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|a Effect of Hydrologic Restoration on the Habitat of The Cape Sable Seaside Sparrow, Annual Report of 2004-2005 |h [electronic resource]. |
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|a Miami, Florida : |b Southeast Environmental Research Center, Florida International University, |c 2006-03-25. |
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|a Please contact the owning institution for licensing and permissions. It is the users responsibility to ensure use does not violate any third party rights. |
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|a The major activities in Year 3 on ‘Effect of hydrologic restoration on the habitat of
the Cape Sable seaside sparrow (CSSS)’ included presentations, field work, data analysis,
and report preparation. During this period, we made 4 presentations, two at the CSSS – fire
planning workshops at Everglades National Park (ENP), one at the Society of Wetland
Scientists’ meeting in Charleston, SC, and a fourth at the Marl Prairie/CSSS performance
measure workshop at ENP. We started field work in the third week of January and continued
till June 3, 2005. Early in the field season, we completed vegetation surveys along two
transects, B and C (~15.1 km). During April and May, vegetation sampling was completed at
199 census sites, bringing to 608 the total number of CSSS census sites with quantitative
vegetation data. We updated data sets from all three years, 2003-05, and analyzed them using
cluster analysis and ordination as in previous two years. However, instead of weighted
averaging, we used weighted-averaging partial least square regression (WA-PLS) model, as
this method is considered an improvement over WA for inferring values of environmental
variables from biological species composition. We also validated the predictive power of the
WA-PLS regression model by applying it to a sub-set of 100 census sites for which
hydroperiods were “known” from two sources, i.e., from elevations calculated from
concurrent water depth measurements onsite and at nearby water level recorders, and from
USGS digital elevation data. Additionally, we collected biomass samples at 88 census sites,
and determined live and dead aboveground plant biomass. Using vegetation structure and
biomass data from those sites, we developed a regression model that we used to predict
aboveground biomass at all transects and census sites. Finally, biomass data was analyzed in
relation to hydroperiod and fire frequency. |
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|a Electronic reproduction. |c Added automatically, |d 2014. |f (dpSobek) |n Mode of access: World Wide Web. |n System requirements: Internet connectivity; Web browser software. |
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|u http://dpanther.fiu.edu/dpService/dpPurlService/purl/FI14090773/00001 |y Click here for full text |
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|a http://dpanther.fiu.edu/sobek/content/FI/14/09/07/73/00001/Hydrologic Restoration 2006thm.jpg |
