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Abstract In dryland ecosystems, vegetation within different plant functional groups exhibits distinct seasonal phenologies that are affected by the prevailing hydroclimatic forcing. The seasonal variability of precipitation, atmospheric evaporative demand, and streamflow influences root-zone water availability to plants in water-limited environments. Increasing interannual variations in climate forcing of the local water balance and uncertainty regarding climate change projections have raised the potential for phenological shifts and changes to vegetation dynamics. This poses significant risks to plant functional types across large areas, especially in drylands and within riparian ecosystems. Due to the complex interactions between climate, water availability, and seasonal plant water use, the timing and amplitude of phenological responses to specific hydroclimate forcing cannot be determined a priori , thus limiting efforts to dynamically predict vegetation greenness under future climate change. Here, we analyze two decades (1994–2021) of remote sensing data (soil adjusted vegetation index (SAVI)) as well as contemporaneous hydroclimate data (precipitation, potential evapotranspiration, depth to groundwater, and air temperature), to identify and quantify the key hydroclimatic controls on the timing and amplitude of seasonal greenness. We focus on key phenological events across four different plant functional groups occupying distinct locations and rooting depths in dryland SE Arizona: semi-arid grasses and shrubs, xeric riparian terrace and hydric riparian floodplain trees. We find that key phenological events such as spring and summer greenness peaks in grass and shrubs are strongly driven by contributions from antecedent spring and monsoonal precipitation, respectively. Meanwhile seasonal canopy greenness in floodplain and terrace vegetation showed strong response to groundwater depth as well as antecedent available precipitation (aaP = P − PET) throughout reaches of perennial and intermediate streamflow permanence. The timings of spring green-up and autumn senescence were driven by seasonal changes in air temperature for all plant functional groups. Based on these findings, we develop and test a simple, empirical phenology model, that predicts the timing and amplitude of greenness based on hydroclimate forcing. We demonstrate the feasibility of the model by exploring simple, plausible climate change scenarios, which may inform our understanding of phenological shifts in dryland plant communities and may ultimately improve our predictive capability of investigating and predicting climate-phenology interactions in the future. 

Abstract. Despite clear signals of regional impacts of the recent severe drought inCalifornia, e.g., within Californian Central Valley groundwater storage and Sierra Nevada forests, our understanding of how this drought affected soil moisture and vegetation responses in lowland grasslands is limited. In order to better understand the resulting vulnerability of these landscapes to fire and ecosystem degradation, we aimed to generalize drought-induced changes in subsurface soil moisture and to explore its effects within grassland ecosystems of Southern California. We used a high-resolution in situ dataset of climate and soil moisture from two grassland sites (coastal and inland), alongside greenness (Normalized Difference Vegetation Index) data from Landsat imagery, to explore drought dynamics in environments with similar precipitation but contrasting evaporative demand over the period 2008–2019. We show that negative impacts of prolonged precipitation deficits on vegetation at the coastal site were buffered by fog and moderate temperatures. During the drought, the Santa Barbara region experienced an early onset of the dry season in mid-March instead of April, resulting in premature senescence of grasses by mid-April. We developed a parsimonious soil moisture balance model that captures dynamic vegetation–evapotranspiration feedbacks and analyzed the links between climate, soil moisture, and vegetation greenness over several years of simulated drought conditions, exploring the impacts of plausible climate change scenarios that reflect changes to precipitation amounts, their seasonal distribution, and evaporative demand. The redistribution of precipitation over a shortened rainy season highlighted a strong coupling of evapotranspiration to incoming precipitation at the coastal site, while the lower water-holding capacity of soils at the inland site resulted in additional drainage occurring under this scenario. The loss of spring rains due to a shortening of the rainy season also revealed a greater impact on the inland site, suggesting less resilience to low moisture at a time when plant development is about to start. The results also suggest that the coastal site would suffer disproportionally from extended dry periods, effectively driving these areas into more extreme drought than previously seen. These sensitivities suggest potential future increases in the risk of wildfires under climate change, as well as increased grassland ecosystem vulnerability. 

Intermittent and ephemeral streams in dryland environments support diverse assemblages of aquatic and terrestrial life. Understanding when and where water flows provide insights into the availability of water, its response to external controlling factors, and potential sensitivity to climate change and a host of human activities. Knowledge regarding the timing of drying/wetting cycles can also be useful to map critical habitats for species and ecosystems that rely on these temporary water sources. However, identifying the locations and monitoring the timing of streamflow and channel sediment moisture remains a challenging endeavor. In this paper, we analyzed daily conductivity from 37 sensors distributed along 10 streams across an arid mountain front in Arizona (United States) to assess spatiotemporal patterns in flow permanence, defined as the timing and extent of water in streams. Conductivity sensors provide information on surface flow and sediment moisture, supporting a stream classification based on seasonal flow dynamics. Our results provide insight into flow responses to seasonal rainfall, highlighting stream reaches very reactive to rainfall versus those demonstrating more stable streamflow. The strength of stream responses to precipitation are explored in the context of surficial geology. In summary, conductivity data can be used to map potential stream habitat for water‐dependent species in both space and time, while also providing the basis upon which sensitivity to ongoing climate change can be evaluated.