USGS Science⌕ Search

SEARCH · USGS Science

Results for “Range Ecology & Management”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15Linked to original sources

A spatial model of streaked horned lark breeding habitat in the Columbia River, USA

The streaked horned lark (hereafter “lark”; Eremophila alpestris strigata ) is a federally listed bird subspecies of the Pacific Northwest that occupies open landscapes with short vegetation and abundant bare ground. Across its breeding range, which has contracted dramatically, the lark relies primarily on human-modified habitats maintained in early successional states (e.g., agricultural fields, airfields, deposition islands). The focus of our study is the lower Columbia River where larks primarily occupy deposition islands created as a byproduct of shipping channel deepening (dredging) projects. The U.S. Army Corps of Engineers has proactively adopted a shifting-habitat-mosaic management approach when placing dredge (sand) materials to maintain lark habitat throughout the project area. To help achieve their goal, we created a geospatial tool capable of quantifying and tracking habitat suitability for larks throughout the project area with satellite imagery. We created spatial models of lark breeding habitat by incorporating lark survey data, Sentinel-2 satellite imagery, dredge-deposition maps, and surface-elevation models. We built candidate predictive models of lark breeding habitat after combining survey data (years 2016 and 2017), predictor variables, and logistic regression. In addition, we created a novel seral-stage predictor variable to identify young, mature, old, and unsuitable locations; critical information for lark conservation planning and dredge-disposal operational planning. We challenged probability models the year they were constructed (2016) and the following year (2017) with set-aside survey data. The best model contained terrain ruggedness, deposition age, vegetation greenness (e.g., lushness and density of vegetation) inside a 10-m cell, and heterogeneity in greenness within a 100-m radius. Verification accuracy ranged from 75 to 83% depending on the model tested and year. Importantly, the seral-stage variable allowed us to quantify and locate early, optimal, and late habitats. Model results will facilitate conservation planning decisions by informing real-time management decisions. Furthermore, they provide a foundation for application in other human-modified habitats across the species’ range.

Oregon↗

Estimating landscape carrying capacity through maximum clique analysis

Habitat suitability (HS) maps are widely used tools in wildlife science and establish a link between wildlife populations and landscape pattern. Although HS maps spatially depict the distribution of optimal resources for a species, they do not reveal the population size a landscape is capable of supporting--information that is often crucial for decision makers and managers. We used a new approach, "maximum clique analysis," to demonstrate how HS maps for territorial species can be used to estimate the carrying capacity, N(k), of a given landscape. We estimated the N(k) of Ovenbirds (Seiurus aurocapillus) and bobcats (Lynx rufus) in an 1153-km2 study area in Vermont, USA. These two species were selected to highlight different approaches in building an HS map as well as computational challenges that can arise in a maximum clique analysis. We derived 30-m2 HS maps for each species via occupancy modeling (Ovenbird) and by resource utilization modeling (bobcats). For each species, we then identified all pixel locations on the map (points) that had sufficient resources in the surrounding area to maintain a home range (termed a "pseudo-home range"). These locations were converted to a mathematical graph, where any two points were linked if two pseudo-home ranges could exist on the landscape without violating territory boundaries. We used the program Cliquer to find the maximum clique of each graph. The resulting estimates of N(k) = 236 Ovenbirds and N(k) = 42 female bobcats were sensitive to different assumptions and model inputs. Estimates of N(k) via alternative, ad hoc methods were 1.4 to > 30 times greater than the maximum clique estimate, suggesting that the alternative results may be upwardly biased. The maximum clique analysis was computationally intensive but could handle problems with < 1500 total pseudo-home ranges (points). Given present computational constraints, it is best suited for species that occur in clustered distributions (where the problem can be broken into several, smaller problems), or for species with large home ranges relative to grid scale where resampling the points to a coarser resolution can reduce the problem to manageable proportions.

Ecological Applications↗

Networks - The assessment of marine reserve networks: Guidelines for ecological evaluation

