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At least 145 records · Page 8Linked to original sources

Controlling the spread of invasive species while sampling

Invasive species have a substantial impact on natural resource management. The economic cost of invasive species to people in the United States is an estimated US$137 billion annually (Pimental et al. 2000). The environmental cost is much greater and usually incalculable (Pimental et al. 2005). Nearly half of the plant and animal species federally listed in the United States' Endangered Species Act are threatened or endangered primarily as a consequence of invasive species that directly prey on native species or outcompete them for limited resources (Wilcove et al. 1998; Pimental et al. 2005) The result is reduced population numbers and, sometimes, local extinction of native plants and animals (Pimental at al. 2005). Such environmental damage is often irreparable. As natural resource managers, it is our responsibility to manage and conserve valuable natural resources. However, if our focus is limited to specific projects and tasks at hand, we may overlook the broader ramifications of our actions and unintentionally contribute to the invasive species problem. This chapter focuses on measures that should be taken to present, minimize, or control the spread of invasive species in the routine work we do as natural resource professionals. Inadvertently transporting potentially harmful organisms undermines our purposed as natural resource professionals. It is imperative that we understand that pathways that we create and strive to eliminate (when possible) or minimize the potential damage that may result from our actions. A combination of technologies, education, codes of conduct, and government overshot, as recommended by the Ecological Society of America, can prevent invasive species introductions from pathways that already exist (Lodge et al. 2006). In the long run, a purposeful prevention strategy for stopping unintentional species introductions will promote responsible natural resource management and will help us to achieve agency goals.

Book chapter↗

The quantification of instream flow rights to water

Energy development of all types continues to grow in the Rocky Mountain Region of the western United States. Federal resource managers increasingly need to balance energy demands, their effects on the natural and human landscape, and public perceptions towards these issues. The Western Energy Citation Clearinghouse (WECC v.1.0), part of a suite of data and information management tools developed and managed by the Wyoming Landscape Conservation Initiative (WLCI), provides resource managers with a searchable online database of citations that covers a broad spectrum of energy and landscape related topics relevant to resource managers, such as energy sources, natural and human landscape effects, and new research, methods and models. Based on the 2011 USGS Open-file Report "Abbreviated bibliography on energy development" (Montag, et al. 2011), WECC is an extensive collection of energy-related citations, as well as categorized lists of additional online resources related to oil and gas development, best practices, energy companies and Federal agencies. WECC incorporates the powerful web services of Sciencebase 2.0, the enterprise data and information platform for USGS scientists and partners, to provide secure, role-based data management features. For example, public/unauthenticated WECC users have full search and read access to the entire energy citation collection, while authenticated WLCI data stewards can manage WECC's citation collection using Sciencebase data management forms.

Book↗

Scale-appropriate adaptation strategies and actions in the Northeast and Midwest United States

Climate Change Adaptation is a growing field within conservation and natural resource management. Actions taken toward climate change adaptation account for climate impacts and ecological responses, both current and projected into the future. These actions attempt to accomplish a number of goals, including the conservation of wildlife and ecosystems by reducing vulnerability and increasing resilience. Climate change adaptation strategies and approaches for natural resources can be thought of as part of a continuum of potential actions ranging from 1) options or goals to 2) strategies, 3) approaches, and 4) tactics. There are a range of decision support tools and processes to aid climate change adaptation. This document highlights several including the Adaptation Workbook, Climate Change Vulnerability Assessments, Structured Decision Making, Adaptive Resource Management, and Scenario Planning. It will also provide case studies on the application of these tools across the Northeast and Midwest. Improved, better-integrated, and increasingly coordinated monitoring systems would be helpful to detect, track, and attribute species and habitat shifts to climate change over spatiotemporal scales. We highlight regional examples of projects and programs addressing these challenges. Illustrative case studies of climate change adaptation efforts are presented across landscape/ecoregion, state, and local scales. Appendix 4.1 provides a synthesis of over 900 general, species and habitat-specific adaptation strategies and tactics from 9 regional studies being considered or implemented across the region. The study of climate change adaptation is a relatively new and rapidly growing field focused on preparing for and responding to the current and future impacts of climate change. The goal of this chapter is to highlight different approaches, processes, and tools currently being used across the region through illustrative case studies at varying scales. In addition, we provide a synthesis of numerous species and habitat-specific adaptation strategies and actions from existing assessment reports and management plans, which is intended to showcase a range of possibilities for natural resource management under future global change. This report does not prescribe one specific approach to taking action; instead, we outline a range of adaptation 5 tactics, which will require thoughtful consideration of the needs of the species, habitat, and location, the stakeholders and partners involved, the scale that a decision or policy is being implemented at, and the financial and personnel resources available to managers.

