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Some seagrass meadows in coastal shallow waters have displayed large scale changes in seagrass spatial extent and hurricanes and/or tropical storms have been suggested as factors responsible for reduction in coverage. Taking advantage of the incidence of three tropical storms passing near a study site along the central west Florida coast within a two-month period in 2004, we evaluated whether satellite remote sensing techniques (Landsat 5 Thematic Mapper (TM) imagery) are useful for assessing dynamics of seagrass (=submerged aquatic vegetation: SAV) cover/abundance in response to these multiple disturbances. We also examined whether an image preprocessing procedure, which included water column correction, applied to the Landsat TM images could further improve the classification and mapping of detailed SAV coverage. We compared a historical set of Landsat TM images, acquired in Fall 2003 and Fall and late Summer 2005, which were processed to classify %SAV cover into five classes using a maximum likelihood classifier. Importantly, our experimental results demonstrated that the application of the image preprocessing procedures led to an overall accuracy 2–14% improvement in SAV classification due to water column correction compared to that currently reported in the literature when similar Landsat TM data are utilized. Based upon the classification results mapped from the TM images and as well as a similar classification of SAV interpreted from aerial photographs collected before and after the passage of these same storms, SAV coverage over the study areas was found to increase about 6% (integrating SAV losses and gains) by 2005/2006 in comparison to cover levels present prior to the repeated storm activity. We conclude that heavy rains during 2004 along with physical disturbance from gale force winds from the tropical storms/hurricanes did not produce any SAV bed loss at the study site that was sustained for more than one year after multiple storm passage.

Seagrass habitats provide a variety of ecosystem functions thus monitoring of seagrass habitat is a priority of coastal management. Remote sensing techniques can provide spatial and temporal information about seagrass habitats. Given the availability and accessibility of Landsat-5 Thematic Mapper (TM) and the advanced nature of Earth Observing-1 Advanced Land Imager (ALI) and Hyperion (HYP), we compared the capability of the three 30 m resolution satellite sensors and tested regression models based on two seagrass metrics [percent cover of submerged aquatic vegetation (%SAV) and leaf area index (LAI)] for mapping and assessing seagrass habitats within a shallow coastal area along the central western coast of FL, USA. We also evaluated a water depth correction approach to create water depth-invariant bands calculated from the three sensors' data. Then a maximum likelihood classifier was used to classify the %SAV cover into two classification schemes (3-class and 5-class). Based upon the two seagrass metrics measured in the field, six multiple regression models were developed and %SAV and LAI were estimated with spectral variables derived from the three sensors to assess the seagrass habitats in mapped units. Our results indicate that the HYP sensor produced the best seagrass cover maps in the two classification schemes: 3-class [overall accuracy (OA) = 95.9%] and 5-class (OA = 78.4%) and the best %SAV and LAI estimation models [R2 = 0.78 and 0.59, and cross-validation (CV) = 18.1% and 1.40 for %SAV and LAI, respectively] for assessing seagrass habitats. These results are likely due to the many narrow bands in the visible spectral range and rich subtle spectral information available in the HYP hyperspectral data. ALI outperformed TM (OA = 94.6% vs. 92.5% for the 3-class scheme, and OA = 77.8% vs. 66.0% for the 5-class scheme) for mapping %SAV likely due to its higher radiometric resolution. Our findings also demonstrate that the water depth correction approach was effective in mapping the detailed seagrass habitats with the data from the three sensors. The protocol developed and utilized here represents a new contribution to the existing set of tools used by researchers for documenting the amount of seagrass and which can guide future studies.

