25 resultados para Conservation analysis


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OKACOM's Transboundary Diagnostic Analysis study used integrated flows analysis to develop scenarios for possible developments in the Okavango River Basin. (PDF contains 2 pages)

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English: We describe an age-structured statistical catch-at-length analysis (A-SCALA) based on the MULTIFAN-CL model of Fournier et al. (1998). The analysis is applied independently to both the yellowfin and the bigeye tuna populations of the eastern Pacific Ocean (EPO). We model the populations from 1975 to 1999, based on quarterly time steps. Only a single stock for each species is assumed for each analysis, but multiple fisheries that are spatially separate are modeled to allow for spatial differences in catchability and selectivity. The analysis allows for error in the effort-fishing mortality relationship, temporal trends in catchability, temporal variation in recruitment, relationships between the environment and recruitment and between the environment and catchability, and differences in selectivity and catchability among fisheries. The model is fit to total catch data and proportional catch-at-length data conditioned on effort. The A-SCALA method is a statistical approach, and therefore recognizes that the data collected from the fishery do not perfectly represent the population. Also, there is uncertainty in our knowledge about the dynamics of the system and uncertainty about how the observed data relate to the real population. The use of likelihood functions allow us to model the uncertainty in the data collected from the population, and the inclusion of estimable process error allows us to model the uncertainties in the dynamics of the system. The statistical approach allows for the calculation of confidence intervals and the testing of hypotheses. We use a Bayesian version of the maximum likelihood framework that includes distributional constraints on temporal variation in recruitment, the effort-fishing mortality relationship, and catchability. Curvature penalties for selectivity parameters and penalties on extreme fishing mortality rates are also included in the objective function. The mode of the joint posterior distribution is used as an estimate of the model parameters. Confidence intervals are calculated using the normal approximation method. It should be noted that the estimation method includes constraints and priors and therefore the confidence intervals are different from traditionally calculated confidence intervals. Management reference points are calculated, and forward projections are carried out to provide advice for making management decisions for the yellowfin and bigeye populations. Spanish: Describimos un análisis estadístico de captura a talla estructurado por edad, A-SCALA (del inglés age-structured statistical catch-at-length analysis), basado en el modelo MULTIFAN- CL de Fournier et al. (1998). Se aplica el análisis independientemente a las poblaciones de atunes aleta amarilla y patudo del Océano Pacífico oriental (OPO). Modelamos las poblaciones de 1975 a 1999, en pasos trimestrales. Se supone solamente una sola población para cada especie para cada análisis, pero se modelan pesquerías múltiples espacialmente separadas para tomar en cuenta diferencias espaciales en la capturabilidad y selectividad. El análisis toma en cuenta error en la relación esfuerzo-mortalidad por pesca, tendencias temporales en la capturabilidad, variación temporal en el reclutamiento, relaciones entre el medio ambiente y el reclutamiento y entre el medio ambiente y la capturabilidad, y diferencias en selectividad y capturabilidad entre pesquerías. Se ajusta el modelo a datos de captura total y a datos de captura a talla proporcional condicionados sobre esfuerzo. El método A-SCALA es un enfoque estadístico, y reconoce por lo tanto que los datos obtenidos de la pesca no representan la población perfectamente. Además, hay incertidumbre en nuestros conocimientos de la dinámica del sistema e incertidumbre sobre la relación entre los datos observados y la población real. El uso de funciones de verosimilitud nos permite modelar la incertidumbre en los datos obtenidos de la población, y la inclusión de un error de proceso estimable nos permite modelar las incertidumbres en la dinámica del sistema. El enfoque estadístico permite calcular intervalos de confianza y comprobar hipótesis. Usamos una versión bayesiana del marco de verosimilitud máxima que incluye constreñimientos distribucionales sobre la variación temporal en el reclutamiento, la relación esfuerzo-mortalidad por pesca, y la capturabilidad. Se incluyen también en la función objetivo penalidades por curvatura para los parámetros de selectividad y penalidades por tasas extremas de mortalidad por pesca. Se usa la moda de la distribución posterior conjunta como estimación de los parámetros del modelo. Se calculan los intervalos de confianza usando el método de aproximación normal. Cabe destacar que el método de estimación incluye constreñimientos y distribuciones previas y por lo tanto los intervalos de confianza son diferentes de los intervalos de confianza calculados de forma tradicional. Se calculan puntos de referencia para el ordenamiento, y se realizan proyecciones a futuro para asesorar la toma de decisiones para el ordenamiento de las poblaciones de aleta amarilla y patudo.

