Forecasting sites of future coastal marsh loss using topographical relationships and logistic regression

Abstract

The last two assessments of the Intergovernmental Panel on Climate Change (IPCC) predict that rates of sea level rise will begin to accelerate by c. 2030–2040 CE. Considering that many marsh systems are already under threat from existing sea level trends, a dramatic upswing in rate only a few decades away poses critical questions about what the future may hold for these marshes (and those yet to manifest sea level impacts) requires coast-wide assessments. Extrapolations of detailed historical trends traditionally have provided the least equivocal way of providing such information, but the necessary data required for this approach are often lacking. In this paper, we describe how logistic regression analysis applied to spatial data on marsh loss and degradation—in this case derived from a validated Landsat-based marsh condition model—and its relation to such readily determined parameters as distance from shorelines or tidal creeks can be used to predict where future marsh losses may occur, even in those systems not presently affected. As such, it affords more targeted information for planning than can be had from general submergence versus accretion/elevation change models (e.g., SLAMM) that are limited by the paucity of vertical accretion data. The results also reinforce the concept that marsh adjustment to sea level rise can be broadly deduced at the landscape level, which in some respects is independent of marsh type and is responsive to tidal frame and coastal profile.