Connecticut, Delaware, Iowa, Illinois, Indiana, Ke↗

Bright spots for advancing ecological understanding and conservation decision-making

A lot can be learned by studying bright spots—defined as unexpected positive outcomes. In fields like public health, education, and oncology, identifying factors behind bright spots reveals previously unknown drivers of success that can be replicated elsewhere. This concept is being applied in conservation but is hampered by variations in definitions of bright spots and confusion with hotspots—sites with high absolute values of a metric. We developed a framework to clearly define and distinguish between hotspots (e.g., a wetland with high plant diversity) and bright spots (e.g., a biodiverse wetland in a housing development), which outperform conservation expectations. The framework is an iterative cycle, consisting of setting expectations for relative comparisons, classifying systems into bright, dark, hot, and cold categories, and digging deeper to reveal hidden mechanisms and opportunities for intervention. We drew on examples from diverse fields to demonstrate how our framework can generate new knowledge, identify potential interventions, and inform management priorities. Defining conservation and management expectations, often through predictive models, is essential to understanding drivers of success and fosters hypotheses about overlooked factors. Our framework can enhance ecological understanding, guide interventions, and help prioritize actions in conservation and natural resource management.

Conservation Biology↗

The 3D Elevation Program: summary for Florida

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Florida, elevation data are critical for natural resources conservation; flood risk management; infrastructure and construction management; coastal zone management; sea level rise and subsidence; wildfire management, planning, and response; and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios.The new 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the OMB Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Florida↗

Adaptive management: The U.S. Department of the Interior technical guide

The purpose of this technical guide is to present an operational definition of adaptive management, identify the conditions in which adaptive management should be considered, and describe the process of using adaptive management for managing natural resources. The guide is not an exhaustive discussion of adaptive management, nor does it include detailed specifications for individual projects. However, it should aid U.S. Department of the Interior (DOI) managers and practitioners in determining when and how to apply adaptive management. Adaptive management is framed within the context of structured decision making, with an emphasis on uncertainty about resource responses to management actions and the value of reducing that uncertainty to improve management. Though learning plays a key role in adaptive management, it is seen here as a means to an end, namely good management, and not an end in itself. The operational definition used in the guide is adopted from the National Research Council, which characterizes adaptive management as an iterative learning process producing improved understanding and improved management over time: Adaptive management [is a decision process that] promotes flexible decision making that can be adjusted in the face of uncertainties as outcomes from management actions and other events become better understood. Careful monitoring of these outcomes both advances scientific understanding and helps adjust policies or operations as part of an iterative learning process. Adaptive management also recognizes the importance of natural variability in contributing to ecological resilience and productivity. It is not a ‘trial and error’ process, but rather emphasizes learning while doing. Adaptive management does not represent an end in itself, but rather a means to more effective decisions and enhanced benefits. Its true measure is in how well it helps meet environmental, social, and economic goals, increases scientific knowledge, and reduces tensions among stakeholders. Adaptive management as defined here involves ongoing, real-time learning and knowledge creation, both in a substantive sense and in terms of the adaptive process itself. It is described in what follows in a series of 9 steps, as summarized in section 4.1, involving stakeholder involvement, management objectives, management alternatives, predictive models, monitoring plans, decision making, monitoring responses to management, assessment, and adjustment to management actions. An adaptive approach actively engages stakeholders in all phases of a project over its timeframe, facilitating mutual learning and reinforcing the commitment to learning-based management. Adaptive management in DOI is implemented within a legal context that includes statutory authorities such as the National Environmental Policy Act (NEPA), the Endangered Species Act, and the Federal Advisory Committee Act. For many important problems now facing the resource management community, adaptive management holds great promise in reducing the uncertainties that limit the effective management of natural resource systems. For many conservation and management problems, utilizing management itself in an experimental context may be the only feasible way to gain the system understanding needed to improve management. Though it is commonly thought that an adaptive approach can produce results quickly at low cost, the opposite is more likely to be true. An initial investment of time and effort will increase the likelihood of better decision making and resource stewardship in the future, but patience, flexibility, and support are needed over the life of an adaptive management project. For these reasons it is important to carefully consider the potential use of an adaptive approach, and to engage in careful planning and evaluation when adaptive management is used.

