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SCIENCE FOR AVIAN CONSERVATION: PRIORITIES FOR THE NEW MILLENNIUM

2003· article· en· W2112305647 sur OpenAlex

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Notice bibliographique

RevueThe Auk · 2003
Typearticle
Langueen
DomaineEnvironmental Science
ThématiquePlant Ecology and Soil Science
Établissements canadiensnon disponible
Organismes subventionnairesU.S. Geological Survey
Mots-clésGeographyConservation scienceEcologyBiologyBiodiversity

Résumé

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Over the past decade, bird conservation activities have become the preeminent natural resource conservation effort in North America. Maturation of the North American Waterfowl Management Plan (NAWMP), establishment of Partners in Flight (PIF), and creation of comprehensive colonial waterbird and shorebird conservation plans have stimulated unprecedented interest in, and funding for, bird conservation in the United States, Canada, Mexico, and other countries in the western hemisphere. Key to that success in the United States has been active collaboration among federal, state and local governments, conservation organizations, academia, and industry. The U.S. Department of the Interior (DOI), which has primary statutory responsibility for migratory bird conservation and management, has been a key partner. Despite the great strides that have been made in bird conservation science, historical approaches to research and monitoring have often failed to provide sufficient information and understanding to effectively manage bird populations at large spatial scales. That shortcoming, and the lack of an integrated strategy and comprehensive set of research priorities, is more evident in light of the goals established by the North American Bird Conservation Initiative (NABCI). The NABCI is a trinational, coalition-driven effort to provide an organizational umbrella for existing conservation initiatives. The expanded focus of NABCI and individual bird conservation initiatives is to work together in an integrated, holistic fashion to keep common birds common and to increase populations of declining, threatened, and endangered species. To assist bird conservation initiatives in defi ning goals and developing new approaches to effective research, the U.S. Geological Survey (USGS), the research agency of DOI, convened a workshop, “Science for Avian Conservation: Understanding, Modeling, and Applying Ecological Relationships,” on 31 October–2 November 2000, which brought together 51 scientists from USGS, as well as scientists and conservationists from other agencies and organizations actively participating in NABCI. As the lead federal agency involved in bird conservation research, USGS has a clear legislative mandate to provide scientific information upon which future management plans and actions will be built. This article summarizes key issues and recommendations that arose from that workshop. The principal goal of the workshop was to guide USGS in defining its role, assessing capabilities, and directing future agency planning in support of bird conservation. A major component was to identify key areas of research needed in this new era of bird conservation science. Although tailored to the mission of USGS, workshop recommendations visualize a bold direction for future avian conservation science in which research and monitoring work in tandem with management to increase our understanding of avian populations and the processes that affect them. The USGS is a science agency whose role is to provide objective scientific information to management agencies and therefore is not directly involved in high-level resource policy-making or on-the-ground management decision making. Nevertheless, it is important to note that effective policy decision making must integrate the best available science with political and economic realities to achieve successful avian conservation—an important subject acknowledged in the workshop, but largely beyond its scope of discussion. Williams (2003) questions regarding how scientific information can be effectively communicated to decision makers and incorporated into natural resource policy. Without an aggressive vision and the willingness of researchers, managers, and policy makers to implement it, conservation of North American birds is likely to proceed without the full benefit of scientific investigation. These recommendations represent the principal conclusions drawn by workshop participants and do not necessarily reflect official USGS policy. Historically, avian research has been species specific, disciplinary, focused at relatively small scales, and monitoring has been disconnected from research and management activities. However, with the evolution of avian conservation efforts over the last decades, avian science has begun to focus on a more holistic systems view in which research is integrative, interdisciplinary, and focused on larger spatial, temporal, and organizational scales. Both historic and recent approaches are essential for developing an understanding of the underlying causes of ecological patterns and for identifying effective conservation actions. However, it is clear that we need to revise and broaden our fundamental approaches to addressing avian conservation science needs (Martin and Finch 1995, Marzluff and Sallabanks 1998). Avian conservation research is necessarily multifaceted, complex, and diverse, requiring an integrated approach. Bird conservation activities are conducted at a range of geographic and ecological scales that require coordinated management at local, regional, national, and international levels. Management plans must consider a wide range of natural resource, economic, and political objectives. These challenges are compounded by avian conservation efforts that involve numerous partners, with a wide range of missions and agendas, pursuing conservation goals and activities under a variety of initiatives. Population monitoring and traditional re-search activities, including studies of taxonomy, natural history, behavior, and factors affecting avian populations, have provided the biological foundation for many resource management decisions. However, intensive research is often local in scale, providing