Methods to characterize spatial-temporal patterns of pond transitions in estuarine ecosystems

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Aiyin Zhang, Graduate School of Geography, Clark University, Worcester, MA

Background/Question/Methods
Tidal ponds, also known as tidal pools are natural formations of inundated pools commonly found in salt marshes. Ponds are valuable habitats for a number of key species and provide other essential ecosystem services such as fish production. Ponds in salt marshes are increasing in both number and area, and studies speculate that the increase in tidal ponds is caused by climate change-induced sea-level rise (SLR). Pond increase is also a major contributing factor to the area loss of salt marshes. Investigating long-term pond transitions at estuarine ecosystems in response to SLR requires an understanding of the spatial-temporal pattern of pond transitions. I developed quantitative methods to characterize spatial-temporal patterns of pond transition at the Plum Island Ecosystems Long Term Ecological Research (PIE-LTER) site. Manually digitized land cover maps of PIE at the years 1938, 1971, and 2013 show pond transitions across the 3 time points. By overlaying the 3 maps, I mapped various spatial-temporal patterns of pond transitions, and developed metrics that characterize and quantify temporal differences of ponds.

Results/Conclusions
Results reveal dramatic changes in ponds at PIE-LTER that raise questions about the reliability of the dataset for the purpose of studying long term change of ponds. The data show gross gain is greater than gross loss of ponds from 1938 to 2013. Among the entire area of pond that is pond at any time, only 5% is area of pond that is present at all three time points. Sixty-eight percent of pond at any time is the total area of pond that appear in exactly one time point. The annual gross gain of ponds during the first time interval, 1938-1971 is greater than the annual gross gain of ponds during the second time interval, 1971-2013, while the annual gross loss of ponds during the second time interval is larger than that of the first time interval. These results call for further investigation of the quality of the dataset.