Detection of drought‐induced blue oak mortality in the Sierra Nevada Mountains, California

How megadrought causes extensive mortality in a deep-rooted shrub species normally resistant to drought-induced dieback: The role of a biotic mortality agent

Southern California experienced unprecedented megadrought between 2012 and 2018. During this time, Malosma laurina, a chaparral species normally resilient to single-year intense drought, developed extensive mortality exceeding 60% throughout low-elevation coastal populations of the Santa Monica Mountains. We assessed the physiological mechanisms by which the advent of megadrought predisposed M. laurina to extensive shoot dieback and whole-plant death. We found that hydraulic conductance of stem xylem (Ks, native ) was reduced seven to 11-fold in dieback adult and resprout branches, respectively. Staining of stem xylem vessels revealed that dieback plants experienced 68% solid-blockage, explaining the reduction in water transport. Following Koch's postulates, persistent isolation of a microorganism in stem xylem of dieback plants but not healthy controls indicated that the causative agent of xylem blockage was an opportunistic endophytic fungus, Botryosphaeria dothidea. We inoculated healthy M. laurina saplings with fungal isolates and compared hyphal elongation rates under well-watered, water-deficit, and carbon-deficit treatments. Relative to controls, we found that both water deficit and carbon-deficit increased hyphal extension rates and the incidence of shoot dieback.

Capturing patterns of evolutionary relatedness with reflectance spectra to model and monitor biodiversity

Biogeographic history can set initial conditions for vegetation community assemblages that determine their climate responses at broad extents that land surface models attempt to forecast. Numerous studies have indicated that evolutionarily conserved biochemical, structural, and other functional attributes of plant species are captured in visible-to-short wavelength infrared, 400 to 2,500 nm, reflectance properties of vegetation. Here, we present a remotely sensed phylogenetic clustering and an evolutionary framework to accommodate spectra, distributions, and traits. Spectral properties evolutionarily conserved in plants provide the opportunity to spatially aggregate species into lineages (interpreted as "lineage functional types" or LFT) with improved classification accuracy. In this study, we use Airborne Visible/Infrared Imaging Spectrometer data from the 2013 Hyperspectral Infrared Imager campaign over the southern Sierra Nevada, California flight box, to investigate the potential for incorporating evolutionary thinking into landcover classification. We link the airborne hyperspectral data with vegetation plot data from 1372 surveys and a phylogeny representing 1,572 species. Despite temporal and spatial differences in our training data, we classified plant lineages with moderate reliability (Kappa = 0.76) and overall classification accuracy of 80.9%. We present an assessment of classification error and detail study limitations to facilitate future LFT development. This work demonstrates that lineage-based methods may be a promising way to leverage the new-generation high-resolution and high return-interval hyperspectral data planned for the forthcoming satellite missions with sparsely sampled existing ground-based ecological data.