Sensitivity of primary production to precipitation across the United States

Driving mechanism of natural vegetation response to climate change in China from 2001 to 2022

Understanding driving mechanism of natural vegetation response to climate change is crucial for maintaining vegetation stability. In this study, driving mechanism of natural vegetation sensitivity to precipitation (SVP) and temperature (SVT) changes in China were analyzed based on Normalized Difference Vegetation Index (NDVI), Solar-induced Chlorophyll Fluorescence (SIF), Dead Fuel Index (DFI), and climate, hydrological, and CO2 data. Results showed that NDVI and SIF significantly increased but DFI significantly decreased from 2001 to 2022, with proportion of over 67 % of natural vegetation area. The SVP of NDVI (SVPN) and DFI (SVPD) of natural vegetation decreased while SVP of SIF (SVPS) increased during 2001-2022, with average of -6.8 × 10-5/mm, -9.9 × 10-3/mm, and 2.3 × 10-5/mm, respectively. The SVPN and SVPD decreased from arid to humid regions, SVPS was high in semi-arid and semi-humid regions. The SVP was correlated with precipitation, runoff, CO2 and surface soil moisture (SSM), and their correlation was higher in drier regions. The SVT of NDVI (SVTN) of natural vegetation increased while SVT of SIF (SVTS) and DFI (SVTD) decreased during 2001-2022, with average of 13.3 × 10-3/°C, 7 × 10-3/°C, and -1.2/°C, respectively. And there was no significant spatial variation of SVT in different climate regions. The SVT was correlated with aridity index (AI), potential evapotranspiration (PET), temperature and SSM. The explanation of climate, hydrological, and CO2 for SVP and SVT was over 64 %, especially for SVTD at 76.2 %. The influencing factors had great explanations for alpine vegetation, desert, needle-leaf forest, and shrubland, and small explanations for broadleaf forest, mixed forest, and wetland. Overall, natural vegetation of China greened and its dependence on climate change decreased, SVP and SVT were driven by hydrology and heat, respectively. These findings will provide scientific basis for vegetation to cope with future extreme events and maintain vegetation stability.

Extreme Drought Increases the Temporal Variability of Grassland Productivity by Suppressing Dominant Grasses

Extreme droughts are intensifying, yet their impact on temporal variability of grassland functioning and its drivers remains poorly understood. We imposed a 6-year extreme drought in two semiarid grasslands to explore how drought influences the temporal variability of ANPP and identify potential stabilising mechanisms. Drought decreased ANPP while increasing its temporal variability across grasslands. In the absence of drought, ANPP variability was strongly driven by the dominant plant species (i.e., mass-ratio effects), as captured by community-weighted traits and species stability. However, drought decreased the dominance of perennial grasses, providing opportunities for subordinate species to alter the stability of productivity through compensatory dynamics. Specifically, under drought, species asynchrony emerged as a more important correlate of ANPP variability than community-weighted traits or species stability. Our findings suggest that in grasslands, prolonged, extreme droughts may decrease the relative contribution of mass-ratio effects versus compensatory dynamics to productivity stability by reducing the influence of dominant species.

Abrupt changes in algal biomass of thousands of US lakes are related to climate and are more likely in low-disturbance watersheds

Climate change is predicted to intensify lake algal blooms globally and result in regime shifts. However, observed increases in algal biomass do not consistently correlate with air temperature or precipitation, and evidence is lacking for a causal effect of climate or the nonlinear dynamics needed to demonstrate regime shifts. We modeled the causal effects of climate on annual lake chlorophyll (a measure of algal biomass) over 34 y for 24,452 lakes across broad ecoclimatic zones of the United States and evaluated the potential for regime shifts. We found that algal biomass was causally related to climate in 34% of lakes. In these cases, 71% exhibited abrupt but mostly temporary shifts as opposed to persistent changes, 13% had the potential for regime shifts. Climate was causally related to algal biomass in lakes experiencing all levels of human disturbance, but with different likelihood. Climate causality was most likely to be observed in lakes with minimal human disturbance and cooler summer temperatures that have increased over the 34 y studied. Climate causality was variable in lakes with low to moderate human disturbance, and least likely in lakes with high human disturbance, which may mask climate causality. Our results explain some of the previously observed heterogeneous climate responses of lake algal biomass globally and they can be used to predict future climate effects on lakes.

