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Abstract Climate‐driven warming is projected to intensify wildfires, increasing their frequency and severity globally. Wildfires are an increasingly significant source of atmospheric deposition, delivering nutrients, organic matter, and trace metals to coastal and open ocean waters. These inputs have the potential to fertilize or inhibit microbial growth, yet their ecological impacts remain poorly understood. This study examines how ash leachate, derived from the 2017 Thomas Fire in California and lab‐produced ash from Oregon vegetation, affects coastal plankton communities. Shipboard experiments off the California coast examined how pre‐existing plankton biomass concentrations mediate responses to ash leachates. We found that ash leachate contained dissolved organic matter (DOM) that significantly increased bacterioplankton specific growth rates and DOM remineralization rates but had a negligible effect on bacterioplankton growth efficiency, suggesting low DOM bioavailability. Furthermore, ash‐derived DOM had a higher potential to accumulate in high biomass water, where pre‐existing DOM substrates may better support bacterial metabolism. Ash leachate had a neutral to negative effect on phytoplankton division rates and decreased microzooplankton grazing rates, particularly in low biomass water, leading to increased phytoplankton accumulation. Nanoeukaryotes accumulated in low biomass water, whereas picoeukaryotes andSynechococcusaccumulated in high biomass water. Our findings suggest that the influence of ash deposition on DOM cycling, phytoplankton accumulation, and broader marine food web dynamics depends on pre‐existing biomass levels. Understanding these interactions is critical for predicting the biogeochemical consequences of increasing wildfire activity on marine ecosystems. 

ABSTRACT Climate change is altering precipitation regimes that control nitrogen (N) cycling in terrestrial ecosystems. In ecosystems exposed to frequent drought, N can accumulate in soils as they dry, stimulating the emission of both nitric oxide (NO; an air pollutant at high concentrations) and nitrous oxide (N₂O; a powerful greenhouse gas) when the dry soils wet up. Because changes in both N availability and soil moisture can alter the capacity of nitrifying organisms such as ammonia‐oxidizing bacteria (AOB) and archaea (AOA) to process N and emit N gases, predicting whether shifts in precipitation may alter NO and N₂O emissions requires understanding how both AOA and AOB may respond. Thus, we ask: How does altering summer and winter precipitation affect nitrifier‐derived N trace gas emissions in a dryland ecosystem? To answer this question, we manipulated summer and winter precipitation and measured AOA‐ and AOB‐derived N trace gas emissions, AOA and AOB abundance, and soil N concentrations. We found that excluding summer precipitation increased AOB‐derived NO emissions, consistent with the increase in soil N availability, and that increasing summer precipitation amount promoted AOB activity. Excluding precipitation in the winter (the most extreme water limitation we imposed) did not alter nitrifier‐derived NO emissions despite N accumulating in soils. Instead, nitrate that accumulated under drought correlated with high N₂O emission via denitrification upon wetting dry soils. Increases in the timing and intensity of precipitation that are forecasted under climate change may, therefore, influence the emission of N gases according to the magnitude and season during which the changes occur. 

Abstract Wildfires have increased in size, frequency, and intensity in arid regions of the western United States because of human activity, changing land use, and rising temperature. Fire can degrade water quality, reshape aquatic habitat, and increase the risk of high discharge and erosion. Drawing from patterns in montane dry forest, chaparral, and desert ecosystems, we developed a conceptual framework describing how interactions and feedbacks among material accumulation, combustion of fuels, and hydrologic transport influence the effects of fire on streams. Accumulation and flammability of fuels shift in opposition along gradients of aridity, influencing the materials available for transport. Hydrologic transport of combustion products and materials accumulated after fire can propagate the effects of fire to unburned stream–riparian corridors, and episodic precipitation characteristic of arid lands can cause lags, spatial heterogeneity, and feedbacks in response. Resolving uncertainty in fire effects on arid catchments will require monitoring across hydroclimatic gradients and episodic precipitation. 

