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At least 145 records · Page 8Linked to original sources
USGS2012

Managing inherent complexity for sustainable walleye fisheries in Lake Erie

In Lake Erie, Walleye ( Sander vitreus vitreus ) is king. The naturally occurring species is the foundation of commercial fishing operations on the Canadian side of the lake and is a much-prized sport fish on the American side. Management of Lake Erie walleye fisheries is complex and takes place in an inter-jurisdictional setting composed of resource agencies from the states of Michigan (MDNR), Ohio (ODNR), Pennsylvania (PFBC), and New York (NYDEC) and the province of Ontario (OMNR). The complexity of walleye management is exacerbated by interactions among environmental and ecological changes in Lake Erie, complex life-history characteristics of the species, public demand for walleye, and cultural/governance differences among managing groups and their respective constituents. Success of future management strategies will largely hinge upon our ability to understand these inherent complexities and to employ tactics that successfully accommodate stock productivity and human demand in a highly dynamic environment. In this report, we review the history of Lake Erie walleye management, outline the multi-jurisdictional process for international management of walleye, and discuss strategies to address challenges facing managers.

Book chapter↗
USGS2020

Shorebird reproductive response to exceptionally early and late springs varies across sites in Arctic Alaska

While increases in overall temperatures are widely reported in the Arctic, large inter-annual variation in spring weather, with extreme early and late conditions, is also occurring. Using data collected from three sites in Arctic Alaska, we explored how shorebird breeding density, nest initiation, nest synchrony, nest survival, and phenological mismatch varied between two exceptionally early (2015 and 2016) and late (2017 and 2018) springs. We assessed these differences in the context of long-term data from each site and whether species exhibited conservative or opportunistic reproductive strategies. Conservative shorebirds typically display nest-site fidelity and territoriality, consistent population densities, relatively even individual spacing, and monogamous mating systems with bi-parental incubation. In contrast, opportunistic shorebirds display the opposite traits, and a polygamous mating system with uniparental incubation. In this study, we evaluated 2,239 nests from 13 shorebird species, 2015–2018, and found that shorebirds of both strategies bred earlier and in higher numbers in early, warm springs relative to historic levels (based on 3,789 nests, 2005–2014); opposite trends were observed in late springs. In early springs, nests were initiated less synchronously than in late springs. Nest survival was unrelated to spring type, but was greater in earlier laid nests overall. Invertebrate food resources emerged earlier in early springs, resulting in a greater temporal asynchrony between invertebrate emergence and chick hatching in early than late springs. However, invertebrate abundance was quite variable among sites and years regardless of spring type. Overall, our results were generally consistent with predicted relationships between spring conditions and reproductive parameters. However, we detected differences among sites that could not be explained by other ecological factors (e.g., predators or alternative prey). Differences in shorebird community composition and other subtler methodological/ecological differences among sites highlight the difficulty of understanding the complex nature of these ecological systems and the importance of evaluating questions at multiple sites across multiple years. Our study demonstrates that shorebirds exhibit a high degree of behavioral flexibility in response to variable Arctic conditions, but whether this flexibility is enough to allow them to optimally track changing environmental conditions or if evolutionary adjustments will be necessary is unknown.

Alaska↗
USGS2009

Quantifying ecological, morphological, and genetic variation to delimit species in the coast horned lizard species complex (Phrynosoma)

Lineage separation and divergence form a temporally extended process whereby populations may diverge genetically, morphologically, or ecologically, and these contingent properties of species provide the operational criteria necessary for species delimitation.We inferred the historical process of lineage formation in the coast horned lizard (Phrynosoma coronatum) species complex by evaluating a diversity of operational species criteria, including divergence in mtDNA (98 specimens; 2,781 bp) and nuclear loci (RAG-1, 1,054 bp; BDNF 529 bp), ecological niches (11 bioclimatic variables; 285 unique localities), and cranial horn shapes (493 specimens; 16 landmarks). A phylogenetic analysis of mtDNA recovers 5 phylogeographic groups arranged latitudinally along the Baja California Peninsula and in California. The 2 southern phylogeographic groups exhibit concordance between genetic, morphological, and ecological divergence; however, differentiation is weak or absent at more recent levels defined by phylogeographic breaks in California. Interpreting these operational species criteria together suggests that there are 3 ecologically divergent and morphologically diagnosable species within the P. coronatum complex. Our 3-species taxonomic hypothesis invokes a deep coalescence event when fitting the mtDNA genealogy into the species tree, which is not unexpected for populations that have diverged recently. Although the hypothesis that the 3 phylogeographic groups distributed across California each represent distinctive species is not supported by all of the operational species criteria evaluated in this study, the conservation status of the imperiled populations represented by these genealogical units remains critical.

