11 resultados para optimal route finding

em Aquatic Commons


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Executive Summary: The marine environment plays a critical role in the amount of carbon dioxide (CO2) that remains within Earth’s atmosphere, but has not received as much attention as the terrestrial environment when it comes to climate change discussions, programs, and plans for action. It is now apparent that the oceans have begun to reach a state of CO2 saturation, no longer maintaining the “steady-state” carbon cycle that existed prior to the Industrial Revolution. The increasing amount of CO2 present within the oceans and the atmosphere has an effect on climate and a cascading effect on the marine environment. Potential physical effects of climate change within the marine environment, including ocean acidification, changes in wind and upwelling regimes, increasing global sea surface temperatures, and sea level rise, can lead to dramatic, fundamental changes within marine and coastal ecosystems. Altered ecosystems can result in changing coastal economies through a reduction in marine ecosystem services such as commercial fish stocks and coastal tourism. Local impacts from climate change should be a front line issue for natural resource managers, but they often feel too overwhelmed by the magnitude of this issue to begin to take action. They may not feel they have the time, funding, or staff to take on a challenge as large as climate change and continue to not act as a result. Already, natural resource managers work to balance the needs of humans and the economy with ecosystem biodiversity and resilience. Responsible decisions are made each day that consider a wide variety of stakeholders, including community members, agencies, non-profit organizations, and business/industry. The issue of climate change must be approached as a collaborative effort, one that natural resource managers can facilitate by balancing human demands with healthy ecosystem function through research and monitoring, education and outreach, and policy reform. The Scientific Expert Group on Climate Change in their 2007 report titled, “Confronting Climate Change: Avoiding the Unmanageable and Managing the Unavoidable” charged governments around the world with developing strategies to “adapt to ongoing and future changes in climate change by integrating the implications of climate change into resource management and infrastructure development”. Resource managers must make future management decisions within an uncertain and changing climate based on both physical and biological ecosystem response to climate change and human perception of and response to the issue. Climate change is the biggest threat facing any protected area today and resource managers must lead the charge in addressing this threat. (PDF has 59 pages.)

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The implementation of various types of marine protected areas is one of several management tools available for conserving representative examples of the biological diversity within marine ecosystems in general and National Marine Sanctuaries in particular. However, deciding where and how many sites to establish within a given area is frequently hampered by incomplete knowledge of the distribution of organisms and an understanding of the potential tradeoffs that would allow planners to address frequently competing interests in an objective manner. Fortunately, this is beginning to change. Recent studies on the continental shelf of the northeastern United States suggest that substrate and water mass characteristics are highly correlated with the composition of benthic communities and may therefore, serve as proxies for the distribution of biological biodiversity. A detailed geo-referenced interpretative map of major sediment types within Stellwagen Bank National Marine Sanctuary (SBNMS) has recently been developed, and computer-aided decision support tools have reached new levels of sophistication. We demonstrate the use of simulated annealing, a type of mathematical optimization, to identify suites of potential conservation sites within SBNMS that equally represent 1) all major sediment types and 2) derived habitat types based on both sediment and depth in the smallest amount of space. The Sanctuary was divided into 3610 0.5 min2 sampling units. Simulations incorporated constraints on the physical dispersion of sampling units to varying degrees such that solutions included between one and four site clusters. Target representation goals were set at 5, 10, 15, 20, and 25 percent of each sediment type, and 10 and 20 percent of each habitat type. Simulations consisted of 100 runs, from which we identified the best solution (i.e., smallest total area) and four nearoptimal alternates. We also plotted total instances in which each sampling unit occurred in solution sets of the 100 runs as a means of gauging the variety of spatial configurations available under each scenario. Results suggested that the total combined area needed to represent each of the sediment types in equal proportions was equal to the percent representation level sought. Slightly larger areas were required to represent all habitat types at the same representation levels. Total boundary length increased in direct proportion to the number of sites at all levels of representation for simulations involving sediment and habitat classes, but increased more rapidly with number of sites at higher representation levels. There were a large number of alternate spatial configurations at all representation levels, although generally fewer among one and two versus three- and four-site solutions. These differences were less pronounced among simulations targeting habitat representation, suggesting that a similar degree of flexibility is inherent in the spatial arrangement of potential protected area systems containing one versus several sites for similar levels of habitat representation. We attribute these results to the distribution of sediment and depth zones within the Sanctuary, and to the fact that even levels of representation were sought in each scenario. (PDF contains 33 pages.)

