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Interannual variability in precipitation has increased globally as climate warming intensifies. The increased variability impacts both terrestrial plant production and carbon (C) sequestration. However, mechanisms driving these changes are largely unknown. Here, we examined mechanisms underlying the response of aboveground net primary production (ANPP) to interannual precipitation variability in global drylands with mean annual precipitation (MAP)

Soil microbial respiration is an important source of uncertainty in projecting future climate and carbon (C) cycle feedbacks. However, its feedbacks to climate warming and underlying microbial mechanisms are still poorly understood. Here we show that the temperature sensitivity of soil microbial respiration (Q10) in a temperate grassland ecosystem persistently decreases by 12.0 ± 3.7% across 7 years of warming. Also, the shifts of microbial communities play critical roles in regulating thermal adaptation of soil respiration. Incorporating microbial functional gene abundance data into a microbially-enabled ecosystem model significantly improves the modeling performance of soil microbial respiration by 5–19%, and reduces model parametric uncertainty by 55–71%. In addition, modeling analyses show that the microbial thermal adaptation can lead to considerably less heterotrophic respiration (11.6 ± 7.5%), and hence less soil C loss. If such microbially mediated dampening effects occur generally across different spatial and temporal scales, the potential positive feedback of soil microbial respiration in response to climate warming may be less than previously predicted., Mechanisms and consequences of the acclimation of soil respiration to warming are unclear. Here, the authors combine soil respiration, metagenomics, and functional gene results from a 7-year grassland warming experiment to a microbial-enzyme decomposition model, showing functional gene information to lower uncertainty and improve fit.

Shifts in dominance and species reordering can occur in response to global change. However, it is not clear how altered precipitation and disturbance regimes interact to affect species composition and dominance.We explored community‐level diversity and compositional similarity responses, both across and within years, to a manipulated precipitation gradient and annual clipping in a mixed‐grass prairie in Oklahoma, USA. We imposed seven precipitation treatments (five water exclusion levels [−20%, −40%, −60%, −80%, and −100%], water addition [+50%], and control [0% change in precipitation]) year‐round from 2016 to 2018 using fixed interception shelters. These treatments were crossed with annual clipping to mimic hay harvest.We found that community‐level responses were influenced by precipitation across time. For instance, plant evenness was enhanced by extreme drought treatments, while plant richness was marginally promoted under increased precipitation.Clipping promoted species gain resulting in greater richness within each experimental year. Across years, clipping effects further reduced the precipitation effects on community‐level responses (richness and evenness) at both extreme drought and added precipitation treatments. Synthesis: Our results highlight the importance of studying interactive drivers of change both within versus across time. For instance, clipping attenuated community‐level responses to a gradient in precipitation, suggesting that management could buffer community‐level responses to drought. However, precipitation effects were mild and likely to accentuate over time to produce further community change., Shifts in dominance and species reordering can occur in response to global change. We manipulated an experimental precipitation gradient combined with clipping in a temperate mixed‐grass prairie to examine how both treatments can shape plant communities. We found that initial shifts in abundance were detected by examining species‐ to community‐level changes over time; drought increased evenness and this was related to the decline of the dominant species and increase in subdominants, while mesic conditions mildly promoted plant richness.

The denitrification process profoundly affects soil nitrogen (N) availability and generates its byproduct, nitrous oxide, as a potent greenhouse gas. There are large uncertainties in predicting global denitrification because its controlling factors remain elusive. In this study, we compiled 4301 observations of denitrification rates across a variety of terrestrial ecosystems from 214 papers published in the literature. The averaged denitrification rate was 3516.3 ± 91.1 µg N kg

Ecosystem carbon (C) transit time is a critical diagnostic parameter to characterize land C sequestration. This parameter has different variants in the literature, including a commonly used turnover time. However, we know little about how different transit time and turnover time are in representing carbon cycling through multiple compartments under a non-steady state. In this study, we estimate both C turnover time as defined by the conventional stock over flux and mean C transit time as defined by the mean age of C mass leaving the system. We incorporate them into the Community Atmosphere Biosphere Land Exchange (CABLE) model to estimate C turnover time and transit time in response to climate warming and rising atmospheric [CO2]. Modelling analysis shows that both C turnover time and transit time increase with climate warming but decrease with rising atmospheric [CO2]. Warming increases C turnover time by 2.4 years and transit time by 11.8 years in 2100 relative to that at steady state in 1901. During the same period, rising atmospheric [CO2] decreases C turnover time by 3.8 years and transit time by 5.5 years. Our analysis shows that 65 % of the increase in global mean C transit time with climate warming results from the depletion of fast-turnover C pool. The remaining 35 % increase results from accompanied changes in compartment C age structures. Similarly, the decrease in mean C transit time with rising atmospheric [CO2] results approximately equally from replenishment of C into fast-turnover C pool and subsequent decrease in compartment C age structure. Greatly different from the transit time, the turnover time, which does not account for changes in either C age structure or composition of respired C, underestimated impacts of warming and rising atmospheric [CO2] on C diagnostic time and potentially led to deviations in estimating land C sequestration in multi-compartmental ecosystems.

