Precipitation regimes are predicted to become more variable with more extreme rainfall events punctuated by longer intervening dry periods. Water-limited ecosystems are likely to be highly responsive to altered precipitation regimes. The bucket model predicts that increased precipitation variability will reduce soil moisture stress and increase primary productivity and soil respiration in aridland ecosystems. To test this hypothesis, we experimentally altered the size and frequency of precipitation events during the summer monsoon (July through September) in 2007 and 2008 in a northern Chihuahuan Desert grassland in central New Mexico, USA. Treatments included (1) ambient rain, (2) ambient rain plus one 20 mm rain event each month, and (3) ambient rain plus four 5 mm rain events each month. Throughout two monsoon seasons, we measured soil temperature, soil moisture content (y), soil respiration (R s ), along with leaf-level photosynthesis (A net ), predawn leaf water potential (C pd ), and seasonal aboveground net primary productivity (ANPP) of the dominant C 4 grass, Bouteloua eriopoda. Treatment plots receiving a single large rainfall event each month maintained significantly higher seasonal soil y which corresponded with a significant increase in R s and ANPP of B. eriopoda when compared with plots receiving multiple small events. Because the strength of these patterns differed between years, we propose a modification of the bucket model in which both the mean and variance of soil water change as a consequence of interannual variability from 1 year to the next. Our results demonstrate that aridland ecosystems are highly sensitive to increased precipitation variability, and that more extreme precipitation events will likely have a positive impact on some aridland ecosystem processes important for the carbon cycle.

Understanding drivers of aboveground net primary production (ANPP) has long been a goal of ecology. Decades of investigation have shown total annual precipitation to be an important determinant of ANPP within and across ecosystems. Recently a few studies at individual sites have shown precipitation during specific seasons of the year can more effectively predict ANPP. Here we determined whether seasonal or total precipitation better predicted ANPP across a range of terrestrial ecosystems, from deserts to forests, using long‐term data from 36 plant communities. We also determined whether ANPP responses were dependent on ecosystem type or plant functional group. We found that seasonal precipitation generally explained ANPP better than total precipitation. Precipitation in multiple parts of the growing season often correlated with ANPP, but rarely interacted with each other. Surprisingly, the amount of variation explained by seasonal precipitation was not correlated with ecosystem type or plant functional group. Overall, examining seasonal precipitation can significantly improve ANPP predictions across a broad range of ecosystems and plant types, with implications for understanding current and future ANPP variation. Further work examining precipitation timing relative to species phenology may further improve our ability to predict ANPP, especially in response to climate change.

Climate models suggest that extreme rainfall events will become more common with increased atmospheric warming. Consequently, changes in the size and frequency of rainfall will influence biophysical drivers that regulate the strength and timing of soil CO2 efflux – a major source of terrestrial carbon flux. We used a rainfall manipulation experiment during the summer monsoon season (July–September) to vary both the size and frequency of precipitation in an arid grassland 2 years before and 2 years after a lightning‐caused wildfire. Soil CO2 efflux rates were always higher under increased rainfall event size than under increased rainfall event frequency, or ambient precipitation. Although fire reduced soil CO2 efflux rates by nearly 70%, the overall responses to rainfall variability were consistent before and after the fire. The overall sensitivity of soil CO2 efflux to temperature (Q10) converged to 1.4, but this value differed somewhat among treatments especially before the fire. Changes in rainfall patterns resulted in differences in the periodicity of soil CO2 efflux with strong signals at 1, 8, and 30 days. Increased rainfall event size enhanced the synchrony between photosynthetically active radiation and soil CO2 efflux over the growing season before and after fire, suggesting a change in the temporal availability of substrate pools that regulate the temporal dynamics and magnitude of soil CO2 efflux. We conclude that arid grasslands are capable of rapidly increasing and maintaining high soil CO2 efflux rates in response to increased rainfall event size more than increased rainfall event frequency both before and after a fire. Therefore, the amount and pattern of multiple rain pulses over the growing season are crucial for understanding CO2 dynamics in burned and unburned water‐limited ecosystems.

HighlightExpression of cyanobacterial FBP/SBPase in soybean prevents yield depression in a free air CO2 enrichment experiment under simulated future climate conditions with combination of elevated CO2 and elevated temperature.

Extremes in climate may severely impact ecosystem structure and function, with both the magnitude and rate of response differing among ecosystem types and processes. We conducted a modeling analysis of the effects of extreme drought on two key ecosystem processes, production and respiration, and to provide broader context we complemented this with a synthesis of published results across multiple ecosystems. The synthesis indicated that across a broad range of biomes gross primary production (GPP) generally was more sensitive to extreme drought (defined as proportional reduction relative to average rainfall periods) than was ecosystem respiration (ER). Furthermore, this differential sensitivity between production and respiration increased as drought severity increased. The modeling analysis was designed to better understand the mechanisms underlying this pattern and focused on four grassland sites arrayed across the Great Plains, USA. Model results consistently showed that net primary productivity (NPP) was reduced more than heterotrophic respiration (Rh) by extreme drought (i.e., 67% reduction in annual ambient rainfall) at all four study sites. The sensitivity of NPP to drought was directly attributable to rainfall amount, whereas sensitivity of Rh to drought was driven by both soil drying and a drought-induced reduction in soil carbon (C) content, a much slower process. However, differences in reductions in NPP and Rh diminished as extreme drought continued due to a gradual decline in the soil C pool leading to further reductions in Rh. We also varied the way in which drought was imposed in the modeling analysis, either as reductions in rainfall event size (ESR) or by reducing rainfall event number (REN). Modeled NPP and Rh decreased more by ESR than REN at the two relatively mesic sites but less so at the two xeric sites. Our findings suggest that responses of production and respiration differ in magnitude, occur on different timescales and are affected by different mechanisms under extreme, prolonged drought

