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Accurate characterization of evapotranspiration (ET) is imperative in water-limited cropping systems such as California vineyards and almond orchards. Satellite-based ET modeling techniques, including the atmosphere–land exchange inverse model (ALEXI) and associated flux disaggregation technique (DisALEXI), have proven reliable in determining field scale ET. However, validation efforts typically focus on ET and omit an evaluation of partitioned evaporation (E) and transpiration (T). ALEXI/DisALEXI is based on the two-source energy balance (TSEB) model, making it uniquely qualified to derive E and T individually. The current study evaluated E and T estimates derived using two formulations of DisALEXI; one based on Priestley-Taylor (DisALEXI-PT) and the other on Penman-Monteith (DisALEXI-PM). The modeled values were validated against partitioned fluxes derived from the conditional eddy covariance (CEC) approach using EC flux towers in three wine grape vineyards and three almond orchards for the year 2021. Modeled estimates were derived using Landsat 8 Collection 2 thermal infrared and surface reflectance imagery as well as Harmonized Landsat and Sentinel-2 surface reflectance datasets as input into DisALEXI. The results indicated that the modeled total ET fluxes were similar between the two methods, but the partitioned values diverged, with DisALEXI-PT overestimating E and slightly underestimating T when compared to CEC estimates. Conversely, DisALEXI-PM agreed better with CEC-derived E and overestimated T estimates under non-advective conditions. Compared to one another, DisALEXI-PM estimated canopy temperatures ~5 °C cooler and soil temperatures ~5 °C warmer than DisALEXI-PT, causing differences in E and T of −2.6 mm day−1 and +2.6 mm day−1, respectively. The evaluation of the iterative process required for DisALEXI indicates DisALEXI-PM ET values converge on ALEXI ET with proportionate adjustments to E and T, while DisALEXI-PT convergence is driven by adjustments to E. The analysis presented here can potentially drive improvements in the modeling framework to provide specific soil and canopy consumptive water use information in unique canopy structures, allowing for improved irrigation and water use efficiencies in these water-limited systems. [ABSTRACT FROM AUTHOR]

Sustainable use of available water resources in viticulture can be aided by frequent high-resolution information on vineyard water status. Recently, a new Shuttleworth–Wallace evapotranspiration (ET) model, which uses a contextual framework to determine dry and wet extremes from the Sentinel-2 surface reflectance data (SW-S2), showed promising results when tested over a GRAPEX (Grape Remote-sensing Atmospheric Profile and ET eXperiment) site in California. However, current knowledge on its applicability across the climate gradient in California and how the selections of modeling domain and meteorological data influence model outputs are limited. This study expands the evaluation of the SW-S2 model across multiple domains and meteorological inputs covering all three GRAPEX sites over the 2018–2020 growing seasons. In comparison with flux tower observations, the size of the modeling domain did not have a strong influence on model performance, although the model performed marginally better under a larger domain (yielding root mean square error within 1.03–1.11 mm d−1 and mean biases within 2%). The source and quality of meteorological forcing data, in particular vapor pressure deficit (VPD) and wind speed (u), were found to have a strong influence on model output as indicated by the poor performance of the model with less accurate regional and coarse-scale gridded meteorological inputs. Results suggest that simple regression for local bias correction of VPD and u significantly improved model performance. Overall, this study supports future research aiming to merge outputs from more frequent spectral and less frequent thermal-based ET models and reduce latency in ET monitoring of California vineyards. [ABSTRACT FROM AUTHOR]

The island spotted skunk (Spilogale gracilis amphiala) is endemic to the 2 largest California Channel Islands, Santa Cruz and Santa Rosa. Unlike the island fox (Urocyon littoralis) and island subspecies of the deer mouse (Peromyscus maniculatus), the island spotted skunk shows no morphological differentiation between islands and is differentiated only weakly from mainland subspecies, suggesting recent colonization. However, the islands have been isolated from each other and the mainland throughout the Quaternary Period. We used 8 microsatellite loci to investigate the distribution of genetic variation within and among populations of spotted skunks from 8 localities (the 2 islands and 6 mainland localities), representing 4 subspecies. Tissue samples were obtained from 66 fresh specimens collected from 2000 to 2002 and 142 museum specimens collected from 1906 to 1994. Allelic richness and heterozygosity in island spotted skunk populations was approximately 30% lower than that found in mainland localities or subspecies. All localities or subspecies were significantly differentiated (mean FST was 0.17 and 0.13 for localities and subspecies, respectively). Contrary to comparisons based on morphological data, genetic differentiation was especially strong between islands and between island and mainland localities or subspecies. Patterns of differentiation suggest that skunks colonized the Channel Islands shortly before rising sea levels separated Santa Cruz and Santa Rosa islands (11,500 years ago). Our results indicate that the taxonomic status of the island spotted skunk should be reconsidered and that both island populations might constitute evolutionarily significant units worthy of conservation. [ABSTRACT FROM AUTHOR]

A new approach is proposed to derive evapotranspiration (E) and irrigation requirements by implementing the combination equation models of Penman–Monteith and Shuttleworth and Wallace with surface parameters and resistances derived from Sentinel-2 data. Surface parameters are derived from Sentinel-2 and used as an input in these models; namely: the hemispherical shortwave albedo, leaf area index and water status of the soil and canopy ensemble evaluated by using a shortwave infrared-based index. The proposed approach has been validated with data acquired during the GRAPEX (Grape Remote-sensing Atmospheric Profile and Evapotranspiration eXperiment) in California irrigated vineyards. The E products obtained with the combination equation models are evaluated by using eddy covariance flux tower measurements and are additionally compared with surface energy balance models with Landsat-7 and -8 thermal infrared data. The Shuttleworth and Wallace (S-W S-2) model provides an accuracy comparable to thermal-based methods when using local meteorological data, with daily E errors < 1 mm/day, which increased from 1 to 1.5 mm/day using meteorological forcing data from atmospheric models. The advantage of using the S-W S-2 modeling approach for monitoring ET is the high temporal revisit time of the Sentinel-2 satellites and the finer pixel resolution. These results suggest that, by integrating the thermal-based data fusion approach with the S-W S-2 modeling scheme, there is the potential to increase the frequency and reliability of satellite-based daily evapotranspiration products. [ABSTRACT FROM AUTHOR]