Phosphorus limitation on terrestrial plant growth is being incorporated into Earth system models. The global pattern of terrestrial phosphorus limitation, however, remains unstudied. Here, we examined the global-scale latitudinal pattern of terrestrial phosphorus limitation by analysing a total of 1068 observations of aboveground plant production response to phosphorus additions at 351 forest, grassland or tundra sites that are distributed globally. The observed phosphorus-addition effect varied greatly (either positive or negative), depending significantly upon fertilisation regime and production measure, but did not change significantly with latitude. In contrast, phosphorus-addition effect standardised by fertilisation regime and production measure was consistently positive and decreased significantly with latitude. Latitudinal gradient in the standardised phosphorus-addition effect was explained by several mechanisms involving substrate age, climate, vegetation type, edaphic properties and biochemical machinery. This study suggests that latitudinal pattern of terrestrial phosphorus limitation is jointly shaped by macro-scale driving forces and the fundamental structure of life.

Nitrogen immobilization usually leads to nitrogen retention in soil and, thus, influences soil nitrogen supply for plant growth. Understanding soil nitrogen immobilization is important for predicting soil nitrogen cycling under anthropogenic activities and climate changes. However, the global patterns and drivers of soil nitrogen immobilization remain unclear. We synthesized 1350 observations of gross soil nitrogen immobilization rate (NIR) from 97 articles to identify patterns and drivers of NIR. The global mean NIR was 8.77 ± 1.01 mg N kg-1 soil day-1 . It was 5.55 ± 0.41 mg N kg-1 soil day-1 in croplands, 15.74 ± 3.02 mg N kg-1 soil day-1 in wetlands, and 15.26 ± 2.98 mg N kg-1 soil day-1 in forests. The NIR increased with mean annual temperature, precipitation, soil moisture, soil organic carbon, total nitrogen, dissolved organic nitrogen, ammonium, nitrate, phosphorus, and microbial biomass carbon. But it decreased with soil pH. The results of structural equation models showed that soil microbial biomass carbon was a pivotal driver of NIR, because temperature, total soil nitrogen, and soil pH mostly indirectly influenced NIR via changing soil microbial biomass. Moreover, microbial biomass carbon accounted for most of the variations in NIR among all direct relationships. Furthermore, the efficiency of transforming the immobilized nitrogen to microbial biomass nitrogen was lower in croplands than in natural ecosystems (i.e., forests, grasslands, and wetlands). These findings suggested that soil nitrogen retention may decrease under the land use change from forests or wetlands to croplands, but NIR was expected to increase due to increased microbial biomass under global warming. The identified patterns and drivers of soil nitrogen immobilization in this study are crucial to project the changes in soil nitrogen retention.

Soil respiration, the major pathway for ecosystem carbon (C) loss, has the potential to enter a positive feedback loop with the atmospheric CO

Soil microbial respiration is an important source of uncertainty in projecting future climate and carbon (C) cycle feedbacks. Despite intensive studies for two decades, the magnitude, direction, and duration of such feedbacks are uncertain, and their underlying microbial mechanisms are still poorly understood. Here we examined the responses of soil respiration and microbial community structure to long-term experimental warming in a temperate grassland ecosystem. Our results indicated that the temperature sensitivity of soil microbial respiration (i.e.,Q10) persistently decreased by 12.0±3.7% across 7 years of warming. Integrated metagenomic and functional analyses showed that microbial community adaptation played critical roles in regulating respiratory acclimation. Incorporating microbial functional gene abundance data into a microbially-enabled ecosystem model significantly improved the modeling performance of soil microbial respiration by 5–19%, compared to the traditional non-microbial model. Model parametric uncertainty was also reduced by 55–71% when gene abundances were used. In addition, our modeling analyses suggested that decreased temperature sensitivity could lead to considerably less heterotrophic respiration (11.6±7.5%), and hence less soil C loss. If such microbially mediated dampening effects occur generally across different spatial and temporal scales, the potential positive feedback of soil microbial respiration in response to climate warming may be less than previously predicted.