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The United States has managed and analyzed its marine fisheries since 1871, and since 1970 via NOAA’s National Marine Fisheries Service (NMFS). As the primary directive moved from aiding fishermen in expanding their operations emphasizing conservation, the government over time recognized that management involves influencing people not fish, and has hired social scientists to complement the biologists who assess fish populations. This change has not always been smooth. We use archival documents and oral histories to trace the development of sociocultural analytic capabilities within NMFS and describe future plans for growing the program. Four points are made. First, NMFS has created the best developed social science program in NOAA. Second, established institutions change slowly; achieving the social science presence in NMFS has taken over 25 years. Third, change needs visionaries and champions with both tenacity and opportunity. Fourth, social science data collection and research helps in making fishery management decisions, but they have also been useful in evaluating the impact and helping with the recovery from Hurricane Katrina. Good work finds other uses.

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The California fishery for red sea urchins, Strongylocentrotus franciscanus, has undergone explosive growth in recent years and is approaching full exploitation. Thus, there is considerable interest in enhancing stocks to maintain a high rate of landings. Fishable stocks of red sea urchins in different areas appear to be limited at three stages in their life history: By the availability of larvae, by the survival of newly settled to mid-sized animals, and by the food available to support growth and reproduction of larger animals. Here I review other efforts, notably the extensive Japanese work, to enhance fishable stocks of benthic marine invertebrates, and consider the potential options for red sea urchins at different points of limitation. These include collecting or culturing seed for outplanting, physical habitat improvement measures, improving the food supply, and conservation measures to protect existing stocks until alternate methods are proven and in place. The options are compared in terms of biological feasibility, capital and labor requirements, and potential implications for change in the structure of the fishing industry.

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This is the Mersey Estuary baseline survey: Analysis of macroinfaunal samples, literature review and database production report produced by the Environment Agency North West in 2002. This report presents an ecological review of the Mersey estuary along with an extensive bibliography of the available environmental literature for this system. The central objective of this programme has been to provide the information necessary to support the Environment Agency's review of existing and future consents (for discharges, abstractions etc) in the Mersey estuary. This review of consents was required because the Mersey had been designated as a Special Protection Area (SPA) under the EC Birds Directive. Therefore under Regulation 50 of the Conservation, the Environment Agency was responsible for reviewing any extant consent, or future applications, which may directly or indirectly, affected this SPA.

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This is the NRA's role in wetland conservation report produced by the National Rivers Authority in 1995. This document is the third of a series of three R&D Notes produced as part of an integrated research programme addressing aspects of the NRA's role in wetland management and conservation. Chapter 1 considers the nature of the wetland resource and its definition. Chapter 2 presents the NRA's current legislative and policy framework relating to its role in wetland conservation. National and international legislation and agreements are considered, and particular attention is afforded to the potential implications of the 'Habitats Directive'. Chapter 4 presents key examples of operational casework involving wetlands. Differences in approach and external perceptions of the NRA's current and likely future role in wetland conservation are discussed within Chapter 5. Other issues highlighted in this report are: policy guidance required on NRA’s role in land drainage; standard of flood defence service for wetlands; cost-benefit analysis; strategies for halting and reversing the decline and degradation of wetland resource; and Catchment Management Planning.