Contrasting drought sensitivity of Eurasian and North American grasslands

Extreme droughts generally decrease productivity in grassland ecosystems1-3 with negative consequences for nature's contribution to people4-7. The extent to which this negative effect varies among grassland types and over time in response to multi-year extreme drought remains unclear. Here, using a coordinated distributed experiment that simulated four years of growing-season drought (around 66% rainfall reduction), we compared drought sensitivity within and among six representative grasslands spanning broad precipitation gradients in each of Eurasia and North America-two of the Northern Hemisphere's largest grass-dominated regions. Aboveground plant production declined substantially with drought in the Eurasian grasslands and the effects accumulated over time, while the declines were less severe and more muted over time in the North American grasslands. Drought effects on species richness shifted from positive to negative in Eurasia, but from negative to positive in North America over time. The differing responses of plant production in these grasslands were accompanied by less common (subordinate) plant species declining in Eurasian grasslands but increasing in North American grasslands. Our findings demonstrate the high production sensitivity of Eurasian compared with North American grasslands to extreme drought (43.6% versus 25.2% reduction), and the key role of subordinate species in determining impacts of extreme drought on grassland productivity.

Drivers of forest productivity in two regions of the United States: Relative impacts of management and environmental variables

Climate, environmental conditions, and management strategies are key factors affecting forest net ecosystem production (NEP). However, little is known about the relationship between management approaches and regional to continental-scale forest productivity. In this study, we utilized forests of the U.S. Southeast (SEUS) and Pacific Northwest (PNW), two ecologically and socio-politically distinct regions, to answer the question: Does management exert a stronger influence on NEP than environmental factors? We estimated Geographically Weighted Regression models of NEP derived from the Ecosystem Demography Model as a function of soil, topography, climate, and forest management practices for the period 2000-2015 using 383 and 407 10 × 10 km2 landscapes in SEUS and PNW, respectively. Results showed that forest management practices were important in predicting NEP only in mountainous northeastern areas of the SEUS; in the PNW, NEP had a more complex relationship with management and was positively related to ecological, preservation, and passive management. Management, topography, and soil were more strongly correlated with NEP in the PNW than in the SEUS, in which 81%, 83%, and 83% of PNW locations showed significant relationships with at least one management, topography, or soil variable, repectively. In contrast, seasonal precipitation and temperature were stronger predictors of NEP in the SEUS than other drivers, with 99% and 84% of the locations influenced by at least one seasonal temperature or precipitation variable, respectively. The findings of this study may provide a valuable framework for forest management - climate change strategies that could be extended across regional scales.

Global increase in the occurrence and impact of multiyear droughts

Persistent multiyear drought (MYD) events pose a growing threat to nature and humans in a changing climate. We identified and inventoried global MYDs by detecting spatiotemporally contiguous climatic anomalies, showing that MYDs have become drier, hotter, and led to increasingly diminished vegetation greenness. The global terrestrial land affected by MYDs has increased at a rate of 49,279 ± 14,771 square kilometers per year from 1980 to 2018. Temperate grasslands have exhibited the greatest declines in vegetation greenness during MYDs, whereas boreal and tropical forests have had comparably minor responses. With MYDs becoming more common, this global quantitative inventory of the occurrence, severity, trend, and impact of MYDs provides an important benchmark for facilitating more effective and collaborative preparedness toward mitigation of and adaptation to such extreme events.

Large global-scale vegetation sensitivity to daily rainfall variability

Rainfall events are globally becoming less frequent but more intense under a changing climate, thereby shifting climatic conditions for terrestrial vegetation independent of annual rainfall totals1-3. However, it remains uncertain how changes in daily rainfall variability are affecting global vegetation photosynthesis and growth3-17. Here we use several satellite-based vegetation indices and field observations indicative of photosynthesis and growth, and find that global annual-scale vegetation indices are sensitive to the daily frequency and intensity of rainfall, independent of the total amount of rainfall per year. Specifically, we find that satellite-based vegetation indices are sensitive to daily rainfall variability across 42 per cent of the vegetated land surfaces. On average, the sensitivity of vegetation to daily rainfall variability is almost as large (95 per cent) as the sensitivity of vegetation to annual rainfall totals. Moreover, we find that wet-day frequency and intensity are projected to change with similar magnitudes and spatial extents as annual rainfall changes. Overall, our findings suggest that daily rainfall variability and its trends are affecting global vegetation photosynthesis, with potential implications for the carbon cycle and food security.

