Vegetation differentiation in the patterned landscape of the central Everglades: importance of local and landscape drivers

Abstract

Aim We present a model to account for self-assembly of the slough-ridge-tree island patterned landscape of the central Everglades in southern Florida via feedbacks among landforms, hydrology, vegetation and biogeochemistry. We test aspects of this model by analysing vegetation composition in relation to local and landscape-level drivers.Location We quantified vegetation composition and environmental characteristics in central Water Conservation Area (WCA) 3A, southern WCA-3A and southern WCA-3B in southern Florida, based on their divergence in water management and flow regimes over the past 50 years. MethodsIn 562 quadrats, we estimated species coverages and quantified maximum, minimum and average water depth, soil depth to bedrock, normalized difference vegetation index (NDVI) and proximity to the nearest tree island. We used non-metric multi-dimensional scaling (NMS) to relate compositional variation to local and landscape-level factors, and evaluated environmental differences among eight a priori vegetation types via  .Results Water depth and hydroperiod decreased from sloughs to ridges to tree islands, but regions also differed significantly in the abundance of several community types and the hydroregimes characterizing them. NMS revealed two significant axes of compositional variation, tied to local gradients of water depth and correlated factors, and to a landscape-scale gradient of proximity to tall tree islands. Sawgrass height and soil thickness increased toward higher ridges, and NDVI was greatest on tree islands. Main conclusionsThis study supports four components of our model: positive feedback of local substrate height on itself, woody plant invasion and subsequent P transport and concentration by top predators nesting on taller tree islands, compositional shifts in sites close to tree islands due to nutrient leakage, and flow-induced feedback against total raised area. Regional divergence in the relationship of community types to current hydroregimes appears to reflect a lag of a few years after shifts in water management; a longer lag would be expected for shifts in landscape patterning. Both local and landscape-level drivers appear to shape vegetation composition and soil thickness in the central Everglades.

Across-scale patterning of plant-soil–water interactions surrounding tree islands in Southern Everglades landscapes

“…Recent research supports the assumption that N and P resource islands play a sink/source role in landscape-scale biogeochemical cycling (e.g. Jayachandran et al 2004;Ross et al 2006;Wetzel et al 2005Wetzel et al , 2009Givnish et al 2008), but the spatial patterns of resource island gradients have not yet been fully described.…”

“…P may also adsorb onto soil particles as calcium phosphate under alkaline conditions. For tree island nucleation to occur, a portion of accumulated P must be available for new recruits (Givnish et al 2008). P-availability and mobility within the Everglades system are primarily controlled by calcium solubility and organic P metabolism/ mineralization (Reddy et al 1998), both of which are decelerated by prolonged flooding and alkaline pH.…”

Nutrients and Hydrology Indicate the Driving Mechanisms of Peatland Surface Patterning

“…Further, we assumed a maximum difference in hydraulic conductivity between hollows and hummocks of 2 orders of magnitude ( fig. 3B; Waddington and Roulet 1997;Givnish et al 2008). It is important to note that we did not take into account vertical variations in hydraulic conductivity.…”

Quantitative Comparison of Plant Community Hydrology Using Large-Extent, Long-Term Data

“…Although hydroperiods have been defined in various ways (Ross et al 2003;Childers et al 2006;Givnish et al 2008;Zweig and Kitchens 2008;Todd et al 2010;LoGalbo et al 2013), they are usually calculated as annual means. In our study, use of environmentally-defined hydroperiods (the hydrologic interval) enlarged the hydrological description by allowing the length of the wet or dry event to extend over several years when appropriate.…”

“…Hydrology can be quantified in a number of ways; variables often include measures of depth and duration of wetness (hydroperiod), as well as flow rate. Typically, variables such as annual mean water depth or hydroperiod length are defined based on Julian years (January 1 to December 31), and data are summarized as averages across years (David 1996;Givnish et al 2008;Todd et al 2010). In seasonal wetland environments, however, such measures smooth out variations that may be important in defining differences among plant community types.…”