Using a GIS-tool to evaluate potential eelgrass reestablishment in estuaries

Mogens R. Flindt, Erik K. Rasmussen, Thomas Valdemarsen, Anders Erichsen, Hanne Kaas and Paula Canal-Vergés

Ecological Modelling, 2016, vol. 338, issue C, 122-134

Abstract: The lacking recovery of eelgrass (Zostera marina) has been observed in many coastal areas throughout the world. Through a strategic field project we managed to characterize and quantify the impact of new and already known stressors and their thresholds on the recovery process. The stressing mechanisms were 1) Physical stress from wave and current action 2) low sediment anchoring capacity facilitate uprooting of eelgrass seedlings; 3) benthic light intensity 4) ballistic stress from drifting macroalgae are damaging seedlings, 5) too frequent resuspension impoverishing the benthic light climate and dispersing seeds to deeper areas not sufficiently supported with light, 6) lugworms burial of seeds, and uprooting or burial of seedlings. Based on the field and supporting laboratory studies we present a GIS-tool that from data on a suite of stressors are able to predict potential areas for recovery of eelgrass by transplantation actions and seed broadcast. Input data may be field data or model simulation results. Here we have used model results. These input data were reclassified into 5 ranges, according to how much it impacted the eelgrass recovery process: 1) Optimal recovery, 2) Good recovery, 3) Threshold for recovery, 4) Poor recovery and 5) Very poor recovery. Afterward a weighed overlay function was performed, ending up with an accumulated value for stress impact on the eelgrass recovery process in all location in the Danish estuary, Odense Fjord. The GIS-tool is able to calculate and visualize areas of individual and/or multi-stress situations at specific locations. It also managed to identify potential recovery area at the present loading and after a 30% reduction of the external nitrogen loading of the system. Further validation by field activities is needed to verify the precision of the tool.

Keywords: Eelgrass; Recovery; GIS-analysis (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:338:y:2016:i:c:p:122-134

DOI: 10.1016/j.ecolmodel.2016.07.005

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