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184 results for “FCE”
Greenhouse experiment (FCE) in April and August 2001: Responses of neotropical mangrove saplings to the combined effect of hydroperiod and salinity/Biomass
A greenhouse experiment was performed for 13.5 months to evaluate the effect of salinity and hydroperiod on seedling growth rates of 2 mangrove species( Laguncularia racemosa and Rizhophora mangle). Data analyses are currently being performed.
Greenhouse mixed culture experiment from August 2002 to April 2003 (FCE): Evaluate the effect of salinity and hydroperiod on interspecific mangrove seedlings growth rate (mixed culture) / Morphometric variables
A greenhouse experiment (mixed culture experiment) was performed for 8 months to evaluate the effect of salinity and hydroperiod on seedling growth rates of 2 mangrove species( Laguncularia racemosa and Rizhophora mangle). Data analyses are currently being performed.
Bulk Parameters for Soils/Sediments from the Shark River Slough and Taylor Slough, Everglades National Park (FCE), from October 2000 to January 2001
The main goal of this research is the characterization of the sources, transport and fate of soil/sediment organic matter in Everglades National Park, and the determination of future potential effects of Everglades restoration on the source strength and accumulation rates of this OM. The general approach of this study is the seasonal sampling and analysis of bulk and molecular characteristics of soil/sediment samples from the FCE-LTER sites. Bulk parameters measured are d13C, C/N and %OC, while molecular characterizations are based on detailed biomarker analyses of extractable lipids and CP/MAS 13C-NMR of bulk OM. Preliminary results have allowed to characterize OM source strength throughout the transects, as well as determining other minor OM sources, diagenetic differences based upon OM quality and marine influences in the estuarine areas of the FCE-LTER study area.
Minnowtrap Data from Rookery Branch and the North, Watson, and Roberts Rivers National Park (FCE) from November 2004 to April 2008
This study examines temporal and spatial dynamics in the fish community of the oligohaline to mesohaline reaches of ecotonal creeks along the southwest region of Everglades National Park. Sampling is conducted at 15 mangrove creeks in two drainages: Rookery Branch and the North, Roberts, and Watson rivers. The sampling in Rookery Branch expands over a 12-km stretch of ecotonal mangrove creeks upstream of Tarpon Bay. Minnow traps are used to target small-bodied forage fish. Sampling started in the wet season of 2004, and has been conducted three times per year at these approximate times: November (wet season); February (transition); and April (dry season). In the Rookery Branch region, fish abundance varies markedly yearly and seasonally. Catches peak in the drier months, reflecting a pulse of movement by freshwater taxa into creeks as marshes upstream dry. The timing of this pulse is closely tied to the pattern of water recession in upstream marshes, and has important ramifications for wading bird prey availability.
Fish and consumer data collected from Northeast Shark Slough, Everglades National Park (FCE) from September 2006 to September 2008
Three 1m2 throwtrap sites were selected randomly within a few meters of the location. All fish and macroinvertebrates were sampled within each trap using a seine; the trap is determined to be clear of fish and macroinvertebrates once three empty seines are recovered. The count is reset whenever a fish or invertebrate is caught. Once the trap is determined to be clear, five sweeps are done using a couple of nets. The count resets whenever fish is caught, while an extra sweep is added whenever an invertebrate is captured. The trap is finally cleared once the fifth sweep doesn't capture any organisms. All captured organisms are anesthesized in a plastic cup filled with water and MS222; they are then preserved using a 10% formaldehyde solution for identification and archiving in the lab
Bull shark catches, water temperatures, salinities, and dissolved oxygen levels in the Shark River Slough, Everglades National Park (FCE) , from May 2005 to May 2009
This dataset provides information on the catches of bull sharks in the Shark River Slough in relation to physical factors including dissolved oxygen, water temperature, salinity, and distance upstream. Analysis of data collected from 2005-2007 indicate that distance from the Gulf of Mexico and dissolved oxygen concentrations have the largest effects on bull shark catch rates. Data are presented for both young of the year sharks, which are concentrated in areas away from the main channel approximately 20km upstream, and older juvenile sharks which are found along the main channel at similar distances upstream. Salinity has a surprisingly weak impact on catches over the time frame initially investigated.
