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Modeled Sea Level Rise Impacts on Coastal Ecosystems at Six Major Estuaries on Florida's Gulf Coast: Implications for Adaptation Planning.

Geselbracht LL, Freeman K, Birch AP, Brenner J, Gordon DR - PLoS ONE (2015)

Bottom Line: The Charlotte Harbor and Tampa Bay study areas were predicted to experience the greatest net loss in coastal wetlands The uncertainty analyses revealed low to moderate changes in results when some numerical SLAMM input parameters were varied highlighting the value of collecting long-term sedimentation, accretion and erosion data to improve SLAMM precision.The changes predicted by SLAMM will affect exposure of adjacent human communities to coastal hazards and ecosystem functions potentially resulting in impacts to property values, infrastructure investment and insurance rates.The results and process presented here can be used as a guide for communities vulnerable to SLR to identify and prioritize adaptation strategies that slow and/or accommodate the changes underway.

View Article: PubMed Central - PubMed

Affiliation: The Nature Conservancy, Florida Chapter, Altamonte Springs, Florida, United States of America.

ABSTRACT
The Sea Level Affecting Marshes Model (SLAMM) was applied at six major estuaries along Florida's Gulf Coast (Pensacola Bay, St. Andrews/Choctawhatchee Bays, Apalachicola Bay, Southern Big Bend, Tampa Bay and Charlotte Harbor) to provide quantitative and spatial information on how coastal ecosystems may change with sea level rise (SLR) and to identify how this information can be used to inform adaption planning. High resolution LiDAR-derived elevation data was utilized under three SLR scenarios: 0.7 m, 1 m and 2 m through the year 2100 and uncertainty analyses were conducted on selected input parameters at three sites. Results indicate that the extent, spatial orientation and relative composition of coastal ecosystems at the study areas may substantially change with SLR. Under the 1 m SLR scenario, total predicted impacts for all study areas indicate that coastal forest (-69,308 ha; -18%), undeveloped dry land (-28,444 ha; -2%) and tidal flat (-25,556 ha; -47%) will likely face the greatest loss in cover by the year 2100. The largest potential gains in cover were predicted for saltmarsh (+32,922 ha; +88%), transitional saltmarsh (+23,645 ha; na) and mangrove forest (+12,583 ha; +40%). The Charlotte Harbor and Tampa Bay study areas were predicted to experience the greatest net loss in coastal wetlands The uncertainty analyses revealed low to moderate changes in results when some numerical SLAMM input parameters were varied highlighting the value of collecting long-term sedimentation, accretion and erosion data to improve SLAMM precision. The changes predicted by SLAMM will affect exposure of adjacent human communities to coastal hazards and ecosystem functions potentially resulting in impacts to property values, infrastructure investment and insurance rates. The results and process presented here can be used as a guide for communities vulnerable to SLR to identify and prioritize adaptation strategies that slow and/or accommodate the changes underway.

No MeSH data available.


Related in: MedlinePlus

Bar graph of loss/gain of coastal ecosystems for all six study areas (summed).The SLAMM results illustrated in this bar graph are for the following 3 sea level rise scenarios: 0.7m, 1m, 2m. All scenarios were run with developed dry land protected from change in the SLAMM user interface.
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pone.0132079.g009: Bar graph of loss/gain of coastal ecosystems for all six study areas (summed).The SLAMM results illustrated in this bar graph are for the following 3 sea level rise scenarios: 0.7m, 1m, 2m. All scenarios were run with developed dry land protected from change in the SLAMM user interface.

Mentions: Overall, coastal wetland ecosystems at all six study areas along Florida’s Gulf Coast are likely to change substantially. Under the 1 m SLR scenario, SLAMM predicted that coastal forest, tidal flat, inland freshwater marsh and tidal swamp will lose the most spatial extent, -69,309 ha, -25,552 ha, -7,733 ha, and -5,069 ha, respectively (Table 4; Fig 9). In terms of percent loss, the coastal wetland ecosystems predicted to be most adversely affected included tidal swamp, tidal flat, coastal forest and estuarine beach with -54%, -47%, -18% and -17%, respectively. In addition, undeveloped dry land was predicted by SLAMM to lose -28,445 ha under the 1 m SLR scenario, or 2% of the developed dry land in the study areas. Coastal wetland ecosystems predicted by SLAMM to gain spatial extent under the 1 m SLR scenario included saltmarsh (+32,923 ha; 88%), transitional saltmarsh (+23,645 ha; 81%), mangrove forest (+12,583 ha; 60%), brackish marsh (+6,365 ha; 40%) and tidal freshwater marsh (+3,594 ha). As was noted for some of the individual study areas, some reversals were noted in habitat responses between the 1 m and 2 m SLR by 2100 scenarios (Fig 9). For example, at the slower rates of SLR studied (0.7 m and 1 m by 2100), mangrove forests were able to expand in extent, but at 2 m of SLR by 2100, they lost extent to open water. The same threshold seemed to be acting on estuarine beach and ocean beach as both these ecosystems more than doubled in percent lost between the 1 m and 2 m SLR by 2100 scenarios.