As marine ecosystems are plagued by an ever-increasing suite of threats including climate change, pollution, habitat degradation, and fisheries impacts (Roessig et al ., 2004; Lotze et al ., 2006; Jackson, 2008), there are now no ocean areas that are exempt from anthropogenic impacts (Halpern et al ., 2008). In order to preserve marine biodiversity, ecosystem function, and the goods and services provided by resistant and/or resilient systems, marine reserves have been increasingly recommended as part of an ecosystem-based approach to management (Browman and Stergiou, 2004; Levin et al ., 2009). Marine reserves are defined as “areas of the ocean completely protected from all extractive and destructive activities” (Lubchenco et al ., 2003) and can be experimental controls for evaluating the impact of these activities on marine ecosystems. Growing scientific information has shown consistent increases in species density, biomass, size, and diversity in response to full protection inside reserves of varying sizes and ages located in diverse regions (Claudet et al ., 2008; Lester et al ., 2009; Molloy et al ., 2009). However, most of these data are from individual marine reserves and therefore have inherently limited transferability to networks of marine reserves, which when properly designed can outperform single marine reserves for a variety of ecological, economic, and social management goals (Roberts et al ., 2003; Almany et al ., 2009; Gaines et al ., 2010). The concept of marine reserve networks grew out of a desire to achieve both conservation and fishery management goals by minimizing the potential negative economic, social, and cultural impacts of a single large reserve while still producing similar or even greater ecological and economic returns (Murray et al ., 1999; Gaines et al ., 2010). In addition, reserves networks can provide insurance by protecting areas across a region and spreading the risk that these sites may be impacted by localized catastrophes such as hurricanes or oil spills (Allison et al ., 2003). The World Conservation Union's Marine Programme defines a network as “a collection of individual marine protected areas (MPAs) or reserves operating co-operatively and synergistically, at various spatial scales and with a range of protection levels that are designed to meet objectives that a single reserve cannot achieve” (IUCN–WCPA, 2008). However, general terms such as “co-operatively” and “synergistically” can have myriad meanings. Without a clear definition of a network, it becomes difficult to identify attainable management goals and design a process for evaluating whether the network achieves those goals. Besides, different management goals may in turn result in the need for different types of networks. The use of MPAs with varying protection levels together with no-take zones in multiple-zoning schemes adds another layer of complexity to network design and evaluation; however, partially protected areas are generally used to manage coastal uses and avoid conflicts (rather than for strict ecological purposes) and are therefore a function of the local social, economic, and cultural context. As we are here interested in the ecological effects of networks, for the purposes of this chapter, we focus on marine reserves because these areas are no-take and therefore offer greater ecological benefits than other types of MPAs that allow some forms of extraction (Lester and Halpern, 2008).

Book chapter↗

Sediment classification and the characterization, identification, and mapping of geologic substrates for the glaciated Gulf of Maine seabed and other terrains, providing a physical framework for ecological research and seabed management

A geologic substrate is a surface (or volume) of sediment or rock where physical, chemical, and biological processes occur, such as the movement and deposition of sediment, the formation of bedforms, and the attachment, burrowing, feeding, reproduction, and sheltering of organisms. Seabed mapping surveys in the Stellwagen Bank region off Boston, Massachusetts, from 1993 to 2004 have led to the development of a methodology for characterizing, identifying, and mapping geologic substrates. The resulting high-resolution interpretive maps (1:25,000) show the distribution of substrates in a glaciated terrain of banks and basins in water depths of 30 to 185 meters. Data sources used to characterize substrates are multibeam sonar bathymetric and backscatter imagery to document seabed topography and patterns of sediment and rock distribution, grain-size analyses of sediment samples to determine substrate composition, and video and photographic imagery of the seabed to aid in the interpretation of multibeam sonar imagery and to provide information on substrate layering and mobility, seabed structures, and sediments and nonsediment materials that cannot be physically sampled. Sediment composition is a major property of many seabed substrates. Sediment grains belong to a continuum of grain-diameter sizes previously classified into grades (for example, fine sand, medium sand) and into aggregates (mud, sand, gravel). The definition of grade and aggregate boundaries in a classification is arbitrary, and a useful classification is limited to as few classes as are needed to effectively organize and apply information. For the purpose of mapping substrates, sediment grades and aggregates were simplified and re-classified into eight composite grades based on grain-size content, mode of transport, and ecological role. Five composite grades are identified using grain-size analysis and three are identified using video and photographic imagery of the seabed. Naturally occurring sediments contain various amounts of the aggregates mud, sand, and gravel. The separation of naturally occurring sediments into sediment classes, based on grain-size analysis, requires that limits be set on the amount of mud, sand, and gravel each class contains. Fifteen previously identified basic sediment classes provided interpretive information on sediment transport by emphasizing gravel content (a low 0.01-weight-percent threshold) and on winnowing processes based on the sand-to-mud ratio. The present study recognizes 20 basic sediment classes that are combinations of aggregates in which the lower limits for recognition of mud and sand are 10 weight percent and of gravel, 25 weight percent. These sediment classes can be made more specific by listing their content of the composite grades fine-grained sand (3 and 4 phi), which is transported in suspension, and coarse-grained sand (0, 1, and 2 phi), which is transported as bedload. Additional sediment classes and nonsediment classes that cannot be sampled are recognized on the basis of visual analysis of seabed video and photographic imagery and include pebble, cobble, and boulder gravel, rock outcrops, and shell beds, among others. Substrates are not classified because their properties are too varied for a classification to be concise and useful. Rather, substrates are characterized and identified by sediment grain-size composition (the sediment class); the distribution, in millimeters, of grain diameters in the sediment; the presence of nonsediments (for example, rock outcrops); substrate mobility based on the presence of sediment ripples; substrate layering (for example, a partial veneer of sand on gravel); and seabed structures. These properties have interpretive value by providing information about sedimentary processes acting on a substrate and about its ecological function. A geologic substrate, when it is associated with one or more species, is an important element of a habitat. This methodology was developed to map a glaciated terrain characterized by geologic substrates that typify a wide range of erosional and depositional sedimentary environments, and it likely will be useful for mapping substrates in other terrains. Substrate maps provide the physical framework required for identifying sediment transport processes, validating sediment transport models, studying the ecology of species and communities, and managing marine resources and seabed usage.

