the sagebrush region, was also predictive of wildfire probability, and predictions were highest in areas with a low proportion of precipitation received in summer, intermediate precipitation, and high temperature. Conclusions We developed a carefully validated model that contains relatively simple and biologically plausible relationships, with the goal of adequate performance under novel conditions so that useful projections of average annual wildfire probability can be made given general changes in conditions. Previous studies on the impacts of vegetation and climate on wildfire probability in sagebrush ecosystems have generally used more complex machine learning approaches and have usually been applicable to only portions of the sagebrush region. Therefore, our model complements existing work and forms an additional tool for understanding future wildfire and ecological dynamics across the sagebrush region.

Fire Ecology↗
USGS2016

Dynamic social networks based on movement

Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.

The Annals of Applied Statistics↗
USGS2005

Effects of Surface-Water Diversions on Habitat Availability for Native Macrofauna, Northeast Maui, Hawaii

Effects of surface-water diversions on habitat availability for native stream fauna (fish, shrimp, and snails) are described for 21 streams in northeast Maui, Hawaii. Five streams (Waikamoi, Honomanu, Wailuanui, Kopiliula, and Hanawi Streams) were chosen as representative streams for intensive study. On each of the five streams, three representative reaches were selected: (1) immediately upstream of major surface-water diversions, (2) midway to the coast, and (3) near the coast. This study focused on five amphidromous native aquatic species (alamoo, nopili, nakea, opae, and hihiwai) that are abundant in the study area. The Physical Habitat Simulation (PHABSIM) System, which incorporates hydrology, stream morphology and microhabitat preferences to explore relations between streamflow and habitat availability, was used to simulate habitat/discharge relations for various species and life stages, and to provide quantitative habitat comparisons at different streamflows of interest. Hydrologic data, collected over a range of low-flow discharges, were used to calibrate hydraulic models of selected transects across the streams. The models were then used to predict water depth and velocity (expressed as a Froude number) over a range of discharges up to estimates of natural median streamflow. The biological importance of the stream hydraulic attributes was then assessed with the statistically derived suitability criteria for each native species and life stage that were developed as part of this study to produce a relation between discharge and habitat availability. The final output was expressed as a weighted habitat area of streambed for a representative stream reach. PHABSIM model results are presented to show the area of estimated usable bed habitat over a range of streamflows relative to natural conditions. In general, the models show a continuous decrease in habitat for all modeled species as streamflow is decreased from natural conditions. The PHABSIM modeling results from the intensively studied streams were normalized to develop relations between the relative amount of diversion from a stream and the resulting relative change in habitat in the stream. These relations can be used to estimate changes in habitat for diverted streams in the study area that were not intensively studied. The relations indicate that the addition of even a small amount of water to a dry stream has a significant effect on the amount of habitat available. Equations relating stream base-flow changes to habitat changes can be used to provide an estimate of the relative habitat change in the study area streams for which estimates of diverted and natural median base flow have been determined but for which detailed habitat models were not developed. Stream water temperatures, which could have an effect on stream ecology and taro cultivation, were measured in five streams in the study area. In general, the stream temperatures measured at any of the monitoring sites were not elevated enough, based on currently available information, to adversely effect the growth or mortality of native aquatic macrofauna or to cause wetland taro to be susceptible to fungi and associated rotting diseases.

Scientific Investigations Report↗
USGS2003

Development and testing of method for assessing and mapping agricultural areas susceptible to atrazine leaching in the state of Washington

In a joint effort by the Washington State Department of Agriculture, the Washington Department of Ecology, and the U.S. Geological Survey, the Environmental Protection Agency's Pesticide Root Zone Model and a Geographic Information System were used to develop and test a method for screening and mapping the susceptibility of ground water in agricultural areas to pesticide contamination. The objective was to produce a map that would be used by the Washington State Department of Agriculture to allocate resources for monitoring pesticide levels in ground water. The method was tested by producing a map showing susceptibility to leaching of the pesticide atrazine for the Columbia Basin Irrigation Project, which encompasses an area of intensive agriculture in eastern Washington. The reliability of the atrazine map was assessed by using statistical procedures to determine whether the median of the percentage of atrazine simulated to leach below the root zone in wells where atrazine was detected was statistically greater than the median percentage at wells where atrazine was not detected (at or above 0.001 microgram per liter) in 134 wells sampled by the U.S. Geological Survey. A statistical difference in medians was not found when all 134 wells were compared. However, a statistical difference was found in medians for two subsets of the 134 wells that were used in land-use studies (studies examining the quality of ground water beneath specific crops). The statistical results from wells from the land-use studies indicate that the model potentially can be used to map the relative susceptibility of agricultural areas to atrazine leaching. However, the distinction between areas of high and low susceptibility may not yet be sufficient to use the method for allocating resources to monitor water quality. Several options are offered for improving the reliability of future simulations.

