Mapping changes in tidal wetland vegetation composition and pattern across a salinity gradient using high spatial resolution imagery (original) (raw)
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Ecological Indicators, 2011
Tidal salt marshes in the San Francisco Estuary region display heterogeneous vegetation patterns that influence wetland function and provide adequate habitat for native or endangered wildlife. In addition to analyzing the extent of vegetation, monitoring the dynamics of vegetation pattern within restoring wetlands can offer valuable information about the restoration process. Pattern metrics, derived from classified remotely sensed imagery, have been used to measure composition and configuration of patches and landscapes, but they can be unpredictable across scales, and inconsistent across time. We sought to identify pattern metrics that are consistent across spatial scale and time -and thus robust measures of vegetation and habitat configuration -for a restored tidal marsh in the San Francisco Bay, CA, USA. We used high-resolution (20 cm) remotely sensed color infrared imagery to map vegetation pattern over 2 years, and performed a multi-scale analysis of derived vegetation pattern metrics. We looked at the influence on metrics of changes in grain size through resampling and changes in minimum mapping unit (MMU) through smoothing. We examined composition, complexity, connectivity and heterogeneity metrics, focusing on perennial pickleweed (Sarcocornia pacifica), a dominant marsh plant. At our site, pickleweed patches grew larger, more irregularly shaped, and closely spaced over time, while the overall landscape became more diverse. Of the two scale factors examined, grain size was more consistent than MMU in terms of identifying relative change in composition and configuration of wetland marsh vegetation over time. Most metrics exhibited unstable behavior with larger MMUs. With small MMUs, most metrics were consistent across grain sizes, from fine (e.g. 0.16 m 2 ) to relatively large (e.g. 16 m 2 ) pixel sizes. Scale relationships were more variable at the landcover class level than at the landscape level (across all classes). This information may be useful to applied restoration practitioners, and adds to our general understanding of vegetation change in a restoring marsh.
Vegetation Colonization in a Restoring Tidal Marsh: A Remote Sensing Approach
Restoration Ecology, 2008
Although remote sensing offers the ability to monitor wetland restoration, few have tested automated methods for quantifying vegetation change. We implemented a semiautomated technique using color infrared aerial photography and a common vegetation index, Normalized Difference Vegetation Index (NDVI), to document vegetation colonization in a restoring salt marsh. Change in vegetation over a period of 10 years was analyzed using a postclassification comparison technique where each image year was classified individually into vegetated and nonvegetated areas using NDVI thresholds and then differenced between years to identify areas of vegetation change. Vegetated and nonvegetated areas were identified using this technique, as were areas and time periods of vegetation change. By comparing classified NDVI imagery, we calculated that 90% of our study site was vege-tated 10 years after restoration. This study demonstrated that high-resolution remotely sensed data can be analyzed with common geospatial software to monitor change in a rapidly vegetating wetland and that long time frames with yearly image acquisition are needed to quantify plant colonization rates. This method was effective at detecting change in vegetation over time in a variable tidal marsh environment using imagery that had inconsistent specifications and quality across years. Inconsistencies included interannual climate variation, phenology, and presence of algae, as well as differences in pixel size and image brightness. Our findings indicate that remote sensing is useful for postrestoration monitoring of tidal marsh ecosystems.
Plant Ecology, 2001
A hierarchical classification of forested wetland communities was developed for the lower Roanoke River floodplain of northeastern North Carolina, USA, through the use of multitemporal and multispectral satellite digital data. Landsat Thematic Mapper (TM) images from different seasons (March-April, May-June, July-August) throughout a single year were used to exploit the phenological variability of forest communities for generating a landcover classification of ecologically important vegetation types within the floodplain. A hierarchical classification scheme was developed that relied upon customized spectral 'feature sets' of Landsat TM bands and their transformations to generate the classified images for each level of the forest community classification scheme. The objective was to enhance the discrimination of the community types at subsequent levels of the hierarchical classification scheme through different spectral inputs from the assembled satellite time series in conjunction with detailed floristic information collected though in-situ methods. As such, general landcover classes were iteratively reclassified into more detailed classes at correspondingly 'deeper' levels or nodes in the hierarchy. Vegetation classes included 21 forest communities and several other ecologically important classes in the study area. The integration of detailed field data permitted spatially-explicit and highly descriptive definitions of the forest types occurring within the floodplain. Additional field data were used to validate the compositional and structural characteristics of the mapped plant communities described by the classification scheme. Use of fuzzy set theory in the accuracy assessment provided details on the magnitude and direction of errors in the classification, and permitted ecological interpretation of those errors. The application of fuzzy set concepts to the mapping of bottomland forest communities is significant because these forests typically exhibit substantial variation in species composition and support diverse canopy dominants. Unlike the discrete classification assessments that are traditionally employed, fuzzy sets report accuracy according to the degree of correctness of a mapped class. By this method, the natural variability of the forest communities can be reported relative to a continuous scale ranging from full membership, to partial membership, to zero membership. Using the most stringent rules for class membership, the classification was 92.1% accurate, but was 96.6% accurate when fuzzy (transitional) relationships between forest types were considered. Diagnostic statistics indicated the magnitude of classification correctness and the degree of confusion and/or ambiguity for classes at various levels of the classification scheme. Assessing classification accuracy through a continuous scale of membership simulated the natural variability and transitional nature of the forested wetland communities within the study area.