Phosphorus (P) limitation of aboveground plant production is usually assumed to occur in tropical regions but rarely elsewhere. Here we report that such P limitation is more widespread and much stronger than previously estimated. In our global meta-analysis, almost half (46.2%) of 652 P-addition field experiments reveal a significant P limitation on aboveground plant production. Globally, P additions increase aboveground plant production by 34.9% in natural terrestrial ecosystems, which is 7.0–15.9% higher than previously suggested. In croplands, by contrast, P additions increase aboveground plant production by only 13.9%, probably because of historical fertilizations. The magnitude of P limitation also differs among climate zones and regions, and is driven by climate, ecosystem properties, and fertilization regimes. In addition to confirming that P limitation is widespread in tropical regions, our study demonstrates that P limitation often occurs in other regions. This suggests that previous studies have underestimated the importance of altered P supply on aboveground plant production in natural terrestrial ecosystems., Plants are thought to be limited by phosphorus (P) especially in tropical regions. Here, Hou et al. report a meta-analysis of P fertilization experiments to show widespread P limitation on plant growth across terrestrial ecosystems modulated by climate, ecosystem properties, and fertilization regimes

Anthropogenic nitrogen (N) deposition is expected to increase substantially and continuously in the future. Soil N availability regulates microbial communities and the decomposition and formation of soil organic matter, which have great impacts on global carbon (C) cycling. We conducted a meta-analysis based on 454 N-addition experiments in order to synthesize the patterns and mechanisms of responses by soil microbial communities to N addition in various biomes (i.e., boreal forest, temperate forest, tropical/subtropical forest, grassland, and desert). Results showed that the effects of N addition on the total microbial biomass varied depending on biome types, methodologies (fumigation–extraction technique vs. total phospholipid fatty acid), and N-addition rates. Nitrogen addition consistently decreased the microbial C:N and fungi to bacteria ratio (F:B), but increased Gram positive bacteria to Gram negative bacteria ratio (GP:GN) among biome types and N-addition rates. Nitrogen addition increased soil N availability and thereby resulted in soil acidification. Regression technique and principal component analyses showed that the shifts in the F:B and GP:GN mainly resulted from enhanced N availability due to N addition rather than soil acidification. When the N addition rate is lower than 100 kg N ha−1 year−1, about ten times higher than of global normal rate, the positive response of microbial growth was found. Overall, these findings revised the previous notion that N addition inhibited the microbial growth. Microbial species shifts might accentuate or mitigate the effects of alterations in microbial biomass at the ecosystem level, highlighting the critical role of microbial community composition in soil ecosystem functions under N deposition scenarios.

Uptake of anthropogenically emitted carbon (C) dioxide by terrestrial ecosystem is critical for determining future climate. However, Earth system models project large uncertainties in future C storage. To help identify sources of uncertainties in model predictions, this study develops a transient traceability framework to trace components of C storage dynamics. Transient C storage (X) can be decomposed into two components, C storage capacity (Xc) and C storage potential (Xp). Xc is the maximum C amount that an ecosystem can potentially store and Xp represents the internal capacity of an ecosystem to equilibrate C input and output for a network of pools. Xc is co-determined by net primary production (NPP) and residence time (τN), with the latter being determined by allocation coefficients, transfer coefficients, environmental scalar, and exit rate. Xp is the product of redistribution matrix (τch) and net ecosystem exchange. We applied this framework to two contrasting ecosystems, Duke Forest and Harvard Forest with an ecosystem model. This framework helps identify the mechanisms underlying the responses of carbon cycling in the two forests to climate change. The temporal trajectories of X are similar between the two ecosystems. Using this framework, we found that different mechanisms leading to a similar trajectory between the two ecosystems. This framework has potential to reveal mechanisms behind transient C storage in response to various global change factors. It can also identify sources of uncertainties in predicted transient C storage across models and can therefore be useful for model intercomparison.

Terrestrial ecosystems have absorbed roughly 30 % of anthropogenic CO2 emissions over the past decades, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling and experimental and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under global change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, which is the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3-D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. In addition, the physical emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. Overall, this new mathematical framework offers new approaches to understanding, evaluating, diagnosing, and improving land C cycle models.

The enhanced vegetation growth by climate warming plays a pivotal role in amplifying the seasonal cycle of atmospheric CO 2 at northern lands (>50° N) since 1960s. However, the correlation between vegetation growth, temperature and seasonal amplitude of atmospheric CO 2 concentration have become elusive with the slowed increasing trend of vegetation growth and weakened temperature control on CO 2 uptake since late 1990s. Here, based on in situ atmospheric CO 2 concentration records from the Barrow observatory site, we found a slowdown in the increasing trend of the atmospheric CO 2 amplitude from 1990s to mid-2000s. This phenomenon was associated with the paused decrease in the minimum CO 2 concentration ([CO 2 ] min ), which was significantly correlated with the slowdown of vegetation greening and growing-season length extension. We then showed that both the vegetation greenness and growing-season length were positively correlated with spring but not autumn temperature over the northern lands. Furthermore, such asymmetric dependences of vegetation growth upon spring and autumn temperature cannot be captured by the state-of-art terrestrial biosphere models. These findings indicate that the responses of vegetation growth to spring and autumn warming are asymmetric, and highlight the need of improving autumn phenology in the models for predicting seasonal cycle of atmospheric CO 2 concentration.