Massachusetts↗

Lower lethal temperatures for nonnative freshwater fishes in Everglades National Park, Florida

Temperature is an important factor that shapes biogeography and species composition. In southern Florida, the tolerance of nonnative freshwater fishes to low temperatures is a critical factor in delineating their geographic spread. In this study, we provide empirical information on experimentally derived low-temperature tolerance limits of Banded Cichlid Heros severus and Spotfin Spiny Eel Macrognathus siamensis, two nonnative Everglades fishes that were lacking data, and African Jewelfish Hemichromis letourneuxi and Mayan Cichlid Cichlasoma urophthalmus, species for which previous results were derived from studies with small sample sizes. We also provide a literature review summarizing the current state of knowledge of low-temperature tolerances for all 17 nonnative freshwater fishes that have been found in Everglades National Park. Mean lower lethal temperature tolerances ranged from 4°C (Orinoco Sailfin Catfish Pterygoplichthys multiradiatus) to 16.1°C (Butterfly Peacock Bass Cichla ocellaris). These low-temperature limits may inform the understanding of the ecological role or influence of nonnative fishes and may lead to potential management opportunities and applications.

Florida↗

Second chance for the plains bison

Before European settlement the plains bison ( Bison bison bison ) numbered in the tens of millions across most of the temperate region of North America. Within the span of a few decades during the mid- to late-1800s its numbers were reduced by hunting and other factors to a few hundred. The plight of the plains bison led to one of the first major movements in North America to save an endangered species. A few individuals and the American Bison Society rescued the remaining animals. Attempts to hybridize cattle and bison when bison numbers were low resulted in extensive cattle gene introgression in bison. Today, though approximately 500,000 plains bison exist in North America, few are free of cattle gene introgression, 96% are subject to anthropogenic selection for commodity production, and only 4% are in herds managed primarily for conservation purposes. Small herd size, artificial selection, cattle-gene introgression, and other factors threaten the diversity and integrity of the bison genome. In addition, the bison is for all practical purposes ecologically extinct across its former range, with multiple consequences for grassland biodiversity. Urgent measures are needed to conserve the wild bison genome and to restore the ecological role of bison in grassland ecosystems. Socioeconomic trends in the Great Plains, combined with new information about bison conservation needs and new conservation initiatives by both the public and public sectors, have set the stage for significant progress in bison conservation over the next few years.

Biological Conservation↗

Ecological thresholds as a basis for defining management triggers for National Park Service vital signs: case studies for dryland ecosystems