Fine-Scale Mapping of Coastal Plant Communities in the Northeastern USA
Wetlands, 2018
Salt marshes of the northeastern United States are dynamic landscapes where the tidal flooding regime creates patterns of plant zonation based on differences in elevation, salinity, and local hydrology. These patterns of zonation can change quickly due to both natural and anthropogenic stressors, making tidal marshes vulnerable to degradation and loss. We compared several remote sensing techniques to develop a tool that accurately maps high-and low-marsh zonation to use in management and conservation planning for this ecosystem in the northeast USA. We found that random forests (RF) outperformed other classifier tools when applied to the most recent National Agricultural Imagery Program (NAIP) imagery, NAIP derivatives, and elevation data between coastal Maine and Virginia, USA. We then used RF methods to classify plant zonation within a 500-m buffer around coastal marsh delineated in the National Wetland Inventory. We found mean classification accuracies of 94% for high marsh, 76% for low marsh zones, and 90% overall map accuracy. The detailed output is a 3-m resolution continuous map of tidal marsh vegetation communities and cover classes that can be used in habitat modeling of marsh-obligate species or to monitor changes in marsh plant communities over time.
The purpose of this project was to evaluate and compare methodologies for using remotely sensed hyperspatial imagery from both Unmanned Aircraft Systems (UAS) and nextgeneration satellite technology to calculate species composition and ecosystem service metrics in a coastal intermediate marsh. Such methods would be important steps towards comprehensive monitoring of wetland landscapes and would provide useful metrics to study wetland condition and response to ecosystem restoration and disturbance events. BACKGROUND: Plant species composition, cover, density, and biomass are structural components of coastal marshes that are commonly used to quantify vegetative characteristics and often serve as indicators of wetland condition (Chamberlain and Ingram 2012; Cretini et al. 2012). Historically, regional and coastwide surveys to map coastal vegetation have consisted of laborious traversing of wetland landscapes, including time consuming and subjective ocular estimates of species type and cover (O'Neil 1949; Chabreck and Linscombe 1978; Sasser et al. 2014). Although recent surveys, like those in coastal Louisiana, enlist the use of helicopters for transport between, and hovering over, sampling sites, they continue to rely on ocular estimates of dominant species and abundance (i.e., Braun-Blanquet cover scale), they are costly, and are typically reproduced approximately every ten years. Rapid species classification (even of dominant plants) using remotely sensed data would provide many advantages over traditional field techniques.
Remote Sensing of Environment, 2007
We used LiDAR topographic data, AVIRIS hyperspectral data, and locally measured tidal fluctuations to characterize patterns of plant distribution within a southern California salt marsh (Carpinteria Salt Marsh (CSM)). LiDAR data required ground truthing and correction before they were suitable for use. Twenty to forty percent of the uncertainty associated with LiDAR was due to variance in the elevation of the target surface, the balance was attributed to error inherent in the LiDAR system. The incidence of LiDAR penetration of plant canopy cover (i.e., registration of ground elevation) was only three percent. The depth of LiDAR penetration into the plant canopy varied according to plant species composition; plant species-specific corrections significantly improved LiDAR accuracy (58% reduction in overall uncertainty) and with the use of ground-based surveys, reduced overall RMSE to an average of 6.3 cm in vegetated areas. A supervised classification of AVIRIS data was used to generate a vegetation map with six classification types; overall classification accuracy averaged 59% with a kappa coefficient of 0.40. The vegetation classification map was overlaid with a LiDAR-based digital elevation model (DEM) to compute elevation distributions and frequencies of tidal inundation. The average elevations of the dominant plant classifications found in CSM (e.g., Salicornia virginica, Jaumea carnosa, and salt-grass mix, a mixture of multiple marsh plant species) occurred within a 17 cm range, a vertical change that resulted in a 7% difference in the period of tidal inundation.
Urban development in the California coastal zone has greatly impacted the ecological integrity of estuarine wetlands. Anthropogenic modifications to natural wetland structure and hydrology can have negative consequences for the composition of estuarine biotic communities. Monitoring wetlands at the ecoregion level is an important tool for understanding how wetland condition is changing over time and can be the basis for hypotheses about the causative factors influencing resource condition. It provides information for managers beyond the site scale and can better guide agency priorities for management and restoration region-wide. Our study was a component of the 2002 United States Environmental Protection Agency (USEPA) Environmental Monitoring and Assessment Program (EMAP) Western Pilot. We measured indicators of estuarine wetland plant community condition in two regions: southern California and the San Francisco (SF) Bay, with the goal of providing information of practical use to wetland managers. The regional surveys included a comprehensive assessment of the plant communities at probabilistically selected locations across the intertidal marsh plain. In addition, in southern California, an assessment of anthropogenic stressors was conducted determining the amount of tidal muting and by assessing the intensity of surrounding land use and human population density. Results indicate that the two regions differed substantially in terms of plant community composition and structure. Southern California wetlands supported a higher diversity of plant species, were more prone to invasion by exotic species, and exhibited less zonation of plant species within the intertidal zone than the SF Bay. There were negative effects of tidal muting on the marsh plant community within southern California, such as disappearance of certain native species and the propensity for invasive species to encroach the marsh plain. Conversely, indicators of anthropogenic stress in the surrounding landscape did not correlate with plant community structure. This paper evaluates the effectiveness of the indicators used in this study, explores the utility and drawbacks of the selected survey design, and discusses how results from such surveys may inform restoration and management actions in southern California estuarine wetlands.