Water-Resources Investigations Report↗
USGS2001

Continuing education needs for fishery professionals: a survey of North American fisheries administrators

North American fishery professionals? continuing education needs were investigated in an American Fisheries Society questionnaire sent to 111 senior fishery officials in winter 2000. Based on a response rate of 52.2% (N = 58), a minimum of 2,967 individuals would benefit from additional training, especially in the areas of statistics and analysis (83% endorsement rate), restoration and enhancement (81%), population dynamics (81%), multi-species interactions (79%), and technical writing (79%). Other skills and techniques recommended by respondents included computer skills (72%), fishery modeling (69%), habitat modification (67%), watershed processes (66%), fishery management (64%), riparian and stream ecology (62%), habitat management (62%), public administration (62%), nonindigenous species (57%), and age and growth (55%). Additional comments by respondents recommended new technical courses, training in various communications skills, and courses to more effectively manage workloads.

Fisheries↗
USGS1998

Large-area mapping of biodiversity

The age of discovery, description, and classification of biodiversity is entering a new phase. In responding to the conservation imperative, we can now supplement the essential work of systematics with spatially explicit information on species and assemblages of species. This is possible because of recent conceptual, technical, and organizational progress in generating synoptic views of the earth's surface and a great deal of its biological content, at multiple scales of thematic as well as geographic resolution. The development of extensive spatial data on species distributions and vegetation types provides us with a framework for: (a) assessing what we know and where we know it at meso-scales, and (b) stratifying the biological universe so that higher-resolution surveys can be more efficiently implemented, coveting, for example, geographic adequacy of specimen collections, population abundance, reproductive success, and genetic dynamics. The land areas involved are very large, and the questions, such as resolution, scale, classification, and accuracy, are complex. In this paper, we provide examples from the United States Gap Analysis Program on the advantages and limitations of mapping the occurrence of terrestrial vertebrate species and dominant land-cover types over large areas as joint ventures and in multi-organizational partnerships, and how these cooperative efforts can be designed to implement results from data development and analyses as on-the-ground actions. Clearly, new frameworks for thinking about biogeographic information as well as organizational cooperation are needed if we are to have any hope of documenting the full range of species occurrences and ecological processes in ways meaningful to their management. The Gap Analysis experience provides one model for achieving these new frameworks.

Conference Paper↗
USGS2009

IPANE: Could New England's Early Detection Network benefit eastern Canada?

The Invasive Plant Analysis of New England (IPANE: ipane.org) is a multifaceted approach to regional early detection of invasive plants. IPANE, was founded in 2001 to create a comprehensive six state New England regional partnership to: minimize the ecological damage caused by invasive plants; provide reliable and accessible educational material; maintain a network of professional and trained volunteers to gather information and to locate new incursions; provide a web-accessible database and maps of invasive and potentially invasive plants; conduct and encourage research on the biology and ecology of invasive plants; and, use program-generated data to develop predictive distribution models for the region. This program uses the synergy of all the components to create a regional early detection and rapid assessment network to curtail new invasions before they become widespread on the regional landscape. IPANE is a model for the United States Geological Survey National Early Detection Network Toolbox, a compendium of information developed for use by Network partners. In addition, an Early Detection Alert system has been developed to inform key federal and state agency staff, conservation organizations, and those with vegetation management responsibilities about new or potential invaders to the region. These include current and anticipated distribution, diagnostic characters, images, pertinent biological and control information, and key contacts. Most of the non-native species currently considered invasive by IPANE appear to be spreading into New England from the south or west. IPANE is strategically placed to act as an advanced warning system for the 5 provinces of Eastern and Maritime Canada. At the meeting held in Nova Scotia in September 2007, this idea was suggested to attendees from 4 of these 5 provinces and the Canadian government. By expanding its alert systems, IPANE could serve as a focal point for Early Detection information moving in any direction and tie Eastern Canada into the National Early Detection Network of the United States.