Threshold concepts are used in research and management of ecological systems to describe and interpret abrupt and persistent reorganization of ecosystem properties (Walker and Meyers, 2004; Groffman and others, 2006). Abrupt change, referred to as a threshold crossing, and the progression of reorganization can be triggered by one or more interactive disturbances such as land-use activities and climatic events (Paine and others, 1998). Threshold crossings occur when feedback mechanisms that typically absorb forces of change are replaced with those that promote development of alternative equilibria or states (Suding and others, 2004; Walker and Meyers, 2004; Briske and others, 2008). The alternative states that emerge from a threshold crossing vary and often exhibit reduced ecological integrity and value in terms of management goals relative to the original or reference system. Alternative stable states with some limited residual properties of the original system may develop along the progression after a crossing; an eventual outcome may be the complete loss of pre-threshold properties of the original ecosystem. Reverting to the more desirable reference state through ecological restoration becomes increasingly difficult and expensive along the progression gradient and may eventually become impossible. Ecological threshold concepts have been applied as a heuristic framework and to aid in the management of rangelands (Bestelmeyer, 2006; Briske and others, 2006, 2008), aquatic (Scheffer and others, 1993; Rapport and Whitford 1999), riparian (Stringham and others, 2001; Scott and others, 2005), and forested ecosystems (Allen and others, 2002; Digiovinazzo and others, 2010). These concepts are also topical in ecological restoration (Hobbs and Norton 1996; Whisenant 1999; Suding and others, 2004; King and Hobbs, 2006) and ecosystem sustainability (Herrick, 2000; Chapin and others, 1996; Davenport and others, 1998). Achieving conservation management goals requires the protection of resources within the range of desired conditions (Cook and others, 2010). The goal of conservation management for natural resources in the U.S. National Park System is to maintain native species and habitat unimpaired for the enjoyment of future generations. Achieving this goal requires, in part, early detection of system change and timely implementation of remediation. The recent National Park Service Inventory and Monitoring program (NPS I&M) was established to provide early warning of declining ecosystem conditions relative to a desired native or reference system (Fancy and others, 2009). To be an effective tool for resource protection, monitoring must be designed to alert managers of impending thresholds so that preventive actions can be taken. This requires an understanding of the ecosystem attributes and processes associated with threshold-type behavior; how these attributes and processes become degraded; and how risks of degradation vary among ecosystems and in relation to environmental factors such as soil properties, climatic conditions, and exposure to stressors. In general, the utility of the threshold concept for long-term monitoring depends on the ability of scientists and managers to detect, predict, and prevent the occurrence of threshold crossings associated with persistent, undesirable shifts among ecosystem states (Briske and others, 2006). Because of the scientific challenges associated with understanding these factors, the application of threshold concepts to monitoring designs has been very limited to date (Groffman and others, 2006). As a case in point, the monitoring efforts across the 32 NPS I&M networks were largely designed with the knowledge that they would not be used to their full potential until the development of a systematic method for understanding threshold dynamics and methods for estimating key attributes of threshold crossings. This report describes and demonstrates a generalized approach that we implemented to formalize understanding and estimating of threshold dynamics for terrestrial dryland ecosystems in national parks of the Colorado Plateau. We provide a structured approach to identify and describe degradation processes associated with threshold behavior and to estimate indicator levels that characterize the point at which a threshold crossing has occurred or is imminent (tipping points) or points where investigative or preventive management action should be triggered (assessment points). We illustrate this method for several case studies in national parks included in the Northern and Southern Colorado Plateau NPS I&M networks, where historical livestock grazing, climatic change, and invasive species are key agents of change. The approaches developed in these case studies are intended to enhance the design, effectiveness, and management-relevance of monitoring efforts in support of conservation management in dryland systems. They specifically enhance National Park Service (NPS) capacity for protecting park resources on the Colorado Plateau but have applicability to monitoring and conservation management of dryland ecosystems worldwide.

Colorado Plateau↗

Southern sea otter range expansion and habitat use in the Santa Barbara Channel, California

The re-colonization of the Santa Barbara channel by sea otters brings these ESA-listed marine mammals closer to active oil and gas production facilities, shipping lanes and naturally occurring oil and gas seeps. However, the degree to which sea otters may actually be affected by human-caused oil spills or exposure to natural oil seeps is currently unknown. Between 2012 and 2014, the U.S. Geological Survey and collaborating agencies conducted a telemetry-based study of sea otters in Santa Barbara channel, in order to provide critical information for resource managers (specifically the Bureau of Ocean Energy Management, henceforth BOEM, and the U.S. Fish and Wildlife Service, henceforth USFWS) about the spatial ecology, population status, and potential population threats to sea otters in Santa Barbara Channel, with particular reference to exposure to manmade structures and sources of oil and natural gas. Analysis of spatial monitoring data using a Bayesian-based synoptic model allowed for description of sea otter home ranges, identification of hot-spots of use, and insights into habitat selection behavior by male and female sea otters. Important findings included the deeper modal depth preferred by males versus females, strong preferences by both sexes for areas with persistent kelp canopy, and greater use of soft-sediment areas by males. The synoptic model also provided the ability to predict population-level density distribution for each sex in new habitats: by calculating the value of these probability density distributions at the known locations of natural seeps, we were able to identify those seeps with higher potential for sea otter encounters. The relative probability of occurrence at locations near to some seeps was sufficiently high (about 1% likelihood of occurrence for some of our study animals) that one would anticipate occasional encounters. Data on male and female survival, reproductive success, activity budgets, and body condition all indicated that sea otters in Santa Barbara Channel are not resource limited, and thus we would expect to see continued strong population growth in this area. However, the principal cause of death for study animals was lethal bites by white sharks, suggesting that shark bite mortality represents the single biggest threat to continued population growth in the Santa Barbara Channel.