Evidence for the acclimation of ecosystem photosynthesis to soil moisture

Ecosystem gross primary productivity (GPP) is the largest carbon flux between the atmosphere and biosphere and is strongly influenced by soil moisture. However, the response and acclimation of GPP to soil moisture remain poorly understood, leading to large uncertainties in characterizing the impact of soil moisture on GPP in Earth system models. Here we analyze the GPP-soil moisture response curves at 143 sites from the global FLUXNET. We find that GPP at 108 sites exhibits hump-shaped response curves with increasing soil moisture, and an apparent optimum soil moisture (SM opt GPP , at which GPP reaches the maximum) exists widely with large variability among sites and biomes around the globe. Variation inSM opt GPP is mostly explained by local water availability, with drier ecosystems having lowerSM opt GPP than wetter ecosystems, reflecting the water acclimation ofSM opt GPP . This acclimation is further supported by a field experiment that only manipulates water and keeps other factors constant, which shows a downward shift inSM opt GPP after long-term water deficit, and thus a lower soil water requirement to maximize GPP. These results provide compelling evidence for the widespreadSM opt GPP and its acclimation, shedding new light on understanding and predicting carbon-climate feedbacks.

Heterogeneity promotes resilience in restored prairie: Implications for the environmental heterogeneity hypothesis

Enhancing resilience in formerly degraded ecosystems is an important goal of restoration ecology. However, evidence for the recovery of resilience and its underlying mechanisms require long-term experiments and comparison with reference ecosystems. We used data from an experimental prairie restoration that featured long-term soil heterogeneity manipulations and data from two long-term experiments located in a comparable remnant (reference) prairie to (1) quantify the recovery of ecosystem functioning (i.e., productivity) relative to remnant prairie, (2) compare the resilience of restored and remnant prairies to a natural drought, and (3) test whether soil heterogeneity enhances resilience of restored prairie. We compared sensitivity and legacy effects between prairie types (remnant and restored) and among four prairie sites that included two remnant prairie sites and prairie restored under homogeneous and heterogeneous soil conditions. We measured sensitivity and resilience as the proportional change in aboveground net primary productivity (ANPP) during and following drought (sensitivity and legacy effects, respectively) relative to average ANPP based on 4 pre-drought years (2014-2017). In nondrought years, total ANPP was similar between remnant and restored prairie, but remnant prairie had higher grass productivity and lower forb productivity compared with restored prairie. These ANPP patterns generally persisted during drought. The sensitivity of total ANPP to drought was similar between restored and remnant prairie, but grasses in the restored prairie were more sensitive to drought. Post-drought legacy effects were more positive in the restored prairie, and we attributed this to the more positive and less variable legacy response of forb ANPP in the restored prairie, especially in the heterogeneous soil treatment. Our results suggest that productivity recovers in restored prairie and exhibits similar sensitivity to drought as in remnant prairie. Furthermore, creating heterogeneity promotes forb productivity and enhances restored prairie resilience to drought.

Temporal variation characteristics in the association between climate and vegetation in Northwest China

Northwest China has undergone notable alterations in climate and vegetation growth in recent decades. Nevertheless, uncertainties persist concerning the response of different vegetation types to climate change and the underlying mechanisms. This study utilized the Normalized Difference Vegetation Index (NDVI) and three sets of meteorological data to investigate the interannual variations in the association between vegetation and climate (specifically precipitation and temperature) from 1982 to 2015. Several conclusions were drawn. (1) RNDVI-GP (relationship between Growing Season NDVI and precipitation) decreased significantly across all vegetation, while RNDVI-GT (relationship between Growing Season NDVI and temperature) showed an insignificant increase. (2) Trends of RNDVI-GP and RNDVI-GT exhibited great variations across various types of vegetation, with forests displaying notable downward trends in both indices. The grassland exhibited a declining trend in RNDVI-GP but an insignificant increase in RNDVI-GT, while no significant temporal changes in RNDVI-GP or RNDVI-GT were observed in the barren land. (3) The fluctuations in RNDVI-GP and RNDVI-GT closely aligned with variations in drought conditions. Specifically, in regions characterized by VPD (vapor pressure deficit) trends less than 0.02 hpa/yr, which are predominantly grasslands, a rise in SWV (soil water volume) tended to cause a reduction in RNDVI-GP but an increase in RNDVI-GT. However, a more negative trend in SWV was associated with a more negative trend in both RNDVI-GP and RNDVI-GT when the VPD trend exceeded 0.02 hPa/yr, primarily in forests. Our results underscore the variability in the relationship between climate change and vegetation across different vegetation types, as well as the role of drought in modulating these associations.