Water Levels and Porewater Temperature data from the Shark River and Taylor River Slough mangrove sites, Everglades National Park (FCE LTER), South Florida, USA: May 2001 - ongoing
Water levels for SRS4 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m inland at Tarpon Bay. Water levels for SRS5 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m at the Shark River Slough. Water levels for SRS6 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m at the Shark River Slough. Water levels for SRS7 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m at the Shark River Slough. Water levels for TS/Ph6a are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m inland at the Taylor River Slough. Water level recorder is located in between of two 20 by 20 m permanent monitoring plots. Water levels for TS/Ph7a are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 60 m inland at the Taylor River Slough. Water level recorder is located in between of two 20 by 20 m permanent monitoring plots. Water levels for TS/Ph8 are recorded at 1h intervals. Water level recorder is located in the mangrove forests 40 m inland at the Joe Bay area. Water level recorder is located in between of two 20 by 20 m permanent monitoring plots. All water level data are measured by Florida International University.
Global Climate Change Impacts on the Vegetation and Fauna of Mangrove Forested Ecosystems in Florida (FCE): Nekton Mass from March 2000 to April 2004
Bottomless lift nets are buried within the mangrove forest floor and raised remotely on slack high spring tides to enclose a 6m2 area. As the tide ebbs, fishes retreat into a subtidal refuge cleared when the tide has fallen. Three replicate nets have been sampled at 3 locations along a salinity gradient on Shark River for 4 years. Small resident forage fish and grass shrimp dominate the collections. Exotic species and estuarine transient species that use the estuary as a nursery are rare within the assemblage of fishes that routinely use the flooded forest.
Standard Lengths and Mean Weights for Prey-base Fishes from Taylor River and Joe Bay Sites, Everglades National Park (FCE), South Florida from January 2000 to April 2004
Prey-base fishes. The small demersal fishes of the coastal wetlands are a keystone element in this ecosystem. They are the primary and secondary consumers of the plants mentioned above and they are the primary food resource for myriad piscine (e.g. game species of fish), reptilian (e.g. juvenile crocodiles) and avian (e.g. wading birds) predators. The community dynamics of these fishes are dictated by hydrologic and hydrographic parameters so they also respond predictably to water management practices. Because they are a bottle-neck in the food web, their abundance and availability dictate the success of higher trophic levels. Fish are sampled in June, September and monthly from November through April at five locations. A 9m2 drop trap designed specifically for this habitat are used to quantify fish use. Nine traps are used at each site.
Subsurface Water Temperatures taken in Shark River Slough and Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, May 2010 - December 2015
At each site, two vertical columns of temperature sensors (107-L Temperature Probes, Campbell Scientific, Logan, Utah) were installed and connected to data loggers (CR1000 Dataloggers, Campbell Scientific, Logan, Utah). At each, one temperature sensor in a heat shield was installed 2 m above the ground surface. The remaining temperature sensors were installed at or below the ground surface, with the depths and depth intervals depending upon the total depth of the column. The data were collected hourly between May 19, 2010 and December 1, 2015.
Monthly monitoring fluorescence data for Shark River Slough and Taylor Slough, Everglades National Park (FCE) for October 2004 to February 2014
Dissolved organic matter plays an important role in biogeochemical processes in aquatic environments such as elemental cycling, microbial loop energetics, and the transport of materials across landscapes. Since most of N (> 90%) and P (around 90%) is in the organic form in the oligotrophic subtropical Florida Coastal Everglades (FCE), study of the source and dynamics of dissolved organic matter (DOM) in the ecosystem is crucial for the better understanding of the biogeochemical cycling of nutrients. FCE are composed of estuaries with distinct regions with different biogeochemical processes. Freshwater marsh primarily receives terrestrial input and local autochthonous vegetation production. Mangrove ecotone, nevertheless, is affected by the tidal contributions from Florida Bay and local mangrove production. Florida Bay (FB) is a wedge-shaped shallow oligotrophic estuary which lays south of the Everglades, the bottom of which is covered with a dense biomass of seagrass. The sources of both freshwater and nutrients in FCE are difficult to quantify, owing to the non-point source nature of runoff from the Everglades and the dendritic cross channels in the mangroves. Furthermore, the combination of multiple DOM sources (freshwater marsh vegetation, mangroves, phytoplankton, seagrass, etc.), and the potential seasonal variability of their relative contribution, along with the history of (photo)chemical and microbial diagenetic processing, and complex advective circulation, makes the study of DOM dynamics in FCE particularly difficult using standard schemes of estuarine ecology. Quantitative information of DOM is very useful to investigate the biogeochemical cycling of DOM to a certain degree, however, qualitative information is necessary to better understand the source and dynamics of DOM. Since fluorescence spectroscopic techniques are very sensitive, quick and simple, they have been applied to investigate the fate of DOM in estuaries.