Conference Paper↗
USGS2009

Predicting the natural flow regime: Models for assessing hydrological alteration in streams

Understanding the extent to which natural streamflow characteristics have been altered is an important consideration for ecological assessments of streams. Assessing hydrologic condition requires that we quantify the attributes of the flow regime that would be expected in the absence of anthropogenic modifications. The objective of this study was to evaluate whether selected streamflow characteristics could be predicted at regional and national scales using geospatial data. Long-term, gaged river basins distributed throughout the contiguous US that had streamflow characteristics representing least disturbed or near pristine conditions were identified. Thirteen metrics of the magnitude, frequency, duration, timing and rate of change of streamflow were calculated using a 20-50 year period of record for each site. We used random forests (RF), a robust statistical modelling approach, to develop models that predicted the value for each streamflow metric using natural watershed characteristics. We compared the performance (i.e. bias and precision) of national- and regional-scale predictive models to that of models based on landscape classifications, including major river basins, ecoregions and hydrologic landscape regions (HLR). For all hydrologic metrics, landscape stratification models produced estimates that were less biased and more precise than a null model that accounted for no natural variability. Predictive models at the national and regional scale performed equally well, and substantially improved predictions of all hydrologic metrics relative to landscape stratification models. Prediction error rates ranged from 15 to 40%, but were 25% for most metrics. We selected three gaged, non-reference sites to illustrate how predictive models could be used to assess hydrologic condition. These examples show how the models accurately estimate predisturbance conditions and are sensitive to changes in streamflow variability associated with long-term land-use change. We also demonstrate how the models can be applied to predict expected natural flow characteristics at ungaged sites. ?? 2009 John Wiley & Sons, Ltd.

River Research and Applications↗
USGS2023

Sediment sources and connectivity linked to hydrologic pathways and geomorphic processes: A conceptual model to specify sediment sources and pathways through space and time

Sediment connectivity is a framework for transfer and storage of sediment among different geomorphic compartments across upland and channel network of the catchment sediment cascade. Sediment connectivity and dysconnectivity (i.e., source delivery and storage processes) are linked to the water cycle and hydrologic systems with the associated multiscale interactions with climate, soil, topography, ecology, and landuse/landcover under natural variability and human intervention. We review the sediment connectivity concept and frameworks developed in the last few decades to examine and quantify water and sediment transfer in catchment systems. Past conceptual models of connectivity have attempted to integrate multiple processes into sediment domain, including geomorphic, hydrologic, and ecological processes (i.e., “holistic approach to connectivity”). In particular, multiple studies highlight the importance of sediment and water interaction in defining landscape connectivity. There are also efforts to quantify the topographic controls on sediment connectivity, in the advent of increasingly high-resolution digital terrain models. More recent modeling efforts have integrated structural and functional connectivity through coupling topographic information with hydrologic simulation models. Though this recent modeling development is encouraging, a comprehensive sediment connectivity framework that integrates geomorphic and hydrologic processes across spatiotemporal scales is yet to be conceived. Such an effort will require understanding the governing hydrologic and geomorphic processes that control sediment source, storage, and transport. A conceptual model is proposed to describe dominant hydrologic-sediment connectivity regimes through spatial-temporal feedbacks between hydrologic processes (rainfall, flow routing, and water residence time) and geomorphic drivers (upland soil erosion and deposition, and geomorphic channel erosion and deposition response). Recent advancements in landscape monitoring techniques using geochemical tracers, remote-sensing, increasing availability of hydrologic monitoring data, and the integration of various analytic methods (e.g., isotopic hydrograph separation, stormflow concentration-discharge, hysteretic behavior analysis) have the potential to broaden the spatial and temporal scales of geomorphic observations and understanding of landscape sediment connectivity. Using the conceptual model as a “thinking” space, we examine sediment and hydrologic interactions in real world examples of watershed studies using multiple lines of evidence and modeling techniques.

Conference Paper↗
USGS2012

A conceptual model to facilitate amphibian conservation in the northern Great Plains

As pressures on agricultural landscapes to meet worldwide resource needs increase, amphibian populations face numerous threats including habitat destruction, chemical contaminants, disease outbreaks, wetland sedimentation, and synergistic effects of these perturbations. To facilitate conservation planning, we developed a conceptual model depicting elements critical for amphibian conservation in the northern Great Plains. First, we linked upland, wetland, and landscape features to specific ecological attributes. Ecological attributes included adult survival; reproduction and survival to metamorphosis; and successful dispersal and recolonization. Second, we linked ecosystem drivers, ecosystem stressors, and ecological effects of the region to each ecological attribute. Lastly, we summarized information on these ecological attributes and the drivers, stressors, and effects that work in concert to influence the maintenance of viable and genetically diverse amphibian populations in the northern Great Plains. While our focus was on the northern Great Plains, our conceptual model can be tailored to other geographic regions and taxa.

Iowa, Minnesota, Montana, Nebraska, North Dakota, ↗