Disturbance amplifies sensitivity of dryland productivity to precipitation variability

Variability of the terrestrial global carbon sink is largely determined by the response of dryland productivity to annual precipitation. Despite extensive disturbance in drylands, how disturbance alters productivity-precipitation relationships remains poorly understood. Using remote-sensing to pair more than 5600 km of natural gas pipeline corridors with neighboring undisturbed areas in North American drylands, we found that disturbance reduced average annual production 6 to 29% and caused up to a fivefold increase in the sensitivity of net primary productivity (NPP) to interannual variation in precipitation. Disturbance impacts were larger and longer-lasting at locations with higher precipitation (>450 mm mean annual precipitation). Disturbance effects on NPP dynamics were mostly explained by shifts from woody to herbaceous vegetation. Severe disturbance will amplify effects of increasing precipitation variability on NPP in drylands.

Grassland sensitivity to drought is related to functional composition across East Asia and North America

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

Extreme drought impacts have been underestimated in grasslands and shrublands globally

Climate change is increasing the frequency and severity of short-term (~1 y) drought events-the most common duration of drought-globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function-aboveground net primary production (ANPP)-was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought.

Precipitation change affects forest soil carbon inputs and pools: A global meta-analysis

The impacts of precipitation change on forest carbon (C) storage will have global consequences, as forests play a major role in sequestering anthropogenic CO2. Although forest soils are one of the largest terrestrial C pools, there is great uncertainty around the response of forest soil organic carbon (SOC) to precipitation change, which limits our ability to predict future forest C storage. To address this, we conducted a meta-analysis to determine the effect of drought and irrigation experiments on SOC pools, plant C inputs and the soil environment based on 161 studies across 139 forest sites worldwide. Overall, forest SOC content was not affected by precipitation change, but both drought and irrigation altered plant C inputs and soil properties associated with SOC formation and storage. Drought may enhance SOC stability by altering soil aggregate fractions, but the effect of irrigation on SOC fractions remains unexplored. The apparent insensitivity of SOC to precipitation change can be explained by the short duration of most experiments and by biome-specific responses of C inputs and pools to drought or irrigation. Importantly, we demonstrate that SOC content is more likely to decline under irrigation at drier temperate sites, but that dry forests are currently underrepresented across experimental studies. Thus, our meta-analysis advances research into the impacts of precipitation change in forests by revealing important differences among forest biomes, which are likely linked to plant adaptation to extant conditions. We further demonstrate important knowledge gaps around how precipitation change will affect SOC stability, as too few studies currently consider distinct soil C pools. To accurately predict future SOC storage in forests, there is an urgent need for coordinated studies of different soil C pools and fractions across existing sites, as well as new experiments in underrepresented forest types.

Spatiotemporal variation in sensitivity of urban vegetation growth and greenness to vegetation water content: Evidence from Chinese megacities

Understanding the sensitivity of vegetation growth and greenness to vegetation water content change is crucial for elucidating the mechanism of terrestrial ecosystems response to water availability change caused by climate change. Nevertheless, we still have limited knowledge of such aspects in urban in different climatic contexts under the influence of human activities. In this study, we employed Google Earth Engine (GEE), remote sensing satellite imagery, meteorological data, and Vegetation Photosynthesis Model (VPM) to explore the spatiotemporal pattern of vegetation growth and greenness sensitivity to vegetation water content in three megacities (Beijing, Shanghai, and Guangzhou) located in eastern China from 2001 to 2020. We found a significant increase (slope > 0, p < 0.05) in the sensitivity of urban vegetation growth and greenness to vegetation water content (SLSWI). This indicates the increasing dependence of urban vegetation ecosystems on vegetation water resources. Moreover, evident spatial heterogeneity was observed in both SLSWI and the trends of SLSWI, and spatial heterogeneity in SLSWI and the trends of SLSWI was also present among identical vegetation types within the same city. Additionally, both SLSWI of vegetation growth and greenness and the trend of SLSWI showed obvious spatial distribution differences (e.g., standard deviations of trends in SLSWI of open evergreen needle-leaved forest of GPP is 14.36 × 10-2 and standard deviations of trends in SLSWI of open evergreen needle-leaved forest of EVI is 10.16 × 10-2), closely associated with factors such as vegetation type, climatic conditions, and anthropogenic influences.

