3rd UF Water Institute Symposium Abstract

Submitter's Name Jing Yuan
Session Name Posters - Hydroecology
Category Ecology
Poster Number 15
Author(s) Jing Yuan,  School of Natural Resources and Environment (Presenting Author)
  Matthew Cohen,  School of Forest Resources and Conservation
  Danielle Watts, School of Natural Resources and Environment
  David Kaplan, School of Forest Resources and Conservation
  Detecting Pattern and Pattern Loss in the Everglades Ridge and Slough Landscape
  Detecting vegetation change in the Everglades is vital for effective ecosystem management and monitoring restoration performance. The ridge and slough patterned landscape in the central Everglades has been changing in response to altered hydrology and water quality. The characteristic patches (ridges and sloughs) are on average 75 meters wide, and markedly elongated parallel to historical flow . The spatial configuration patches is widely thought to be a response historical flow regime, and massive system-wide hydrologic over the last 60 years are changing that configuration. Specifically, pattern loss is most evident in significant topographic flattening; this loss of corrugated peat surface morphology, which is strongly bi-modal under the best conserved conditions, ultimately results in loss of the habitat mosaic as vegetation becomes more uniform. Recent evidence suggests that the loss of peat elevation bi-modality precedes changes in simple vegetation pattern metrics as an indicator of landscape degradation. Because the costs of collecting field measurements of soil elevation are high, refined metrics of pattern that yield leading or at least contemporary indicators of landscape degradation are needed. In this work, we present a suite of new and existing pattern metrics developed from theory regarding the source of pattern prevalence , geometry and connectivity; implement those metrics in numerous settings spanning the hydrological gradient from too dry to well conserved to too wet based on high quality vegetation maps delineated from aerial imagery ; and evaluate these metrics based on co-variation with contemporary measurements of soil elevation bi-modality. Preliminary results indicate that some of the metrics in the best conserved areas are distinctly different from hydrologically modified areas, suggesting potential early warning signals of pattern degradation and ultimately vegetation change. By linking pattern metrics explicitly with bimodality, we hope to identify new sensitive and specific diagnostic indicators of landscape change.