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Extreme events such as the summer drought of 2018 in Central Europe are projected to occur more frequently in the future and may cause major damages including increased tree mortality and negative impacts on forest ecosystem services. Here, we quantify the response of >1 million forest pixels of 10 × 10 m across Switzerland to the 2018 drought in terms of resistance, recovery, and resilience. We used the Normalized Difference Water Index (NDWI) derived from Sentinel‐2 satellite data as a proxy for canopy water content and analyzed its relative change. We calculated NDWI change between the 2017 pre‐drought and 2018 drought years (indicating resistance), 2018 and the 2019 post‐drought (indicating recovery), and between 2017–2019 (indicating resilience). Analyzing the data from this large natural experiment, we found that for 4.3% of the Swiss forest the NDWI declined between 2017 and 2018, indicating areas with low resistance of the forest canopy to drought effects. While roughly 50% of this area recovered, in 2.7% of the forested area NDWI continued to decline from 2018 to 2019, suggesting prolonged negative effects or delayed damage. We found differential forest responses to drought associated with site topographic characteristics and forest stand characteristics, and to a lesser extent with climatic conditions and interactions between these drivers. Low drought resistance and high recovery were most prominent at forest edges, but also on south‐facing slopes and lower elevations. Tree functional type was the most important driver of drought resilience, with most of the damage in stands with high conifer abundance. Our results demonstrate the suitability of satellite‐based quantification of drought‐induced forest damage at high spatial resolution across large areas. Such information is important to predict how local site characteristics may impact forest vulnerability to future extreme events and help in the search for appropriate adaptation strategies. [ABSTRACT FROM AUTHOR]

Abstract Mangroves are valuable ecosystems for coastal protection, carbon sequestration and storage, and they provide habitat, refuge and rearing areas for many important marine species. To control mosquito outbreaks in coastal regions, mangroves were often impounded and managed using a variety of techniques that ranged from the application of insecticides to water level manipulation. Since continuous impounding had been shown to have negative effects on mangrove vegetation, other techniques have been used to manage hydrology in impoundments. A recent technique is called rotational impoundment management (RIM) and it involves flooding impoundments in summer and spring, the reproductive season of the mosquitos. In this study, we assessed the effects of 5 years of RIM management on mangrove vegetation in an impoundment on the east coast of Florida. We compared mangrove vegetation in the RIM impoundment with an adjacent impoundment that was not managed. We created a map of leaf area index (LAI) to assess vegetation productivity and its change in the two impoundments. We classified color-infrared aerial photographs from 2008 to 2010 and a WorldView-2 satellite image from 2014 to measure the extent of mangrove vegetation types and temporal changes in the two impoundments. We found a 38% increase in cover of dense mangrove vegetation after five years for the RIM-impounded area. Classification accuracy was around 80% for all imagery. The increased growth of plants and cover of dense mangroves in the RIM impoundment was corroborated by observed leaf area index values. Overall, the study demonstrates that vegetation in the RIM impoundment is becoming denser and in the near future will probably become similar to an impoundment that is open to tidal exchange or mangrove dominated areas that are not impounded. [ABSTRACT FROM AUTHOR]

Coastal ecosystems are greatly endangered due to anthropogenic development and climate change. Multiple disturbances may erode the ability of a system to recover from stress if there is little time between disturbance events. We evaluated the ability of the saltmarshes in Barataria Bay, Louisiana, USA, to recover from two successive disturbances, the DeepWater Horizon oil spill in 2010 and Hurricane Isaac in 2012. We measured recovery using vegetation indices and land cover change metrics. We found that after the hurricane, land loss along oiled shorelines was 17.8%, while along oil-free shorelines, it was 13.6% within the first 7 m. At a distance of 7-14 m, land loss from oiled regions was 11.6%, but only 6.3% in oil-free regions. We found no differences in vulnerability to land loss between narrow and wide shorelines; however, vegetation in narrow sites was significantly more stressed, potentially leading to future land loss. Treated oiled regions also lost more land due to the hurricane than untreated regions. These results suggest that ecosystem recovery after the two disturbances is compromised, as the observed high rates of land loss may prevent salt marsh from establishing in the same areas where it existed prior to the oil spill. [ABSTRACT FROM AUTHOR]