Modeled Sea Level Rise Impacts on Coastal Ecosystems at Six Major Estuaries on Florida's Gulf Coast: Implications for Adaptation Planning.

Geselbracht LL, Freeman K, Birch AP, Brenner J, Gordon DR - PLoS ONE (2015)

Bar graph of loss/gain of coastal ecosystems for all six study areas (summed).The SLAMM results illustrated in this bar graph are for the following 3 sea level rise scenarios: 0.7m, 1m, 2m. All scenarios were run with developed dry land protected from change in the SLAMM user interface.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4514811&req=5

pone.0132079.g009: Bar graph of loss/gain of coastal ecosystems for all six study areas (summed).The SLAMM results illustrated in this bar graph are for the following 3 sea level rise scenarios: 0.7m, 1m, 2m. All scenarios were run with developed dry land protected from change in the SLAMM user interface.
Mentions: Overall, coastal wetland ecosystems at all six study areas along Florida’s Gulf Coast are likely to change substantially. Under the 1 m SLR scenario, SLAMM predicted that coastal forest, tidal flat, inland freshwater marsh and tidal swamp will lose the most spatial extent, -69,309 ha, -25,552 ha, -7,733 ha, and -5,069 ha, respectively (Table 4; Fig 9). In terms of percent loss, the coastal wetland ecosystems predicted to be most adversely affected included tidal swamp, tidal flat, coastal forest and estuarine beach with -54%, -47%, -18% and -17%, respectively. In addition, undeveloped dry land was predicted by SLAMM to lose -28,445 ha under the 1 m SLR scenario, or 2% of the developed dry land in the study areas. Coastal wetland ecosystems predicted by SLAMM to gain spatial extent under the 1 m SLR scenario included saltmarsh (+32,923 ha; 88%), transitional saltmarsh (+23,645 ha; 81%), mangrove forest (+12,583 ha; 60%), brackish marsh (+6,365 ha; 40%) and tidal freshwater marsh (+3,594 ha). As was noted for some of the individual study areas, some reversals were noted in habitat responses between the 1 m and 2 m SLR by 2100 scenarios (Fig 9). For example, at the slower rates of SLR studied (0.7 m and 1 m by 2100), mangrove forests were able to expand in extent, but at 2 m of SLR by 2100, they lost extent to open water. The same threshold seemed to be acting on estuarine beach and ocean beach as both these ecosystems more than doubled in percent lost between the 1 m and 2 m SLR by 2100 scenarios.

Bottom Line: The Charlotte Harbor and Tampa Bay study areas were predicted to experience the greatest net loss in coastal wetlands The uncertainty analyses revealed low to moderate changes in results when some numerical SLAMM input parameters were varied highlighting the value of collecting long-term sedimentation, accretion and erosion data to improve SLAMM precision.The changes predicted by SLAMM will affect exposure of adjacent human communities to coastal hazards and ecosystem functions potentially resulting in impacts to property values, infrastructure investment and insurance rates.The results and process presented here can be used as a guide for communities vulnerable to SLR to identify and prioritize adaptation strategies that slow and/or accommodate the changes underway.

View Article: PubMed Central - PubMed

Affiliation: The Nature Conservancy, Florida Chapter, Altamonte Springs, Florida, United States of America.

ABSTRACT
The Sea Level Affecting Marshes Model (SLAMM) was applied at six major estuaries along Florida's Gulf Coast (Pensacola Bay, St. Andrews/Choctawhatchee Bays, Apalachicola Bay, Southern Big Bend, Tampa Bay and Charlotte Harbor) to provide quantitative and spatial information on how coastal ecosystems may change with sea level rise (SLR) and to identify how this information can be used to inform adaption planning. High resolution LiDAR-derived elevation data was utilized under three SLR scenarios: 0.7 m, 1 m and 2 m through the year 2100 and uncertainty analyses were conducted on selected input parameters at three sites. Results indicate that the extent, spatial orientation and relative composition of coastal ecosystems at the study areas may substantially change with SLR. Under the 1 m SLR scenario, total predicted impacts for all study areas indicate that coastal forest (-69,308 ha; -18%), undeveloped dry land (-28,444 ha; -2%) and tidal flat (-25,556 ha; -47%) will likely face the greatest loss in cover by the year 2100. The largest potential gains in cover were predicted for saltmarsh (+32,922 ha; +88%), transitional saltmarsh (+23,645 ha; na) and mangrove forest (+12,583 ha; +40%). The Charlotte Harbor and Tampa Bay study areas were predicted to experience the greatest net loss in coastal wetlands The uncertainty analyses revealed low to moderate changes in results when some numerical SLAMM input parameters were varied highlighting the value of collecting long-term sedimentation, accretion and erosion data to improve SLAMM precision. The changes predicted by SLAMM will affect exposure of adjacent human communities to coastal hazards and ecosystem functions potentially resulting in impacts to property values, infrastructure investment and insurance rates. The results and process presented here can be used as a guide for communities vulnerable to SLR to identify and prioritize adaptation strategies that slow and/or accommodate the changes underway.

No MeSH data available.


Related in: MedlinePlus