Proceedings of the National Academy of Sciences of↗
USGS2025

Mapping predicted ecological states at landscape scales using remote sensing data and machine learning

Dryland ecosystems, covering 45% of the Earth's land and supporting over one-third of the global population, face significant threats from land degradation and ecological state change. Managing these ecosystems is complex, and science-based frameworks like Ecological Site Descriptions and state-and-transition models are essential tools for guiding decisions to support ecological health while maintaining stakeholder values such as grazing, wildlife, and recreation. However, alignment of these frameworks with smaller scale soil survey maps limits their applicability to broader ecological processes. Here, we extend these frameworks to larger landscapes with a machine learning approach that integrates large-scale, high-resolution vegetation data with identified ecological states from a data-driven state-and-transition model developed for a landscape-scale Ecological Site Group. A “global” model, which used combined inputs from multiple remotely sensed datasets, outperformed individual dataset models based on evaluation with independent data. Ecological state maps generated through this approach broaden the utility of state-and-transition models across Ecological Site Groups, providing a more spatially robust tool for land management at watershed and larger landscape scales. These methods, and the associated ecological state maps, can help meet critical needs for improved land condition assessments that support development of resource management plans and help identify priority areas for restoration and conservation.

Arizona, Colorado, New Mexico, Utah, Wyoming↗
USGS2020

Simulation modeling of complex climate, wildfire, and vegetation dynamics to address wicked problems in land management

Complex, reciprocal interactions among climate, disturbance, and vegetation dramatically alter spatial landscape patterns and influence ecosystem dynamics. As climate and disturbance regimes shift, historical analogs and past empirical studies may not be entirely appropriate as templates for future management. The need for a better understanding of the potential impacts of climate changes on ecosystems is reaching a new level of urgency, especially in highly perturbed or vulnerable ecological systems. Simulation models are extremely useful tools for guiding management decisions in an era of rapid change, thus providing potential solutions for wicked problems in land management—those that are difficult to solve and inherently resistant to easily definable solutions. We identify three experimental approaches for landscape modeling that address management challenges in the context of uncertain climate futures and complex ecological interactions: (1) an historical comparative approach, (2) a future comparative approach, and (3) threshold detection. We provide examples of each approach from previously published studies of simulated climate, disturbance, and landscape dynamics in forested landscapes of the western United States, modeled with the FireBGCv2 ecosystem process model. Cumulatively, model outcomes indicate that typical land management strategies will likely not be sufficient to counteract the impacts of rapid climate change and altered disturbance regimes that threaten the stability of ecosystems. Without implementation of new, adaptive management strategies, future landscapes are very likely to be different than historical or contemporary ones, with significant and sometimes persistent changes triggered by interactions of climate and wildfire.