results with limited application to conservation of regional and continental populations. Many traditional research tools are not designed to provide insight into causes of bird population change. Research direction is also complicated by vague management goals and poor communication between managers and researchers (Arnett and Sallabanks 1998, Hejl and Granillo 1998). Such factors argue for significant improvements in approaches to avian research and stronger part-nerships between research and management components of bird conservation. An approach that combines research results, management activities, and monitoring into a coherent system for learning from management activities while incorporating increased understanding into future management actions provides an operational framework for advancement of avian conservation science and management. The NABCI provides a new opportunity and a new approach to bird conservation. Developed in 1998, its goal is to “deliver the full spectrum of bird conservation through regionally based, biologically driven, landscape-oriented partnerships” (U.S. North American Bird Conservation Initiative Committee 2000a). The NABCI's guiding principles include the need for (1) integration of management needs and actions across species and landscapes; (2) a standardized ecological framework for efficient planning, implementation, and evaluation; (3) the best available scientific information; and (4) an adaptive approach to bird conservation to build knowledge in concert with management actions. The NABCI goals and principles reinforce the need to broaden traditional avian conservation science, emphasizing an integrative, interdisciplinary, holistic approach to problem solving that not only combines research, management, and monitoring into a coherent system, but also incorporates a diverse array of scientific disciplines and tools. Proposing comprehensive, process-based solutions to the dilemmas facing avian conservation—how to best integrate science and management on the ground, and how to ensure participation of decision makers and enforcement of policies—was beyond the scope of the workshop. The workshop presented the broad context within which future avian conservation must be conducted and demonstrated the need for integrated solutions. However, participants, primarily research scientists, addressed this challenge at the level more appropriate to their expertise—identifying science that should be conducted and science approaches that should be used to accomplish these complex, integrated solutions. Research activities in support of avian conservation must be closely linked to NABCI and its partner programs and should provide the scientific foundation required to guide conservation and management decisions. The USGS workshop participants identified five priority research areas needed to support integrated avian conservation efforts: (1) avian life history, populations, and ecology; (2) habitat and environment; (3) integration of ecological information; (4) bird conservation planning; and (5) communication of ecological information. Detailed ecological information needed for effective management of many species is still largely lacking despite nearly 100 years of surveys, monitoring, and natural-history-based studies. Basic ecological research can be gathered through observational and retrospective studies and manipulative experiments, and can involve management actions applied in an adaptive framework. Basic ecological research should be directed at factors that affect population dynamics on breeding, migration, and wintering areas; understanding the relationships between breeding and wintering populations; and identifying source and sink populations within larger metapopulation complexes. Research must be directed at increasing our understanding of the distribution, life history, and limiting factors, as well as population and metapopulation dynamics of high-priority species as they are defined by the various bird-conservation initiatives. Accurate assessment of current population status and trends of avian species is needed for assessment of management activities. Monitoring programs must be designed, developed, and implemented for breeding, migration, and over-wintering populations of high-priority species. Those monitoring efforts should be closely tied to management objectives and activities, and should be sensitive to the geographic scales at which populations are managed. Reliable scientific information about bird populations should be collected in a broad variety of scientific and conservation settings (e.g. documenting results of conservation efforts and validating models). Even primary data sets such as the North American Breeding Bird Survey (BBS) need validation. Bird population information should provide unbiased estimates of population attributes, be collected at appropriate spatial and temporal scales, and be coordinated with collection of information on relevant environmental covariates. To ensure credibility, survey designers must establish clearly defined and achievable objectives, explicitly address issues of detectability and sample frames, evaluate usefulness of estimates to support predictive modeling, and maintain the integrity and metadata of the database. Bird population monitoring programs, when not explicitly linked to research, are of limited use in determining causes of population changes. Consequently, research efforts need to be strengthened to develop new sources of information on avian survival and productivity, refine survey methods, and develop approaches in which survey data can be used to assess causes of population change. Conservation of bird populations is typically accomplished through preservation and management of habitats upon which they depend. Many habitats are subject to large-scale disturbances (e.g. selective cutting, burning, habitat restoration). Research is needed to assess the response of bird populations to various land-use changes, configurations, and management actions and to use tools such as multiscale, predictive models to provide managers with relevant information describing implications of alternative management scenarios. To avoid being accused of suggesting there are no existing attempts to address the recommendations