Abstract Atmospheric nitrogen (N) deposition and climate change are transforming the way N moves through dryland watersheds. For example, N deposition is increasing N export to streams, which may be exacerbated by changes in the magnitude, timing, and intensity of precipitation (i.e., the precipitation regime). While deposition can control the amount of N entering a watershed, the precipitation regime influences rates of internal cycling; when and where soil N, plant roots, and microbes are hydrologically coupled via diffusion; how quickly plants and microbes assimilate N; and rates of denitrification, runoff, and leaching. We used the ecohydrological model RHESSys to investigate (a) how N dynamics differ between N‐limited and N‐saturated conditions in a dryland watershed, and (b) how total precipitation and its intra‐annual intermittency (i.e., the time between storms in a year), interannual intermittency (i.e., the duration of dry months across multiple years), and interannual variability (i.e., variance in the amount of precipitation among years) modify N dynamics and export. Streamflow nitrate (NO₃⁻) export was more sensitive to increasing rainfall intermittency (both intra‐annual and interannual) and variability in N‐limited than in N‐saturated model scenarios, particularly when total precipitation was lower—the opposite was true for denitrification which is more sensitive in N‐saturated than N‐limited scenarios. N export and denitrification increased or decreased more with increasing interannual intermittency than with other changes in precipitation amount. This suggests that under future climate change, prolonged droughts that are followed by more intense storms may pose a major threat to water quality in dryland watersheds. 

Abstract Climate change and nitrogen (N) pollution are altering biogeochemical and ecohydrological processes in dryland watersheds, increasing N export, and threatening water quality. While simulation models are useful for projecting how N export will change in the future, most models ignore biogeochemical “hotspots” that develop in drylands as moist microsites in the soil become hydrologically disconnected from plant roots when soils dry out. These hotspots enable N to accumulate over dry periods and rapidly flush to streams when soils wet up. To better project future N export, we developed a framework for representing hotspots using the ecohydrological model RHESSys. We then conducted a series of virtual experiments to understand how uncertainties in model structure and parameters influence N export to streams. Modeled N export was sensitive to three major factors (a) the abundance of hotspots in a watershed: N export increased linearly and then reached an asymptote with increasing hotspot abundance; this occurred because carbon and N inputs eventually became limiting as hotspots displaced vegetation cover, (b) the soil moisture threshold required for subsurface flow from hotspots to reestablish: peak streamflow N export increased and then decreased with an increasing threshold due to tradeoffs between N accumulation and export that occur with increasingly disconnected hotspots, and (c) the rate at which water diffused out of hotspots as soils dried down: N export was generally higher when the rate was slow because more N could accumulate in hotspots over dry periods, and then be flushed more rapidly to streams at the onset of rain. In a case study, we found that when hotspots were modeled explicitly, peak streamflow nitrate export increased by 29%, enabling us to better capture the timing and magnitude of N losses observed in the field. N export further increased in response to interannual precipitation variability, particularly when multiple dry years were followed by a wet year. This modeling framework can improve projections of N export in watersheds where hotspots play an increasingly important role in water quality. 

Predicting winter flooding is critical to protecting people and securing water resources in California’s Sierra Nevada. Rain-on-snow (ROS) events are a common cause of widespread flooding and are expected to increase in both frequency and magnitude with anthropogenic climate change in this region. ROS flood severity depends on terrestrial water input (TWI), the sum of rain and snowmelt that reaches the land surface. However, an incomplete understanding of the processes that control the flow and refreezing of liquid water in the snowpack limits flood prediction by operational and research models. We examine how antecedent snowpack conditions alter TWI during 71 ROS events between water years 1981 and 2019. Observations across a 500-m elevation gradient from the Independence Creek catchment were input into SNOWPACK, a one-dimensional, physically based snow model, initiated with the Richards equation and calibrated with collocated snow pillow observations. We compare observed “historical” and “scenario” ROS events, where we hold meteorologic conditions constant but vary snowpack conditions. Snowpack variables include cold content, snow density, liquid water content, and snow water equivalent. Results indicate that historical events with TWI > rain are associated with the largest observed streamflows. A multiple linear regression analysis of scenario events suggests that TWI is sensitive to interactions between snow density and cold content, with denser (>0.30 g cm⁻³) and colder (<−0.3 MJ of cold content) snowpacks retaining >50 mm of TWI. These results highlight the importance of hydraulic limitations in dense snowpacks and energy limitations in warm snowpacks for retaining liquid water that would otherwise be available as TWI for flooding. Significance StatementThe purpose of this study is to understand how the snowpack modulates quantities of water that reach the land surface during rain-on-snow (ROS) events. While the amount of near-term storm rainfall is reasonably predicted by meteorologists, major floods associated with ROS are more difficult to predict and are expected to increase in frequency. Our key findings are that liquid water inputs to the land surface vary with snowpack characteristics, and although many hydrologic models incorporate snowpack cold content and density to some degree, the complexity of ROS events justifies the need for additional observations to improve operational forecasting model results. Our findings suggest additional comparisons between existing forecasting models and those that physically represent the snowpack, as well as field-based observations of cold content and density and liquid water content, would be useful follow-up investigations.