Montana, New Mexico, Wyoming↗
USGS2013

LANDFIRE 2010 - updated data to support wildfire and ecological management

Wildfire is a global phenomenon that affects human populations and ecosystems. Wildfire effects occur at local to global scales impacting many people in different ways (Figure 1). Ecological concerns due to land use, fragmentation, and climate change impact natural resource use, allocation, and conservation. Access to consistent and current environmental data is a constant challenge, yet necessary for understanding the complexities of wildfire and ecological management. Data products and tools from the LANDFIRE Program help decision-makers to clarify problems and identify possible solutions when managing fires and natural resources. LANDFIRE supports the reduction of risk from wildfire to human lives and property, monitoring of fire danger, prediction of fire behavior on active incidents, and assessment of fire severity and impacts on natural systems [1] [2] [3]. LANDFIRE products are unique in that they are nationally consistent and provide the only complete geospatial dataset describing vegetation and wildland fuel information for the entire U.S. As such, LANDFIRE data are useful for many ecological applications [3]. For example, LANDFIRE data were recently integrated into a decision-support system for resource management and conservation decision-making along the Appalachian Trail. LANDFIRE is a joint effort between the U.S. Department of the Interior Office of Wildland Fire, U.S. Department of Agriculture Forest Service Fire & Aviation Management, and The Nature Conservancy. To date, seven versions of LANDFIRE data have been released, with each successive version improving the quality of the data, adding additional features, and/or updating the time period represented by the data. The latest version, LANDFIRE 2010 (LF 2010), released mid-2013, represents circa 2010 landscape conditions and succeeds LANDFIRE 2008 (LF 2008), which represented circa 2008 landscape conditions. LF 2010 used many of the same processes developed for the LF 2008 effort [3]. Ongoing refinement of the LANDFIRE vegetation and fuel data is necessary to improve the quality and usability of the data and to capture landscape disturbance. LANDFIRE relies on Landsat multi-spectral imagery to produce and update vegetation and fuel data. The deep Landsat archive provides data needed for vegetation classification, change analysis, and historical disturbance characterization, for which LANDFIRE has used more than 24,000 image scenes since the program’s inception. In addition, LF 2010 used airborne and spaceborne lidar, and spaceborne synthetic aperture radar (SAR) to map vegetation structure in areas where ground-based field information was lacking, including Alaska and U.S.-affiliated islands in the Caribbean and the Pacific. The mapping of insular areas is new for the 2010 data release; previous versions of LANDFIRE were limited to the conterminous U.S., Alaska, and Hawaii.

Earthzine↗
USGS2024

White-tailed deer detection rates increase when coyotes are present

Predator species can indirectly affect prey species through the cost of anti-predator behavior responses, which may involve shifts in occupancy, space use, or movement. Quantifying the various strategies implemented by prey species to avoid adverse interactions with predators can lead to a better understanding of potential population-level repercussions. Therefore, the purpose of this study was to examine predator–prey interactions by quantifying the effect of predator species presence on detection rates of prey species, using coyotes ( Canis latrans ) and white-tailed deer ( Odocoileus virginianus ) in Central Appalachian forests of the eastern United States as a model predator–prey system. To test two competing hypotheses related to interspecific interactions, we modeled species detections from 319 camera traps with a two-species occupancy model that incorporated a continuous-time detection process. We found that white-tailed deer occupancy was independent of coyote occupancy, but white-tailed deer were more frequently detectable and had greater detection intensity at sites where coyotes were present, regardless of vegetation-related covariates. In addition, white-tailed deer detection rates at sites with coyotes were highest when presumed forage availability was relatively low. These findings suggest that white-tailed deer may be exhibiting an active avoidance behavioral response to predators by increasing movement rates when coyotes are present in an area, perhaps due to reactive evasive maneuvers and/or proactive attempts to reduce adverse encounters with them. Concurrently, coyotes could be occupying sites with higher white-tailed deer densities. Because white-tailed deer did not exhibit significant shifts in daily activity patterns based on coyote occupancy, we further suggest that white-tailed deer in our study system generally do not use temporal partitioning as their primary strategy for avoiding encounters with coyotes. Overall, our study implements a recently developed analytical approach for modeling multi-species occupancy from camera traps and provides novel ecological insight into the complex relationships between predator and prey species.