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We developed a habitat suitability index (HSI) model to understand and identify the optimal habitat and potential fishing grounds for neon f lying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean. Remote sensing data, including sea surface temperature, sea surface salinity, sea surface height, and chlorophyll-a concentrations, as well as fishery data from Chinese mainland squid f leets in the main fishing ground (150–165°E longitude) from August to October, from 1999 to 2004, were used. The HSI model was validated by using fishery data from 2005. The arithmetic mean modeling with three of the environmental variables—sea surface temperature, sea surface height anomaly, and chlorophyll- a concentrations—was defined as the most parsimonious HSI model. In 2005, monthly HSI values >0.6 coincided with productive fishing grounds and high fishing effort from August to October. This result implies that the model can reliably predict potential f ishing grounds for O. bartramii. Because spatially explicit fisheries and environmental data are becoming readily available, it is feasible to develop a dynamic, near real-time habitat model for improving the process of identifying potential fishing areas for and optimal habitats of neon flying squid.

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A new method of finding the optimal group membership and number of groupings to partition population genetic distance data is presented. The software program Partitioning Optimization with Restricted Growth Strings (PORGS), visits all possible set partitions and deems acceptable partitions to be those that reduce mean intracluster distance. The optimal number of groups is determined with the gap statistic which compares PORGS results with a reference distribution. The PORGS method was validated by a simulated data set with a known distribution. For efficiency, where values of n were larger, restricted growth strings (RGS) were used to bipartition populations during a nested search (bi-PORGS). Bi-PORGS was applied to a set of genetic data from 18 Chinook salmon (Oncorhynchus tshawytscha) populations from the west coast of Vancouver Island. The optimal grouping of these populations corresponded to four geographic locations: 1) Quatsino Sound, 2) Nootka Sound, 3) Clayoquot +Barkley sounds, and 4) southwest Vancouver Island. However, assignment of populations to groups did not strictly reflect the geographical divisions; fish of Barkley Sound origin that had strayed into the Gold River and close genetic similarity between transferred and donor populations meant groupings crossed geographic boundaries. Overall, stock structure determined by this partitioning method was similar to that determined by the unweighted pair-group method with arithmetic averages (UPGMA), an agglomerative clustering algorithm.

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The integration of agriculture and aquaculture as a means of intensifying resource use and improving the productivity of many current farming practices in Southeast Asian and African countries is discussed. A brief account is given of work undertaken by ICLARM in Malawi and India regarding the improved use of marginal lands to integrate crops, vegetables, trees, livestock and fish, outlining also the various problems involved in the extension of such integrated fish farming systems.

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Economic analysis and performance of the integrated rice-prawn farming systems in the Mekong Delta (Vietnam) are reviewed, including the problems and constraints of this integrated system technology.

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Increasing interest in the use of stock enhancement as a management tool necessitates a better understanding of the relative costs and benefits of alternative release strategies. We present a relatively simple model coupling ecology and economic costs to make inferences about optimal release scenarios for summer flounder (Paralichthys dentatus), a subject of stock enhancement interest in North Carolina. The model, parameterized from mark-recapture experiments, predicts optimal release scenarios from both survival and economic standpoints for varyious dates-of-release, sizes-at-release, and numbers of fish released. Although most stock enhancement efforts involve the release of relatively small fish, the model suggests that optimal results (maximum survival and minimum costs) will be obtained when relatively large fish (75–80 mm total length) are released early in the nursery season (April). We investigated the sensitivity of model predictions to violations of the assumption of density-independent mortality by including density-mortality relationships based on weak and strong type-2 and type-3 predator functional responses (resulting in depensatory mortality at elevated densities). Depending on postrelease density, density-mortality relationships included in the model considerably affect predicted postrelease survival and economic costs associated with enhancement efforts, but do not alter the release scenario (i.e. combination of release variables) that produces optimal results. Predicted (from model output) declines in flounder over time most closely match declines observed in replicate field sites when mortality in the model is density-independent or governed by a weak type-3 functional response. The model provides an example of a relatively easy-to-develop predictive tool with which to make inferences about the ecological and economic potential of stock enhancement of summer flounder and provides a template for model creation for additional species that are subjects of stock enhancement interest, but for which limited empirical data exist.

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Sri Lanka is a comparatively small island (65.584 km²) within the equatorial belt of calms. There are only slight seasonal variations in temperature, air humidity and day length. A description is given of the amphibian and reptile material brought back from the Austrian Indo-Pacific expedition, 1970-71. Some notes on the habitat of the animals are included.