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Environ Monit Assess. 2011 Dec;183(1-4):395-408. doi: 10.1007/s10661-011-1928-7. Epub 2011 Mar 4.

Spatial distributions and eco-partitioning of soil biogeochemical properties in the Everglades National Park.

Author information

1
Soil and Water Science Department, University of Florida, 106 Newell Hall, PO Box 110510, Gainesville, FL 32611-0510, USA. osbornet@ufl.edu

Abstract

Large-scale ecosystem restoration efforts, such as those in the Florida Everglades, can be long-term and resource intensive. To gauge success, restoration efforts must have a means to evaluate positive or negative results of instituted activities. Edaphic properties across the Everglades landscape have been determined to be a valuable metric for such evaluation, and as such, a baseline condition from which to make future comparisons and track ecosystem response is necessary. The objectives of this work were to document this baseline condition in the southern most hydrologic unit of the Everglades, Everglades National Park (ENP), and to determine if significant eco-partitioning of soil attributes exists that would suggest the need to focus monitoring efforts in particular eco-types within the ENP landscape. A total of 342 sites were sampled via soil coring and parameters such as total phosphorus (TP), total nitrogen (TN), total carbon (TC), total calcium, total magnesium, and bulk density were measured at three depth increments in the soil profile (floc, 0-10 cm, and 10-20 cm). Geostatistical analysis and GIS applications were employed to interpolate site-specific biogeochemical properties of soils across the entire extent of the ENP. Spatial patterns and eco-type comparisons suggest TC and TN to be highest in Shark River Slough (SRS) and the mangrove interface (MI), following trends of greatest organic soil accumulation. However, TP patterns suggest greatest storages in MI, SRS, and western marl and wet prairies. Eco-partitioning of soil constituents suggest local drivers of geology and hydrology are significant in determining potential areas to focus monitoring for future change detection.

PMID:
21374053
DOI:
10.1007/s10661-011-1928-7
[Indexed for MEDLINE]

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