Marine & Environmental Sciences Faculty Articles

Metacommunity Structure Along Resource and Disturbance Gradients in Everglades Wetlands

Document Type

Article

Publication Title

Wetlands

ISSN

0277-5212

Publication Date

6-2014

Keywords

Niche-based models, Dispersal, Metacommunity, Community structure, Community assembly, Variation partitioning

Abstract

We evaluated metacommunity hypotheses of landscape arrangement (indicative of dispersal limitation) and environmental gradients (hydroperiod and nutrients) in structuring macroinvertebrate and fish communities in the southern Everglades. We used samples collected at sites from the eastern boundary of the southern Everglades and from Shark River Slough, to evaluate the role of these factors in metacommunity structure. We used eigenfunction spatial analysis to model community structure among sites and distance-based redundancy analysis to partition the variability in communities between spatial and environmental filters. For most animal communities, hydrological parameters had a greater influence on structure than nutrient enrichment, however both had large effects. The influence of spatial effects indicative of dispersal limitation was weak and only periphyton infauna appeared to be limited by regional dispersal. At the landscape scale, communities were well-mixed, but strongly influenced by hydrology. Local-scale species dominance was influenced by water-permanence and nutrient enrichment. Nutrient enrichment is limited to water inflow points associated with canals, which may explain its impact in this data set. Hydroperiod and nutrient enrichment are controlled by water managers; our analysis indicates that the decisions they make have strong effects on the communities at the base of the Everglades food web.

DOI

10.1007/s13157-013-0413-1

Volume

34

Issue

Supplement 1

First Page

135

Last Page

146

Comments

©Society of Wetland Scientists 2013

Additional Comments

FIU/National Park Service Cooperative Agreement #: H5000060104, Task: J5284060023; NSF grant #: DBI-0620409

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Peer Reviewed

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