Abstract. Extremes in climate may severely impact ecosystem structure and function, with both the magnitude and rate of response differing among ecosystem types and processes. We conducted a modeling analysis of the effects of extreme drought on two key ecosystem processes, production and respiration, and, to provide a broader context, we complemented this with a synthesis of published results that cover a wide variety of ecosystems. The synthesis indicated that across a broad range of biomes, gross primary production (GPP) was generally more sensitive to extreme drought (defined as proportional reduction relative to average rainfall periods) than was ecosystem respiration (ER). Furthermore, this differential sensitivity between production and respiration increased as drought severity increased; it occurred only in grassland ecosystems, and not in evergreen needle-leaf and broad-leaf forests or woody savannahs. The modeling analysis was designed to enable a better understanding of the mechanisms underlying this pattern, and focused on four grassland sites arrayed across the Great Plains, USA. Model results consistently showed that net primary productivity (NPP) was reduced more than heterotrophic respiration (Rh) by extreme drought (i.e., 67% reduction in annual ambient rainfall) at all four study sites. The sensitivity of NPP to drought was directly attributable to rainfall amount, whereas the sensitivity of Rh to drought was driven by soil drying, reduced carbon (C) input and a drought-induced reduction in soil C content – a much slower process. However, differences in reductions in NPP and Rh diminished as extreme drought continued, due to a gradual decline in the soil C pool leading to further reductions in Rh. We also varied the way in which drought was imposed in the modeling analysis; it was either imposed by simulating reductions in rainfall event size (ESR) or by reducing rainfall event number (REN). Modeled NPP and Rh decreased more by ESR than REN at the two relatively mesic sites but less so at the two xeric sites. Our findings suggest that responses of production and respiration differ in magnitude, occur on different timescales, and are affected by different mechanisms under extreme, prolonged drought.

Elevated atmospheric CO2 concentration ([CO2]) generally enhances C3 plant productivity, whereas acute heat stress, which occurs during heat waves, generally elicits the opposite response. However, little is known about the interaction of these two variables, especially during key reproductive phases in important temperate food crops, such as soybean (Glycine max). Here, we grew soybean under elevated [CO2] and imposed high‐ (+9°C) and low‐ (+5°C) intensity heat waves during key temperature‐sensitive reproductive stages (R1, flowering; R5, pod‐filling) to determine how elevated [CO2] will interact with heat waves to influence soybean yield. High‐intensity heat waves, which resulted in canopy temperatures that exceeded optimal growth temperatures for soybean, reduced yield compared to ambient conditions even under elevated [CO2]. This was largely due to heat stress on reproductive processes, especially during R5. Low‐intensity heat waves did not affect yields when applied during R1 but increased yields when applied during R5 likely due to relatively lower canopy temperatures and higher soil moisture, which uncoupled the negative effects of heating on cellular‐ and leaf‐level processes from plant‐level carbon assimilation. Modeling soybean yields based on carbon assimilation alone underestimated yield loss with high‐intensity heat waves and overestimated yield loss with low‐intensity heat waves, thus supporting the influence of direct heat stress on reproductive processes in determining yield. These results have implications for rain‐fed cropping systems and point toward a climatic tipping point for soybean yield when future heat waves exceed optimum temperature.

Abstract. Extracellular enzyme activities (EEAs) are indicators of both soil microbial activity and nutrient availability for plants. However, it is unclear how EEAs change over the growing season in desert grasslands. We examined whether EEAs changed in response to the size and frequency of rain events during the summer monsoon in the northern Chihuahuan Desert, and if the response varied between plant and interspace associated soils. Potential EEAs were measured within a rainfall manipulation experiment at the Sevilleta National Wildlife Refuge in central New Mexico, USA. Rainfall treatments included either three 10-mm events or one 30-mm rain event per month throughout the three month summer monsoon (July-September). EEAs were measured immediately before and within hours after experimental rain events under plants and in unvegetated interspaces. Throughout the season hydrolase activities were higher under vegetation than in interspace soils. Potential activities of hydrolytic enzymes were similar for the two rainfall regimes. Activities increased following early season rain, showed little response to midseason rain, and decreased following late-season rain. Although enzyme activities did not differ between rainfall treatments, ratios between enzymes varied, indicating different nutrient limitations imposed by rain event size and frequency. Larger nitrogen and phosphorus limitations occurred in interspace soils that experienced large, frequent rain events. Many factors, including location relative to plants, seasonality, and rainfall size and frequency, influenced enzyme activities and nutrient availability in these Chihuahuan Desert soils throughout the monsoon season.