Mapping changing distributions of dominant species in oil-contaminated salt marshes of Louisiana using imaging spectroscopy

The April 2010 Deepwater Horizon (DWH) oil spill was the largest coastal spill in U.S. history. Monitoring subsequent change in marsh plant community distributions is critical to assess ecosystem impacts and to establish future coastal management priorities. Strategically deployed airborne imaging spectrometers, like the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), offer the spectral and spatial resolution needed to differentiate plant species. However, obtaining satisfactory and consistent classification accuracies over time is a major challenge, particularly in dynamic intertidal landscapes.Here, we develop and evaluate an image classification system for a time series of AVIRIS data for mapping dominant species in a heavily oiled salt marsh ecosystem. Using field-referenced image endmembers and canonical discriminant analysis (CDA), we classified 21 AVIRIS images acquired during the fall of 2010, 2011 and 2012. Classification results were evaluated using ground surveys that were conducted contemporaneously to AVIRIS collection dates. We analyzed changes in dominant species cover from 2010 to 2012 for oiled and non-oiled shorelines.CDA discriminated dominant species with a high level of accuracy (overall accuracy=82%, kappa=0.78) and consistency over three imaging dates (overall2010=82%, overall2011=82%, overall2012=88%). Marshes dominated by Spartina alterniflora were the most spatially abundant in shoreline zones (â¤28m from shore) for all three dates (2010=79%, 2011=61%, 2012=63%), followed by Juncus roemerianus (2010=11%, 2011=19%, 2012=17%) and Distichlis spicata (2010=4%, 2011=10%, 2012=7%).Marshes that were heavily contaminated with oil exhibited variable responses from 2010 to 2012. Marsh vegetation classes converted to a subtidal, open water class along oiled and non-oiled shorelines that were similarly situated in the landscape. However, marsh loss along oil-contaminated shorelines doubled that of non-oiled shorelines. Only S. alterniflora dominated marshes were extensively degraded, losing 15% (354,604m2) cover in oiled shoreline zones, suggesting that S. alterniflora marshes may be more vulnerable to shoreline erosion following hydrocarbon stress, due to their landscape position

Floristic Quality Index and Forested Floristic Quality Index: Assessment Tools for Restoration Projects and Monitoring Sites in Coastal Louisiana

In 2003, the Coastwide Reference Monitoring System (CRMS) program was established in coastal Louisiana marshes and swamps to assess the effectiveness of individual coastal restoration projects and the cumulative effects of multiple projects at regional and coastwide scales (Steyer et al., 2003). In order to make these assessments, analytical teams were assembled for each of the primary data types sampled under theCRMS program, including vegetation, hydrology, landscape, and soils. These teams consisted of scientists and support staff from the US Geological Survey and other federal agencies, the Coastal Protection and Restoration Authority of Louisiana, and university academics. Each team was responsible for developing or identifying parameters, indices, or tools that can be used to assess coastal wetlands at various scales. The CRMS Vegetation Analytical Team has developed a Floristic Quality Index (FQI) for coastal Louisiana to determine the quality of a wetland based on the composition and abundance of its herbaceous plant species (Cretini et al., 2012). The team has also developed a Forested Floristic Quality Index (FFQI) that uses basal area by species to assess the quality and quantity of the overstory at forested wetland sites in Louisiana (Wood et al., 2017). Together these indices can provide an estimate of wetland vegetation health in coastal Louisiana marshes and swamps. The FQI has been developed and used for several regions throughout the United States to provide an objective assessment of the vegetation quality or biological integrity of wetland plant communities. The FQI was first developed as a weighted average of the native plant species at a site (Swink and Wilhelm, 1979). It is based on a coefficient of conservatism (CC) score that is scaled from 0 to 10 and is applied to each plant species in a local flora. The score reflects a species’ tolerance to disturbance and specificity to a particular habitat type. Species adapted to disturbed areas are often not habitat specific and, as such, have a low CC score. In contrast, habitat-specific species are generally not tolerant to disturbances and, as such, have a high CC score. A group of experts on local plants agrees upon and assigns CC scores. The FFQI, which is similar to the FQI, was developed to evaluate ecosystem structural changes among forested wetland sites. The FFQI will be used to (1) evaluate forested wetland sites on a continuum from severely degraded to healthy, (2) assist in defining areas where forested wetland restoration is needed, and (3) determine the effectiveness of future restoration projects aiming to return degraded forested wetlands to healthy ecosystems. While the FQI is based on the percent cover of emergent herbaceous species, the FFQI uses this emergent herbaceous layer data in conjunction with the basal area at a species level and canopy cover. As such, the FFQI is a natural extension of the FQI and can be used in conjunction with the FQI of the understory herbaceous community in forested wetland systems, as there is typically an inverse relation between tree and herbaceous layer vegetation dominance in Louisiana’s coastally restricted forested wetlands that represents natural succession (Conner and Day, 1992a; Shaffer et al., 2009; Nyman, 2014). As environmentally driven temporal shifts occur in the ecosystem, the FFQI contains valuable information that depicts a trajectory in system function. Generally, coastal flooded forested wetlands have transitioned to shrub-scrub; fresh, floating, and intermediate marshes; and open water. Conversely, in a few select locations, such as the Atchafalaya River Delta, the natural deltaic cycle causes the reversal of this trend. In this emerging deltaic environment, the succession of fresh marsh is transitioning into young forested wetlands populated by low value pioneer and disturbance woody species, leading to the development of fledgling swamps (Johnson et al., 1985; Shaffer et al., 1992). These two contrasting successional trajectories occurring within the same coastal system and same monitoring network highlight the need for a multivariable and index approach to site and restoration assessment

Oiling accelerates loss of salt marshes, southeastern Louisiana.