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Seagrass ecosystems are protected under the federal "no-net-loss" policy for wetlands and form one of the most productive plant communities on the planet, performing important ecological functions. Seagrass beds have been recognized as a valuable resource critical to the health and function of coastal waters. Greater awareness and public education, however, is essential for conservation of this resource. Tremendous losses of this habitat have occurred as a result of development within the coastal zone. Disturbances usually kill seagrasses rapidly, and recovery is often comparatively slow. Mitigation to compensate for destruction of existing habitat usually follows when the agent of loss and responsible party are known. Compensation assumes that ecosystems can be made to order and, in essence, trades existing functional habitat for the promise of replacement habitat. While ~lant ingse agrass is not technically complex, there is no easy way to meet the goal of maintaining or increasing seagrass acreage. Rather, the entire process of planning, planting and monitoring requires attention to detail and does not lend itself to oversimplification.

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Land-based pollution is commonly identified as a major contributor to the observed deterioration of shallow-water coral reef ecosystem health. Human activity on the coastal landscape often induces nutrient enrichment, hypoxia, harmful algal blooms, toxic contamination and other stressors that have degraded the quality of coastal waters. Coral reef ecosystems throughout Puerto Rico, including Jobos Bay, are under threat from coastal land uses such as urban development, industry and agriculture. The objectives of this report were two-fold: 1. To identify potentially harmful land use activities to the benthic habitats of Jobos Bay, and 2. To describe a monitoring plan for Jobos Bay designed to assess the impacts of conservation practices implemented on the watershed. This characterization is a component of the partnership between the U.S. Department of Agriculture (USDA) and the National Oceanic and Atmospheric Administration (NOAA) established by the Conservation Effects Assessment Project (CEAP) in Jobos Bay. CEAP is a multi-agency effort to quantify the environmental benefits of conservation practices used by private landowners participating in USDA programs. The Jobos Bay watershed, located in southeastern Puerto Rico, was selected as the first tropical CEAP Special Emphasis Watershed (SEW). Both USDA and NOAA use their respective expertise in terrestrial and marine environments to model and monitor Jobos Bay resources. This report documents NOAA activities conducted in the first year of the three-year CEAP effort in Jobos Bay. Chapter 1 provides a brief overview of the project and background information on Jobos Bay and its watershed. Chapter 2 implements NOAA’s Summit to Sea approach to summarize the existing resource conditions on the watershed and in the estuary. Summit to Sea uses a GIS-based procedure that links patterns of land use in coastal watersheds to sediment and pollutant loading predictions at the interface between terrestrial and marine environments. The outcome of Summit to Sea analysis is an inventory of coastal land use and predicted pollution threats, consisting of spatial data and descriptive statistics, which allows for better management of coral reef ecosystems. Chapters 3 and 4 describe the monitoring plan to assess the ecological response to conservation practices established by USDA on the watershed. Jobos Bay is the second largest estuary in Puerto Rico, but has more than three times the shoreline of any other estuarine area on the island. It is a natural harbor protected from offshore wind and waves by a series of mangrove islands and the Punta Pozuelo peninsula. The Jobos Bay marine ecosystem includes 48 km² of mangrove, seagrass, coral reef and other habitat types that span both intertidal and subtidal areas. Mapping of Jobos Bay revealed 10 different benthic habitats of varying prevalence, and a large area of unknown bottom type covering 38% of the entire bay. Of the known benthic habitats, submerged aquatic vegetation, primarily seagrass, is the most common bottom type, covering slightly less than 30% of the bay. Mangroves are the dominant shoreline feature, while coral reefs comprise only 4% of the total benthic habitat. However, coral reefs are some of the most productive habitats found in Jobos Bay, and provide important habitat and nursery grounds for fish and invertebrates of commercial and recreational value.

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Training included: Geographic Information System (GIS)concept and software; Global Positioning System (GPS); Ecological Gap Analysis and Marine Protected Area (MPA) design using Marine Reserve Design using Spatially Explicit Annealing (MARXAN); and cartography.