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Abstract Switchgrass (Panicum virgatumL.) is a prominent bioenergy crop with robust resilience to environmental stresses. However, our knowledge regarding how precipitation changes affect switchgrass photosynthesis and its responses to light and CO₂remains limited. To address this knowledge gap, we conducted a field precipitation experiment with five different treatments, including −50%, −33%, 0%, +33%, and +50% of ambient precipitation. To determine the responses of leaf photosynthesis to CO₂concentration and light, we measured leaf net photosynthesis of switchgrass under different CO₂concentrations and light levels in 2020 and 2021 for each of the five precipitation treatments. We first evaluated four light and CO₂response models (i.e., rectangular hyperbola model, nonrectangular hyperbola model, exponential model, and the modified rectangular hyperbola model) using the measurements in the ambient precipitation treatment. Based on the fitting criteria, we selected the nonrectangular hyperbola model as the optimal model and applied it to all precipitation treatments, and estimated model parameters. Overall, the model fit field measurements well for the light and CO₂response curves. Precipitation change did not influence the maximum net photosynthetic rate (P_max) but influenced other model parameters including quantum yield (α), convexity (θ), dark respiration (R_d), light compensation point (LCP), and saturated light point (LSP). Specifically, the meanP_maxof five precipitation treatments was 17.6 μmol CO₂m⁻² s⁻¹, and the ambient treatment tended to have a higherP_max. The +33% treatment had the highestα, and the ambient treatment had lowerθandLCP, higherRd, and relatively lowerLSP. Furthermore, precipitation significantly influenced all model parameters of CO₂response. The ambient treatment had the highestP_max, largestα, and lowestθ,R_d, and CO₂compensation pointLCP. Overall, this study improved our understanding of how switchgrass leaf photosynthesis responds to diverse environmental factors, providing valuable insights for accurately modeling switchgrass ecophysiology and productivity. 

Switchgrass (Panicum virgatum L.) is a prominent bioenergy crop with robust resilience to environmental stresses. However, our knowledge regarding how precipitation changes affect switchgrass photosynthesis and its responses to light and CO2 remains limited. To address this knowledge gap, we conducted a field precipitation experiment with five different treatments, including -50%, -33%, 0%, +33%, and +50% of ambient precipitation. To determine the responses of leaf photosynthesis to CO2 concentration and light, we measured leaf net photosynthesis of switchgrass under different CO2 concentrations and light levels in 2020 and 2021 for each of the five precipitation treatments. We first evaluated four light and CO2 response models (i.e., rectangular hyperbola model, nonrectangular hyperbola model, exponential model, and the modified rectangular hyperbola model) using the measurements in the ambient precipitation treatment. Based on the fitting criteria, we selected the nonrectangular hyperbola model as the optimal model and applied it to all precipitation treatments, and estimated model parameters. Overall, the model fit field measurements well for the light and CO2 response curves. Precipitation change did not influence the maximum net photosynthetic rate (Pmax) but influenced other model parameters including quantum yield (α), convexity (θ), dark respiration (Rd), light compensation point (LCP), and saturated light point (LSP). Specifically, the mean Pmax of five precipitation treatments was 17.6 μmol CO2 m-2s-1, and the ambient treatment tended to have a higher Pmax. The +33% treatment had the highest α, and the ambient treatment had lower θ and LCP, higher Rd, and relatively lower LSP. Furthermore, precipitation significantly influenced all model parameters of CO2 response. The ambient treatment had the highest Pmax, largest α, and lowest θ, Rd, and CO2 compensation point LCP. Overall, this study improved our understanding of how switchgrass leaf photosynthesis responds to diverse environmental factors, providing valuable insights for accurately modeling switchgrass ecophysiology and productivity. 