Despite the importance of future carbon (C) pools for policy and land management decisions under various climate change scenarios, predictions of these pools under altered climate vary considerably. Chronic warming will likely impact both ecosystem C fluxes and the abundance and distribution of plant functional types (PFTs) within systems, potentially interacting to create novel patterns of C exchange. Here, we report results from a 3-year warming experiment using open top chambers (OTC) on the Tibetan Plateau meadow grassland. Warming significantly increased C uptake through gross primary productivity (GPP) but not ecosystem respiration (ER), resulting in a 31.0% reduction in net ecosystem exchange (NEE) in warmed plots. The OTC-induced changes in ecosystem C fluxes were not fully explained by the corresponding changes in soil temperature and moisture. Warming treatments significantly increased the biomass of graminoids and legumes by 12.9 and 27.6%. These functional shifts were correlated with enhanced local GPP, but not ER, resulting in more negative NEE in plots with larger increases in graminoid and legume biomass. This may be due to a link between greater legume abundance and higher levels of total inorganic nitrogen, which can potentially drive higher GPP, but not higher ER. Overall, our results indicate that C-climate feedbacks might be closely mediated by climate-induced changes in PFTs. This highlights the need to consider the impacts of changes in PFTs when predicting future responses of C pools under altered climate scenarios.

Responses of grassland carbon (C) cycling to climate change and land use remain a major uncertainty in model prediction of future climate. To explore the impacts of global change on ecosystem C fluxes and the consequent changes in C storage, we have conducted a field experiment with warming (+3 °C), altered precipitation (doubled and halved), and annual clipping at the end of growing seasons in a mixed-grass prairie in Oklahoma, USA, from 2009 to 2013. Results showed that although ecosystem respiration (ER) and gross primary production (GPP) negatively responded to warming, net ecosystem exchange of CO2 (NEE) did not significantly change under warming. Doubled precipitation stimulated and halved precipitation suppressed ER and GPP equivalently, with the net outcome being unchanged in NEE. These results indicate that warming and altered precipitation do not necessarily have profound impacts on ecosystem C storage. In addition, we found that clipping enhanced NEE due to a stronger positive response of GPP compared to ER, indicating that clipping could potentially be an effective land practice that could increase C storage. No significant interactions between warming, altered precipitation, and clipping were observed. Meanwhile, we found that belowground net primary production (BNPP) in general was sensitive to climate change and land use though no significant changes were found in NPP across treatments. Moreover, negative correlations of the ER/GPP ratio with soil temperature and moisture did not differ across treatments, highlighting the roles of abiotic factors in mediating ecosystem C fluxes in this grassland. Importantly, our results suggest that belowground C cycling (e.g., BNPP) could respond to climate change with no alterations in ecosystem C storage in the same period.

Unique soil properties in rhizosphere can affect plant growth and biogeochemical cycles of ecosystems. While rhizosphere has been widely investigated, little is known about differences in the rhizosphere effect (RE) between co-existing overstory trees and understory shrubs and herbs in forest ecosystems. In this study, we investigated REs on soil chemical properties of overstory trees and understory shrubs and herbs in forest plantations of southern China. Bulk soil and rhizospheres were sampled in April, July and December 2017. Soil pH, nitrate and ammonium nitrogen, dissolved organic carbon, available phosphorus, total carbon, total nitrogen, and total phosphorus were tested. The REs were defined as the ratios of the chemical properties of the rhizospheres to those of the bulk soil. Our results showed that pH was lower and nutrient contents were higher in the plant rhizospheres than the bulk soil. REs were generally larger in trees than understory plants. The REs were larger in July than April and December. Our findings indicated that the RE varied among plant life forms, species and sampling times, emphasizing the functional role of the RE of understory vegetation in subtropical forests.