California↗

Climate-induced glacier and snow loss imperils alpine stream insects

Climate warming is causing rapid loss of glaciers and snowpack in mountainous regions worldwide. These changes are predicted to negatively impact the habitats of many range-restricted species, particularly endemic, mountaintop species dependent on the unique thermal and hydrologic conditions found only in glacier-fed and snowmelt-driven alpine streams. Though progress has been made, existing understanding of the status, distribution, and ecology of alpine aquatic species, particularly in North America, is lacking, thereby hindering conservation and management programs. Two aquatic insects – the meltwater stonefly Lednia tumana and the glacier stonefly Zapada glacier – were recently proposed for listing under the U.S. Endangered Species Act due to climate-change-induced habitat loss. Using a large dataset (272 streams, 482 total sites) with high-resolution climate and habitat information, we describe the distribution, status, and key environmental features that limit L. tumana and Z. glacier across the northern Rocky Mountains. Lednia tumana was detected in 113 streams (175 sites) within Glacier National Park (GNP) and surrounding areas. The probability of L. tumana occurrence increased with cold stream temperatures and close proximity to glaciers and permanent snowfields. Similarly, densities of L. tumana declined with increasing distance from stream source. Zapada glacier was only detected in 10 streams (20 sites), six in GNP and four in mountain ranges up to ~600 km southwest. Our results show that both L. tumana and Z. glacier inhabit an extremely narrow distribution, restricted to short sections of cold, alpine streams often below glaciers predicted to disappear over the next two decades. Climate warming-induced glacier and snow loss clearly imperils the persistence of L. tumana and Z. glacier throughout their ranges, highlighting the role of mountaintop aquatic invertebrates as sentinels of climate change in mid-latitude regions.

Global Change Biology↗

The influence of layout on Appalachian Trail soil loss, widening, and muddiness: Implications for sustainable trail design and management

This research investigates the influence of layout and design on the severity of trail degradation. Previous trail studies have been restricted by relatively small study areas which provide a limited range of environmental conditions and therefore produce findings with limited applicability; this research improves on this limitation by analyzing a representative sample of the Appalachian Trail with significant topographical, ecological, use-related, and managerial diversity. Many trail science studies have also focused on a singular form of trail degradation, whereas this study investigates all three core types of trail impact: trail soil loss, widening and muddiness. Relational analyses with all three indicators provide a more cohesive understanding of trail impact and reveal interrelationships between trail degradation processes. ANOVA testing of the mean values for these trail impact indicators across categories of influential independent factors confirms and refines the relevance of core trail design principles, specifically the sustainability advantages of trails with low grades and side-hill alignments. Findings also reveal and clarify the importance of landform grade in determining the susceptibility of trails to degradation and the influence of routing decisions; these relationships have received relatively little attention in the literature. The results also reveal several methodological considerations for trail alignment metrics and trail impact indicators

Connecticut, Georgia, Maine, Massachusetts, Maryla↗

Physiological responses of Yellowstone bison to winter nutritional deprivation

Because nutrition is critically related to other aspects of bison ( Bison bison ) ecology, and the winter ranges inhabited by bison in Yellowstone National Park (YNP) are ecologically diverse, it was important to determine if nutritional deprivation differences occurred among winter ranges. We used chemistry profiles of urine suspended in snow to compare nutritional deprivation of bison from January to April 1988 on 4 sampling areas of 3 winter ranges in YNP. Declining (P < 0.001) trends of urinary potassium: creatinine ratios in bison on all 4 sampling areas indicated progressive nutritional deprivation through late March. Concurrent increases (P ≤ 0.001) in mean urea nitrogen: creatinine ratios from late February through late march in 3 of 4 areas suggested that increased net catabolism was occurring. Diminished creatinine ratios of sodium and phosphorus reflected low dietary intake of these minerals throughout winter. Mean values and trends of urinary characteristics indicated nutritional deprivation varied among 3 winter ranges in YNP. Continued physiological monitoring of nutritional deprivation, along with detailed examination of other aspects of the bison's ecology, will provide greater insight into the role of ungulate nutrition in the dynamics of such a complex system and improve management.

Journal of Wildlife Management↗

U.S. Geological Survey ecosystems science strategy—Advancing discovery and application through collaboration

