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The primary mechanism driving plant species loss after nitrogen (N) addition has been often hypothesized to be asymmetric competition for light, resulting from increased aboveground biomass. However, it is largely unknown whether plants’ access to soil water at different depths would affect their responses, fate, and community composition under nitrogen addition. In a semiarid grassland exposed to 8-years of N addition, we measured plant aboveground biomass and diversity under four nitrogen addition rates (0, 4, 10, and 16 g m 2 year 1), and evaluated plant use of water across the soil profile using oxygen isotope. Aboveground biomass increased significantly, but diversity and shallow soil-water content decreased, with increasing rate of nitrogen addition. The water isotopic signature for both plant and soil water at the high N rate indicated that Leymus secalinus (a perennial grass) absorbed 7% more water from the subsurface soil layer (20e100 cm) compared to Elymus dahuricus (a perennial grass) and Artemisia annua (an annual forb). L. secalinus thus had a significantly larger biomass and was more abundant than the other two species at the high N rate but did not differ significantly from the other two species under ambient and the low N rate. Species that could use water from deeper soil layers became dominant when water in the shallow layers was insufficient to meet the demands of increased aboveground plant biomass. Our study highlights the importance of water across soil depths as key driver of plant growth and dominance in grasslands under N addition. 

Background and aims: Nutrient addition increases plant aboveground production but causes species richness decline in many herbaceous communities. Asymmetric competition for light and detrimental effects of nitrogen have been shown to cause species richness decline in mesic ecosystems. However, it remains unclear whether and how other limiting factors may also play a role in the decline of species richness, especially in ecosystems where soil water could be more limiting. Methods: We conducted a meta-analysis of > 1600 experiments on nutrient and water addition across grasslands worldwide. Results: We find that nitrogen addition, alone or combined with other nutrients, significantly increases aboveground production but decreases species richness. However, water addition can avoid species loss when nutrients were added, indicating that water is a crucial limiting resource in driving species richness decline under nutrient addition. Overall, water limitation may be the primary driver of species richness decline under nutrient addition in approximately 70% of global grassland areas where mean annual soil water content is ≤ 30%. Therefore, as nutrient availability increases in global grasslands, soil moisture limitation may be responsible for the decline of species richness in regions. Conclusion: Our study quantifies the soil water threshold below which plant species is mainly driven by water limitation, and highlights a novel and widespread mechanism driving species richness decline in global grasslands under nutrient addition. 

Abstract Litter decomposition is a key ecological process that determines carbon (C) and nutrient cycling in terrestrial ecosystems. The initial concentrations of C and nutrients in litter play a critical role in this process, yet the global patterns of litter initial concentrations of C, nitrogen (N) and phosphorus (P) are poorly understood.We employed machine learning with a global database to quantitatively assess the global patterns and drivers of leaf litter initial C, N and P concentrations, as well as their returning amounts (i.e. amounts returned to soils).The medians of litter C, N and P concentrations were 46.7, 1.1, and 0.1%, respectively, and the medians of litter C, N and P returning amounts were 1.436, 0.038 and 0.004 Mg ha⁻¹ year⁻¹, respectively. Soil and climate emerged as the key predictors of leaf litter C, N and P concentrations. Predicted global maps showed that leaf litter N and P concentrations decreased with latitude, while C concentration exhibited an opposite pattern. Additionally, the returning amounts of leaf litter C, N and P all declined from the equator to the poles in both hemispheres.Synthesis: Our results provide a quantitative assessment of the global concentrations and returning amounts of leaf litter C, N and P, which showed new light on the role of leaf litter in global C and nutrients cycling. 

Abstract Aim Understanding the considerable variability and drivers of global leaf photosynthetic capacity [indicated by the maximum carboxylation rate standardized to 25°C ( V c,max25 )] is an essential step for accurate modelling of terrestrial plant photosynthesis and carbon uptake under climate change. Although current environmental conditions have often been connected with empirical and theoretical models to explain global V c,max25 variability through acclimatization and adaptation, long‐term evolutionary history has largely been neglected, but might also explicitly play a role in shaping the V c,max25 variability. Location Global. Time period Contemporary. Major taxa studied Terrestrial plants. Methods We compiled a geographically comprehensive global dataset of V c,max25 for C 3 plants ( n  = 6917 observations from 2157 species and 425 sites covering all major biomes world‐wide), explored the biogeographical and phylogenetic patterns of V c,max25 , and quantified the relative importance of current environmental factors and evolutionary history in driving global V c,max25 variability. Results We found that V c,max25 differed across different biomes, with higher mean values in relatively drier regions, and across different life‐forms, with higher mean values in non‐woody relative to woody plants and in legumes relative to non‐leguminous plants. The values of V c,max25 displayed a significant phylogenetic signal and diverged in a contrasting manner across phylogenetic groups, with a significant trend along the evolutionary axis towards a higher V c,max25 in more modern clades. A Bayesian phylogenetic linear mixed model revealed that evolutionary history (indicated by phylogeny and species) explained nearly 3‐fold more of the variation in global V c,max25 than present‐day environment (53 vs. 18%). Main conclusions These findings contribute to a comprehensive assessment of the patterns and drivers of global V c,max25 variability, highlighting the importance of evolutionary history in driving global V c,max25 variability, hence terrestrial plant photosynthesis. 

