土壤碳氮特征沿干旱梯度时空格局及对气候变化的响应——基于中国生态系统研究网络(CERN)长期定位监测数据

土壤碳氮含量及其化学计量特征是表征生态系统碳汇能力和土壤质量的重要指标，在支撑生态系统结构功能以及缓解气候变化中起着关键作用。利用中国生态系统研究网络(CERN)长期定位监测数据，分析了土壤碳氮特征沿干旱梯度的时空规律及其对气候变化的响应。结果表明：空间上，典型荒漠草原生态系统随着干旱加剧，土壤有机碳和全氮含量减少，土壤有机碳对干旱响应的敏感性降低，而土壤全氮对干旱响应的敏感性增加，土壤有机碳随土壤全氮含量的增加而增加。时间上，2005—2018年，荒漠草原生态系统土壤有机碳和全氮含量变化速率沿干旱梯度表现出由负转正的增加趋势，其中，干旱区呈减少趋势，半干旱和半湿润地区呈增加趋势，鄂尔多斯站和沙坡头站呈显著增加趋势。从影响因素来看，土壤碳氮特征对降水量增加的敏感性沿干旱梯度呈现出先增强后减弱的“上凸”抛物线趋势，温度变化对土壤碳氮特征的调控没有表现出明显的干旱梯度效应。土壤碳氮比、土壤有机碳含量、土壤全氮含量对降水量和平均温度变化响应的敏感性均依次降低。不同干旱梯度土壤碳氮特征的变化规律为未来气候变化下生态系统结构与功能预测提供科学依据。     

Sensitivity of mean annual primary production to precipitation

In many terrestrial ecosystems, variation in aboveground net primary production (ANPP) is positively correlated with variation in interannual precipitation. Global climate change will alter both the mean and the variance of annual precipitation, but the relative impact of these changes in precipitation on mean ANPP remains uncertain. At any given site, the slope of the precipitation‐ANPP relationship determines the sensitivity of mean ANPP to changes in mean precipitation, whereas the curvature of the precipitation‐ANPP relationship determines the sensitivity of ANPP to changes in precipitation variability. We used 58 existing long‐term data sets to characterize precipitation‐ANPP relationships in terrestrial ecosystems and to quantify the sensitivity of mean ANPP to the mean and variance of annual precipitation. We found that most study sites have a nonlinear, saturating relationship between precipitation and ANPP, but these nonlinearities were not strong. As a result of these weak nonlinearities, ANPP was nearly 40 times more sensitive to precipitation mean than variance. A 1% increase in mean precipitation caused a ?0.2% to 1.8% change in mean ANPP, with a 0.64% increase on average. Sensitivities to precipitation mean peaked at sites with a mean annual precipitation near 500 mm. Changes in species composition and increased intra‐annual precipitation variability could lead to larger ANPP responses to altered precipitation regimes than predicted by our analysis.     

Aridity Induces Nonlinear Effects of Human Disturbance on Precipitation-Use Efficiency of Iberian Woodlands

The effects of ecosystem degradation are pervasive worldwide and increasingly concerning under the present context of global changes in climate and land use. Theoretical studies and empirical evidence increasingly suggest that drylands are particularly prone to develop nonlinear functional changes in response to climate variations and human disturbance. Precipitation-use efficiency (PUE) represents the ratio of vegetation production to precipitation and provides a tool for evaluating human and climate impacts on landscape functionality. Holm oak (Quercus ilex) woodlands are one of the most conspicuous dry forest ecosystems in the western Mediterranean basin and present a variety of degraded states, due to their long history of human use. We studied the response of Iberian holm oak woodlands to human disturbance along an aridity gradient (that is, semi-arid, dry-transition and sub-humid conditions) using PUE estimations from enhanced vegetation index (EVI) observations of the Moderate-Resolution Imaging Spectroradiometer (MODIS). Our results indicated that PUE decreased linearly with disturbance intensity in sub-humid holm oak woodlands, but showed accelerated, nonlinear reductions with increased disturbance intensity in semi-arid and dry-transition holm oak sites. The impact of disturbance on PUE was larger for dry years than for wet years, and these differences increased with aridity from sub-humid to dry-transition and semi-arid holm oak woodlands. Therefore, aridity may also interact with ecosystem degradation in holm oak woodlands by reducing the landscape ability to buffer large changes in vegetation production caused by climate variability.     