Climate warming is leading to greater precipitation variability, resulting in increased frequency and intensity of both drought and wet extremes. However, how these extreme events interact with climate warming and hay-harvest in grasslands to impact ecosystem functions has not yet been well explored. In this study, we took advantage of a long-term experiment to examine how climate warming and clipping (i.e., mimicking hay harvest) regulated impacts of naturally occurring drought and wet extremes on ecosystem CO2 fluxes of a tallgrass prairie in the Great Plains, USA. Warming resulted in net ecosystem carbon release (i.e., positive net ecosystem CO2 exchange, NEE) in the extreme drought year of 2011, but significantly enhanced net carbon uptake in the extremely wet year of 2015 in comparison with NEE in normal years. Warming-induced carbon release in the drought year was due to significantly enhanced ecosystem respiration (ER) from mid-summer to early-autumn, whereas warming-enhanced NEE in the wet year was due to an increase in aboveground net primary production (ANPP) compared to those in normal years. Drought diminished warming-induced increases in ANPP to about one sixth of that in the wet year in the unclipped plots. Interestingly, clipping offset the drought-mediated ecosystem carbon loss by increasing GPP and weakened the wet-enhanced ANPP. Overall, our results suggest that a future, warmer climate may exacerbate carbon losses in terrestrial ecosystems during drought extremes but stimulate the ecosystem carbon sink under wet extremes.

Succession theory predicts altered sensitivity of ecosystem functions to disturbance (i.e., climate change) due to the temporal shift in plant community composition. However, empirical evidence in global change experiments is lacking to support this prediction. Here, we present findings from an 8-year long-term global change experiment with warming and altered precipitation manipulation (double and halved amount). First, we observed a temporal shift in species composition over 8 years, resulting in a transition from an annual C3 -dominant plant community to a perennial C4 -dominant plant community. This successional transition was independent of any experimental treatments. During the successional transition, the response of aboveground net primary productivity (ANPP) to precipitation addition magnified from neutral to +45.3%, while the response to halved precipitation attenuated substantially from -17.6% to neutral. However, warming did not affect ANPP in either state. The findings further reveal that the time-dependent climate sensitivity may be regulated by successional change in species composition, highlighting the importance of vegetation dynamics in regulating the response of ecosystem productivity to precipitation change.

Quantifying the ecological patterns of loss of ecosystem function in extreme drought is important to understand the carbon exchange between the land and atmosphere. Rain-use efficiency [RUE; gross primary production (GPP)/precipitation] acts as a typical indicator of ecosystem function. In this study, a novel method based on maximum rain-use efficiency (RUEmax) was developed to detect losses of ecosystem function globally. Three global GPP datasets from the MODIS remote sensing data (MOD17), ground upscaling FLUXNET observations (MPI-BGC), and process-based model simulations (BESS), and a global gridded precipitation product (CRU) were used to develop annual global RUE datasets for 2001–2011. Large, well-known extreme drought events were detected, e.g. 2003 drought in Europe, 2002 and 2011 drought in the U.S., and 2010 drought in Russia. Our results show that extreme drought-induced loss of ecosystem function could impact 0.9% ± 0.1% of earth's vegetated land per year and was mainly distributed in semi-arid regions. The reduced carbon uptake caused by functional loss (0.14 ± 0.03 PgC/yr) could explain >70% of the interannual variation in GPP in drought-affected areas (p ≤ 0.001). Our results highlight the impact of ecosystem function loss in semi-arid regions with increasing precipitation variability and dry land expansion expected in the future.