Large-scale and rapid improvement in wastewater treatment is common practice in developing countries, yet this influence on nutrient regimes in receiving waterbodies is rarely examined at broad spatial and temporal scales. Here, we present a study linking decadal nutrient monitoring data in lakes with the corresponding estimates of five major anthropogenic nutrient discharges in their surrounding watersheds over time. Within a continuous monitoring dataset covering the period 2008 to 2017, we find that due to different rates of change in TN and TP concentrations, 24 of 46 lakes, mostly located in China’s populated regions, showed increasing TN/TP mass ratios; only 3 lakes showed a decrease. Quantitative relationships between in-lake nutrient concentrations (and their ratios) and anthropogenic nutrient discharges in the surrounding watersheds indicate that increase of lake TN/TP ratios is associated with the rapid improvement in municipal wastewater treatment. Due to the higher removal efficiency of TP compared with TN, TN/TP mass ratios in total municipal wastewater discharge have continued to increase from a median of 10.7 (95% confidence interval, 7.6 to 15.1) in 2008 to 17.7 (95% confidence interval, 13.2 to 27.2) in 2017. Improving municipal wastewater collection and treatment worldwide is an important target within the 17 sustainable development goals set by the United Nations. Given potential ecological impacts on biodiversity and ecosystem function of altered nutrient ratios in wastewater discharge, our results suggest that long-term strategies for domestic wastewater management should not merely focus on total reductions of nutrient discharges but also consider their stoichiometric balance. 

A wide range of research shows that nutrient availability strongly influences terrestrial carbon (C) cycling and shapes ecosystem responses to environmental changes and hence terrestrial feedbacks to climate. Nonetheless, our understanding of nutrient controls remains far from complete and poorly quantified, at least partly due to a lack of informative, comparable, and accessible datasets at regional-to-global scales. A growing research infrastructure of multi-site networks are providing valuable data on C fluxes and stocks and are monitoring their responses to global environmental change and measuring responses to experimental treatments. These networks thus provide an opportunity for improving our understanding of C-nutrient cycle interactions and our ability to model them. However, coherent information on how nutrient cycling interacts with observed C cycle patterns is still generally lacking. Here, we argue that complementing available C-cycle measurements from monitoring and experimental sites with data characterizing nutrient availability will greatly enhance their power and will improve our capacity to forecast future trajectories of terrestrial C cycling and climate. Therefore, we propose a set of complementary measurements that are relatively easy to conduct routinely at any site or experiment and that, in combination with C cycle observations, can provide a robust characterization of the effects of nutrient availability across sites. In addition, we discuss the power of different observable variables for informing the formulation of models and constraining their predictions. Most widely available measurements of nutrient availability often do not align well with current modelling needs. This highlights the importance to foster the interaction between the empirical and modelling communities for setting future research priorities. 

Summary Allocation of leaf phosphorus (P) among different functional fractions represents a crucial adaptive strategy for optimizing P use. However, it remains challenging to monitor the variability in leaf P fractions and, ultimately, to understand P‐use strategies across diverse plant communities.We explored relationships between five leaf P fractions (orthophosphate P, P_i; lipid P, P_L; nucleic acid P, P_N; metabolite P, P_M; and residual P, P_R) and 11 leaf economic traits of 58 woody species from three biomes in China, including temperate, subtropical and tropical forests. Then, we developed trait‐based models and spectral models for leaf P fractions and compared their predictive abilities.We found that plants exhibiting conservative strategies increased the proportions of P_Nand P_M, but decreased the proportions of P_iand P_L, thus enhancing photosynthetic P‐use efficiency, especially under P limitation. Spectral models outperformed trait‐based models in predicting cross‐site leaf P fractions, regardless of concentrations (R² = 0.50–0.88 vs 0.34–0.74) or proportions (R² = 0.43–0.70 vs 0.06–0.45).These findings enhance our understanding of leaf P‐allocation strategies and highlight reflectance spectroscopy as a promising alternative for characterizing large‐scale leaf P fractions and plant P‐use strategies, which could ultimately improve the physiological representation of the plant P cycle in land surface models. 

Abstract Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.