Pennsylvania, West Virginia↗
USGS2025

Groundwater structures fish growth and production across a riverscape

Landscapes are composed of habitat patches and conditions that vary across space and time. While habitat variability and complexity can support important ecological processes and ecosystem services, the dynamic nature of habitats can also constrain organismal growth and production as optimal conditions are fleeting. In riverine ecosystems, groundwater discharge to streams stabilises water temperature and flow regimes, thus mediating how habitat complexity is expressed. Yet, how stable habitats structure growth and production within the broader landscape matrix is not well understood. In this study, we explored the effects of groundwater on spatiotemporal variation in growth and production for juvenile Yellowstone cutthroat trout ( Oncorhynchus virginalis bouvieri ) across the upper Snake River catchment, Wyoming, USA. We combined machine learning techniques and remotely sensed landscape data to estimate groundwater availability across the river network, which we linked to stream temperature regimes and conspecific density. We then used Bayesian hierarchical models to quantify the effects of temperature, density and groundwater on spatiotemporal variation in fish growth and production in 52 focal reaches. Finally, we predicted body size trajectories and trends in total production continuously over both space and time to understand the effect of groundwater at the riverscape scale. Groundwater discharged to streams where topography changes abruptly in valley-bottom areas underlain by coarse glacial deposits. Groundwater stabilised temperature regimes and was associated with high trout densities. Temperature and density, in turn, interacted to influence growth rates: growth increased strongly with temperature, but this effect was reduced when density was high. Accordingly, variation in groundwater availability among stream reaches diversified growth and production regimes. In reaches with low groundwater availability, growth and production declined over time from summer maxima. In contrast, in reaches with high groundwater availability, temporal trends in growth and production were hump-shaped—peaking in autumn—and mean production was greater. At the riverscape scale, temporal asynchrony in growth rates generated convergent spatial variation in growth capacity, but—when combined with density—led to the formation of distinct hotspots of production. Our results demonstrate how groundwater, an important driver of aquatic ecosystem heterogeneity, structures trout growth and production across space and time. Importantly, rare, but stable habitats may disproportionately affect ecological processes and serve as key sources of population diversity at larger spatial scales.

Wyoming↗
USGS2010

Ecological hierarchies and self-organisation - Pattern analysis, modelling and process integration across scales

A continuing discussion in applied and theoretical ecology focuses on the relationship of different organisational levels and on how ecological systems interact across scales. We address principal approaches to cope with complex across-level issues in ecology by applying elements of hierarchy theory and the theory of complex adaptive systems. A top-down approach, often characterised by the use of statistical techniques, can be applied to analyse large-scale dynamics and identify constraints exerted on lower levels. Current developments are illustrated with examples from the analysis of within-community spatial patterns and large-scale vegetation patterns. A bottom-up approach allows one to elucidate how interactions of individuals shape dynamics at higher levels in a self-organisation process; e.g., population development and community composition. This may be facilitated by various modelling tools, which provide the distinction between focal levels and resulting properties. For instance, resilience in grassland communities has been analysed with a cellular automaton approach, and the driving forces in rodent population oscillations have been identified with an agent-based model. Both modelling tools illustrate the principles of analysing higher level processes by representing the interactions of basic components.The focus of most ecological investigations on either top-down or bottom-up approaches may not be appropriate, if strong cross-scale relationships predominate. Here, we propose an 'across-scale-approach', closely interweaving the inherent potentials of both approaches. This combination of analytical and synthesising approaches will enable ecologists to establish a more coherent access to cross-level interactions in ecological systems. ?? 2010 Gesellschaft f??r ??kologie.

Basic and Applied Ecology↗
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↗
USGS2013

Social-ecological predictors of global invasions and extinctions

Most assessments of resilience have been focused on local conditions. Studies focused on the relationship between humanity and environmental degradation are rare, and are rarely comprehensive. We investigated multiple social-ecological factors for 100 countries around the globe in relation to the percentage of invasions and extinctions within each country. These 100 countries contain approximately 87% of the world’s population, produce 43% of the world’s per capita gross domestic product (GDP), and take up 74% of the earth’s total land area. We used an information theoretic approach to determine which models were most supported by our data, utilizing an a priori set of plausible models that included a combination of 15 social-ecological variables, each social-ecological factor by itself, and selected social-ecological factors grouped into three broad classes. These variables were per capita GDP, export-import ratio, tourism, undernourishment, energy efficiency, agricultural intensity, rainfall, water stress, wilderness protection, total biodiversity, life expectancy, adult literacy, pesticide regulation, political stability, and female participation in government. Our results indicate that as total biodiversity and total land area increase, the percentage of endangered birds also increases. As the independent variables (agricultural intensity, rainfall, water stress, and total biodiversity) in the ecological class model increase, the percentage of endangered mammals in a country increases. The percentage of invasive birds and mammals in a country increases as per capita GDP increases. As life expectancy increases, the percentage of invasive and endangered birds and mammals increases. Although our analysis does not determine mechanisms, the patterns observed in this study provide insight into the dynamics of a complex, global, social-ecological system.

