4 resultados para River spatial complexity

em Digital Commons at Florida International University


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We present here a 4-year dataset (2001–2004) on the spatial and temporal patterns of aboveground net primary production (ANPP) by dominant primary producers (sawgrass, periphyton, mangroves, and seagrasses) along two transects in the oligotrophic Florida Everglades coastal landscape. The 17 sites of the Florida Coastal Everglades Long Term Ecological Research (FCE LTER) program are located along fresh-estuarine gradients in Shark River Slough (SRS) and Taylor River/C-111/Florida Bay (TS/Ph) basins that drain the western and southern Everglades, respectively. Within the SRS basin, sawgrass and periphyton ANPP did not differ significantly among sites but mangrove ANPP was highest at the site nearest the Gulf of Mexico. In the southern Everglades transect, there was a productivity peak in sawgrass and periphyton at the upper estuarine ecotone within Taylor River but no trends were observed in the C-111 Basin for either primary producer. Over the 4 years, average sawgrass ANPP in both basins ranged from 255 to 606 g m−2 year−1. Average periphyton productivity at SRS and TS/Ph was 17–68 g C m−2 year−1 and 342–10371 g C m−2 year−1, respectively. Mangrove productivity ranged from 340 g m−2 year−1 at Taylor River to 2208 g m−2 year−1 at the lower estuarine Shark River site. Average Thalassia testudinum productivity ranged from 91 to 396 g m−2 year−1 and was 4-fold greater at the site nearest the Gulf of Mexico than in eastern Florida Bay. There were no differences in periphyton productivity at Florida Bay. Interannual comparisons revealed no significant differences within each primary producer at either SRS or TS/Ph with the exception of sawgrass at SRS and the C−111 Basin. Future research will address difficulties in assessing and comparing ANPP of different primary producers along gradients as well as the significance of belowground production to the total productivity of this ecosystem.

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In tropical and subtropical estuaries, gradients of primary productivity and salinity are generally invoked to explain patterns in community structure and standing crops of fishes. We documented spatial and temporal patterns in fish community structure and standing crops along salinity and nutrient gradients in two subtropical drainages of Everglades National Park, USA. The Shark River drains into the Gulf of Mexico and experiences diurnal tides carrying relatively nutrient enriched waters, while Taylor River is more hydrologically isolated by the oligohaline Florida Bay and experiences no discernable lunar tides. We hypothesized that the more nutrient enriched system would support higher standing crops of fishes in its mangrove zone. We collected 50 species of fish from January 2000 to April 2004 at six sampling sites spanning fresh to brackish salinities in both the Shark and Taylor River drainages. Contrary to expectations, we observed lower standing crops and density of fishes in the more nutrient rich tidal mangrove forest of the Shark River than in the less nutrient rich mangrove habitats bordering the Taylor River. Tidal mangrove habitats in the Shark River were dominated by salt-tolerant fish and displayed lower species richness than mangrove communities in the Taylor River, which included more freshwater taxa and yielded relatively higher richness. These differences were maintained even after controlling for salinity at the time of sampling. Small-scale topographic relief differs between these two systems, possibly created by tidal action in the Shark River. We propose that this difference in topography limits movement of fishes from upstream marshes into the fringing mangrove forest in the Shark River system, but not the Taylor River system. Understanding the influence of habitat structure, including connectivity, on aquatic communities is important to anticipate effects of construction and operational alternatives associated with restoration of the Everglades ecosystem.

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In the tropical and subtropical wet and dry regions, maintaining natural hydrologic connections between coastal rivers and adjacent ephemeral wetlands is critical to conserving and sustaining high levels of fisheries production within these systems. Though there is a consensus that there is a need to maintain these natural connections, little is known about what attributes of floodplain inundation regimes are most important in sustaining fisheries production. Two attributes of the flood season and thus floodplain inundation that may be particularly influential to fisheries are the amplitude of the flood season (floodplain water depth and spatial extent of inundation) and the duration of the flood season (i.e., time floodplains are inundated). In mangrove-dominated Everglades coastal rivers, seasonal inundation of upstream marsh floodplains may play an important role in provisioning recreational fisheries; however, this relationship remains unknown. Using two Everglades coastal river fisheries as a model, we tested whether the amplitude of the flood season or the duration of the flood season is more important in explaining variation in angler catch records of common snook and largemouth bass collected from 1992 to 2012. We validated angler catches with fisheries-independent electrofishing conducted in the same region from 2004 to 2012. Our results showed (1) that bass angler catches tracked electrofishing catches, while snook catches were completely mismatched. And (2) that previous year's marsh dynamics, particularly the duration of the flood season, was more influential than the flood season amplitude in explaining variation in bass catches, such that bass angler catches were negatively correlated to the period time that floodplains remained disconnected from coastal rivers in the previous year, while snook catches were not very well explained by floodplain inundation terms.

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The purpose of this research was to investigate the influence of elevation and other terrain characteristics over the spatial and temporal distribution of rainfall. A comparative analysis was conducted between several methods of spatial interpolations using mean monthly precipitation values in order to select the best. Following those previous results it was possible to fit an Artificial Neural Network model for interpolation of monthly precipitation values for a period of 20 years, with input values such as longitude, latitude, elevation, four geomorphologic characteristics and anchored by seven weather stations, it reached a high correlation coefficient (r=0.85). This research demonstrated a strong influence of elevation and other geomorphologic variables over the spatial distribution of precipitation and the agreement that there are nonlinear relationships. This model will be used to fill gaps in time-series of monthly precipitation, and to generate maps of spatial distribution of monthly precipitation at a resolution of 1km2.