Executive Summary Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policymakers are faced with countless decisions each year at local, regional, and national levels on issues as diverse as renewable and nonrenewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decisionmaking is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and wellbeing of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decisionmakers as they develop policies to adapt to these changes. This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that U.S. Geological Survey (USGS) scientists and partners can play in building scientific understanding and providing timely information to decisionmakers. The strategy underscores the connection between scientific discoveries and the application of new knowledge, and it integrates ecosystem science and decisionmaking, producing new scientific outcomes to assist resource managers and providing public benefits. We envision the USGS as a leader in integrating scientific information into decisionmaking processes that affect the Nation’s natural resources and human well-being. The USGS is uniquely positioned to play a pivotal role in ecosystem science. With its wide range of expertise, the Bureau can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the Department of the Interior (DOI) and other partners in the natural sciences, in both conducting science and applying the results. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct. The heart of this strategy is a framework for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected components that reinforce our vision of the USGS providing science that is at the forefront of decisionmaking: Improve understanding of ecosystem structure, function, and processes. The focus for this goal is an understanding of how ecosystems work, including the dynamics of species, their populations, interactions, and genetics, and how they change across spatial and temporal scales. Advance understanding of how drivers influence ecosystem change. The challenges here are explaining the drivers of ecosystem change, their spatio-temporal patterns, their uncertainties and interactions, and their influence on ecosystem processes and dynamics. Improve understanding of the services that ecosystems provide to society. Here the emphasis is on the measurement of environmental capital and ecosystem services, and the identification of sources and patterns of change in space and time. Develop tools, technologies, and capacities to inform decisionmaking about ecosystems. This includes developing new technologies and approaches for conducting applications-oriented ecosystem science. A principal challenge will be how to quantify uncertainty and incorporate it in decision analysis. Apply science to enhance strategies for management, conservation, and restoration of ecosystems. These challenges include development of novel approaches to monitoring, assessment, and restoration of ecosystems; new methods to address species of concern and communities at risk; and innovations in decision analysis and support to address imminent ecosystem changes or those that are underway. Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy: Assess information needs for ecosystem science through enhanced partnerships. Work with the DOI and other agencies and institutions to identify, design, and implement priority decision-driven ecological research. Promote the use of interdisciplinary ecosystem science. Design and conduct interdisciplinary process-oriented research in ecosystem science. Enhance modeling and forecasting. Build models to forecast ecosystem change, assess future management scenarios, and reduce uncertainties through an adaptive learning process. Support decisionmaking. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management. Following the four strategic approaches are a set of proposed actions that represent a sampling of specific USGS activities that align with this strategy and that address the Nation’s most pressing environmental needs. The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio. Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role in guiding sound decisionmaking during the next decade by advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.

Circular↗

The U.S. Geological Survey Ecosystem Science Strategy, 2012-2022 - Advancing discovery and application through collaboration

Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policy-makers are faced with countless decisions each year at local, state, tribal, territorial, and national levels on issues as diverse as renewable and non-renewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decision-making is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and well-being of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decision-makers as they develop policies to adapt to these changes. This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that USGS scientists and partners can play in building scientific understanding and providing timely information to decision-makers. The strategy underscores the connection between scientific discoveries and the application of new knowledge. The strategy integrates ecosystem science and decision-making, producing new scientific outcomes to assist resource managers and providing public benefits. The USGS is uniquely positioned to play an important role in ecosystem science. With its wide range of expertise, the agency can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the DOI and other partners in the natural sciences, in both conducting science and its application. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct. The heart of this strategy is a framework and vision for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected and reinforcing components: • Improve understanding of ecosystem structure, function, and processes. The focus for this goal is an understanding of how ecosystems work, including the dynamics of species, their populations, interactions, and genetics, and how they change across spatial and temporal scales. • Advance understanding of how drivers influence ecosystem change. The challenges here are explaining the drivers of ecosystem change, their spatio-temporal patterns, their uncertainties and interactions, and their influence on ecosystem processes and dynamics. • Improve understanding of the services that ecosystems provide to society. Here the emphasis is on the measurement of environmental capital and ecosystem services, and the identification of sources and patterns of change in space and time. • Develop tools, technologies, and capacities to inform decision-making about ecosystems. This includes developing new technologies and approaches for conducting applications-oriented ecosystem science. A principal challenge will be how to quantify uncertainty and incorporate it in decision analysis. • Apply science to enhance strategies for management, conservation, and restoration of ecosystems. These challenges include development of novel approaches to monitoring, assessment, and restoration of ecosystems; new methods to address species of concern and communities at risk; and innovations in decision analysis and support to address imminent ecosystem changes or those that are underway. Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy: • Assess information needs for ecosystem science through enhanced partnerships. Work with the DOI and other agencies and institutions to identify, design, and implement priority decision-driven ecological research. • Promote the use of interdisciplinary ecosystem science. Design and conduct interdisciplinary process-oriented research in ecosystem science. • Enhance modeling and forecasting. Build models to forecast ecosystem change, assess future management scenarios, and reduce uncertainties through an adaptive learning process. • Support decision-making. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management. Following the strategic approaches are a set of proposed actions that represent a sampling of specific activities that align with this strategy and that address the Nation’s most pressing environmental needs. The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct both discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio. Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role over the next decade in advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.

