Directional connectivity in hydrology and ecology

• Published in: Ecological applications Vol. 22; no. 8; pp. 2204 - 2220
• Main Authors: Larsen, Laurel G, Jungyill Choi, Martha K. Nungesser, Judson W. Harvey
• Format: Journal Article
• Language: English
• Published: United States Ecological Society of America 01.12.2012
• Subjects: biodiversity; Conservation of Natural Resources; Ecosystem; ecosystems; environmental degradation; environmental indicators; Florida; Geological Phenomena; habitats; Hydrology; image analysis; landscapes; Models, Theoretical; planning; prediction; water flow; Water Movements; wind; Florida
• ISSN: 1051-0761; 1939-5582
• DOI: 10.1890/11-1948.1

Quantifying hydrologic and ecological connectivity has contributed to understanding transport and dispersal processes and assessing ecosystem degradation or restoration potential. However, there has been little synthesis across disciplines. The growing field of ecohydrology and recent recognition that loss of hydrologic connectivity is leading to a global decline in biodiversity underscore the need for a unified connectivity concept. One outstanding need is a way to quantify directional connectivity that is consistent, robust to variations in sampling, and transferable across scales or environmental settings. Understanding connectivity in a particular direction (e.g., streamwise, along or across gradient, between sources and sinks, along cardinal directions) provides critical information for predicting contaminant transport, planning conservation corridor design, and understanding how landscapes or hydroscapes respond to directional forces like wind or water flow. Here we synthesize progress on quantifying connectivity and develop a new strategy for evaluating directional connectivity that benefits from use of graph theory in ecology and percolation theory in hydrology. The directional connectivity index (DCI) is a graph‐theory based, multiscale metric that is generalizable to a range of different structural and functional connectivity applications. It exhibits minimal sensitivity to image rotation or resolution within a given range and responds intuitively to progressive, unidirectional change. Further, it is linearly related to the integral connectivity scale length—a metric common in hydrology that correlates well with actual fluxes—but is less computationally challenging and more readily comparable across different landscapes. Connectivity‐orientation curves (i.e., directional connectivity computed over a range of headings) provide a quantitative, information‐dense representation of environmental structure that can be used for comparison or detection of subtle differences in the physical‐biological feedbacks driving pattern formation. Case‐study application of the DCI to the Everglades in south Florida revealed that loss of directional hydrologic connectivity occurs more rapidly and is a more sensitive indicator of declining ecosystem function than other metrics (e.g., habitat area) used previously. Here and elsewhere, directional connectivity can provide insight into landscape drivers and processes, act as an early‐warning indicator of environmental degradation, and serve as a planning tool or performance measure for conservation and restoration efforts.