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Pelagic ecosystem dynamics on all temporal scales may be driven by the dynamics of very specialized oceanic habitats. One such habitat is the basin-wide chlorophyll front located at the boundary between the low chlorophyll subtropical gyres and the high chlorophyll subarctic gyres. Global satellite maps of surface chlorophyll clearly show this feature in all oceans. In the North Pacific, the front is over 8000 km long and seasonally migrates north and south about 1000 km. In the winter this front is located at about 30–35°N latitude and in the summer at about 40–45°N. It is a zone of surface convergence where cool, vertically mixed, high chlorophyll, surface water on the north side sinks beneath warm, stratified, low chlorophyll water on the south side. Satellite telemetry data on movements of loggerhead turtles and detailed fisheries data for albacore tuna show that both apex predators travel along this front as they migrate across the North Pacific. The front is easily monitored with ocean color satellite remote sensing. A change in the position of the TZCF between 1997 and 1998 appears to have altered the spatial distribution of loggerhead turtles. The position and dynamics of the front varied substantially between the 1998 El Niño and the 1999 La Niña. For example, from May to July 1999 the transition zone chlorophyll front (TZCF) remained between about 35°N and 40°N latitude showing very little meandering, whereas in 1998, during the same period, the TZCF exhibited considerable meandering and greater monthly latitudinal movement. Catch rates for albacore were considerably higher in 1998 than in 1999, and we hypothesize that a meandering TZCF creates regions of convergence, which enhances the foraging habitat for apex predators along the front.  相似文献   
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There is great interest in understanding how climate change will impact aridity through the interaction of precipitation changes with rising temperatures. The Aridity Index (AI), Climatic Moisture Deficit (CMD), and Climatic Moisture Surplus (CMS) are metrics commonly used to quantify and map patterns in aridity and water cycling. Here we show that these metrics have different patterns of change under future climate—based on an ensemble of nine general circulation climate models—and the different metrics are appropriate for different purposes. Based on these differences between the metrics, we propose that aridity can be dissected into three different types—hydrological (CMS), agricultural (CMD), and meteorological. In doing this, we propose a novel modified version of the Aridity Index, called AI+, that can be useful for assessing changes in meteorological aridity. The AI?+?is based on the same ratio between precipitation and evapotranspiration as the traditional AI, but unlike the traditional AI, the AI?+?only accounts for changes to precipitation during months when precipitation is less than reference/potential evapotranspiration (i.e. there is a deficit). Moreover, we show that the traditional AI provides a better estimate of change in moisture surplus driven by changes to precipitation during the wet season, rather than changes in deficit that occur during the drier seasons. These results show that it is important to select the most appropriate metric for assessing climate driven changes in aridity.  相似文献   
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Awareness of increasing water scarcity has driven efforts to model global water resources for improved insight into water resources infrastructure and management strategies. Most water resources models focus explicitly on water systems and represent socio-economic and environmental change as external drivers. In contrast, the system dynamics-based integrated assessment model employed here, ANEMI, incorporates dynamic representations of these systems, so that their broader changes affect and are affected by water resources systems through feedbacks. Sectors in ANEMI therefore include the global climate system, carbon cycle, economy, population, land use and agriculture, and novel versions of the hydrological cycle, global water use and water quality. Since the model focus is on their interconnections through explicit nonlinear feedbacks, simulations with ANEMI provide insight into the nature and structure of connections between water resources and socio-economic and environmental change. Of particular interest to water resources researchers and modelers will be the simulated effects of a new water stress definition that incorporates both water quality and water quantity effects into the measurement of water scarcity. Five simulation runs demonstrate the value of wastewater treatment and reuse programs and the feedback-effects of irrigated agriculture and greater consumption of animal products.  相似文献   
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An existing Ecopath with Ecosim (EwE) model for the Central North Pacific was updated and modified to focus on the area used by the Hawaii-based pelagic longline fishery. The EwE model was combined with output from a coupled NOAA Geophysical Fluid Dynamics Laboratory climate and biogeochemical model to investigate the likely ecosystem impacts of fishing and climate-induced primary productivity changes. Four simulations were conducted based on 2 fishing effort and climate scenarios from 2010 to 2100. Modeled small and large phytoplankton biomass decreased by 10 % and 20 % respectively, resulting in a 10 % decline in the total biomass of all higher trophic level groups combined. Climate impacts also affected the Hawaii longline fishery, with a 25–29 % reduction in modeled target species yield. Climate impacts on the ecosystem and the fishery were partially mitigated by a drop in fishing effort. Scenarios with a 50 % reduction in fishing effort partially restored longline target species yield to current levels, and decreased longline non-target species yield. These model results suggest that a further reduction in fishery landings mortality over time than the 2010 level may be necessary to mitigate climate impacts and help sustain yields of commercially preferred fish species targeted by the Hawaii longline fishery through the 21st century.  相似文献   
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There have been many studies of hydrologic processes and scale. However, some researchers have found that predictions from hydrologic models may not be improved by attempting to incorporate the understanding of these processes into hydrologic models. This paper quantifies the effect of simplifying watershed geometry and averaging the parameter values on simulations generated using the KINEROS2 model. Furthermore, it examines how these changes in model input effect model output. The model was applied on a small semiarid rangeland watershed in which runoff is generated by the infiltration excess mechanism. The study concludes that averaging input parameter values has little effect on runoff volume and peak in simulating runoff. However, geometric simplification does have an effect on runoff peak and volume, but it is not statistically significant. In contrast, both averaging input parameter values and geometric simplification have an effect on model‐predicted sediment yield. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   
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Coastal dunes are dynamic features that are continuously evolving due to constructive (e.g., wind- and wave-driven sediment transport) and destructive (e.g., elevated total water levels during storm events) processes. However, the relative importance of these processes in determining dune evolution is often poorly understood. In this study, ten lidar datasets from 1997 to 2016 are used to determine the relative role of erosion and accretion processes driving foredune change on the coast of Cape Lookout National Seashore, North Carolina, USA. Beach and dune morphometrics reveal that dune toe locations have generally retreated since 1997, while dune crest heights accreted by 0.01–0.02 m/year. We develop three univariate metrics that represent (1) the potential for erosion, i.e., total water level impact hours per year, (2) accretion, i.e., dune building hours per year, and (3) the relative net effect of foredune accretion and erosion processes, i.e., constructive–destructive dune forcing (CDDF) ratio, and test the correlative power of these metrics in explaining changes in foredune morphology. The total water level impact hours per year metric explained as much as 66% and 67% of the variance in dune crest and toe elevations, respectively, across the nearly two decades of dune evolution. The greatest number of dune building hours per year and largest dunes within the study site co-occurred at locations exposed to the dominant cross-shore wind direction as a result of varying shoreline orientation. The CDDF ratio was positively correlated to changes in the dune toe elevation in approximately 70% of dunes within the study site, outperforming the impact and dune building hours per year metrics. Our results show that these three metrics can provide first-order estimates of dune morphometric change across multiple spatial and temporal scales, which may be particularly useful at sites where lidar acquisition is intermittent.  相似文献   
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