Open-File Report↗

Streamflow distribution maps for the Cannon River drainage basin, southeast Minnesota, and the St. Louis River drainage basin, northeast Minnesota

Streamflow distribution maps for the Cannon River and St. Louis River drainage basins were developed by the U.S. Geological Survey, in cooperation with the Legislative-Citizen Commission on Minnesota Resources, to illustrate relative and cumulative streamflow distributions. The Cannon River was selected to provide baseline data to assess the effects of potential surficial sand mining, and the St. Louis River was selected to determine the effects of ongoing Mesabi Iron Range mining. Each drainage basin (Cannon, St. Louis) was subdivided into nested drainage basins: the Cannon River was subdivided into 152 nested drainage basins, and the St. Louis River was subdivided into 353 nested drainage basins. For each smaller drainage basin, the estimated volumes of groundwater discharge (as base flow) and surface runoff flowing into all surface-water features were displayed under the following conditions: (1) extreme low-flow conditions, comparable to an exceedance-probability quantile of 0.95; (2) low-flow conditions, comparable to an exceedance-probability quantile of 0.90; (3) a median condition, comparable to an exceedance-probability quantile of 0.50; and (4) a high-flow condition, comparable to an exceedance-probability quantile of 0.02. Streamflow distribution maps were developed using flow-duration curve exceedance-probability quantiles in conjunction with Soil-Water-Balance model outputs; both the flow-duration curve and Soil-Water-Balance models were built upon previously published U.S. Geological Survey reports. The selected streamflow distribution maps provide a proactive water management tool for State cooperators by illustrating flow rates during a range of hydraulic conditions. Furthermore, after the nested drainage basins are highlighted in terms of surface-water flows, the streamflows can be evaluated in the context of meeting specific ecological flows under different flow regimes and potentially assist with decisions regarding groundwater and surface-water appropriations. Presented streamflow distribution maps are foundational work intended to support the development of additional streamflow distribution maps that include statistical constraints on the selected flow conditions.

Minnesota↗

Leveraging socioeconomic flows to inform shared, migratory species conservation

Migratory species, and the many cultural and economic values they provide, are declining worldwide. Previous research has quantified ecosystem service flows for single migratory species to provide valuable information on the dynamics of socio-ecological systems to inform cross-jurisdictional management. There are efficiencies in implementation to be gained from considering the dynamics of multiple species (e.g., ecological guilds) simultaneously. As proof of concept, this paper demonstrates how ecosystem service flows can be aggregated spatially for a group of three North American migratory species. We further present a flexible approach to estimating how conservation funding can be allocated equitably between regions of the migratory range. Results show that most benefits from these three migratory species are supported locally by habitat within each region, but net interregional flows exist, including a $33.1M annual subsidy from Mexico to the U.S. and Canada. Results also suggest that directing 18% of net conservation funding raised for these species in the U.S. and Canada toward conservation projects in Mexico would redress inequities in shared management responsibility. Considering the values provided by multiple species simultaneously has the potential to broaden coalitions and expedite negotiation of international agreements by providing a better shared understanding of the benefits to each party.

North America↗

Sediment transport in two tributaries to the San Joaquin River immediately below Friant Dam—Cottonwood Creek and Little Dry Creek, California

Two tributaries to the greater San Joaquin River watershed, Cottonwood and Little Dry Creeks, in California’s Central Valley, were assessed for sediment and streamflow dynamics between October 1, 2011, and September 30, 2019. The two systems deliver sediment to the San Joaquin River below Friant Dam, California. Dams create downstream discontinuities in streamflow and sediment transport and therefore influence fish habitat and sediment dynamics. Because these two creeks are directly downriver from Friant Dam, they become the most upstream source of sediment to the San Joaquin River below Friant Dam. The quality and quantity of spawning habitat for fish in the gravel-bedded reach of the San Joaquin River relies on a range of bed material particle size suitable for redd structure. The effects of coarse-sand to fine-gravel supply on salmonid habitat depends primarily on the size of the sediment and the timing of its addition from tributaries to the San Joaquin River; thus, understanding the timing, quantity, and size of sediment supplied from these two tributaries is critical to the management of ecological and biological sustainability. Streamflow from Cottonwood and Little Dry Creeks, along with streamflow from the San Joaquin River below Friant Dam, were compared to continuously measured water-surface elevations to quantify the timing and direction of streamflow. Suspended-sediment samples were collected with multiple automatic samplers and analyzed for concentration and grain-size distribution. Measured suspended-sediment concentrations and streamflows were used to develop sediment rating curves and compute continuous estimates of suspended-sediment load for each tributary. Satellite imagery was used to qualify spatial and temporal dynamics through the lower watersheds and support more quantitative sediment-load estimates. Computed annual sediment loads ranged from 1.32x10 1 to 2.68x10 4 metric tons for Little Dry Creek and 9.82 to 1.98x10 3 metric tons for Cottonwood Creek. Sediment loads computed during the study period for both watersheds show that annual loads were highest during water year 2017 (October 1, 2016, to September 30, 2017). Sediment transport primarily occurred between the months of January and March. In both tributaries, grain-size distributions of suspended sediment were predominantly coarse-sized sand and were finer than the remnant bed material. Both creeks demonstrate backwater effects from the San Joaquin River, but the more tortuous stream channel and historical mining pits within Little Dry Creek provide more capacity for sediment storage compared to the less complex stream network of Cottonwood Creek. Because loads were computed based on upstream streamgages and not at the confluence of each tributary to the San Joaquin River, annual load estimates do not represent direct flux into the San Joaquin River; instead, these results indicated that in Little Dry Creek, particularly, the lowest portion of the watershed stores sediment before it reaches the San Joaquin River.