Responses of terrestrial ecosystems to temperature and precipitation change: a meta‐analysis of experimental manipulation

Global mean temperature is predicted to increase by 2–7 °C and precipitation to change across the globe by the end of this century. To quantify climate effects on ecosystem processes, a number of climate change experiments have been established around the world in various ecosystems. Despite these efforts, general responses of terrestrial ecosystems to changes in temperature and precipitation, and especially to their combined effects, remain unclear. We used meta‐analysis to synthesize ecosystem‐level responses to warming, altered precipitation, and their combination. We focused on plant growth and ecosystem carbon (C) balance, including biomass, net primary production (NPP), respiration, net ecosystem exchange (NEE), and ecosystem photosynthesis, synthesizing results from 85 studies. We found that experimental warming and increased precipitation generally stimulated plant growth and ecosystem C fluxes, whereas decreased precipitation had the opposite effects. For example, warming significantly stimulated total NPP, increased ecosystem photosynthesis, and ecosystem respiration. Experimentally reduced precipitation suppressed aboveground NPP (ANPP) and NEE, whereas supplemental precipitation enhanced ANPP and NEE. Plant productivity and ecosystem C fluxes generally showed higher sensitivities to increased precipitation than to decreased precipitation. Interactive effects of warming and altered precipitation tended to be smaller than expected from additive, single‐factor effects, though low statistical power limits the strength of these conclusions. New experiments with combined temperature and precipitation manipulations are needed to conclusively determine the importance of temperature–precipitation interactions on the C balance of terrestrial ecosystems under future climate conditions.     

Carbon and nitrogen dynamics in bioenergy ecosystems: 1. Model development,validation and sensitivity analysis

Biofuel made from conventional (e.g., maize (Zea mays L.)) and cellulosic crops (e.g., switchgrass (Panicum virgatum L.) and Miscanthus (Miscanthus × giganteus)) provides alternative energy to fossil fuels and has been considered to mitigate greenhouse gas emissions. To estimate the large‐scale carbon and nitrogen dynamics of these biofuel ecosystems, process‐based models are needed. Here, we developed an agroecosystem model (AgTEM) based on the Terrestrial Ecosystem Model for these ecosystems. The model was incorporated with biogeochemical and ecophysiological processes including crop phenology, biomass allocation, nitrification, and denitrification, as well as agronomic management of irrigation and fertilization. It was used to estimate crop yield, biomass, net carbon exchange, and nitrous oxide emissions at an ecosystem level. The model was first parameterized for maize, switchgrass, and Miscanthus ecosystems and then validated with field observation data. We found that AgTEM well reproduces the annual net primary production and nitrous oxide fluxes of most sites, with over 85% of total variation explained by the model. Local sensitivity analysis indicated that the model sensitivity varies among different ecosystems. Net primary production of maize is sensitive to temperature, precipitation, cloudiness, fertilizer, and irrigation and less sensitive to atmospheric CO₂ concentrations. In contrast, the net primary production of switchgrass and Miscanthus is most sensitive to temperature among all factors. Nitrous oxide fluxes are sensitive to management in maize ecosystems, and sensitive to climate factors in cellulosic ecosystems. The developed model should help advance our understanding of carbon and nitrogen dynamics of these biofuel ecosystems at both site and regional levels.     

Contrasting Effects of Precipitation Manipulations on Production in Two Sites within the Central Grassland Region, USA

In grassland ecosystems, where soil water most frequently controls ecosystem processes, expected changes in precipitation and temperature may have dramatic effects on ecosystem dynamics. Previous observational studies have reported that aboveground net primary production (ANPP) in grasslands is very sensitive to changes in precipitation. Yet, we lack experimentally based evidence to support these observations. Further, most of the studies have focused solely on ANPP, neglecting belowground production (BNPP). This is an important gap in our knowledge, as BNPP represents 50% or more of total net primary production (NPP) in grasslands. Here, we present results from a 3-year water manipulation experiment (2008–2010) at two sites in the central grassland region of North America, USA. We were successful in changing the soil water content in our treatments, but these changes resulted in different, but significant responses in ANPP and BNPP at our two sites. At the shortgrass steppe, we found that neither NPP nor ANPP were sensitive to treatment precipitation, and although we found BNPP was sensitive to changes in treatment precipitation, the direction of the response varied between years. In contrast, ANPP was very sensitive to treatment precipitation on the mixed-grass prairie, whereas BNPP was insensitive. Based on our finding that two grassland ecosystems showed dramatically different above and belowground production responses to soil water manipulations, we cannot assume that predicted changes in climate will cause similar above- and belowground production responses. Second, our results demonstrated that sites within the same region may differ markedly in the sensitivity of ANPP to changes in growing season precipitation.     