Shark catches (longline), water temperatures, salinities, and dissolved oxygen levels, and stable isotope values in the Shark River Slough, Everglades National Park (FCE LTER), Florida, USA, May 2005 - ongoing
This dataset provides information on the catches of sharks in the Shark River Slough in relation to physical factors including dissolved oxygen, water temperature, salinity, and distance upstream. Analysis of data collected suggest that distance from the Gulf of Mexico and dissolved have the largest effects on shark catch rates, with most juvenile bull sharks being caught in Tarpon Bay. This dataset includes all sharks caught on longline gear, their morphometric data, and CNS stable isotope analysis for selected individuals.
FCE Redlands 1994 Land Use, Miami-Dade County, South Florida
Urban growth models have increasingly been used by planners and policy makers to visualize, organize, understand, and predict urban growth. However, these models reveal a wide disparity in their attention to policy factors. Some urban growth models capture few if any specific policy effects (e.g.,as model variables), while others integrate certain policies but not others. Since zoning policies are the most widely used form of land use control in the United States, their conspicuous absence from so many urban growth models is surprising. This research investigated the impacts of zoning on urban growth by calibrating and simulating a cellular automaton urban growth model, SLEUTH, under two conditions in a South Florida location. The first condition integrated restrictive agricultural zoning into SLEUTH, while the other ignored zoning data. Goodness of fit metrics indicate that including the agricultural zoning data improved model performance. The results further suggest that agricultural zoning has been somewhat successful in retarding urban growth in South Florida. Ignoring zoning information is detrimental to SLEUTH performance in particular, and urban growth modeling in general.
FCE Redlands 1998 Land Use, Miami-Dade County, South Florida
Urban growth models have increasingly been used by planners and policy makers to visualize, organize, understand, and predict urban growth. However, these models reveal a wide disparity in their attention to policy factors. Some urban growth models capture few if any specific policy effects (e.g.,as model variables), while others integrate certain policies but not others. Since zoning policies are the most widely used form of land use control in the United States, their conspicuous absence from so many urban growth models is surprising. This research investigated the impacts of zoning on urban growth by calibrating and simulating a cellular automaton urban growth model, SLEUTH, under two conditions in a South Florida location. The first condition integrated restrictive agricultural zoning into SLEUTH, while the other ignored zoning data. Goodness of fit metrics indicate that including the agricultural zoning data improved model performance. The results further suggest that agricultural zoning has been somewhat successful in retarding urban growth in South Florida. Ignoring zoning information is detrimental to SLEUTH performance in particular, and urban growth modeling in general.
FCE Redlands 1998 Roads, Miami-Dade County, South Florida
Urban growth models have increasingly been used by planners and policy makers to visualize, organize, understand, and predict urban growth. However, these models reveal a wide disparity in their attention to policy factors. Some urban growth models capture few if any specific policy effects (e.g.,as model variables), while others integrate certain policies but not others. Since zoning policies are the most widely used form of land use control in the United States, their conspicuous absence from so many urban growth models is surprising. This research investigated the impacts of zoning on urban growth by calibrating and simulating a cellular automaton urban growth model, SLEUTH, under two conditions in a South Florida location. The first condition integrated restrictive agricultural zoning into SLEUTH, while the other ignored zoning data. Goodness of fit metrics indicate that including the agricultural zoning data improved model performance. The results further suggest that agricultural zoning has been somewhat successful in retarding urban growth in South Florida. Ignoring zoning information is detrimental to SLEUTH performance in particular, and urban growth modeling in general.