Ecology and Society↗
USGS2018

Land use diversification and intensification on elk winter range in Greater Yellowstone: A framework and agenda for social-ecological research

Amenity migration describes the movement of peoples to rural landscapes and the transition toward tourism and recreation and away from production-oriented land uses (ranching, timber harvesting). The resulting mosaic of land uses and community structures has important consequences for wildlife and their management. This research note examines amenity-driven changes to social-ecological systems in the Greater Yellowstone Ecosystem, specifically in lower elevations that serve as winter habitat for elk. We present a research agenda informed by a preliminary and exploratory mixed-methods investigation: the creation of a “social-impact” index of land use change on elk winter range and a focus group with wildlife management experts. Our findings suggest that elk are encountering an increasingly diverse landscape with respect to land use, while new ownership patterns increase the complexity of social and community dynamics. These factors, in turn, contribute to increasing difficulty meeting wildlife management objectives. To deal with rising complexity across social and ecological landscapes of the Greater Yellowstone Ecosystem, future research will focus on property life cycle dynamics, as well as systems approaches.

Rangeland Ecology and Management↗
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↗
USGS2014

Identifying legal, ecological and governance obstacles and opportunities for adapting to climate change

Current governance of regional scale water management systems in the United States has not placed them on a path toward sustainability, as conflict and gridlock characterize the social arena and ecosystem services continue to erode. Changing climate may continue this trajectory, but it also provides a catalyst for renewal of ecosystems and a window of opportunity for change in institutions. Resilience provides a bridging concept that predicts that change in ecological and social systems is often dramatic, abrupt, and surprising. Adapting to the uncertainty of climate driven change must be done in a manner perceived as legitimate by the participants in a democratic society. Adaptation must begin with the current hierarchical and fragmented social-ecological system as a baseline from which new approaches must be applied. Achieving a level of integration between ecological concepts and governance requires a dialogue across multiple disciplines, including ecologists with expertise in ecological resilience, hydrologists and climate experts, with social scientists and legal scholars. Criteria and models that link ecological dynamics with policies in complex, multi-jurisdictional water basins with adaptive management and governance frameworks may move these social-ecological systems toward greater sustainability.

Sustainability↗
USGS2007

Using simulated historical time series to prioritize fuel treatments on landscapes across the United States: The LANDFIRE prototype project

Canopy and surface fuels in many fire-prone forests of the United States have increased over the last 70 years as a result of modern fire exclusion policies, grazing, and other land management activities. The Healthy Forest Restoration Act and National Fire Plan establish a national commitment to reduce fire hazard and restore fire-adapted ecosystems across the USA. The primary index used to prioritize treatment areas across the nation is Fire Regime Condition Class (FRCC) computed as departures of current conditions from the historical fire and landscape conditions. This paper describes a process that uses an extensive set of ecological models to map FRCC from a departure statistic computed from simulated time series of historical landscape composition. This mapping process uses a data-driven, biophysical approach where georeferenced field data, biogeochemical simulation models, and spatial data libraries are integrated using spatial statistical modeling to map environmental gradients that are then used to predict vegetation and fuels characteristics over space. These characteristics are then fed into a landscape fire and succession simulation model to simulate a time series of historical landscape compositions that are then compared to the composition of current landscapes to compute departure, and the FRCC values. Intermediate products from this process are then used to create ancillary vegetation, fuels, and fire regime layers that are useful in the eventual planning and implementation of fuel and restoration treatments at local scales. The complex integration of varied ecological models at different scales is described and problems encountered during the implementation of this process in the LANDFIRE prototype project are addressed.

Ecological Modelling↗
USGS2021

An integrated path for spatial capture–recapture and animal movement modeling

Ecologists and conservation biologists increasingly rely on spatial capture–recapture (SCR) and movement modeling to study animal populations. Historically, SCR has focused on population-level processes (e.g., vital rates, abundance, density, and distribution), whereas animal movement modeling has focused on the behavior of individuals (e.g., activity budgets, resource selection, migration). Even though animal movement is clearly a driver of population-level patterns and dynamics, technical and conceptual developments to date have not forged a firm link between the two fields. Instead, movement modeling has typically focused on the individual level without providing a coherent scaling from individual- to population-level processes, whereas SCR has typically focused on the population level while greatly simplifying the movement processes that give rise to the observations underlying these models. In our view, the integration of SCR and animal movement modeling has tremendous potential for allowing ecologists to scale up from individuals to populations and advancing the types of inferences that can be made at the intersection of population, movement, and landscape ecology. Properly accounting for complex animal movement processes can also potentially reduce bias in estimators of population-level parameters, thereby improving inferences that are critical for species conservation and management. This introductory article to the Special Feature reviews recent advances in SCR and animal movement modeling, establishes a common notation, highlights potential advantages of linking individual-level (Lagrangian) movements to population-level (Eulerian) processes, and outlines a general conceptual framework for the integration of movement and SCR models. We then identify important avenues for future research, including key challenges and potential pitfalls in the developments and applications that lie ahead.