Sensitivity of African biomes to changes in the precipitation regime

Aim Africa is identified by the Inter‐governmental Panel on Climate Change (IPCC) as the least studied continent in terms of ecosystem dynamics and climate variability. The aim of this study was (1) to adapt the Lund‐Postdam‐Jena‐GUESS (LPJ‐GUESS) ecological modelling framework to Africa by providing new parameter values for tropical plant functional types (PFT), and (2) to assess the sensitivity of some African biomes to changes in precipitation regime. Location The study area was a representative transect (0–22° N and 7–18° E) through the transition from equatorial evergreen forests to savannas, steppes and desert northwards. The transect showed large latitudinal variation in precipitation (mean rainfall ranged from 50 to 2300 mm year^?1). Methods New PFT parameters used to calibrate LPJ‐GUESS were based on modern pollen PFTs and remote sensed leaf area index (LAI). The model was validated using independent modern pollen assemblages, LAI and through comparison with White's modern potential vegetation map. Several scenarios were developed by combining changes in total rainfall amount with variation in the length of the dry season in order to test the sensitivity of African biomes. Results Simulated vegetation compared well to observed data at local and regional scales, in terms of ecosystem functioning (LAI), and composition (pollen and White's vegetation map). The assessment of the sensitivity of biomes to changes in precipitation showed that none of the ecosystems would shift towards a new type under the range of precipitation increases suggested by the IPCC (increases from 5 to 20%). However, deciduous and semi‐deciduous forests may be very sensitive to small reductions in both the amount and seasonality of precipitation. Main conclusions This version of LPJ‐GUESS parameterized for Africa simulated correctly the vegetation present over a wide precipitation gradient. The biome sensitivity assessment showed that, compared with savannas and grasslands, closed canopy forests may be more sensitive to change in precipitation regime due to the synergetic effects of changed rainfall amounts and seasonality on vegetation functioning.     

Pushing precipitation to the extremes in distributed experiments: recommendations for simulating wet and dry years

Intensification of the global hydrological cycle, ranging from larger individual precipitation events to more extreme multiyear droughts, has the potential to cause widespread alterations in ecosystem structure and function. With evidence that the incidence of extreme precipitation years (defined statistically from historical precipitation records) is increasing, there is a clear need to identify ecosystems that are most vulnerable to these changes and understand why some ecosystems are more sensitive to extremes than others. To date, opportunistic studies of naturally occurring extreme precipitation years, combined with results from a relatively small number of experiments, have provided limited mechanistic understanding of differences in ecosystem sensitivity, suggesting that new approaches are needed. Coordinated distributed experiments (CDEs) arrayed across multiple ecosystem types and focused on water can enhance our understanding of differential ecosystem sensitivity to precipitation extremes, but there are many design challenges to overcome (e.g., cost, comparability, standardization). Here, we evaluate contemporary experimental approaches for manipulating precipitation under field conditions to inform the design of ‘Drought‐Net’, a relatively low‐cost CDE that simulates extreme precipitation years. A common method for imposing both dry and wet years is to alter each ambient precipitation event. We endorse this approach for imposing extreme precipitation years because it simultaneously alters other precipitation characteristics (i.e., event size) consistent with natural precipitation patterns. However, we do not advocate applying identical treatment levels at all sites – a common approach to standardization in CDEs. This is because precipitation variability varies >fivefold globally resulting in a wide range of ecosystem‐specific thresholds for defining extreme precipitation years. For CDEs focused on precipitation extremes, treatments should be based on each site's past climatic characteristics. This approach, though not often used by ecologists, allows ecological responses to be directly compared across disparate ecosystems and climates, facilitating process‐level understanding of ecosystem sensitivity to precipitation extremes.     