California↗

Status and management of the PaliIa, an endangered Hawaiian honeycreeper, 1987-1996

A single, relictual population of Palila Loxioides bailleui, a Hawaiian honeycreeper, survives on the slopes of Mauna Kea volcano on the island of Hawai'i, where it feeds principally on flowers and green seeds of the mamane tree Sophora chrysophylla. The Palila was listed as an endangered species by state and federal governments because of continuing damage to its habitat by browsing Feral and Mouflon Sheep Ovis aries and O. musimon and Goats Capra hircus and because of the bird's restricted range and low numbers. Ecology of the Palila was studied from 1987 to 1996. Annual population estimates fluctuated between 1 600 and 5 700 and averaged 3 400 birds. Estimates varied with availability of mamane seeds, which are less abundant in drought years. In drought years, most birds did not attempt to breed, and survival rates were lower because of a shortage of food. Availability of mamane seeds also showed large seasonal variability. While some nests were preyed upon by Owls Asio flammeus, Cats Felis catus and Rats Rattus rattus, losses were high at the end of the season from unexplained death of eggs and chicks. Genetic studies did not implicate inbreeding depression. Neither avian malaria nor avian pox appeared at this site, where the mosquito vector was absent. However, weather and food shortage worsened towards the end of the nesting season. Availability of food and habitat remain the principal factors limiting increase in the Palila population. Recovery efforts now focus on reducing numbers of feral ungulates, fire management, removing mammalian predators, and developing techniques for captive propagation and introduction to currently unoccupied sites within the bird's former range. Reforestation adjacent to the Mauna Kea Forest Reserve would allow the Palila population to expand and grow.

Pacific Conservation Biology↗

Movement dynamics influence population monitoring and adaptive harvest management strategies in migratory birds

Informed population monitoring efforts are essential for sound management of harvested species, and adaptive strategies that provide detailed information to monitoring efforts often require data inputs from complimentary sources. Movement ecology information is seldom directly incorporated into population monitoring or adaptive harvest management strategies, yet can provide valuable information on species distributions, emigration and immigration rates, and aid in determining optimal population monitoring timing. The Rocky Mountain Population (RMP) of Sandhill Cranes is a harvested population subject to a stringent adaptive harvest management framework and an annual aerial survey to estimate population abundance, but movements of Sandhill Cranes during survey windows, and subsequent changes to harvest quotas based on their movement and distribution have not been investigated. We used seven years of GPS tracking data to estimate state-specific emigration and immigration rates, using a Bayesian multi-state capture-recapture model, among states within the RMP distribution to understand how seasonal crane movements may influence optimal aerial survey timing. We then leveraged these transition probabilities in conjunction with aerial survey count data to model how changes in aerial survey timing and movement-informed crane distribution would influence the current RMP Sandhill Crane adaptive harvest management model resulting in estimated changes to harvest allocation among states based on Sandhill Crane movement. We found that Sandhill Crane emigration from northern states began to increase the week of the aerial survey in late September, and continued to increase as autumn migration progressed into October. As expected, immigration to southern states began as emigration from northern states increased. Importantly, little movement among states occurred prior to the current aerial survey design timing. Overall, we found that current survey timing and shortly thereafter (∼1 week) did not greatly influence estimates of Sandhill Crane distribution, and did not greatly influence the harvest reallocation to each state until mid to late October (range of −42–+52 tag allocation change), much later than the current survey design would allow. Using GPS locations, we found that optimal population monitoring efforts could be improved to account for both detection and seasonal movements, while minimally influencing current adaptive harvest management strategies to stakeholders. Linking movement ecology with population monitoring efforts and subsequently adaptive harvest management strategies yields insightful information that can be beneficial for conservation planning, decision-making, and optimal species management of a migratory bird.

Colorado, Idaho, Montaha, Utah, Wyoming↗