The 2010 BP Deepwater Horizon (DWH) oil spill damaged thousands of km2 of intertidal marsh along shorelines that had been experiencing elevated rates of erosion for decades. Yet, the contribution of marsh oiling to landscape-scale degradation and subsequent land loss has been difficult to quantify. Here, we applied advanced remote sensing techniques to map changes in marsh land cover and open water before and after oiling. We segmented the marsh shorelines into non-oiled and oiled reaches and calculated the land loss rates for each 10% increase in oil cover (e.g. 0% to >70%), to determine if land loss rates for each reach oiling category were significantly different before and after oiling. Finally, we calculated background land-loss rates to separate natural and oil-related erosion and land loss. Oiling caused significant increases in land losses, particularly along reaches of heavy oiling (>20% oil cover). For reaches with ≥20% oiling, land loss rates increased abruptly during the 2010-2013 period, and the loss rates during this period are significantly different from both the pre-oiling (p < 0.0001) and 2013-2016 post-oiling periods (p < 0.0001). The pre-oiling and 2013-2016 post-oiling periods exhibit no significant differences in land loss rates across oiled and non-oiled reaches (p = 0.557). We conclude that oiling increased land loss by more than 50%, but that land loss rates returned to background levels within 3-6 years after oiling, suggesting that oiling results in a large but temporary increase in land loss rates along the shoreline

Land loss rates over reach oiling categories.

<p>Pre-oiling (2006–2010), post-oiling (2010–2013), post-oiling (2013–2016), and background land loss rates over reach oiling categories.</p

Maps of shoreline oiling category and corresponding land loss in Bay Jimmy (map location is shown in Fig 1).

<p>Map A shows shoreline zones and reach mean oil fractions, and map B shows marsh land loss along the same reaches over the three time periods. Narrow strip of the Bay Jimmy island (red box) is an area that experienced extensive oiling treatments for remediation.</p

Cumulative land loss plots.

<p>Shows land losses in m²yr^-1 (A) and percent of cumulative losses (B) over reaches with increasing oil fractions for the three time periods.</p

Maps of shoreline oiling category and corresponding land loss (map location is shown in Fig 1).

<p>Map A shows shoreline zones and reach mean oil fractions, and map B shows marsh land loss along the same reaches of northern Bay Jimmy over the three time periods.</p

Maps of shoreline oiling category and corresponding land loss in Bay Batiste (map location is shown in Fig 1).

<p>Map A shows shoreline zones and reach mean oil fractions, and map B shows marsh land loss along the same reaches of southeastern Bay Batiste over the three time periods.</p

Upper Barataria Bay study area.

<p>Shows shoreline reach oil fractions, NDVI validation locations (red x’s), water level measurement site (blue circle).</p

Assessing coastal wetland vulnerability to sea-level rise along the northern Gulf of Mexico coast: Gaps and opportunities for developing a coordinated regional sampling network.

Coastal wetland responses to sea-level rise are greatly influenced by biogeomorphic processes that affect wetland surface elevation. Small changes in elevation relative to sea level can lead to comparatively large changes in ecosystem structure, function, and stability. The surface elevation table-marker horizon (SET-MH) approach is being used globally to quantify the relative contributions of processes affecting wetland elevation change. Historically, SET-MH measurements have been obtained at local scales to address site-specific research questions. However, in the face of accelerated sea-level rise, there is an increasing need for elevation change network data that can be incorporated into regional ecological models and vulnerability assessments. In particular, there is a need for long-term, high-temporal resolution data that are strategically distributed across ecologically-relevant abiotic gradients. Here, we quantify the distribution of SET-MH stations along the northern Gulf of Mexico coast (USA) across political boundaries (states), wetland habitats, and ecologically-relevant abiotic gradients (i.e., gradients in temperature, precipitation, elevation, and relative sea-level rise). Our analyses identify areas with high SET-MH station densities as well as areas with notable gaps. Salt marshes, intermediate elevations, and colder areas with high rainfall have a high number of stations, while salt flat ecosystems, certain elevation zones, the mangrove-marsh ecotone, and hypersaline coastal areas with low rainfall have fewer stations. Due to rapid rates of wetland loss and relative sea-level rise, the state of Louisiana has the most extensive SET-MH station network in the region, and we provide several recent examples where data from Louisiana's network have been used to assess and compare wetland vulnerability to sea-level rise. Our findings represent the first attempt to examine spatial gaps in SET-MH coverage across abiotic gradients. Our analyses can be used to transform a broadly disseminated and unplanned collection of SET-MH stations into a coordinated and strategic regional network. This regional network would provide data for predicting and preparing for the responses of coastal wetlands to accelerated sea-level rise and other aspects of global change