Report↗

The 3D Elevation Program: summary for Wisconsin

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Wisconsin, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, infrastructure and construction management, water supply and quality, and other business uses. Today, high-quality light detection and ranging (lidar) data are the sources for creating elevation models and other elevation datasets. Federal, State, and local agencies work in partnership to (1) replace data, on a national basis, that are (on average) 30 years old and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The new 3D Elevation Program (3DEP) initiative, managed by the U.S. Geological Survey (USGS), responds to the growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation’s natural and constructed features.

Wisconsin↗

The 3D Elevation Program: summary for Minnesota

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Minnesota, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, infrastructure and construction management, water supply and quality, coastal zone management, and other business uses. Today, high-quality light detection and ranging (lidar) data are the sources for creating elevation models and other elevation datasets. Federal, State, and local agencies work in partnership to (1) replace data, on a national basis, that are (on average) 30 years old and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The new 3D Elevation Program (3DEP) initiative, managed by the U.S. Geological Survey (USGS), responds to the growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation’s natural and constructed features.

Minnesota↗

The 3D Elevation Program: summary for Missouri

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Missouri, elevation data are critical for agriculture and precision farming; natural resources conservation; flood risk management; homeland security, law enforcement, and disaster response; infrastructure and construction management; water supply and quality; and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Missouri↗

The 3D Elevation Program: summary for Michigan

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Michigan, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, water supply and quality, infrastructure and construction management, coastal zone management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation's natural and constructed features. The Michigan Statewide Authoritative Imagery and Lidar (MiSAIL) program provides statewide lidar coordination with local, State, and national groups in support of 3DEP for Michigan.

Michigan↗

The 3D Elevation Program: summary for Ohio

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Ohio, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, infrastructure and construction management, water supply and quality, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation's natural and constructed features.

Ohio↗

The 3D Elevation Program—Supporting Utah’s economy

Introduction High-quality elevation data for Utah inform decision making to improve the State’s economy. Light detection and ranging (lidar) data are used to support infrastructure planning and management, assess natural resources, and improve resiliency to hazards. The expanding availability of current and more accurate lidar data helps to better support natural resource conservation, wildfire risk management, geologic hazard investigation and mitigation, flood risk management, water supply planning, and urban planning and development. Critical applications that meet the State’s management needs depend on lidar data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features. The 3D Elevation Program is managed by the U.S. Geological Survey in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Utah. The status of available and in-progress 3DEP baseline lidar data in Utah is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 ( https://www.usgs.gov/3dep/lidarspec ) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $8.70 million in new benefits annually to the State. The top 10 Utah business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.

Utah↗

The 3D Elevation Program: summary for Puerto Rico

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, scientific research, national security, recreation, and many others. For the Commonwealth of Puerto Rico, elevation data are critical for flood risk management, landslide mitigation, natural resources conservation, sea level rise and subsidence, coastal zone management, infrastructure and construction management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, U.S. territorial, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States, Hawaii, and selected U.S. territories, and quality level 5 interferometric synthetic aperture radar (IfSAR) data for Alaska, all with a 6- to 10-year acquisition cycle, provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A‒16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other three-dimensional (3D) representations of the Nation’s natural and constructed features.

Puerto Rico↗

RE-ARMing salt marshes: A resilience-experimentalist approach to prescribed fire and bird conservation in high marshes of the Gulf of Mexico

Uncertainty, complexity, and dynamic changes present challenges for conservation and natural resource management. Evidence-based approaches grounded in reliable information and rigorous analysis can enhance the navigation of the uncertainties and trade-offs inherent in conservation problems. This study highlights the importance of collaborative efforts and evidence-based decision-making, specifically implementing the Resilience-Experimentalist school of adaptive management (RE-ARM), which emphasizes stakeholder involvement, shared understanding, and experimentation. Our goal was to develop an adaptive management framework to reduce the uncertainty around the use of prescribed fire to manage the habitat for eastern black rails ( Laterallus jamaicensis jamaicensis ) and mottled ducks ( Anas fulvigula ) in saltmarshes of the Gulf of Mexico. Supported by discussions at a series of workshops, we used a value of information analysis to select a fire management hypothesis to test, developed an influence diagram to represent the system under fire management, used the influence diagram to develop a Bayesian decision network (BDN), and conducted a power analysis to guide management experiments and monitoring. Value of information analysis identified fire return interval as the critical uncertainty. Our BDN provided valuable insight into how managers believe prescribed fire influences vegetation characteristics and how vegetation influences both eastern black rail occupancy and mottled duck abundance. The results of the power analysis indicated that a standard occupancy modeling framework was more useful to compare 2- and 5-year fire return intervals for black rails than two alternative designs (removal and conditional). Our BDN can be used to predict the probability of achieving the desirable vegetative response to increase the occupancy probability of black rails and abundance of mottled ducks, and monitoring data can be used to update the BDN (learn) and improve best management practices for prescribed burns (adapt). Linking the value of information, BDNs, and power analysis enhances our understanding of the system, improves management decision-making, and builds trust among scientists, interested parties, and decision-makers. This approach lays the groundwork for knowledge co-production and adaptive management.