Separating the effects of climate and vegetation on evapotranspiration along a successional chronosequence in the southeastern US

We combined Eddy‐covariance measurements with a linear perturbation analysis to isolate the relative contribution of physical and biological drivers on evapotranspiration (ET) in three ecosystems representing two end‐members and an intermediate stage of a successional gradient in the southeastern US (SE). The study ecosystems, an abandoned agricultural field [old field (OF)], an early successional planted pine forest (PP), and a late‐successional hardwood forest (HW), exhibited differential sensitivity to the wide range of climatic and hydrologic conditions encountered over the 4‐year measurement period, which included mild and severe droughts and an ice storm. ET and modeled transpiration differed by as much as 190 and 270 mm yr^?1, respectively, between years for a given ecosystem. Soil water supply, rather than atmospheric demand, was the principal external driver of interannual ET differences. ET at OF was sensitive to climatic variability, and results showed that decreased leaf area index (L) under mild and severe drought conditions reduced growing season (GS) ET (ET_GS) by ca. 80 mm compared with a year with normal precipitation. Under wet conditions, higher intrinsic stomatal conductance (g_s) increased ET_GS by 50 mm. ET at PP was generally larger than the other ecosystems and was highly sensitive to climate; a 50 mm decrease in ET_GS due to the loss of L from an ice storm equaled the increase in ET from high precipitation during a wet year. In contrast, ET at HW was relatively insensitive to climatic variability. Results suggest that recent management trends toward increasing the land‐cover area of PP‐type ecosystems in the SE may increase the sensitivity of ET to climatic variability.     

Asymmetric responses of primary productivity to precipitation extremes: A synthesis of grassland precipitation manipulation experiments

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.     

Grassland gross carbon dioxide uptake based on an improved model tree ensemble approach considering human interventions: global estimation and covariation with climate

Grassland ecosystems act as a crucial role in the global carbon cycle and provide vital ecosystem services for many species. However, these low‐productivity and water‐limited ecosystems are sensitive and vulnerable to climate perturbations and human intervention, the latter of which is often not considered due to lack of spatial information regarding the grassland management. Here by the application of a model tree ensemble (MTE‐GRASS) trained on local eddy covariance data and using as predictors gridded climate and management intensity field (grazing and cutting), we first provide an estimate of global grassland gross primary production (GPP). GPP from our study compares well (modeling efficiency NSE = 0.85 spatial; NSE between 0.69 and 0.94 interannual) with that from flux measurement. Global grassland GPP was on average 11 ± 0.31 Pg C yr^?1 and exhibited significantly increasing trend at both annual and seasonal scales, with an annual increase of 0.023 Pg C (0.2%) from 1982 to 2011. Meanwhile, we found that at both annual and seasonal scale, the trend (except for northern summer) and interannual variability of the GPP are primarily driven by arid/semiarid ecosystems, the latter of which is due to the larger variation in precipitation. Grasslands in arid/semiarid regions have a stronger (33 g C m^?2 yr^?1/100 mm) and faster (0‐ to 1‐month time lag) response to precipitation than those in other regions. Although globally spatial gradients (71%) and interannual changes (51%) in GPP were mainly driven by precipitation, where most regions with arid/semiarid climate zone, temperature and radiation together shared half of GPP variability, which is mainly distributed in the high‐latitude or cold regions. Our findings and the results of other studies suggest the overwhelming importance of arid/semiarid regions as a control on grassland ecosystems carbon cycle. Similarly, under the projected future climate change, grassland ecosystems in these regions will be potentially greatly influenced.     

Divergent phenological response to hydroclimate variability in forested mountain watersheds

