A Meta-analysis of Tropical Cyclone Effects on Seagrass Meadows

Correia, Kelly M.; Smee, Delbert L.

doi:10.1007/s13157-022-01611-0

Cited by 9 publications

(3 citation statements)

References 96 publications

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“…This corresponded with the prevailing wind direction of the leading edge (the most destructive/strongest winds) of the outer wind bands of Ivan (Figure A4). Several studies that have employed the use of wave models have reported similar directional impacts of storms on seagrass beds/meadows; these impacts were also associated with the prevailing direction of the storm winds [81,82]. Also, seagrass declines following storms are usually associated with persistent changes in seawater quality and burial [83].…”

Section: Spatial Pattern Predictors Of Sav Changementioning

confidence: 93%

“…Also, seagrass declines following storms are usually associated with persistent changes in seawater quality and burial [83]. Greater exposure to the direction of the prevailing winds of a storm was one of two factors that explained the depth of burial of seagrasses found along the Spanish Mediterranean coast (higher exposure to storm winds increased burial depths) that were impacted by Storm Gloria in 2020 [82]. Burial may have been the main impact of Ivan, as there were several bare sand patches present during the 2006-2013 period (Figure 3), one of which was described as a "sand bar" by [30].…”

Section: Spatial Pattern Predictors Of Sav Changementioning

confidence: 99%

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Long-Term Spatial Pattern Predictors (Historically Low Rainfall, Benthic Topography, and Hurricanes) of Seagrass Cover Change (1984 to 2021) in a Jamaican Marine Protected Area

McLaren,

Sedman,

McIntyre

et al. 2024

Remote Sensing

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Climate change and other anthropogenic factors have caused a significant decline in seagrass cover globally. Identifying the specific causes of this decline is paramount if they are to be addressed. Consequently, we identified the causes of long-term change in seagrass/submerged aquatic vegetation (SAV) percentage cover and extent in a marine protected area on Jamaica’s southern coast. Two random forest regression (RFr) models were built using 2013 hydroacoustic survey SAV percentage cover data (dependent variable), and auxiliary and 2013 Landsat 7 and 8 reflectance data as the predictors. These were used to generate 24 SAV percentage cover and benthic feature maps (SAV present, absent, and coral reef) for the period 1984–2021 (37 years) from Landsat satellite series reflectance data. These maps and rainfall data were used to determine if SAV extent/area (km2) and average percentage cover and annual rainfall changed significantly over time and to evaluate the influence of rainfall. Additionally, rainfall impact on the overall spatial patterns of SAV loss, gain, and percentage cover change was assessed. Finally, the most important spatial pattern predictors of SAV loss, gain, and percentage cover change during 23 successive 1-to-4-year periods were identified. Predictors included rainfall proxies (distance and direction from river mouth), benthic topography, depth, and hurricane exposure (a measure of hurricane disturbance). SAV area/extent was largely stable, with >70% mean percentage cover for multiple years. However, Hurricane Ivan (in 2004) caused a significant decline in SAV area/extent (by 1.62 km2, or 13%) during 2002–2006, and a second hurricane (Dean) in 2007 delayed recovery until 2015. Additionally, rainfall declined significantly by >1000 mm since 1901, and mean monthly rainfall positively influenced SAV percentage cover change and had a positive overall effect on the spatial pattern of SAV cover percentage change (across the entire bay) and gain (close to the mouth of a river). The most important spatial pattern predictors were the two rainfall proxies (areas closer to the river mouth were more likely to experience SAV loss and gain) and depth, with shallow areas generally having a higher probability of SAV loss and gain. Three hurricanes had significant but different impacts depending on their distance from the southern coastline. Specifically, a hurricane that made landfall in 1988 (Gilbert), resulted in higher SAV percentage cover loss in 1987–1988. Benthic locations with a northwestern/northern facing aspect (the predominant direction of Ivan’s leading edge wind bands) experienced higher SAV losses during 2002–2006. Additionally, exposure to Ivan explained percentage cover loss during 2006–2008 and average exposure to (the cumulative impact of) Ivan and Dean (both with tracks close to the southern coastline) explained SAV loss during 2013–2015. Therefore, despite historic lows in annual rainfall, overall, higher rainfall was beneficial, multiple hurricanes impacted the site, and despite two hurricanes in three years, SAV recovered within a decade. Hurricanes and a further reduction in rainfall may pose a serious threat to SAV persistence in the future.

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Section: Spatial Pattern Predictors Of Sav Changementioning

confidence: 93%

Section: Spatial Pattern Predictors Of Sav Changementioning

confidence: 99%

Long-Term Spatial Pattern Predictors (Historically Low Rainfall, Benthic Topography, and Hurricanes) of Seagrass Cover Change (1984 to 2021) in a Jamaican Marine Protected Area

McLaren,

Sedman,

McIntyre

et al. 2024

Remote Sensing

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“…Species diversity has received less attention but may also drive seagrass ecosystem functioning: speciesdriven variation in plant physical structure and physiology affect canopy and belowground properties that ultimately affect carbon accumulation and storage. Species diversity, in terms of both richness and identity, may also reflect the community response to an ecological disturbance via succession within a seagrass meadow (Williams 1990;Martínez López et al 2019;Correia and Smee 2022). In this way, species diversity may be correlated to meadow successional status and disturbance history, which are also likely drivers of carbon storage.…”

Section: Introductionmentioning

confidence: 99%

Seagrass meadow stability and composition influence carbon storage

2023

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Context Seagrass ecosystems are lauded for storing organic carbon in underlying sediments, but storage is highly variable, even at relatively small spatial scales. While environmental setting and seagrass cover are known drivers of carbon storage capacity, it is unclear how other seagrass features such as species composition influence carbon storage, and whether historical vs. contemporary features are better predictors of storage. Objectives We examined the influence of historical and contemporary seagrass variables on surface (0–10 cm) sediment organic carbon storage at the meadow-scale (~ 25 km2), in addition to the influence of environmental drivers. Our study area was located within a subtropical mixed-species seagrass meadow along a low-energy coastline in the northeastern Gulf of Mexico (Cedar Key, Florida, USA). Methods We derived historical metrics of seagrass cover and composition from 14-year seagrass monitoring datasets and measured surface sediment carbon densities and grain size, contemporary seagrass biomass and species composition, as well as environmental characteristics related to hydrology and physical disturbance (i.e., relative exposure, elevation, and distance to navigation channels). We assessed bivariate relationships between predictor variables and surface carbon densities with linear regression analyses and used path analysis to assess hypothesized relationships between a subset of predictor variables and carbon densities. Results While low relative to global values, surface carbon densities in Cedar Key seagrass meadows varied by an order of magnitude. Sediment grain size was strongly related to carbon densities, but environmental variables had only indirect effects on carbon densities. Historical seagrass cover, variability in cover, and species diversity were generally better predictors of storage than contemporary variables. Historical and contemporary species identity–specifically the presence of Thalassia testudinum–were also significant drivers of storage. Conclusions In Cedar Key, historically diverse and persistent seagrass meadows dominated by late-successional species contained the largest surface carbon stores. Our results highlight the importance of site history in terms of meadow stability (inversely measured as variability in cover) as well as species identity and diversity in enhancing surface carbon storage. The environmental variables we examined had comparatively weak effects on carbon densities, however, relative exposure and elevation may not be the most relevant hydrological drivers of carbon storage at the meadow scale. Together, these findings suggest that drivers of seagrass meadow carbon storage are context and scale dependent.

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