Salt marshes are among one of the most productive ecosystems in the world and are important components of estuarine systems, since it provide food and nutrients to both estuarine and coastal ocean consumers, serves as a habitat for young and adult estuarine organisms, and a refuge for larval and juvenile organisms and regulating important compounds of the estuarine chemical cycle. The location of salt marshes as a buffer zone between land and sea and the continuously increasing N-‐load from land make it a raising concern regarding monitoring and estimation of its vulnerability to eutrophication and interest in its ability to remove N before its enters the estuaries and coastal ocean waters, along with monitoring of the current N status. Remote sensing is a particular helpful tool when trying to extract information from large areas and to estimate N status of vegetation. The spectral reflectance signature of Spartina alterniflora (a dominant salt marsh species) was investigated in 13 sites with varying N input, within two New England salt marshes (Plum Island Sound and Great Sippewisset Marsh, USA), to survey if remote sensing can be use to sense vegetation response to different nutrient input. Two different remote sensing tools was used; a Duel Channel Unispec, which measure canopy reflectance and a SPAD-‐502 chlorophyll meter, which measure leaf reflectance. Three different vegetation indexes (NDVI, GreenNDVI and EVI) were used to model vegetation biophysical variables. It was not possible to estimate if one index or the other would be better for an overall use to estimate N status but the results indicate the feasibility in predicting N status. SPAD values give an indirect indication of chlorophyll and nitrogen content in leaf biomass but only a low correlation was observed than correlated with red and green reflectance. More emphasis has to be giving on calibration of SPAD measurements to obtain more reliable results. Spectral reflectance data obtained from Unispec measurements, clearly illustrated that the vegetation state in the two sites with highest N input (20 and 300-‐fold larger than reference sites) represented the healthiest green vegetation with a high plant biomass, which correlated with the N input received. In the remaining sites, there was not observed a clear distinguish between the spectral data and observed N input. Remote sensing can provide information about variations in vegetation and give an insight into important vegetation biophysical features. Therefore using remote sensing to determined N status of vegetation is a low cost useful method, but emphasis on future studies in this area should be a priority.
|Educations||Geography, (Bachelor/Graduate Programme) Undergraduate or graduate|
|Publication date||14 Jun 2010|
- SPAD chlorophyll meter
- Remote Sensing
- leaf reflectance
- salt marsh