Abstract
With the increasing appreciation that sea grass habitats are in global decline, there is a great need to be able to efficiently and effectively assess and characterize the status and trends of sea grass in our coastal ecosystems. This paper examines the utility of remotely sensed vs. in situ plot-based monitoring using the Barnegat Bay-Little Egg Harbor (BB-LEH), New Jersey, USA estuarine system as a case study. Eelgrass (Zostera marina) is the dominant species, while widgeon grass (Ruppia maritima) is also common in lower salinity regions of the BB-LEH. Aerial imagery collected during the months of July and August 2009 was interpreted and mapped using object based image analysis techniques, similar to techniques used in the 2003 mapping survey of this system. Boat-based in situ monitoring data were collected concurrently with the aerial photography to assist the image interpretation and for an independent accuracy assessment. We compared the remotely-sensed mapping of sea grass cover change (in 2003 vs. 2009) vs. in situ plot-based monitoring conducted from 2004 through 2009. Comparison of the remotely-sensed vs. the in situ plot-change analysis suggests that the two methodologies had broadly similarly results, with the percent area showing declines in sea grass cover greater than those that exhibited increases. In conclusion, the two studies provide corroborating evidence that sea grass has declined in percent cover in the BB-LEH system during the decade of the 2000’s. While remotely-sensed surveys provide synoptic information for a “big picture” view on sea grass distribution, site specific in situ sampling is required to determine other aspects of sea grass status, e.g. above vs. below-ground biomass, blade length, shoot density, epiphytic loading, etc. Either method alone gives an incomplete picture. As demonstrated in this study, to fully characterize the spatial extent, health, and density of sea grass meadows across the entire estuary, combining remote sensing surveys concomitantly with comprehensive in situ assessment provides the most robust approach.
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