FCE Redlands 2006 Land Use, Miami-Dade County, South Florida
Urban growth models have increasingly been used by planners and policy makers to visualize, organize, understand, and predict urban growth. However, these models reveal a wide disparity in their attention to policy factors. Some urban growth models capture few if any specific policy effects (e.g.,as model variables), while others integrate certain policies but not others. Since zoning policies are the most widely used form of land use control in the United States, their conspicuous absence from so many urban growth models is surprising. This research investigated the impacts of zoning on urban growth by calibrating and simulating a cellular automaton urban growth model, SLEUTH, under two conditions in a South Florida location. The first condition integrated restrictive agricultural zoning into SLEUTH, while the other ignored zoning data. Goodness of fit metrics indicate that including the agricultural zoning data improved model performance. The results further suggest that agricultural zoning has been somewhat successful in retarding urban growth in South Florida. Ignoring zoning information is detrimental to SLEUTH performance in particular, and urban growth modeling in general.
FCE Redlands 2006 Roads, Miami-Dade County, South Florida
Urban growth models have increasingly been used by planners and policy makers to visualize, organize, understand, and predict urban growth. However, these models reveal a wide disparity in their attention to policy factors. Some urban growth models capture few if any specific policy effects (e.g.,as model variables), while others integrate certain policies but not others. Since zoning policies are the most widely used form of land use control in the United States, their conspicuous absence from so many urban growth models is surprising. This research investigated the impacts of zoning on urban growth by calibrating and simulating a cellular automaton urban growth model, SLEUTH, under two conditions in a South Florida location. The first condition integrated restrictive agricultural zoning into SLEUTH, while the other ignored zoning data. Goodness of fit metrics indicate that including the agricultural zoning data improved model performance. The results further suggest that agricultural zoning has been somewhat successful in retarding urban growth in South Florida. Ignoring zoning information is detrimental to SLEUTH performance in particular, and urban growth modeling in general.
FCE Redlands 2001 Land Use, Miami-Dade County, South Florida
Urban growth models have increasingly been used by planners and policy makers to visualize, organize, understand, and predict urban growth. However, these models reveal a wide disparity in their attention to policy factors. Some urban growth models capture few if any specific policy effects (e.g.,as model variables), while others integrate certain policies but not others. Since zoning policies are the most widely used form of land use control in the United States, their conspicuous absence from so many urban growth models is surprising. This research investigated the impacts of zoning on urban growth by calibrating and simulating a cellular automaton urban growth model, SLEUTH, under two conditions in a South Florida location. The first condition integrated restrictive agricultural zoning into SLEUTH, while the other ignored zoning data. Goodness of fit metrics indicate that including the agricultural zoning data improved model performance. The results further suggest that agricultural zoning has been somewhat successful in retarding urban growth in South Florida. Ignoring zoning information is detrimental to SLEUTH performance in particular, and urban growth modeling in general.
FCE Redlands 2008 Slope Mosaic, Miami-Dade County, South Florida
Urban growth models have increasingly been used by planners and policy makers to visualize, organize, understand, and predict urban growth. However, these models reveal a wide disparity in their attention to policy factors. Some urban growth models capture few if any specific policy effects (e.g.,as model variables), while others integrate certain policies but not others. Since zoning policies are the most widely used form of land use control in the United States, their conspicuous absence from so many urban growth models is surprising. This research investigated the impacts of zoning on urban growth by calibrating and simulating a cellular automaton urban growth model, SLEUTH, under two conditions in a South Florida location. The first condition integrated restrictive agricultural zoning into SLEUTH, while the other ignored zoning data. Goodness of fit metrics indicate that including the agricultural zoning data improved model performance. The results further suggest that agricultural zoning has been somewhat successful in retarding urban growth in South Florida. Ignoring zoning information is detrimental to SLEUTH performance in particular, and urban growth modeling in general.
FCE Redlands 2001 Zoning, Miami-Dade County, South Florida
Urban growth models have increasingly been used by planners and policy makers to visualize, organize, understand, and predict urban growth. However, these models reveal a wide disparity in their attention to policy factors. Some urban growth models capture few if any specific policy effects (e.g.,as model variables), while others integrate certain policies but not others. Since zoning policies are the most widely used form of land use control in the United States, their conspicuous absence from so many urban growth models is surprising. This research investigated the impacts of zoning on urban growth by calibrating and simulating a cellular automaton urban growth model, SLEUTH, under two conditions in a South Florida location. The first condition integrated restrictive agricultural zoning into SLEUTH, while the other ignored zoning data. Goodness of fit metrics indicate that including the agricultural zoning data improved model performance. The results further suggest that agricultural zoning has been somewhat successful in retarding urban growth in South Florida. Ignoring zoning information is detrimental to SLEUTH performance in particular, and urban growth modeling in general.
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.