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Quantifying seagrass light requirements using an algorithm to spatially resolve depth of colonization.
Beck, M., Jim Hagy, AND C. Le. Quantifying seagrass light requirements using an algorithm to spatially resolve depth of colonization. Estuaries and Coasts. Estuarine Research Federation, Port Republic, MD, 41(2):592-610, (2018).
This manuscript describes the development and application of an algorithm for estimating seagrass depth of colonization from geospatial datasets. Combined with satellite estimates of water clarity, this information can be used to characterize habitat requirements and is expected to inform more effective management of coastal seagrass communities.
Depth of colonization (Zc) is a useful seagrass growth metric that describes seagrass response to light availability. Similarly, percent surface irradiance at Zc (% SI) is an indicator of seagrass light requirements with applications in seagrass ecology and management. Methods for estimating Zc and % SI are highly variable making meaningful comparisons difficult. A new algorithm is presented to compute maps of median and maximum Zc, Zc,med, and Zc,max, respectively, for four Florida coastal areas (Big Bend, Tampa Bay, Choctawhatchee Bay, Indian River Lagoon). Maps of light attenuation (Kd) based on MODIS satellite imagery, PAR profiles, and Secchi depth measurements were combined with seagrass growth estimates to produce maps of % SI at Zc,med and Zc,max. Among estuary segments, mean Zc,med varied from (±SE) 0.80 ± 0.13 m for Old Tampa Bay to 2.33 ± 0.26 m for Western Choctawhatchee Bay. Standard errors for Zc,med were 1–10% of the segment means. Percent SI at Zc,med averaged 18% for Indian River Lagoon (range = 9–24%), 42% for Tampa Bay (37–48%), and 58% for Choctawhatchee Bay (51–75%). Estimates of % SI were significantly lower in Indian River Lagoon than in the other estuaries, while estimates for Tampa Bay and Choctawhatchee Bay were higher than the often cited estimate of 20%. Spatial gradients in depth of colonization and % SI were apparent in all estuaries. The analytical approach could be applied easily to new data from these estuaries or to other estuaries and could be incorporated routinely in assessments of seagrass status and condition.
Record Details:Record Type: DOCUMENT (JOURNAL/PEER REVIEWED JOURNAL)
Organization:U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
NATIONAL HEALTH AND ENVIRONMENTAL EFFECTS RESEARCH LABORATORY
GULF ECOLOGY DIVISION