Search for: All records

Abstract Climate change is increasing the frequency and severity of droughts globally, and grasslands are particularly vulnerable to such hydrological extremes. Drought effects at the ecosystem scale have been assessed both experimentally and through the study of naturally occurring drought, with emerging evidence that the magnitude of drought effects may vary depending on the approach used. We took advantage of a decadal study of four grasslands to directly contrast responses of aboveground net primary productivity (ANPP) to simulated vs. natural drought. The grasslands spanned a ~ threefold mean annual precipitation gradient (335–857 mm) and were all subjected to a natural 1-year drought (~ 40% reduction in precipitation from the long-term mean) and a 4 year experimental drought (~ 50% precipitation reduction). We expected that the 4 year drought would reduce ANPP more, and that post-drought recovery would be delayed, compared to the 1-year drought. We found instead that the short-term natural drought reduced ANPP more strongly than the simulated drought in all grasslands (~ 10 to ~ 50%) likely due to the co-occurrence of higher temperatures and vapor pressure deficits with reduced precipitation. Post-drought recovery was site specific and each site differed in their recovery from the natural and experimental droughts. These results align with past analyses that experiments that only manipulate soil moisture likely underestimate the magnitude of natural drought events. However, experiments can provide valuable insight into the relative sensitivity of ecosystems to reduced precipitation and soil moisture, a key aspect of drought. 

ABSTRACT Extreme droughts are intensifying, yet their impact on temporal variability of grassland functioning and its drivers remains poorly understood. We imposed a 6‐year extreme drought in two semiarid grasslands to explore how drought influences the temporal variability of ANPP and identify potential stabilising mechanisms. Drought decreased ANPP while increasing its temporal variability across grasslands. In the absence of drought, ANPP variability was strongly driven by the dominant plant species (i.e., mass‐ratio effects), as captured by community‐weighted traits and species stability. However, drought decreased the dominance of perennial grasses, providing opportunities for subordinate species to alter the stability of productivity through compensatory dynamics. Specifically, under drought, species asynchrony emerged as a more important correlate of ANPP variability than community‐weighted traits or species stability. Our findings suggest that in grasslands, prolonged, extreme droughts may decrease the relative contribution of mass‐ratio effects versus compensatory dynamics to productivity stability by reducing the influence of dominant species. 

Abstract This manuscript shares the lessons learned from providing scientific computing support to over 600 researchers and discipline experts, helping them develop reproducible and scalable analytical workflows to process large amounts of heterogeneous data.When providing scientific computing support, focus is first placed on how to foster the collaborative aspects of multidisciplinary projects on the technological side by providing virtual spaces to communicate and share documents. Then insights on data management planning and how to implement a centralized data management workflow for data‐driven projects are provided.Developing reproducible workflows requires the development of code. We describe tools and practices that have been successful in fostering collaborative coding and scaling on remote servers, enabling teams to iterate more efficiently. We have found short training sessions combined with on‐demand specialized support to be the most impactful combination in helping scientists develop their technical skills.Here we share our experiences in enabling researchers to do science more collaboratively and more reproducibly beyond any specific project, with long‐lasting effects on the way researchers conduct science. We hope that other groups supporting team‐ and data‐driven science (in environmental science and beyond) will benefit from the lessons we have learned over the years through trial and error. 

Global climate change is expected to cause more frequent extreme droughts in many parts of the world. Despite the crucial role of roots in water acquisition and plant survival, our understanding of ecosystem vulnerability to drought is primarily based on aboveground impacts. As return intervals between droughts decrease, root responses to one drought might alter responses to subsequent droughts, but this remains unresolved. We conducted a seven‐year experiment that imposed extreme drought (growing season precipitation reduced 66%) in a mesic grassland. Plots were droughted during years 1–2 (‘Drought 1'), or years 5–6 (‘Drought 2') or both. We quantified root production during year 6 (final year of Drought 2) and year 7 (first year after Drought 2), when all plots received ambient precipitation. We found that repeated drought decreased root mass production more than twice as much as a single drought (−63% versus −27%, respectively, relative to ambient precipitation). Root mass production of the dominant C₄grassAndropogon gerardiidid not decrease significantly with either one or two droughts.A. gerardiiroot traits differed from subdominant species on average across all treatments, but drought did not alter root traits of eitherA. gerardiior the subdominant species (collectively). In year 6, root production in plots droughted 4 years ago had not recovered (−21% versus control), but root production recovered in all formerly droughted plots in year 7, when precipitation was above average. Our results highlight the complexity of root responses to drought. Drought‐induced reductions in root production can persist for years after drought and repeated drought can reduce production even further, but this does not preclude rapid recovery of root production in a wet year. 

Abstract Water‐limited ecosystems are highly sensitive to not only precipitation amount, but also precipitation pattern, particularly variability in the size and timing of growing season rainfall events. Both rainfall event size and timing are expected to be altered by climate change, but the relative responses of dryland ecosystems to changes in rainfall event size versus timing have not been resolved. Here, we disentangle the effects of these different aspects of precipitation pattern on ecosystem dynamics.We experimentally assessed how these two aspects of rainfall variability impacted a semi‐arid grassland ecosystem by altering an ambient precipitation pattern to eliminate variability in (a) rainfall event size (all events were made the same size), (b) rainfall event timing (all events were uniformly spaced in time) and (c) both. Total precipitation amount was constant for all treatments. We measured responses of soil moisture, ecosystem carbon flux (e.g. net primary production and soil CO₂flux), plant community composition and physiological responses of the dominant C₄grass,Bouteloua gracilis.Removing variability in rainfall event size altered ecosystem dynamics more than a pattern of uniform event timing, but the largest impact occurred when variability in both were removed. Notably, eliminating variability in both event size and timing increased above‐ground net primary productivity by 23%, consistent with reduced water stress in the dominant C₄grass, while also reducing seasonal variability in soil CO₂flux by 35%, reflecting lower seasonal variability in soil moisture.Synthesis. Unique responses to different aspects of precipitation variability highlight the complexity of predicting how dryland ecosystems will be affected by climate change‐induced shifts in rainfall patterns. Our results provide novel support for the key roles of rainfall event size and timing, in addition to total precipitation amount, as determinants of ecosystem function.