Climatic changes are altering Earth's hydrological cycle, resulting in altered precipitation amounts, increased interannual variability of precipitation, and more frequent extreme precipitation events. These trends will likely continue into the future, having substantial impacts on net primary productivity (NPP) and associated ecosystem services such as food production and carbon sequestration. Frequently, experimental manipulations of precipitation have linked altered precipitation regimes to changes in NPP. Yet, findings have been diverse and substantial uncertainty still surrounds generalities describing patterns of ecosystem sensitivity to altered precipitation. Additionally, we do not know whether previously observed correlations between NPP and precipitation remain accurate when precipitation changes become extreme. We synthesized results from 83 case studies of experimental precipitation manipulations in grasslands worldwide. We used meta-analytical techniques to search for generalities and asymmetries of aboveground NPP (ANPP) and belowground NPP (BNPP) responses to both the direction and magnitude of precipitation change. Sensitivity (i.e., productivity response standardized by the amount of precipitation change) of BNPP was similar under precipitation additions and reductions, but ANPP was more sensitive to precipitation additions than reductions; this was especially evident in drier ecosystems. Additionally, overall relationships between the magnitude of productivity responses and the magnitude of precipitation change were saturating in form. The saturating form of this relationship was likely driven by ANPP responses to very extreme precipitation increases, although there were limited studies imposing extreme precipitation change, and there was considerable variation among experiments. This highlights the importance of incorporating gradients of manipulations, ranging from extreme drought to extreme precipitation increases into future climate change experiments. Additionally, policy and land management decisions related to global change scenarios should consider how ANPP and BNPP responses may differ, and that ecosystem responses to extreme events might not be predicted from relationships found under moderate environmental changes. Fil: Wilcox, Kevin R.. University of Oklahoma; Estados Unidos Fil: Shi, Zheng. University of Oklahoma; Estados Unidos Fil: Gherardi, Laureano. Arizona State University; Estados Unidos Fil: Lemoine, Nathan P.. State University of Colorado - Fort Collins; Estados Unidos Fil: Koerner, Sally E.. University of South Florida; Estados Unidos Fil: Hoover, David L.. United States Department of Agriculture. Agricultural Research Service; Argentina Fil: Bork, Edward. University of Alberta; Canadá Fil: Byrne, Kerry M.. Humboldt State University; Estados Unidos Fil: Cahill Jr., James. University of Alberta; Canadá Fil: Collins, Scott L.. University of New Mexico; Estados Unidos Fil: Evans, Sarah. Michigan State University; Estados Unidos Fil: Gilgen, Anna K.. Swiss Federal Institute of Technology Zurich; Suiza Fil: Holub, Petr. Czech Academy of Sciences; República Checa Fil: Jiang, Lifen. University of Oklahoma; Estados Unidos Fil: Knapp, Alan K.. State University of Colorado - Fort Collins; Estados Unidos Fil: LeCain, Daniel. United States Department of Agriculture. Agricultural Research Service; Argentina Fil: Liang, Junyi. University of Oklahoma; Estados Unidos Fil: García Palacios, Pablo. Universidad Rey Juan Carlos; España Fil: Peñuelas, Josep. Consejo Superior de Investigaciones Científicas. Centre de Recerca Ecológica I Aplicacions Forestals; España. Universitat Autònoma de Barcelona; España Fil: Pockman, William T.. University of New Mexico; Estados Unidos Fil: Smith, Melinda D.. State University of Colorado - Fort Collins; Estados Unidos Fil: Sun, Shanghua. Northwest A & F University; China Fil: White, Shannon R.. Government of Alberta; Canadá Fil: Yahdjian, María Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. ; Argentina Fil: Zhu, Kai. Rice University; Estados Unidos. University of Texas; Estados Unidos Fil: Luo, Yiqi. University of Oklahoma; Estados Unidos

Long‐term, slow ecological processes such as changes in plant community structure and composition strongly regulate ecosystem responses to climate change. Shifts in plant community are expected in chronically altered environments under warming. However, experimental evidence for long‐term shifts and the associated mechanisms is still scarce in temperate grasslands. Here, we explore the long‐term responses of a prairie plant community to 14‐year (2000–2013) manipulations of climate warming and clipping in Oklahoma, USA. Infrared heaters were used to elevate soil temperature by about 2 °C all year round, and annual clipping was applied to mimic hay harvest. Community composition was resistant to experimental warming in the first seven years, but started to show responses starting from the eighth year; clipping consistently affected community composition over the years. Compositional change under long‐term warming was mainly due to one invasive species and three dominant species. The negative correlations in relative abundance between the invasive species and the dominant species suggest interspecific competition. Community structure (i.e. richness, evenness and diversity) had no overall response to experimental warming. However, in 2007, the extreme wet year, warming reduced species richness by 30%. Clipping promoted species richness by 10% on average over the 14 years but decreased community evenness. Warming did not interact with clipping in influencing the plant community variables. Synthesis. Our study provides experimental evidence for long‐term shifts in plant community composition due to warming and revealed novel mechanisms (i.e. species invasion and associated biotic interactions) underlying the long‐term shift. The results also suggest that climate extremes may elicit or advance community responses to climate warming. The findings highlight that long‐term climate change experiments are essential to reveal potential shifts in community composition.

Model intercomparisons and evaluations against observations are essential for better understanding of models’ performance and for identifying the sources of uncertainty in their output. The terrestrial vegetation carbon simulated by 11 Earth system models (ESMs) involved in phase 5 of the Coupled Model Intercomparison Project (CMIP5) was evaluated in this study. The simulated vegetation carbon was compared at three distinct spatial scales (grid, biome, and global) among models and against the observations (an updated database from Olson et al.’s “Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: A Database”). Moreover, the underlying causes of the differences in the models’ predictions were explored. Model–data fit at the grid scale was poor but greatly improved at the biome scale. Large intermodel variability was pronounced in the tropical and boreal regions, where total vegetation carbon stocks were high. While 8 out of 11 ESMs reproduced the global vegetation carbon to within 20% uncertainty of the observational estimate (560 ± 112 Pg C), the simulated global totals varied nearly threefold between the models. The goodness of fit of ESMs in simulating vegetation carbon depended strongly on the spatial scales. Sixty-three percent of the variability in contemporary global vegetation carbon stocks across ESMs could be explained by differences in vegetation carbon residence time across ESMs (P < 0.01). The analysis indicated that ESMs’ performance of vegetation carbon predictions can be substantially improved through better representation of plant longevity (i.e., carbon residence time) and its respective spatial distributions.