Mountain watersheds are primary sources of freshwater, carbon sequestration, and other ecosystem services. There is significant interest in the effects of climate change and variability on these processes over short to long time scales. Much of the impact of hydroclimate variability in forest ecosystems is manifested in vegetation dynamics in space and time. In steep terrain, leaf phenology responds to topoclimate in complex ways, and can produce specific and measurable shifts in landscape forest patterns. The onset of spring is usually delayed at a specific rate with increasing elevation (often called Hopkins' Law; Hopkins, 1918), reflecting the dominant controls of temperature on greenup timing. Contrary with greenup, leaf senescence shows inconsistent trends along elevation gradients. Here, we present mechanisms and an explanation for this variability and its significance for ecosystem patterns and services in response to climate. We use moderate‐resolution imaging spectro‐radiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data to derive landscape‐induced phenological patterns over topoclimate gradients in a humid temperate broadleaf forest in southern Appalachians. These phenological patterns are validated with different sets of field observations. Our data demonstrate that divergent behavior of leaf senescence with elevation is closely related to late growing season hydroclimate variability in temperature and water balance patterns. Specifically, a drier late growing season is associated with earlier leaf senescence at low elevation than at middle elevation. The effect of drought stress on vegetation senescence timing also leads to tighter coupling between growing season length and ecosystem water use estimated from observed precipitation and runoff generation. This study indicates increased late growing season drought may be leading to divergent ecosystem response between high and low elevation forests. Landscape‐induced phenological patterns are easily observed over wide areas and may be used as a unique diagnostic for sources of ecosystem vulnerability and sensitivity to hydroclimate change.     

Ambient precipitation determines the sensitivity of soil respiration to precipitation treatments in a marsh

The effects in field manipulation experiments are strongly influenced by amplified interannual variation in ambient climate as the experimental duration increases. Soil respiration (SR), as an important part of the carbon cycle in terrestrial ecosystems, is sensitive to climate changes such as temperature and precipitation changes. A growing body of evidence has indicated that ambient climate affects the temperature sensitivity of SR, which benchmarks the strength of terrestrial soil carbon–climate feedbacks. However, whether SR sensitivity to precipitation changes is influenced by ambient climate is still not clear. In addition, the mechanism driving the above phenomenon is still poorly understood. Here, a long-term field manipulation experiment with five precipitation treatments (−60%, −40%, +0%, +40%, and +60% of annual precipitation) was conducted in a marsh in the Yellow River Delta, China, which is sensitive to soil drying–wetting cycle caused by precipitation changes. Results showed that SR increased exponentially along the experimental precipitation gradient each year and the sensitivity of SR (standardized by per 100 mm change in precipitation under precipitation treatments) exhibited significant interannual variation from 2016 to 2021. In addition, temperature, net radiation, and ambient precipitation all exhibited dramatic interannual variability; however, only ambient precipitation had a significant negative correlation with SR sensitivity. Moreover, the sensitivity of SR was significantly positively related to the sensitivity of belowground biomass (BGB) across 6 years. Structural equation modeling and regression analysis also showed that precipitation treatments significantly affected SR and its autotrophic and heterotrophic components by altering BGB. Our study demonstrated that ambient precipitation determines the sensitivity of SR to precipitation treatments in marshes. The findings underscore the importance of ambient climate in regulating ecosystem responses in long-term field manipulation experiments.     

Enhanced interannual precipitation variability increases plant functional diversity that in turn ameliorates negative impact on productivity

Although precipitation interannual variability is projected to increase due to climate change, effects of changes in precipitation variance have received considerable less attention than effects of changes in the mean state of climate. Interannual precipitation variability effects on functional diversity and its consequences for ecosystem functioning are assessed here using a 6‐year rainfall manipulation experiment. Five precipitation treatments were switched annually resulting in increased levels of precipitation variability while maintaining average precipitation constant. Functional diversity showed a positive response to increased variability due to increased evenness. Dominant grasses decreased and rare plant functional types increased in abundance because grasses showed a hump‐shaped response to precipitation with a maximum around modal precipitation, whereas rare species peaked at high precipitation values. Increased functional diversity ameliorated negative effects of precipitation variability on primary production. Rare species buffered the effect of precipitation variability on the variability in total productivity because their variance decreases with increasing precipitation variance.     

Changes in autumn vegetation dormancy onset date and the climate controls across temperate ecosystems in China from 1982 to 2010

