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Plant traits can be helpful for understanding grassland ecosystem responses to climate extremes, such as severe drought. However, intercontinental comparisons of how drought affects plant functional traits and ecosystem functioning are rare. The Extreme Drought in Grasslands experiment (EDGE) was established across the major grassland types in East Asia and North America (six sites on each continent) to measure variability in grassland ecosystem sensitivity to extreme, prolonged drought. At all sites, we quantified community‐weighted mean functional composition and functional diversity of two leaf economic traits, specific leaf area and leaf nitrogen content, in response to drought. We found that experimental drought significantly increased community‐weighted means of specific leaf area and leaf nitrogen content at all North American sites and at the wetter East Asian sites, but drought decreased community‐weighted means of these traits at moderate to dry East Asian sites. Drought significantly decreased functional richness but increased functional evenness and dispersion at most East Asian and North American sites. Ecosystem drought sensitivity (percentage reduction in aboveground net primary productivity) positively correlated with community‐weighted means of specific leaf area and leaf nitrogen content and negatively correlated with functional diversity (i.e., richness) on an intercontinental scale, but results differed within regions. These findings highlight both broad generalities but also unique responses to drought of community‐weighted trait means as well as their functional diversity across grassland ecosystems.

 

Controller tuning is a vital step to ensure a controller delivers its designed performance. DiffTune has been proposed as an automatic tuning method that unrolls the dynamical system and controller into a computational graph and uses auto-differentiation to obtain the gradient for the controller’s parameter update. However, DiffTune uses the vanilla gradient descent to iteratively update the parameter, in which the performance largely depends on the choice of the learning rate (as a hyperparameter). In this paper, we propose to use hyperparameter-free methods to update the controller parameters. We find the optimal parameter update by maximizing the loss reduction, where a predicted loss based on the approximated state and control is used for the maximization. Two methods are proposed to optimally update the parameters and are compared with related variants in simulations on a Dubin’s car and a quadrotor. Simulation experiments show that the proposed first-order method outperforms the hyperparameter-based methods and is more robust than the second-order hyperparameter-free methods. 

Plant traits are useful proxies of plant strategies and can influence community and ecosystem responses to climate extremes, such as severe drought. Few studies, however, have investigated both the immediate and lagged effects of drought on community‐weighted mean (CWM) plant traits, with even less research on the relative roles of interspecific vs. intraspecific trait variability in such responses.

We experimentally reduced growing season precipitation by 66% in two cold‐semi‐arid grassland sites in northern China for four consecutive years to explore the drought resistance of CWM traits as well as their recovery 2 years following the drought. In addition, we isolated the effects of both interspecific and intraspecific trait variability on shifts in CWM traits.

At both sites, we observed significant effects of drought on interspecific and intraspecific trait variability which, in some cases, led to significant changes in CWM traits. For example, drought led to reduced CWM plant height and leaf phosphorous content, but increased leaf carbon content at both sites, with responses primarily due to intraspecific trait shifts. Surprisingly, these CWM traits recovered completely 2 years after the extreme drought. Intraspecific trait variability influenced CWM traits via both positive and negative covariation with interspecific trait variability during drought and recovery phases.

These findings highlight the important role of interspecific and intraspecific trait variability in driving the response and recovery of CWM traits following extreme, prolonged drought.

Read the freePlain Language Summaryfor this article on the Journal blog.

 

Grasslands are subject to climate change, such as severe drought, and an important aspect of their functioning is temporal stability in response to extreme climate events. Previous research has explored the impacts of extreme drought and post‐drought periods on grassland stability, yet the mechanistic pathways behind these changes have rarely been studied.

Here, we implemented an experiment with 4 years of drought and 3 years of recovery to assess the effects of drought and post‐drought on the temporal stability of above‐ground net primary productivity (ANPP) and its underlying mechanisms. To do so, we measured community‐weighted mean (CWM) of six plant growth and nine seed traits, functional diversity, population stability and species asynchrony across two cold, semiarid grasslands in northern China. We also performed piecewise structural equation models (SEMs) to assess the relationships between ANPP stability and its underlying mechanisms and how drought and post‐drought periods alter the relative contribution of these mechanisms to ANPP stability.

We found that temporal stability of ANPP was not reduced during drought due to grasses maintaining productivity, which compensated for increased variation of forb productivity. Moreover, ANPP recovered rapidly after drought, and both grasses and forbs contributed to community stability during the post‐drought period. Overall, ANPP stability decreased during the combined drought and post‐drought periods because of rapid changes in ANPP from drought to post‐drought. SEMs revealed that the temporal stability of ANPP during drought and post‐drought periods was modulated by functional diversity and community‐weighted mean traits directly and indirectly by altering species asynchrony and population stability. Specifically, the temporal stability of ANPP was positively correlated with functional divergence of plant communities. CWMs of seed traits (e.g. seed width and thickness), rather than plant growth traits (e.g. specific leaf area and leaf nutrient content), stabilized grassland ANPP. Productivity of plant communities with large and thick seeds was less sensitive to precipitation changes over time.

These results emphasize the importance of considering both the functional trait distribution among species and seed traits of dominant species since their combined effects can stabilize ecosystem functions under global climate change scenarios.

Read the freePlain Language Summaryfor this article on the Journal blog.

 

Recurrent droughts are an inevitable consequence of climate change, yet how grasslands respond to such events is unclear. We conducted a 6‐year rainfall manipulation experiment in a semiarid grassland that consisted of an initial 2‐year drought (2015–2016), followed by a recovery period (2017–2018) and, finally, a second 2‐year drought (2019–2020). In each year, we estimated aboveground net primary productivity (ANPP), species richness, community‐weighted mean (CWM) plant traits, and several indices of functional diversity. The initial drought led to reduced ANPP, which was primarily driven by limited growth of forbs in the first year and grasses in the second year. Total ANPP completely recovered as the rapid recovery of grass productivity compensated for the slow recovery of forb productivity. The subsequent drought led to a greater reduction in total ANPP than the initial drought due to the greater decline of both grass and forb productivity. The structural equation models revealed that soil moisture influenced ANPP responses directly during the initial drought, and indirectly during the subsequent drought by lowering functional diversity, which resulted in reduced total ANPP. Additionally, ANPP was positively influenced by CWM plant height and leaf nitrogen during the recovery period and recurrent drought, respectively. Overall, the greater impact of the second drought on ecosystem function than the initial drought, as well as the underlying differential mechanism, underscores the need for an understanding of how increased drought frequency may alter semiarid grassland functioning.