C:N:P stoichiometry of plants, soils, and microorganisms: Response to altered precipitation

Precipitation changes modify C, N, and P cycles, which regulate the functions and structure of terrestrial ecosystems. Although altered precipitation affects above- and belowground C:N:P stoichiometry, considerable uncertainties remain regarding plant-microbial nutrient allocation strategies under increased (IPPT) and decreased (DPPT) precipitation. We meta-analyzed 827 observations from 235 field studies to investigate the effects of IPPT and DPPT on the C:N:P stoichiometry of plants, soils, and microorganisms. DPPT reduced leaf C:N ratio, but increased the leaf and root N:P ratios reflecting stronger decrease of P compared with N mobility in soil under drought. IPPT increased microbial biomass C (+13%), N (+15%), P (26%), and the C:N ratio, whereas DPPT decreased microbial biomass N (-12%) and the N:P ratio. The C:N and N:P ratios of plant leaves were more sensitive to medium DPPT than to IPPT because drought increased plant N content, particularly in humid areas. The responses of plant and soil C:N:P stoichiometry to altered precipitation did not fit the double asymmetry model with a positive asymmetry under IPPT and a negative asymmetry under extreme DPPT. Soil microorganisms were more sensitive to IPPT than to DPPT, but they were more sensitive to extreme DPPT than extreme IPPT, consistent with the double asymmetry model. Soil microorganisms maintained stoichiometric homeostasis, whereas N:P ratios of plants follow that of the soils under altered precipitation. In conclusion, specific N allocation strategies of plants and microbial communities as well as N and P availability in soil critically mediate C:N:P stoichiometry by altered precipitation that need to be considered by prediction of ecosystem functions and C cycling under future climate change scenarios.

What's going to be on the menu with global environmental changes?

Ongoing anthropogenic change is altering the planet at an unprecedented rate, threatening biodiversity, and ecosystem functioning. Species are responding to abiotic pressures at both individual and population levels, with changes affecting trophic interactions through consumptive pathways. Collectively, these impacts alter the goods and services that natural ecosystems will provide to society, as well as the persistence of all species. Here, we describe the physiological and behavioral responses of species to global changes on individual and population levels that result in detectable changes in diet across terrestrial and marine ecosystems. We illustrate shifts in the dynamics of food webs with implications for animal communities. Additionally, we highlight the myriad of tools available for researchers to investigate the dynamics of consumption patterns and trophic interactions, arguing that diet data are a crucial component of ecological studies on global change. We suggest that a holistic approach integrating the complexities of diet choice and trophic interactions with environmental drivers may be more robust at resolving trends in biodiversity, predicting food web responses, and potentially identifying early warning signs of diversity loss. Ultimately, despite the growing body of long-term ecological datasets, there remains a dearth of diet ecology studies across temporal scales, a shortcoming that must be resolved to elucidate vulnerabilities to changing biophysical conditions.

Changing climate and reorganized species interactions modify community responses to climate variability

While an array of ecological mechanisms has been shown to stabilize natural community dynamics, how the effectiveness of these mechanisms-including both their direction (stabilizing vs. destabilizing) and strength-shifts under a changing climate remains unknown. Using a 35-y dataset (1985 to 2019) from a desert stream in central Arizona (USA), we found that as annual mean air temperature rose 1°C and annual mean precipitation reduced by 40% over the last two decades, macroinvertebrate communities experienced dramatic changes, from relatively stable states during the first 15 y of this study to wildly fluctuating states highly sensitive to climate variability in the last 10 y. Asynchronous species responses to climatic variability, the primary mechanism historically undergirding community stability, greatly weakened. The emerging climate regime-specifically, concurrent warming and prolonged multiyear drought-resulted in community-wide synchronous responses and reduced taxa richness. Diversity loss and new establishment of competitors reorganized species interactions. Unlike manipulative experiments that often suggest stabilizing roles of species interactions, we found that reorganized species interactions switched from stabilizing to destabilizing influences, further amplifying community fluctuations. Our study provides evidence of climate change-induced modifications of mechanisms underpinning long-term community stability, resulting in an overall destabilizing effect.