Vegetation phenology is a sensitive indicator of the dynamic response of terrestrial ecosystems to climate change. In this study, the spatiotemporal pattern of vegetation dormancy onset date (DOD) and its climate controls over temperate China were examined by analysing the satellite‐derived normalized difference vegetation index and concurrent climate data from 1982 to 2010. Results show that preseason (May through October) air temperature is the primary climatic control of the DOD spatial pattern across temperate China, whereas preseason cumulative precipitation is dominantly associated with the DOD spatial pattern in relatively cold regions. Temporally, the average DOD over China's temperate ecosystems has delayed by 0.13 days per year during the past three decades. However, the delay trends are not continuous throughout the 29‐year period. The DOD experienced the largest delay during the 1980s, but the delay trend slowed down or even reversed during the 1990s and 2000s. Our results also show that interannual variations in DOD are most significantly related with preseason mean temperature in most ecosystems, except for the desert ecosystem for which the variations in DOD are mainly regulated by preseason cumulative precipitation. Moreover, temperature also determines the spatial pattern of temperature sensitivity of DOD, which became significantly lower as temperature increased. On the other hand, the temperature sensitivity of DOD increases with increasing precipitation, especially in relatively dry areas (e.g. temperate grassland). This finding stresses the importance of hydrological control on the response of autumn phenology to changes in temperature, which must be accounted in current temperature‐driven phenological models.     

Effects of climate on soil phosphorus cycle and availability in natural terrestrial ecosystems

Climate is predicted to change over the 21st century. However, little is known about how climate change can affect soil phosphorus (P) cycle and availability in global terrestrial ecosystems, where P is a key limiting nutrient. With a global database of Hedley P fractions and key‐associated physiochemical properties of 760 (seminatural) natural soils compiled from 96 published studies, this study evaluated how climate pattern affected soil P cycle and availability in global terrestrial ecosystems. Overall, soil available P, indexed by Hedley labile inorganic P fraction, significantly decreased with increasing mean annual temperature (MAT) and precipitation (MAP). Hypothesis‐oriented path model analysis suggests that MAT negatively affected soil available P mainly by decreasing soil organic P and primary mineral P and increasing soil sand content. MAP negatively affected soil available P both directly and indirectly through decreasing soil primary mineral P; however, these negative effects were offset by the positive effects of MAP on soil organic P and fine soil particles, resulting in a relatively minor total MAP effect on soil available P. As aridity degree was mainly determined by MAP, aridity also had a relatively minor total effect on soil available P. These global patterns generally hold true irrespective of soil depth (≤10 cm or >10 cm) or site aridity index (≤1.0 or >1.0), and were also true for the low‐sand (≤50%) soils. In contrast, available P of the high‐sand (>50%) soils was positively affected by MAT and aridity and negatively affected by MAP. Our results suggest that temperature and precipitation have contrasting effects on soil P availability and can interact with soil particle size to control soil P availability.     

The Influence of Climate, Soils, Weather, and Land Use on Primary Production and Biomass Seasonality in the US Great Plains

Identifying the conditions and mechanisms that control ecosystem processes, such as net primary production, is a central goal of ecosystem ecology. Ideas have ranged from single limiting-resource theories to colimitation by nutrients and climate, to simulation models with edaphic, climatic, and competitive controls. Although some investigators have begun to consider the influence of land-use practices, especially cropping, few studies have quantified the impact of cropping at large scales relative to other known controls over ecosystem processes. We used a 9-year record of productivity, biomass seasonality, climate, weather, soil conditions, and cropping in the US Great Plains to quantify the controls over spatial and temporal patterns of net primary production and to estimate sensitivity to specific driving variables. We considered climate, soil conditions, and long-term average cropping as controls over spatial patterns, while weather and interannual cropping variations were used as controls over temporal variability. We found that variation in primary production is primarily spatial, whereas variation in seasonality is more evenly split between spatial and temporal components. Our statistical (multiple linear regression) models explained more of the variation in the amount of primary production than in its seasonality, and more of the spatial than the temporal patterns. Our results indicate that although climate is the most important variable for explaining spatial patterns, cropping explains a substantial amount of the residual variability. Soil texture and depth contributed very little to our models of spatial variability. Weather and cropping deviation both made modest contributions to the models of temporal variability. These results suggest that the controls over seasonality and temporal variation are not well understood. Our sensitivity analysis indicates that production is more sensitive to climate than to weather and that it is very sensitive to cropping intensity. In addition to identifying potential gaps in out knowledge, these results provide insight into the probable long- and short-term ecosystem response to changes in climate, weather, and cropping.     

