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.

Knowledge coproduction on the impact of decisions for waterbird habitat in a changing climate.

Scientists, resource managers, and decision makers increasingly use knowledge coproduction to guide the stewardship of future landscapes under climate change. This process was applied in the California Central Valley (USA) to solve complex conservation problems, where managed wetlands and croplands are flooded between fall and spring to support some of the largest concentrations of shorebirds and waterfowl in the world. We coproduced scenario narratives, spatially explicit flooded waterbird habitat models, data products, and new knowledge about climate adaptation potential.

Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat.

Highly mobile species, such as migratory birds, respond to seasonal and interannual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species-distribution models typically rely on long-term average habitat conditions, mostly because large-extent, temporally resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown.

Quantifying drought's influence on moist soil seed vegetation in California's Central Valley through remote sensing.

California's Central Valley, USA is a critical component of the Pacific Flyway despite loss of more than 90% of its wetlands. Moist soil seed (MSS) wetland plants are now produced by mimicking seasonal flooding in managed wetlands to provide an essential food resource for waterfowl. Managers need MSS plant area and productivity estimates to support waterfowl conservation, yet this remains unknown at the landscape scale.

Remotely-sensed indicators of N-related biomass allocation in Schoenoplectus acutus.

Coastal marshes depend on belowground biomass of roots and rhizomes to contribute to peat and soil organic carbon, accrete soil and alleviate flooding as sea level rises. For nutrient-limited plants, eutrophication has either reduced or stimulated belowground biomass depending on plant biomass allocation response to fertilization. Within a freshwater wetland impoundment receiving minimal sediments, we used experimental plots to explore growth models for a common freshwater macrophyte, Schoenoplectus acutus.

Temporal and spatial relationships between watershed land use and salt marsh disturbance in a pacific estuary.

Historical and recent remote sensing data can be used to address temporal and spatial relationships between upland land cover and downstream vegetation response at the watershed scale. This is demonstrated for sub-watersheds draining into Elkhorn Slough, California, where salt marsh habitat has diminished because of the formation of sediment fans that support woody riparian vegetation. Multiple regression models were used to examine which land cover variables and physical properties of the watershed most influenced sediment fan size within 23 sub-watersheds (1.