Terrestrial ecosystems absorb roughly 30 % of anthropogenic CO2 emissions since preindustrial era, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling, experimental, and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under climate change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can exactly replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. Moreover, the emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. We also propose that the C storage potential be the targeted variable for research, market trading, and government negotiation for C credits.

Past global change studies have identified changes in species diversity as a major mechanism regulating temporal stability of production, measured as the ratio of the mean to the standard deviation of community biomass. However, the dominant plant functional group can also strongly determine the temporal stability. Here, in a grassland ecosystem subject to 15 years of experimental warming and hay harvest, we reveal that warming increases while hay harvest decreases temporal stability. This corresponds with the biomass of the dominant C4 functional group being higher under warming and lower under hay harvest. As a secondary mechanism, biodiversity also explains part of the variation in temporal stability of production. Structural equation modelling further shows that warming and hay harvest regulate temporal stability through influencing both temporal mean and variation of production. Our findings demonstrate the joint roles that dominant plant functional group and biodiversity play in regulating the temporal stability of an ecosystem under global change., Species diversity is thought to play an important role in maintaining production stability. Shi et al. demonstrate that the dominant C4 plant also makes a substantial contribution to temporal stability in a grassland ecosystem subject to 15 years of experimental warming and hay harvest.

The Yangtze River estuary is an important ecoregion. However, Spartina alterniflora, native to North America, was introduced to the estuary in the 1990s through both natural dispersal and humans and now it is a dominant species in the estuarine ecosystems, with its invasions leading to multiple consequences to the estuary. S. alterniflora had great competitive effects on native species, including Scirpus mariqueter and Phragmites australis, and could potentially exclude the natives locally. The presence of S. alterniflora had little influence on the total density of soil nematodes and macrobenthonic invertebrates, but significantly altered the structure of trophic functional groups of nematode and macrobenthonic invertebrate communities. The conversion of mudflats to Spartina meadows had significant effects on birds of Charadriidae and Scolopacidae, which might be attributable to the reduction of food resources and the physical alterations of habitats for shorebirds. S. alterniflora invasions increased the primary productivity of the invaded ecosystems, and altered carbon and nitrogen cycling processes. Our studies focused mainly on the effects of S. alterniflora invasions on the structure of native ecosystems; thus further studies are clearly needed to investigate how ecosystem functioning is affected by the modification of the structure of estuarine ecosystems by S. alterniflora invasions.

Invasive plants strongly affect physical and biotic environments of native ecosystems. Insects and other arthropods as one of the major components of many ecosystems are very sensitive to subtle changes in abiotic and biotic environments. We examined the effects of exotic Spartina alterniflora invasion on community structure and diets of arthropods in a saltmarsh previously dominated by native Phragmites australis in Yangtze River estuary through net sweeping and plant harvesting methods and stable isotope analysis. Our results showed that diversity indices were not significantly different between exotic and native plant communities, but the total abundance of insects estimated through plant harvesting method was found to be lower in Spartina monoculture than that in Phragmites monoculture. Community structure of insects in Spartina monoculture was dissimilar to that in Phragmites monoculture and Phragmites–Spartina mixture. Moreover, stable carbon isotope patterns of arthropods were significantly different between Phragmites and Spartina monocultures. Although some native arthropods (perhaps generalists) shifted their diets, many native taxa did prefer Phragmites to Spartina even in Spartina monoculture. Spartina invasions resulted in reduced abundances of some arthropds, and increased dominance of others feeding preferably on Spartina. This study provides evidence that invasive plants can change the community structure and diets of native arthropods, which will eventually alter the arthropod food web, and affect the integrity and functioning of native ecosystems within a nature reserve that has been set aside for conserving the native biodiversity and maintaining the ecosystem integrity. In this sense, Spartina invasions in the Yangtze River estuary need to be managed appropriately.