Carbon cycle responses of semi‐arid ecosystems to positive asymmetry in rainfall

Recent evidence shows that warm semi‐arid ecosystems are playing a disproportionate role in the interannual variability and greening trend of the global carbon cycle given their mean lower productivity when compared with other biomes (Ahlström et al. 2015 Science, 348, 895). Using multiple observations (land‐atmosphere fluxes, biomass, streamflow and remotely sensed vegetation cover) and two state‐of‐the‐art biospheric models, we show that climate variability and extremes lead to positive or negative responses in the biosphere, depending on vegetation type. We find Australia to be a global hot spot for variability, with semi‐arid ecosystems in that country exhibiting increased carbon uptake due to both asymmetry in the interannual distribution of rainfall (extrinsic forcing), and asymmetry in the response of gross primary production (GPP) to rainfall change (intrinsic response). The latter is attributable to the pulse‐response behaviour of the drought‐adapted biota of these systems, a response that is estimated to be as much as half of that from the CO₂ fertilization effect during 1990–2013. Mesic ecosystems, lacking drought‐adapted species, did not show an intrinsic asymmetric response. Our findings suggest that a future more variable climate will induce large but contrasting ecosystem responses, differing among biomes globally, independent of changes in mean precipitation alone. The most significant changes are occurring in the extensive arid and semi‐arid regions, and we suggest that the reported increased carbon uptake in response to asymmetric responses might be contributing to the observed greening trends there.     

Vulnerability of the global terrestrial ecosystems to climate change

Climate change has far‐reaching impacts on ecosystems. Recent attempts to quantify such impacts focus on measuring exposure to climate change but largely ignore ecosystem resistance and resilience, which may also affect the vulnerability outcomes. In this study, the relative vulnerability of global terrestrial ecosystems to short‐term climate variability was assessed by simultaneously integrating exposure, sensitivity, and resilience at a high spatial resolution (0.05°). The results show that vulnerable areas are currently distributed primarily in plains. Responses to climate change vary among ecosystems and deserts and xeric shrublands are the most vulnerable biomes. Global vulnerability patterns are determined largely by exposure, while ecosystem sensitivity and resilience may exacerbate or alleviate external climate pressures at local scales; there is a highly significant negative correlation between exposure and sensitivity. Globally, 61.31% of the terrestrial vegetated area is capable of mitigating climate change impacts and those areas are concentrated in polar regions, boreal forests, tropical rainforests, and intact forests. Under current sensitivity and resilience conditions, vulnerable areas are projected to develop in high Northern Hemisphere latitudes in the future. The results suggest that integrating all three aspects of vulnerability (exposure, sensitivity, and resilience) may offer more comprehensive and spatially explicit adaptation strategies to reduce the impacts of climate change on terrestrial ecosystems.     

Impacts of altered precipitation regimes on soil communities and biogeochemistry in arid and semi‐arid ecosystems

Altered precipitation patterns resulting from climate change will have particularly significant consequences in water‐limited ecosystems, such as arid to semi‐arid ecosystems, where discontinuous inputs of water control biological processes. Given that these ecosystems cover more than a third of Earth's terrestrial surface, it is important to understand how they respond to such alterations. Altered water availability may impact both aboveground and belowground communities and the interactions between these, with potential impacts on ecosystem functioning; however, most studies to date have focused exclusively on vegetation responses to altered precipitation regimes. To synthesize our understanding of potential climate change impacts on dryland ecosystems, we present here a review of current literature that reports the effects of precipitation events and altered precipitation regimes on belowground biota and biogeochemical cycling. Increased precipitation generally increases microbial biomass and fungal:bacterial ratio. Few studies report responses to reduced precipitation but the effects likely counter those of increased precipitation. Altered precipitation regimes have also been found to alter microbial community composition but broader generalizations are difficult to make. Changes in event size and frequency influences invertebrate activity and density with cascading impacts on the soil food web, which will likely impact carbon and nutrient pools. The long‐term implications for biogeochemical cycling are inconclusive but several studies suggest that increased aridity may cause decoupling of carbon and nutrient cycling. We propose a new conceptual framework that incorporates hierarchical biotic responses to individual precipitation events more explicitly, including moderation of microbial activity and biomass by invertebrate grazing, and use this framework to make some predictions on impacts of altered precipitation regimes in terms of event size and frequency as well as mean annual precipitation. While our understanding of dryland ecosystems is improving, there is still a great need for longer term in situ manipulations of precipitation regime to test our model.