offered here, we present a few examples incorporating these concepts. Examples are primarily “in-house” (mostly USGS-related), focus on the theme of this article (bird conservation), and involve partnerships among federal and state agencies, academia, and nongovernment organizations. We recognize the long-standing North American BBS (Peterjohn et al. 1996), as well as newer programs that are focused on monitoring demographic parameters, including the Monitoring Avian Productivity and Survivorship (MAPS) program of the Institute for Bird Populations (DeSante 2000) and the Breeding Biology Research and Monitoring Database (BBIRD) (Conway and Martin 2000). Such programs provide valuable information, but continue to struggle to expand sampling coverage and address questions related to scale, site selection, sampling techniques, and analyses (Peterjohn et al. 1995, DeSante and Rosenberg 1998). Habitat management and preservation are critical elements of virtually all bird conservation work, under-scoring a need for research and monitoring activities to understand the role of habitat quality, quantity, and distribution on bird populations. In addition to priorities listed below, many needs related to bird monitoring and information management apply equally to habitat monitoring. Effective bird conservation requires information on status of environmental factors influencing population change, collected at scales consistent with management and monitoring activities. Efforts must be made to assess and monitor key determining factors (e.g. hydrology, climate, habitat, food, disease agents) of avian abundance and distribution. Assessment and monitoring of ecologically relevant habitat components (physical, biological, and environmental features) provide a means for conservationists to document status and trends in habitat quantity and quality and evaluate progress toward habitat-based goals and objectives. An important research challenge is the development of the ability to recognize biologically relevant attributes and diagnostic features of habitat effects on avian population dynamics. Capabilities must be developed that allow for remote and field collection of habitat information at appropriate temporal intervals and spatial scales. Habitat management is one means by which vegetation, food resources, and other features of the environment are maintained to support avian populations. Research is needed to guide distribution and intensity of habitat management, restoration, and enhancement activities by land managers. Ideally, that work should take place as part of an adaptive management program in which models are used to predict consequences of habitat manipulation and monitoring is used to assess the results of management on avian populations. Many existing sources of habitat and environmental data can be applied to avian conservation, including the National Gap Analysis Program (Scott and Jennings 1997), the National Land Cover Dataset (U.S. Geological Survey 2001a), and the Environmental Protection Agency's Environmental Mapping and Assessment Program (Preston and Ribic 1992). The challenge is to integrate that information into avian conservation science. Ecological models are critical tools for predicting consequences of management actions, integrating information across spatial and temporal scales and among disciplines, supporting conservation decision making, and identifying key uncertainties and topics for future investigation. Population models for high priority avian species are necessary to guide conservation planning, improve the design of avian monitoring programs, and provide predictions that can be used in management decision making and tested in the field. Key needs in the development of models include investigations of density-dependent population growth, bird-habitat associations at local and regional scales, and development of statistical methods for modeling bird abundance where estimates of vital rates are unavailable. The ability to identify relevant avian habitat factors and patterns requires a linkage among biological, physical, and socioeconomic processes as sources of population and habitat variation and change. New quantitative methods and approaches relating environmental factors (e.g. water quality, climate, geomorphology, contaminant distribution, habitat dynamics, and human population distribution) to bird population dynamics that can be used in predictive models would be especially valuable for avian conservation. Integration of population and habitat attributes and processes will require development of innovative methods for constructing, visualizing, analyzing, and verifying behaviors of complex ecological systems. Those integrated models provide a basis for conservation planning and future learning. The wide range of models that have developed to understand the needs and responses of waterfowl to habitat, weather, food resources, and wetland conditions (Johnson et al. 1987) is an example of the integrated modeling required for other priority species. Integrated models will provide a valuable basis for conservation planning and future learning (Raphael et al. 1998, Villard et al. 1998). Application of research results to development of credible, effective bird conservation plans is a key component of NABCI. Avian conservation is most successful when plans are built on strong scientific foundations, conservation actions are based on collaboration between researchers and managers, and policy makers are “on board” to ensure implementation of integrated approaches. Scientifically credible and defensible population and habitat objectives are intended to form the cornerstone of bird conservation plans. Yet quantitative, measurable objectives may not always reflect the most defensible scientific and ecological information, due to our lack of understanding of associations among population size, available habitat, and other limiting factors. Additional scientific guidance is needed to help construct legitimate, defensible, and quantitative population and habitat objectives for conservation plans. All plans are built upon an understanding of ecological and environmental factors affecting population and dynamics. research that the of the fundamental with can their Research activities should