Ecology↗
USGS2020

Ecological risk assessment of environmental stress and bioactive chemicals to riverine fish populations: An individual-based model of smallmouth bass Micropterus dolomieu

Ecological risk assessments play an important role in environmental management and decision-making. Although empirical measurements of the effects of habitat changes and chemical exposure are often made at molecular and individual levels, environmental decision-making often requires the quantification of management-relevant, population-level outcomes. In this study, we generalized a modeling framework to evaluate population-level ecological risk of environmental stress and bioactive chemicals. The modeling framework includes (1) a biological model module that incorporates complex and interacting biological and ecological processes, and environmental stochasticity, (2) an effect module that links the impacts of environmental changes and chemical exposure to individual characteristics, and (3) a population module that makes decisions on the choice of population-level properties to best capture the effects and thus to track in the model based on the target species and the research and management interest. This framework is a 3-module procedure that provides an alternative way for researchers to organize, present and communicate the risk assessment modeling studies. To demonstrate this framework, we used a socioeconomically important riverine fish species, smallmouth bass Micropterus dolomieu , as the model species. We developed an individual-based model as the biological model module. We evaluated the impacts of changing water temperature and flow regimes, and the impacts of exposure to estrogenic endocrine disrupting compounds (EEDC) on smallmouth bass populations in the Chesapeake Bay Watershed, USA. Warm summer water temperatures and year-round high flows had the most severe impacts on the smallmouth bass population. An increase in exposure level to EEDC, both year-round and in summer months, substantially reduced population size, spawner and recruit abundance, and the proportion of quality-length individuals. Acute exposure to EEDC was more detrimental to the population than chronic exposure. Acute exposure during spawning season had the most severe impacts. This modeling framework can be extended to other species, environmental factors and chemicals, and can be used to inform management and conservation decisions.

Delaware, Maryland, New York, Pennsylvania, Virgin↗
USGS2021

Diel patterns of predation and fledging at nests of four species of grassland songbirds

Although it is common for nestlings to exhibit a strong bias for fledging in the morning, the mechanisms underlying this behavior are not well understood. Avoiding predation risk has been proposed as a likely mechanism by a number of researchers. We used video surveillance records from studies of grassland birds nesting in North Dakota, Minnesota, and Wisconsin to determine the diel pattern of nest predation and fledging patterns of four ground-nesting obligate grassland passerines (Grasshopper Sparrow ( Ammodramus savannarum ), Savannah Sparrow ( Passerculus sandwichensis ), Bobolink ( Dolichonyx oryzivorus ), and Eastern Meadowlark ( Sturnella magna )). We used the nest predation pattern as a surrogate for predation activity to test whether nestlings minimized predation risk by avoiding fledging when predation activity was high and preferentially fledging when predation risk was low. Predation activity was significantly lower starting 3 hr before sunrise and ending 3 hr after sunrise, followed by a transition to a period of significantly higher activity lasting for 4 hr, before declining to an average activity level for the rest of the diel period. There was little evidence that the four grassland bird species avoided fledging during the high-risk period and Savannah Sparrow fledged at higher rates during that period. All four species had hours during the low-risk period where they fledged at higher rates, but only Grasshopper Sparrow fledged preferentially during that period. Bobolink and Eastern Meadowlark had multiple hours with high fledging rates throughout the daytime period, resulting in no relationship between probability of fledging and predation risk. Given the species variability in fledging pattern seen in our study, it is unlikely that there is a universal response to any driver that affects time of fledging. Further study is needed to understand the complex interplay between species ecology and drivers such as physiology, energetics, and predation in affecting grassland bird fledging behavior.

Minnesota, North Dakota, Wisconsin↗