Frontiers in Conservation Science↗

A guidebook to spatial datasets for conservation planning under climate change in the Pacific Northwest

This guidebook provides user-friendly overviews of a variety of spatial datasets relevant to conservation and management of natural resources in the face of climate change in the Pacific Northwest, United States. Each guidebook chapter was created using a standardized template to summarize a spatial dataset or a group of closely related datasets. Datasets were selected according to standardized criteria based on input through a collaborative process involving researchers and natural-resource managers throughout the Pacific Northwest region. In each chapter, basic spatial and temporal information is provided for the dataset, along with a conceptual overview, glossary of key terms, links to download data and supporting documentation, a brief methods summary describing how the dataset was created, guidelines for dataset interpretation, assessment of uncertainties along with evaluation of caveats and simplifying assumptions, and information about potential and actual conservation applications of the dataset. Collectively, this information provides natural-resource managers with “snapshots” of a variety of datasets representing diverse processes and conditions, including climate projections, changes in hydrologic conditions, vegetation and fire-regime shifts, animal habitat changes, species movements, and topographic and soil conditions relevant to climate change. Along with other types of data and site-specific information, the datasets described in this guidebook have the potential to inform management of valued natural resources throughout the Pacific Northwest region in the context of adaptation to changing climate conditions.

Idaho, Montana, Oregon, Washington↗

Development of the Wildlife Adaptation Menu for Resource Managers

The Climate Change Response Framework is an example of a collaborative, cross-boundary approach to create a set of tools, partnerships, and actions to support climate-informed conservation and land management. Historically, this effort has focused on the needs of forest managers and forestry professionals. In recent years, however, there has been increasing demand for science and tools to address climate change adaptation in wildlife management and conservation. Not only do wildlife and resource managers need the best available science, it must also be presented in a usable format with feasible options within the purview of an individual manager. The research team is first completing a comprehensive review of peer-reviewed studies to summarize what wildlife-related management actions currently exist in climate change adaptation. They will then develop and test a “menu” of climate change adaptation actions that are suitable for wildlife management in terrestrial ecosystems. This Wildlife Adaptation Menu will be modeled off existing adaptation menus for Forestry and Urban Forestry, and it will be designed to be used in conjunction with the Adaptation Workbook . In addition to a menu of adaption strategies and approaches, the scientists will also identify site-level tactics and develop case studies demonstrating the use and implementation of the menu. To ensure that information and tools meet the needs of managers, the team is involving and integrating input from wildlife managers at every step of the process. Managers will be involved in scoping the project, testing the menu, and implementing the menu.

Final Report↗

Identifying resource manager information needs for the North Pacific Landscape Conservation Cooperative

Landscape Conservation Cooperatives (LCCs) are a network of 22 public-private partnerships, defined by ecoregion, that share and provide science to ensure the sustainability of land, water, wildlife and cultural resources in North America. LLCs were established by the U.S. Department of Interior (DOI) in recognition that response to climate change must be coordinated on a landscape-level basis because important resources, ecosystem processes and resource management challenges extend beyond national wildlife refuges, Bureau of Land Management lands, national parks, and even international boundaries. Therefore, DOI agencies must work with other Federal, State, Tribal (U.S. indigenous peoples), First Nation (Canadian indigenous peoples), and local governments, as well as private landowners, to develop landscape-level strategies for understanding and responding to climate change.

Alaska;British Columbia;California;Oregon;Washingt↗

Studying the Earth from space

Pictures of the Earth's surface obtained from satellites are providing scientists with new tools to investigate the Earth and its environment. At the same time, a growing population and an ever-expanding technology place unprecedented demands on natural resources. Man can no longer treat his resources strictly according to immediate economic dictates; a balance must be struck between the short-term demands of technological and industrial development and the long-term effects on the environment. Intelligent development, management, and conservation of resources are goals that represent a challenge in the acquisition and use of information.

General Interest Publication↗