identify used in developing conservation plans and should and revise as information Conservation actions that benefit one species or may with population and habitat objectives established for other species or need to develop that regional for species and effects to priority species or guidance is needed to effectively integrate the objectives, and management actions of species and regional conservation plans. Bird conservation in the the provided by scientists to conservation in conservation The USGS Research is the Bird Conservation incorporated in various bird conservation plans et al. of this research will in future bird conservation planning and An goal of avian conservation science is to provide scientific information about avian populations and habitats that can be applied to management and policy decision making. The in which or related information are and as well as the of between scientists and managers, a key role in the of research (Arnett and Sallabanks 1998, Hejl and Granillo 1998). All these can be through effective data and information management and The ability to and integrate information on comprehensive, coordinated systems for data management, and A existing data and other information should be a high That information should be of data and information among scientists, managers, policy and the should be defined in of and and information That will require development of information and for that data are within and across scales, and approaches to information management and are key to with increasing for to information, and and results must be to the conservation that stimulated research in the key should be incorporated into development of application (1) collaboration and in decision support (2) a for (3) linkage between scientific information, priority management and conservation decision and (4) to ecological models and other decision support tools. The National is an example of the new of programs addressing is an information that diverse, biological information and tools maintained by The a Bird Conservation (U.S. Geological Survey whose primary focus is to provide to bird habitat and population data needed for management and conservation. resource management is a approach for ecological information to resource conservation processes and 1995, et al. Marzluff et al. 2000). provides a framework to and use of predictive guide management actions, and improve scientific knowledge about systems. resource management is an that monitoring and assessment programs, and science into decision making. management are or knowledge from one decision can be applied to the decision 2000). Williams (2003) and its application to resource conservation policy in more support by providing models and information to managers, are an important part of A variety of decision support systems can be developed that the from a data and information framework an on to an system an on upon needs of the and of necessary Such tools help managers the scope of identify and present relevant and refine visualize future and and focus on and decisions. resource management requires clear of management integration of research results into predictive management implementation of management actions, monitoring to assess the consequences of actions, and and models based on monitoring and of for scales at which birds are to be (e.g. local management regional conservation is an important in this management support systems (1) an interdisciplinary, coordinated (2) address processes at various spatial and (3) help bird conservation in an adaptive framework that explicitly results and actions based on A of of decision require research to provide tools for avian conservation, including (1) a understanding of how spatial learning in an adaptive management (2) integration of learning at spatial and temporal and (3) the of decisions. Efforts with the Management for of the have in a of decision support systems. The USGS Environmental available on vegetation, water quality, water scientific and geographic information system data (U.S. Geological Survey to and managers. The decision support system framework an integrated, and scientific approach to management of and provides for an adaptive management approach to decision making and not a science need as the of or and to integrated science programs to activities and of ecological information. in across disciplines and organizational as well as in management objectives can The that these issues are in conservation the need for in our knowledge of avian and avian conservation have been made in the past few Avian conservation science is at a where more integrated approaches will The of NABCI an opportunity and clear for research and monitoring activities required to accomplish avian conservation is to note in a implemented by the federal of the U.S. NABCI a set of future research and information needs was (1) monitoring, (2) integrated modeling and (3) decision (4) adaptive management, and (5) information management (U.S. North American Bird Conservation Initiative Committee The NABCI a by which science organizations can their activities, in collaboration with management organizations, toward avian conservation We can a in which scientists, managers, and policy makers are brought together to identify priority That science is conducted in an adaptive management context where research and monitoring address priority issues at the relevant scale, and the results in such a that future research, monitoring, management, and policy to bird conservation. goals will require and support of scientists, managers, policy and decision and will on innovative beyond the scope of the workshop. In other the by which research priorities are and applied is as important in avian conservation as is the focus of that We are to all participants in the USGS workshop, their and to from which this article was and an provided valuable on of this

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Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,419
Score d'incertitude au seuil0,885

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,021
Tête enseignante GPT0,244
Écart entre enseignants0,223 · la distance entre les deux têtes enseignantes sur ce seul travail
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