Decline in Thermal Habitat Conditions for the Endangered Delta Smelt as Seen from Landsat Satellites (1985-2019).

This study uses Landsat 5, 7, and 8 level 2 collection 2 surface temperature to examine habitat suitability conditions spanning 1985-2019, relative to the thermal tolerance of the endemic and endangered delta smelt (Hypomesus transpacificus) and two non-native fish, the largemouth bass (Micropterus salmoides) and Mississippi silverside (Menidia beryllina) in the upper San Francisco Estuary. This product was validated using thermal radiometer data collected from 2008 to 2019 from a validation site on a platform in the Salton Sea (RMSE = 0.78 °C, r = 0.99, R2 = 0.99, p < 0.01, and n = 237). Thermally unsuitable habitat, indicated by annual maximum water surface temperatures exceeding critical thermal maximum temperatures for each species, increased by 1.5 km2 yr-1 for the delta smelt with an inverse relationship to the delta smelt abundance index from the California Department of Fish and Wildlife (r = -0.44, R2 = 0.2, p < 0.01). Quantile and Theil-Sen regression showed that the delta smelt are unable to thrive when the thermally unsuitable habitat exceeds 107 km2. A habitat unsuitable for the delta smelt but survivable for the non-natives is expanding by 0.82 km2 yr-1. Warming waters in the San Francisco Estuary are reducing the available habitat for the delta smelt.

Detecting forest response to droughts with global observations of vegetation water content.

Droughts in a warming climate have become more common and more extreme, making understanding forest responses to water stress increasingly pressing. Analysis of water stress in trees has long focused on water potential in xylem and leaves, which influences stomatal closure and water flow through the soil-plant-atmosphere continuum. At the same time, changes of vegetation water content (VWC) are linked to a range of tree responses, including fluxes of water and carbon, mortality, flammability, and more. Unlike water potential, which requires demanding in situ measurements, VWC can be retrieved from remote sensing measurements, particularly at microwave frequencies using radar and radiometry. Here, we highlight key frontiers through which VWC has the potential to significantly increase our understanding of forest responses to water stress. To validate remote sensing observations of VWC at landscape scale and to better relate them to data assimilation model parameters, we introduce an ecosystem-scale analog of the pressure-volume curve, the non-linear relationship between average leaf or branch water potential and water content commonly used in plant hydraulics. The sources of variability in these ecosystem-scale pressure-volume curves and their relationship to forest response to water stress are discussed. We further show to what extent diel, seasonal, and decadal dynamics of VWC reflect variations in different processes relating the tree response to water stress. VWC can also be used for inferring belowground conditions-which are difficult to impossible to observe directly. Lastly, we discuss how a dedicated geostationary spaceborne observational system for VWC, when combined with existing datasets, can capture diel and seasonal water dynamics to advance the science and applications of global forest vulnerability to future droughts.

Designing an Observing System to Study the Surface Biology and Geology (SBG) of the Earth in the 2020s.

Observations of planet Earth from space are a critical resource for science and society. Satellite measurements represent very large investments and United States (US) agencies organize their effort to maximize the return on that investment. The US National Research Council conducts a survey of Earth science and applications to prioritize observations for the coming decade. The most recent survey prioritized a visible to shortwave infrared imaging spectrometer and a multispectral thermal infrared imager to meet a range of needs for studying Surface Biology and Geology (SBG). SBG will be the premier integrated observatory for observing the emerging impacts of climate change by characterizing the diversity of plant life and resolving chemical and physiological signatures. It will address wildfire risk, behavior, and recovery as well as responses to hazards such as oil spills, toxic minerals in minelands, harmful algal blooms, landslides, and other geological hazards. The SBG team analyzed needed instrument characteristics (spatial, temporal, and spectral resolutions, measurement uncertainty) and assessed the cost, mass, power, volume, and risk of different architectures. We present an overview of the Research and Applications trade-study analysis of algorithms, calibration and validation needs, and societal applications with specifics of substudies detailed in other articles in this special collection. We provide a value framework to converge from hundreds down to three candidate architectures recommended for development. The analysis identified valuable opportunities for international collaboration to increase the revisit frequency, adding value for all partners, leading to a clear measurement strategy for an observing system architecture.

Turbidity and fecal indicator bacteria in recreational marine waters increase following the 2018 Woolsey Fire.

Wildfires increase runoff and sediment yields that impact downstream ecosystems. While the effects of wildfire on stream water quality are well documented, oceanic responses to wildfire remain poorly understood. Therefore, this study investigated oceanic responses to the 2018 Woolsey Fire using satellite remote sensing and in situ data analyses. We examined 2016-2020 turbidity plume (n = 192) and 2008-2020 fecal indicator bacteria (FIB, n = 15,015) measurements at variable proximity to the Woolsey Fire. Shifts in coastal water quality were more pronounced in the "inside" region, which drained the burn area. The inside region experienced 2018-2019 plume surface area monthly means that were 10 and 9 times greater than 2016-2017 and 2017-2018 monthly means, respectively. Further, linear regressions showed that 2018-2019 three-day precipitation totals produced plumes of greater surface area. We also noted statistically significant increases in the inside region in 2018-2019 total coliform and Enterococcus monthly means that were 9 and 53 times greater than 2008-2018 monthly means, respectively. These results indicate that sediment and microbial inputs to coastal ecosystems can increase substantially post-wildfire at levels relevant to public and environmental health, and underscore the benefit of considering remote sensing and in situ measurements for water quality monitoring.

Determining the intrinsic dimension of a hyperspectral image using random matrix theory.

Determining the intrinsic dimension of a hyperspectral image is an important step in the spectral unmixing process and under- or overestimation of this number may lead to incorrect unmixing in unsupervised methods. In this paper, we discuss a new method for determining the intrinsic dimension using recent advances in random matrix theory. This method is entirely unsupervised, free from any user-determined parameters and allows spectrally correlated noise in the data. Robustness tests are run on synthetic data, to determine how the results were affected by noise levels, noise variability, noise approximation, and spectral characteristics of the endmembers. Success rates are determined for many different synthetic images, and the method is tested on two pairs of real images, namely a Cuprite scene taken from Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) and SpecTIR sensors, and a Lunar Lakes scene taken from AVIRIS and Hyperion, with good results.