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Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.  相似文献   
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Stream habitat assessments are commonplace in fish management, and often involve nonspatial analysis methods for quantifying or predicting habitat, such as ordinary least squares regression (OLS). Spatial relationships, however, often exist among stream habitat variables. For example, water depth, water velocity, and benthic substrate sizes within streams are often spatially correlated and may exhibit spatial nonstationarity or inconsistency in geographic space. Thus, analysis methods should address spatial relationships within habitat datasets. In this study, OLS and a recently developed method, geographically weighted regression (GWR), were used to model benthic substrate from water depth and water velocity data at two stream sites within the Greater Yellowstone Ecosystem. For data collection, each site was represented by a grid of 0.1 m2 cells, where actual values of water depth, water velocity, and benthic substrate class were measured for each cell. Accuracies of regressed substrate class data by OLS and GWR methods were calculated by comparing maps, parameter estimates, and determination coefficient r 2. For analysis of data from both sites, Akaike’s Information Criterion corrected for sample size indicated the best approximating model for the data resulted from GWR and not from OLS. Adjusted r 2 values also supported GWR as a better approach than OLS for prediction of substrate. This study supports GWR (a spatial analysis approach) over nonspatial OLS methods for prediction of habitat for stream habitat assessments.  相似文献   
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Environmental and biological reef monitoring was conducted in Almirante Bay (Bahía Almirante) in Bocas del Toro, Panama, to assess impacts from anthropogenic developments. An integrated monitoring investigated how seasonal temperature stress, turbidity, eutrophication and physical impacts threatened reef health and biodiversity throughout the region. Environmental parameters such as total suspended solids [TSS], carbon isotopes (δ13C), C/N ratios, chlorophyll a, irradiance, secchi depth, size fractions of the sediments and isotope composition of dissolved inorganic carbon [DIC] of the water were measured throughout the years 2010 and 2011 and were analysed in order to identify different impact sources. Compared to data from Collin et al. (Smithsonian Contributions to the Marine Sciences 38:324–334, 2009) chlorophyll a has doubled at sites close to the city and the port Almirante (from 0.46–0.49 to 0.78–0.97 μg l?1) and suspension load increased, visible by a decrease in secchi depth values. Visibility decreased from 9-13 m down to 4 m at the bay inlet Boca del Drago, which is strongly exposed to river run off and dredging for the shipping traffic. Eutrophication and turbidity levels seemed to be the determining factor for the loss of hard coral diversity, most significant at chlorophyll a levels higher than 0.5 μg l?1 and TSS levels higher than 4.7 mg l?1. Hard coral cover within the bay has also declined, at some sites down to <10 % with extremely low diversities (7 hard coral species). The hard coral species Porites furcata dominated the reefs in highly impacted areas and showed a strong recovery after bleaching and a higher tolerance to turbidity and eutrophication compared to other hard coral species in the bay. Serious overfishing was detected in the region by a lack of adult and carnivorous fish species, such as grunts, snappers and groupers. Study sites less impacted by anthropogenic activities and/or those with local protection showed a higher hard coral cover and fish abundance; however, an overall loss of hard coral diversity was observed.  相似文献   
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Prompt assessment and management actions are required if we are to reduce the current rapid loss of habitat and biodiversity worldwide. Statistically valid quantification of the biota and habitat condition in water bodies are prerequisites for rigorous assessment of aquatic biodiversity and habitat. We assessed the ecological condition of streams in a southeastern Brazilian basin. We quantified the percentage of stream length in good, fair, and poor ecological condition according to benthic macroinvertebrate assemblage. We assessed the risk of finding degraded ecological condition associated with degraded aquatic riparian physical habitat condition, watershed condition, and water quality. We describe field sampling and implementation issues encountered in our survey and discuss design options to remedy them. Survey sample sites were selected using a spatially balanced, stratified random design, which enabled us to put confidence bounds on the ecological condition estimates derived from the stream survey. The benthic condition index indicated that 62 % of stream length in the basin was in poor ecological condition, and 13 % of stream length was in fair condition. The risk of finding degraded biological condition when the riparian vegetation and forests in upstream catchments were degraded was 2.5 and 4 times higher, compared to streams rated as good for the same stressors. We demonstrated that the GRTS statistical sampling method can be used routinely in Brazilian rain forests and other South American regions with similar conditions. This survey establishes an initial baseline for monitoring the condition and trends of streams in the region.  相似文献   
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