The scale of landscape pattern formation of an ecological community may provide clues as to the processes influencing its spatial and temporal dynamics. We conducted an examination of the spatial organization of an annual seagrass ( Halophila decipiens ) in an open ocean setting at two spatial scales and growing seasons to identify the relative influence of external (hurricanes) versus internal (clonal growth) factors. Visual surveys of seagrass cover were conducted over 2 years within three replicate 1 km 2 study areas each separated by ∼25 km in an inshore–offshore transect along the southwest coast of Florida at depths between ∼10 and 30 m. A towed video sled allowed observations of seagrass cover of 1 m 2 areas approximately every 6 m over thousands of meters of evenly spaced transects within the study areas (coarse scale). The towed video revealed that 17.5% of the seafloor was disturbed irrespective of location or sample time. Randomly selected 10 × 10 m quadrats within the larger, 1 km 2 study areas were completely surveyed for seagrass cover by divers at 0.625 m 2 resolution (fine scale). The coarse-scale observations were tested using both conventional geostatistics and an application of a time-series technique (Runs test) for scale of seagrass cover contiguity. Fine-scale observations were examined using conventional geostatistics and a least squares approach (cumulative logistic). The coarse-scale observations revealed little scale dependency and indicated that the structure was organized at spatial extents finer than our sample spacing; the cumulative logistic technique revealed potential fine-scale patterns not otherwise discerned. In contrast, surveys of the 10 × 10 m quadrats detected strong scale dependency with multiple small gaps, indicating scale-dependent patterns arising from processes operating at extents generally Halophila decipiens that likely arose from transported seeds. Spatial analysis revealed that the storm led to a shift to greater frequency of H. decipien s, but lower density coverage. Seagrass density remained substantially depressed in all areas a full year following the storm. The short life history of H. decipiens and the apparent existence of a moveable seed bank means that spatial organization of this community is dictated first by large-scale dispersal of plant propagules (hundreds of meters) and then within a growing season, by clonal organization of the seagrass operating over very small distances (m). The two techniques (semivariance and Runs test) led to similar conclusions regarding the organizational scales of seagrass landscape pattern. As with terrestrial examples, this study demonstrates the importance of selecting the appropriate scale for detection of landscape pattern and processes influencing population ecology of a seagrass ecosystem.

Resorption, the remobilization and subsequent transport of leaf constituents (e.g. N, C, and P) into the perennial structures of the plant prior to leaf abscission, may be interrupted or prevented by stressors that interfere with the normal course of leaf senescence. Mangroves that lie along the latitudinal extremes of their distribution are susceptible to freeze damage that may periodically disrupt the normal resorptive process. On January 24, 2003, the white mangroves (Laguncularia racemosa) in a northern portion of Tampa Bay, Florida were exposed to freezing temperatures for 8 h. The leaves of these trees were noticeably withered by this freeze event. Over a four-month period following the freeze, we compared the subsequent rate of leaf litter production at this site to that of two, apparently undamaged, fringing mangrove forests in Tampa Bay. We also examined the carbon and nitrogen concentrations of the leaf litter from the litter traps at these three sites and compared it to that of green, yellow (nearly senescent), and freeze-damaged leaves hand-picked from the mangroves. A pronounced pulse of leaf litter fall (maximum: 7 g dw m−2 d−1) was found at the putatively freeze-damaged site but not at the two comparison sites. In addition, the leaf litter at the freeze-damaged site was richer in nitrogen and carbon, and had a lower C:N than litter collected at the comparison sites. Comparison of the elemental composition of this leaf litter with leaves hand-picked from the mangroves suggests that the freeze event killed the leaves of L. racemosa, interrupting the process of resorption. This perturbation to nutrient flow may have implications for mangrove forest structure and the entry of mangrove material into food webs.

A descriptive study of the architecture of the red mangrove, Rhizophora mangle L., habitat of Tampa Bay, FL, was conducted to assess if plant architecture could be used to discriminate overwash from fringing forest type. Seven above-water (e.g., tree height, diameter at breast height, and leaf area) and 10 below-water (e.g., root density, root complexity, and maximum root order) architectural features were measured in eight mangrove stands. A multivariate technique (discriminant analysis) was used to test the ability of different models comprising above-water, below-water, or whole tree architecture to classify forest type. Root architectural features appear to be better than classical forestry measurements at discriminating between fringing and overwash forests but, regardless of the features loaded into the model, misclassification rates were high as forest type was only correctly classified in 66% of the cases. Based upon habitat architecture, the results of this study do not support a sharp distinction between overwash and fringing red mangrove forests in Tampa Bay but rather indicate that the two are architecturally undistinguishable. Therefore, within this northern portion of the geographic range of red mangroves, a more appropriate classification system based upon architecture may be one in which overwash and fringing forest types are combined into a single, “tide dominated” category.

The size (age) class structure of a population of Manayunkia aestuarina (Bourne) was monitored in a South Carolina salt marsh for 1 year. Reproduction in this polychaete was discontinuous; brooded embryos and juvenile recruitment were not observed in winter months (November–March). The North American population of M. aestuarina displays different reproductive traits from those reported in England although population densities from the two geographic regions appear to be stable over the period of years. M. aestuarina attains sexual maturity while in the meiofaunal size range; yet, there are marked differences in its biology compared to typical ‘interstitial polychaetes’. M. aestuarina and selected meiofaunal taxa exhibit convergent adaptations for a semi-sedentary existence.