Precipitation changes altered soil heterotrophic respiration, but the underlying microbial mechanisms remain rarely studied. This study conducted three-year switchgrass (Panicum virgatum L.) mesocosm experiment to investigate soil heterotrophic respiratory responses to altered precipitation. Five treatments were considered, including ambient precipitation (P0), two wet treatments (P+33 and P+50: 33% and 50% enhancement relative to P0), and two drought treatments (P-33 and P-50: 33% and 50% reduction relative to P0). The plant’s aboveground biomass (AGB), soil organic carbon (SOC), total nitrogen (TN), microbial biomass carbon (MBC), heterotrophic respiration (Rs), biomass-specific respiration (Rss: respiration per unit of microbial biomass as a reciprocal index of microbial growth efficiency), and extracellular enzymes activities (EEAs) were quantified in soil samples (0–15 cm). Despite significantly different soil moisture contents among treatments, results showed no impact of precipitation treatments on SOC and TN. Increasing precipitation had no effect, but decreasing precipitation significantly reduced plant AGB. Relative to P0, P+33 significantly increased Rs by more than 3-fold and caused no changes in MBC, leading to significantly higher Rss (P < 0.05). P+33 also significantly increased hydrolytic enzyme activities associated with labile carbon acquisition (Cacq) by 115%. The only significant effect of drought treatments was the decreased β-D-cellobiosidase (CBH) and peroxidase (PEO) under P-33. Nonparametric analyses corroborated the strong influences of moisture and CBH on the enhanced precipitation, which stimulated soil respiratory carbon loss, likely driven by both elevated hydrolase activities and reduced microbial growth efficiency. However, the less sensitive drought effects suggested potential microbial tolerance to water deficiency despite depressed plant growth. This study informs the likely decoupled impacts of microbes and plants on soil heterotrophic respiration under changing precipitation in the switchgrass mesocosm experiment. 

Abstract QuestionsGrasslands provide important provisioning services worldwide and their management has consequences for these services. Management intensification is a widespread land‐use change and has accelerated across North America to meet rising demands on productivity, yet its impact on the relationship between plant diversity and productivity is still unclear. Here, we investigated the relationship between plant diversity and grassland productivity across nine ecoclimatic domains of the continental United States. We also tested the effect of management intensification on diversity and productivity in four case studies. MethodsWe acquired remotely sensed gross primary productivity data (GPP, 1986–2018) and plant diversity data measured at different spatial scales (1, 10, 100, 400 m²), as well as climate variables including the Palmer drought index from two ecological networks. We used general linear mixed models to relate GPP to plant diversity across sites. For the case study analysis, we used linear mixed models to relate plant diversity to management intensity, and tested if the management intensity influenced the relationship between GPP (mean and temporal variation) and drought. ResultsAcross all sites, we observed positive relationships among species richness, productivity, and the temporal stability of mean annual biomass production. These relationships were not affected by the scale at which species richness was observed. In three out of the four case studies, we observed that management effects on species richness were only significant at broader scales (i.e., ≥10 m²) with no clear effect found at the commonly used 1‐m²quadrat scale. In one case study, species‐poor, intensively managed pastures presented the highest productivity but were more sensitive to dry conditions than less intensified pastures. However, in other case studies, we did not observe significant effects of management intensity on the magnitude or stability of productivity. ConclusionsGeneralization across studies may be difficult and require the development of intensification indices general enough to be applied across diverse management strategies in grazilands. Understanding how management intensification affects grassland productivity will inform the development of sustainable intensification strategies. 

Ecosystems are experiencing changing global patterns of mean annual precipitation (MAP) and enrichment with multiple nutrients that potentially colimit plant biomass production. In grasslands, mean aboveground plant biomass is closely related to MAP, but how this relationship changes after enrichment with multiple nutrients remains unclear. We hypothesized the global biomass–MAP relationship becomes steeper with an increasing number of added nutrients, with increases in steepness corresponding to the form of interaction among added nutrients and with increased mediation by changes in plant community diversity. We measured aboveground plant biomass production and species diversity in 71 grasslands on six continents representing the global span of grassland MAP, diversity, management, and soils. We fertilized all sites with nitrogen, phosphorus, and potassium with micronutrients in all combinations to identify which nutrients limited biomass at each site. As hypothesized, fertilizing with one, two, or three nutrients progressively steepened the global biomass–MAP relationship. The magnitude of the increase in steepness corresponded to whether sites were not limited by nitrogen or phosphorus, were limited by either one, or were colimited by both in additive, or synergistic forms. Unexpectedly, we found only weak evidence for mediation of biomass–MAP relationships by plant community diversity because relationships of species richness, evenness, and beta diversity to MAP and to biomass were weak or opposing. Site-level properties including baseline biomass production, soils, and management explained little variation in biomass–MAP relationships. These findings reveal multiple nutrient colimitation as a defining feature of the global grassland biomass–MAP relationship.