Whether plant invasion increases ecosystem carbon (C) stocks is controversial largely due to the lack of knowledge about differences in ecophysiological properties between invasive and native species. We conducted a field experiment in which we measured ecophysiological properties to explore the response of the ecosystem C stocks to the invasion of Spartina alterniflora (Spartina) in wetlands dominated by native Scirpus mariqueter (Scirpus) and Phragmites australis (Phragmites) in the Yangtze Estuary, China. We measured growing season length, leaf area index (LAI), net photosynthetic rate (Pn), root biomass, net primary production (NPP), litter quality and litter decomposition, plant and soil C and nitrogen (N) stocks in ecosystems dominated by the three species. Our results showed that Spartina had a longer growing season, higher LAI, higher Pn, and greater root biomass than Scirpus and Phragmites. Net primary production (NPP) was 2.16 kg C m−2 y−1 in Spartina ecosystems, which was, on average, 1.44 and 0.47 kg C m−2 y−1 greater than that in Scirpus and Phragmites ecosystems, respectively. The litter decomposition rate, particularly the belowground decomposition rate, was lower for Spartina than Scirpus and Phragmites due to the lower litter quality of Spartina. The ecosystem C stock (20.94 kg m−2) for Spartina was greater than that for Scirpus (17.07 kg m−2), Phragmites (19.51 kg m−2) and the mudflats (15.12 kg m−2). Additionally, Spartina ecosystems had a significantly greater N stock (698.8 g m−2) than Scirpus (597.1 g m−2), Phragmites ecosystems (578.2 g m−2) and the mudflats (375.1 g m−2). Our results suggest that Spartina invasion altered ecophysiological processes, resulted in changes in NPP and litter decomposition, and ultimately led to enhanced ecosystem C and N stocks in the invaded ecosystems in comparison to the ecosystems with native species.

Soil microbes play critical roles in regulating terrestrial carbon (C) cycle and its feedback to climate change. However, it is still unclear how the soil microbial community and abundance respond to future climate change scenarios. In this meta-analysis, we synthesized the responses of microbial community and abundance to experimental warming from 64 published field studies. Our results showed that warming significantly increased soil microbial abundance by 7.6% on average. When grouped by vegetation or soil types, tundras and histosols had the strongest microbial responses to warming with increased microbial, fungal and bacterial abundances by 15.0%, 9.5% and 37.0% in tundra and 16.5%, 13.2% and 13.3% in histosols, respectively. We found significant negative relationships of the response ratios of microbial, fungal and bacterial abundances with the mean annual temperature, indicating that warming had stronger effects in colder than warmer regions. Moreover, the response ratios of microbial abundance to warming were positively correlated with those of soil respiration. Our findings therefore indicate that the large quantities of C stored in colder regions are likely to be more vulnerable to climate warming than the soil C stored in other warmer regions.

© 2016 Macmillan Publishers Limited. All rights reserved. The majority of the Earth's terrestrial carbon is stored in the soil. If anthropogenic warming stimulates the loss of this carbon to the atmosphere, it could drive further planetary warming. Despite evidence that warming enhances carbon fluxes to and from the soil, the net global balance between these responses remains uncertain. Here we present a comprehensive analysis of warming-induced changes in soil carbon stocks by assembling data from 49 field experiments located across North America, Europe and Asia. We find that the effects of warming are contingent on the size of the initial soil carbon stock, with considerable losses occurring in high-latitude areas. By extrapolating this empirical relationship to the global scale, we provide estimates of soil carbon sensitivity to warming that may help to constrain Earth system model projections. Our empirical relationship suggests that global soil carbon stocks in the upper soil horizons will fall by 30 ± 30 petagrams of carbon to 203 ± 161 petagrams of carbon under one degree of warming, depending on the rate at which the effects of warming are realized. Under the conservative assumption that the response of soil carbon to warming occurs within a year, a business-as-usual climate scenario would drive the loss of 55 ± 50 petagrams of carbon from the upper soil horizons by 2050. This value is around 12-17 per cent of the expected anthropogenic emissions over this period. Despite the considerable uncertainty in our estimates, the direction of the global soil carbon response is consistent across all scenarios. This provides strong empirical support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon-climate feedback that could accelerate climate change.

Climate warming affects ecosystem functioning by altering the rates of carbon (C) fixation and release. Modeling warming effect on terrestrial C cycling is critical given the feedbacks between climate and C cycling. However, the effect of warming on key model parameters and the resulting long-term C dynamics has not been carefully examined. In this study, measurements from a nine-year warming experimental site in a tallgrass prairie were assimilated into a terrestrial ecosystem C cycle model to assess warming effect on key model parameters and to quantify uncertainties of long-term C projection. Warming decreased allocation of gross primary production (GPP) to shoot, and turnover rate of the live C pools (i.e., shoot and root C), but increased the turnover rates of litter and fast soil C pools. Consequently, warming increased live C pools, but decreased litter and soil C pools, and overall decreased total ecosystem C in a 90-year model projection. Information content gained from assimilated datasets was m...