Journal of Vegetation Science, 2013
Questions: What is the relative importance of topographic (elevation), edaphic (soil salinity, nitrogen and particle size) and hydrologic (estuarine river flow) gradients for variation in tidal wetland plant composition and diversity? Location: Four Oregon estuaries: a marine-dominated lagoon, two tidal-driven bays, and a river-dominated site. Methods: We surveyed species presence, cover and richness; and environmental factors (soil salinity, grain size, soil nitrogen and elevation) in plots in marsh and swamp. We assessed patterns of community structure and the relative importance of environmental gradients with hierarchical partitioning, ordination, species accumulation curves and path analysis. Results: The relative importance of measured environmental gradients on plant occurrence differed by species. Soil salinity or elevation explained the most variation in the majority of common species. Estuarine hydrology, soil nitrogen and soil clay content were usually of secondary or minor importance. Assemblage composition and species richness varied most strongly with tidal elevation. Local soil salinity also affected composition, but differences in estuarine hydrology had comparatively less effect on composition and richness. Higher-elevation wetlands supported larger species pools and higher plot-level richness; fresher wetlands had larger species pools than salt marsh but plot-level richness was relatively invariant to differences in soil salinity. Conclusions: Elevation and salinity tended to exert more influence on the vegetation structure of tidal wetlands than estuarine hydrology or other edaphic variables. With relative sea-level rise expected to increase both flooding intensity and salinity exposure in future wetlands, global climate change may lead to changes in species distributions, altered floristic composition and reduced plant species richness. because sea-level rise (SLR) or other changes may alter intertidal stressors or resource availability (Parker et al. 2011; Stralberg et al. 2011). Plant composition in coastal marshes and swamps is determined in part by abiotic factors such as salinity and tidal inundation (Engels & Jensen 2009; Watson & Byrne 2009). Elevation relative to tide level is an important driver of plant composition in the Pacific Northwest (Eilers 1975), as it is in other geographic regions (
Marine Ecology Progress Series, 2021
Elevation is a major driver of plant ecology and sediment dynamics in tidal wetlands, so accurate and precise spatial data are essential for assessing wetland vulnerability to sea-level rise and making forecasts. We performed survey-grade elevation and vegetation surveys of the Global Change Research Wetland, a brackish microtidal wetland in the Chesapeake Bay estuary, Maryland (USA), to both intercompare unbiased digital elevation model (DEM) creation techniques and to describe niche partitioning of several common tidal wetland plant species. We identified a tradeoff between scalability and performance in creating unbiased DEMs, with more data-intensive methods such as kriging performing better than 3 more scalable methods involving post-processing of light detection and ranging (LiDAR)-based DEMs. The LiDAR Elevation Correction with Normalized Difference Vegetation Index (LEAN) method provided a compromise between scalability and performance, although it underpredicted variability...
Wetlands Ecology and Management, 2017
Accurately mapping, modeling, and managing the diversity of wetlands present in estuaries often relies on habitat classification systems that consistently identify differences in biotic structure or other ecosystem characteristics between classes. We used field data from four Oregon estuaries to test for differences in vegetation structure and edaphic characteristics among three tidal emergent marsh classes derived from National Wetlands Inventory (NWI) data: low estuarine marsh, high estuarine marsh, and tidal palustrine marsh. Independently of NWI class, we also evaluated the number and types of plant assemblages present and how edaphic variables, nonnative plant cover, and plant species richness varied among them. Pore water salinity varied most strongly across marsh classes, with sediment carbon and nitrogen content, grain size and marsh surface elevation showing smaller differences. Cover of common vascular plant species differed between marsh classes and overall vegetation composition was somewhat distinct among marsh types. High estuarine marsh had the largest species pools. However, plot-level plant diversity was similar among marsh classes. Nonnative species cover was highest in tidal palustrine and high estuarine marshes. The marshes in the study contained a large number of plant assemblages with most occurring across more than one marsh class. The more common assemblages occurred along a continuum of tidal elevation, soil salinity, and edaphic characteristics, with varying plant richness and nonnative cover. Our data suggest that NWI classes are useful for differentiating several general features of Oregon tidal marsh structure, but that more detailed information on plant assemblages found within those wetland classes would allow more precise characterization of additional wetland features such as edaphic conditions and plant diversity.