The Arctic is currently undergoing intense changes in climate; vegetation composition and productivity are expected to respond to such changes. To understand the impacts of climate change on the function of Arctic tundra ecosystems within the global carbon cycle, it is crucial to improve the understanding of vegetation distribution and heterogeneity at multiple scales. Information detailing the fine-scale spatial distribution of tundra communities provided by high resolution vegetation mapping, is needed to understand the relative contributions of and relationships between single vegetation community measurements of greenhouse gas fluxes (e.g., ∼1 m chamber flux) and those encompassing multiple vegetation communities (e.g., ∼300 m eddy covariance measurements). The objectives of this study were: (1) to determine whether dominant Arctic tundra vegetation communities found in different locations are spectrally distinct and distinguishable using field spectroscopy methods; and (2) to test which combination of raw reflectance and vegetation indices retrieved from field and satellite data resulted in accurate vegetation maps and whether these were transferable across locations to develop a systematic method to map dominant vegetation communities within larger eddy covariance tower footprints distributed along a 300 km transect in northern Alaska. We showed vegetation community separability primarily in the 450-510 nm, 630-690 nm and 705-745 nm regions of the spectrum with the field spectroscopy data. This is line with the different traits of these arctic tundra communities, with the drier, often non-vascular plant dominated communities having much higher reflectance in the 450-510 nm and 630-690 nm regions due to the lack of photosynthetic material, whereas the low reflectance values of the vascular plant dominated communities highlight the strong light absorption found here. High classification accuracies of 92% to 96% were achieved using linear discriminant analysis with raw and rescaled spectroscopy reflectance data and derived vegetation indices. However, lower classification accuracies (∼70%) resulted when using the coarser 2.0 m WorldView-2 data inputs. The results from this study suggest that tundra vegetation communities are separable using plot-level spectroscopy with hand-held sensors. These results also show that tundra vegetation mapping can be scaled from the plot level (<1 m) to patch level (<500 m) using spectroscopy data rescaled to match the wavebands of the multispectral satellite remote sensing. We find that developing a consistent method for classification of vegetation communities across the flux tower sites is a challenging process, given the spatial variability in vegetation communities and the need for detailed vegetation survey data for training and validating classification algorithms. This study highlights the benefits of using fine-scale field spectroscopy measurements to obtain tundra vegetation classifications for landscape analyses and use in carbon flux scaling studies. Improved understanding of tundra vegetation distributions will also provide necessary insight into the ecological processes driving plant community assemblages in Arctic environments. [ABSTRACT FROM AUTHOR]

Summary [ABSTRACT FROM AUTHOR]

Abstract: Conservation of threatened and endangered species requires maintenance of critical habitat. The red-cockaded woodpecker Picoides borealis (RCW) is a threatened bird species, endemic to the mixed conifer forests of the southeastern United States. RCW nests and forages preferentially in mature longleaf pine Pinus palustris, but also uses mature loblolly pine Pinus taeda and shortleaf pine Pinus echinata forests. In the last century, the extent of mature pine forests has been greatly reduced by logging. The RCW, in contrast to other woodpeckers, excavates nest cavities in living trees and senescence symptoms (year round leaf chlorosis and leaf mortality) have been observed in mature pine stands across the southeast. Widespread mortality of the mature pine forests would threaten the long-term survival of the RCW. We used airborne hyperspectral data across a portion of Ft. Benning Military Installation, Georgia, U.S.A., to determine if senescent trees can be identified and mapped and assess the likely persistence of mature pines in the RCW habitat. Univariate analysis of variance showed good separation between asymptomatic, senesced and dead physiological conditions with asymptomatic trees having significantly higher reflectance for all bands in the wavelength range between 0.719 and 1.1676µm, senescent trees having significantly lower reflectance for bands in the range between 1.1927 and 1.3122µm, and dead trees having significantly higher reflectance for bands in the range between 1.8151 and 1.9471µm. Classification and Regression Tree (CART) models achieved correct classification rates and kappa statistics above 70%. CART models selected information from wavelength regions similar to those identified from the ANOVA, which likely explains their performance. Our aggregated CART model of tree senescence estimated that 141.4ha (3%) of the study area is affected. RCW nests occurred in areas with significantly higher tree cover, and trees within foraging and home ranges did not have significantly more senescence than areas without RCW. These results indicate that although tree senescence is widespread, mortality is yet to significantly affect RCW habitat. Results and analysis of critical habitat similar to those exemplified in this study can extend our knowledge about the stressors of these important and imperiled components of biodiversity. [Copyright &y& Elsevier]

Abstract: Estuaries are among the most invaded ecosystems on the planet. Such invasions have led in part, to the formation of a massive $1 billion restoration effort in California''s Sacramento–San Joaquin River Delta. However, invasions of weeds into riparian, floodplain, and aquatic habitats threaten the success of restoration efforts within the watershed and jeopardize economic activities. The doctrine of early detection and rapid response to invasions has been adopted by land and water resource managers, and remote sensing is the logical tool of choice for identification and detection. However meteorological, physical, and biological heterogeneity in this large system present unique challenges to successfully detecting invasive weeds. We present three hyperspectral case studies which illustrate the challenges, and potential solutions, to mapping invasive weeds in wetland systems: 1) Perennial pepperweed was mapped over one portion of the Delta using a logistic regression model to predict weed occurrence. 2) Water hyacinth and 3) submerged aquatic vegetation (SAV), primarily composed of Brazilian waterweed, were mapped over the entire Delta using a binary decision tree that incorporated spectral mixture analysis (SMA), spectral angle mapping (SAM), band indexes, and continuum removal products. Perennial pepperweed detection was moderately successful; phenological stage influenced detection rates. Water hyacinth was mapped with modest accuracies, and SAV was mapped with high accuracies. Perennial pepperweed and water hyacinth both exhibited significant spectral variation related to plant phenology. Such variation must be accounted for in order to optimally map these species, and this was done for the water hyacinth case study. Submerged aquatic vegetation was not mapped to the species level due to complex non-linear mixing problems between the water column and its constituents, which was beyond the scope of the current study. We discuss our study in the context of providing guidelines for future remote sensing studies of aquatic systems. [Copyright &y& Elsevier]