Rangelands and semi-arid ecosystems are subject to increasing changes in ecologic makeup from a collection of factors. In much of the northern Great Basin, rangelands invaded by exotic annual grasses such as cheatgrass (Broumus tectorum) and medusahead (Taeniatherum caput-medusae) are experiencing an increasingly short fire cycle which is compounding and persistent. Improving and expanding ground-based field methods for measuring above-ground biomass (AGB) may enable more sample collections across a landscape and over succession regimes, and better harmonize with other remote sensing techniques. Developments and increased adoption of uncrewed aerial vehicles and instrumentation for vegetation monitoring are enabling greater understanding of vegetation in many ecosystems. Research towards understanding the relationship of traditional field measurements with newer aerial platforms in rangeland environments is growing rapidly, and there is increasing interest in exploring the potential use both to quantify AGB and fine fuel load at pasture scales. Our study here uses relatively inexpensive handheld photography with custom sampling frames to collect and automatically reconstruct 3D-models of the vegetation within 0.2 m2 quatrats (n = 288). Next, we examine the relationship between volumetric estimates of vegetation to compare with biomass. We found that volumes calculated with 0.5 cm voxel sizes (0.125 cm3) most closely represented the range of biomass weights. We further develop methods to classify ground points, finding a 2% reduction in predictive ability compared to using the true ground surface. Overall, our reconstruction workflow had an R2 of 0.42, further emphasizing the importance of high-resolution imagery and reconstruction techniques. Ultimately, we conclude that more work is needed of increasing extents (such as from UAS) to better understand and constrain uncertainties in volumetric estimations of biomass in ecosystems with high amounts of invasive annual grasses and fine fuel litter.

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 multi-spectral thermal infrared imager to meet a range of needs. First, and perhaps, foremost, it will be the premier integrated observatory for observing the emerging impacts of climate change . It will characterize the diversity of plant life by resolving chemical and physiological signatures. It will address wildfire, observing pre-fire risk, fire behavior and post-fire recovery. It will inform responses to hazards and disasters guiding responses to a wide range of events, including 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 resolution, measurement uncertainty) and assessed the cost, mass, power, volume, and risk of different architectures. The Research and Applications team examined available algorithms, calibration and validation and societal applications and used end-to-end modeling to assess uncertainty. The team also identified valuable opportunities for international collaboration to increase the frequency of revisit through data sharing, adding value for all partners. Analysis of the science, applications, architecture and partnerships led to a clear measurement strategy and a well-defined observing system architecture.

Ecosystem dynamic models have been widely used to estimate terrestrial carbon flux and to project ecosystem structure and composition over time and space, because of their efficiency over direct field measurements and easy applicability to broader spatial coverage. However, such models have also been associated with internal uncertainties, as well as complexities arising from distinct qualities of the ecosystem being analyzed. The widespread sagebrush-steppe ecosystem (dominated by Artemisia spp.) in Western North America holds high ecological and social significance, but is threatened by anthropogenic forcing factors, including impacts from invasive species, climate change, and altered fire regimes. To restore the ecosystem, land managers have focused on reducing flammable vegetation and seeding native species. However, the collective effects of restoration activities, fire, climate change, and invasive species on ecosystem dynamics are poorly understood. We applied the Ecosystem Demography (ED2) model to analyze its effectiveness in predicting plant function type (PFT) composition and ecosystem fluxes, parameterized and validated using empirical datasets for different carbon, vegetation and fire scenarios at Reynolds Creek Experimental Watershed (RCEW), Idaho, USA. We initialized ED2 with 20 x 40 grids of 1 km resolution representing and allowed PFTs to grow for 20 years to reach an equilibrium state. Results showed shrubs dominating C3 grass in a few years of time, sooner for increased CO2 and initial ecosystem condition. A separate scenario with potential fire showed significant loss in biomass within eight years of time. Results from this modeling study can improve our understanding of broad-scale ecosystem processes in sagebrush-steppe landscapes and inform land management and restoration strategies.

Interactions between the land surface and the atmosphere play essential roles in hydrological variations at local scales. Variations of regional climate patterns over preceding years have key effects on the seasonal water and moisture conditions in the following year. The linkage between regional climate and local hydrology is challenging due to scale differences, both spatially and temporally. In this study, multiple hydroclimatic phases were identified to relate climatic teleconnection patterns to hydrological processes in a small headwater basin within Reynolds Creek Experiment Watershed, Idaho, USA. A singular spectrum analysis and a combination of hydrological observations and outputs from a physically based hydrological model were used for this purpose. Results showed that a positive phase of North Atlantic Oscillation (NAO) is more influential than a positive phase of the Pacific North American (PNA) pattern on the observed annual runoff and the modeled rain on snow runoff in the study area. Specifically, we found a 43% and 26% shift below normal in annual runoff and rain on snow runoff from NAO and a 29% and 9% below normal from PNA. More frequent rain on snow events were observed under a positive phase of Antarctic Oscillation, leading to a 45% increase in the rain on snow runoff, which accounts for one-third of the mean annual runoff. A high runoff-to-precipitation ratio was observed in the study area under negative phases of Arctic Oscillation and Sea Surface Temperature in the Niño 3.4 region of the Equatorial Pacific Ocean. A switch in the phase of the teleconnection patterns of NAO and PNA in 2012 was concomitant with a transition from wet to dry conditions in the basin, suggesting the importance of the regional teleconnections in affecting snow and runoff regimes at local scales. The identified hydroclimatic phases can be implemented in operational models to improve uncertainties in hydrological forecasts, climate projections, and water resources planning.