Large portions of the western United States have witnessed extended dry intervals between rainfall events due to an intensified hydrological cycle triggered by global warming. Semiarid ecosystems in these regions are particularly susceptible to temporal repackaging of rainfall, but how such rainfall repackaging alters plant phenology remains unknown. We examined the effects of rainfall temporal repackaging during the growing season (July–September, from frequent/small events to infrequent/large events, with constant total seasonal rainfall) on plant phenology through a manipulative experiment in a semiarid grassland ecosystem. Using automated high-frequency digital photography, we monitored canopy and plant greenness at both the plot and plant functional type levels, and derived phenological metrics including the start, end and length of the growing season. We found that canopy onset was delayed by 17 to 24 days under infrequent/large events compared to normal historical pattern, with no significant differences among these treatments in canopy descent or growing season length. The phenology metrics of plant functional types showed opposite responses to rainfall repackaging. Perennial grasses had a longer growing season, while annuals had a shorter season under infrequent/large events compared to frequent/small events. Furthermore, growing season length of perennial grasses responded more strongly to deep than shallow soil water conditions. Our analysis demonstrates the potential of high-frequency plant monitoring to enhance our fundamental understanding of community composition and ecological processes that shape semiarid ecosystem responses to rainfall temporal repackaging and its implications for global biogeochemical cycling.

Across large portions of the western United States, drought intervals are increasing, often accompanied by larger-magnitude rainfalls. Semi-arid ecosystems are expected to be especially responsive to such temporal repackaging of rainfall because of their high sensitivity to variation in soil moisture. We conducted a field manipulation experiment to evaluate the impacts of summer rainfall repackaging (small/many events to large/few events with a fixed total seasonal amount) on a semi-arid mixed annual/perennial bunchgrass ecosystem. We monitored the sensitivity of plant greenness and productivity to soil moisture under rainfall pulses by combining automated, high-frequency repeat digital images at both plot- and plant functional type- level, whole plot CO2 uptake measurements, and continuous in-situ soil moisture data. We found that plot greenness was closely correlated with gross primary productivity across all rainfall repackaging treatments (R = 0.82). Plot greenness was weakly correlated to soil moisture at the beginning of the growing season but showed a significant positive correlation during peak and late growing season. Notably, we found a significant lag time of similar to 5 days between changes in soil moisture and canopy greenness under large/few events, while there was no lag under small/many events. This time lag was found to be driven by perennial grass greenness and its sensitivity to the relatively deep soil water infiltration observed with large/few rainfall events. Predicting semi-arid grassland responses to soil moisture dynamics under ongoing rainfall repackaging, and subsequent impacts on the regional to global carbon budget, should consider plant communities' phenological characteristics and functional type composition.

The Arctic and Boreal Region (ABR) is subject to extensive land cover change (LCC) due to elements such as wildfire, permafrost thaw, and shrubification. The natural and anthropogenic ecosystem transitions (i.e. LCC) alter key ecosystem characteristics including land surface temperature (LST), albedo, and evapotranspiration (ET). These biophysical variables are important in controlling surface energy balance, water exchange, and carbon uptake which are important factors influencing the warming trend over the ABR. However, to what extent these variables are sensitive to various LCC in heterogeneous systems such as ABR is still an open question. In this study, we use a novel data-driven approach based on high-resolution land cover data (2003 and 2013) over four million km ^2 to estimate the impact of multiple types of ecosystem transitions on LST, albedo, and ET. We also disentangle the contribution of LCC vs. natural variability of the system in changes in biophysical variables. Our results indicate that from 2003 to 2013 about 46% (∼2 million km ^2 ) of the region experienced LCC, which drove measurable changes to the biophysical environment across ABR over the study period. In almost half of the cases, LCC imposes a change in biophysical variables against the natural variability of the system. For example, in ∼35% of cases, natural variability led to −1.4 ± 0.9 K annual LST reduction, while LCC resulted in a 0.9 ± 0.6 K LST increase, which dampened the decrease in LST due to natural variability. In some cases, the impact of LCC was strong enough to reverse the sign of the overall change. Our results further demonstrate the contrasting sensitivity of biophysical variables to specific LCC. For instance, conversion of sparsely vegetated land to a shrub (i.e. shrubification) significantly decreased annual LST (−2.2 ± 0.1 K); whereas sparsely vegetated land to bare ground increased annual LST (1.6 ± 0.06 K). We additionally highlight the interplay between albedo and ET in driving changes in annual and seasonal LST. Whether our findings are generalizable to the spatial and temporal domain outside of our data used here is unknown, but merits future research due to the importance of the interactions between LCC and biophysical variables.

1. Against a backdrop of rising temperature, large portions of the western United States are experiencing fewer, larger and less frequent precipitation events. How such temporal 'repackaging' of precipitation alters the magnitude and timing of seasonal maximum gross primary productivity (GPP(max)) remains unknown. Addressing this knowledge gap is critical, since changes to GPP(max) magnitude and timing can impact a range of ecosystem services and management decisions. 2. Here we used a field-based precipitation manipulation experiment in a semi-arid mixed annual/perennial bunchgrass ecosystem with mean annual precipitation similar to 384 mm to investigate how temporal repackaging of a fixed total seasonal precipitation amount impacts seasonal GPP(max) and its timing. 3. We found that temporal repackaging of precipitation profoundly influenced the seasonal timing of GPP(max). Many/small precipitation events advanced the seasonal timing of GPP(max) by similar to 13 days in comparison with climatic normal precipitation. Conversely, few/large events led to deeper soil water infiltration, which delayed the timing of GPP(max) by up to 16 days in comparison with climatic normal precipitation, and altered end-of-season community composition by increasing the diversity of shallow-rooted annual plants. While GPP(max) magnitude did not differ across precipitation treatments, it was positively correlated with the abundance and biomass of deeper-rooted perennial bunchgrasses. The sensitivity of plant growth, biomass accumulation and plant life histories to the timing and magnitude of precipitation events and the resulting temporal patterns of soil moisture regulated ecosystem responses to altered precipitation patterns. 4. Our results highlight the sensitivity of semi-arid grassland ecosystem to the temporal repackaging of precipitation. We find that already-observed and model-forecasted shifts toward few/large precipitation events could drive significant delays in the timing of peak productivity for this ecosystem. Adaptive land management frameworks should consider these findings since shifts in peak ecosystem productivity would have major implications for multiple land user communities. Additional research is needed to better understand the role of climate, community composition and soil properties in mediating variability in the seasonal timing of maximum ecosystem productivity.

Wildfire is a major concern worldwide and particularly in Australia. The 2019–2020 wildfires in Australia became historically significant as they were widespread and extremely severe. Linking climate and vegetation settings to wildfires can provide insightful information for wildfire prediction, and help better understand wildfires behavior in the future. The goal of this research was to examine the relationship between the recent wildfires, various hydroclimatological variables, and satellite-retrieved vegetation indices. The analyses performed here show the uniqueness of the 2019–2020 wildfires. The near-surface air temperature from December 2019 to February 2020 was about 1 °C higher than the 20-year mean, which increased the evaporative demand. The lack of precipitation before the wildfires, due to an enhanced high-pressure system over southeast Australia, prevented the soil from having enough moisture to supply the demand, and set the stage for a large amount of dry fuel that highly favored the spread of the fires.