Dryland sensitivity to climate change and variability using nonlinear dynamics

Primary productivity response to climatic drivers varies temporally, indicating state-dependent interactions between climate and productivity. Previous studies primarily employed equation-based approaches to clarify this relationship, ignoring the state-dependent nature of ecological dynamics. Here, using 40 y of climate and productivity data from 48 grassland sites across Mongolia, we applied an equation-free, nonlinear time-series analysis to reveal sensitivity patterns of productivity to climate change and variability and clarify underlying mechanisms. We showed that productivity responded positively to annual precipitation in mesic regions but negatively in arid regions, with the opposite pattern observed for annual mean temperature. Furthermore, productivity responded negatively to decreasing annual aridity that integrated precipitation and temperature across Mongolia. Productivity responded negatively to interannual variability in precipitation and aridity in mesic regions but positively in arid regions. Overall, interannual temperature variability enhanced productivity. These response patterns are largely unrecognized; however, two mechanisms are inferable. First, time-delayed climate effects modify annual productivity responses to annual climate conditions. Notably, our results suggest that the sensitivity of annual productivity to increasing annual precipitation and decreasing annual aridity can even be negative when the negative time-delayed effects of annual precipitation and aridity on productivity prevail across time. Second, the proportion of plant species resistant to water and temperature stresses at a site determines the sensitivity of productivity to climate variability. Thus, we highlight the importance of nonlinear, state-dependent sensitivity of productivity to climate change and variability, accurately forecasting potential biosphere feedback to the climate system.

Effects of grazing and precipitation addition induced by functional groups on the relationship between aboveground biomass and species richness of a typical steppe

Several studies have explored the influence of grazing or precipitation addition (PA), two important components of human activities and global climate change on the structure and function of communities. However, the response of communities to a combination of grazing and PA remains largely unexplored. We investigated the impact of grazing and PA on the relationship between aboveground biomass (AGB) and species richness (SR) of communities in three-year field experiments conducted in a typical steppe in the Loess Plateau, using a split-plot design with grazing as the main-plot factor and PA as the split-plot factor. AGB and SR have response threshold value to PA, which was decreased by grazing for AGB, but increased for SR. This indicates that implementing grazing management strategies is conducive to strengthening the protection of biodiversity in arid and semi-arid grasslands. Grazing promoted the AGB-SR coupling of the community by increasing the SR of medium drought tolerance (MD), low drought tolerance, and grazing tolerant functional groups. Grazing also accelerated the AGB-SR decoupling of the community by changing the AGB of high drought tolerance, MD, high grazing tolerance, and medium grazing tolerance functional groups. PA mediated changes in MD and SR of both drought and grazing tolerant functional groups and AGB of low grazing tolerance promoted the coupling of AGB-SR of the community. The Two-dimension functional groups classification method reflects the changes of AGB and SR in communities more reasonable than the division of single-factor functional groups.

As above, not so below: Long-term dynamics of net primary production across a dryland transition zone

Drylands are key contributors to interannual variation in the terrestrial carbon sink, which has been attributed primarily to broad-scale climatic anomalies that disproportionately affect net primary production (NPP) in these ecosystems. Current knowledge around the patterns and controls of NPP is based largely on measurements of aboveground net primary production (ANPP), particularly in the context of altered precipitation regimes. Limited evidence suggests belowground net primary production (BNPP), a major input to the terrestrial carbon pool, may respond differently than ANPP to precipitation, as well as other drivers of environmental change, such as nitrogen deposition and fire. Yet long-term measurements of BNPP are rare, contributing to uncertainty in carbon cycle assessments. Here, we used 16 years of annual NPP measurements to investigate responses of ANPP and BNPP to several environmental change drivers across a grassland-shrubland transition zone in the northern Chihuahuan Desert. ANPP was positively correlated with annual precipitation across this landscape; however, this relationship was weaker within sites. BNPP, on the other hand, was weakly correlated with precipitation only in Chihuahuan Desert shrubland. Although NPP generally exhibited similar trends among sites, temporal correlations between ANPP and BNPP within sites were weak. We found chronic nitrogen enrichment stimulated ANPP, whereas a one-time prescribed burn reduced ANPP for nearly a decade. Surprisingly, BNPP was largely unaffected by these factors. Together, our results suggest that BNPP is driven by a different set of controls than ANPP. Furthermore, our findings imply belowground production cannot be inferred from aboveground measurements in dryland ecosystems. Improving understanding around the patterns and controls of dryland NPP at interannual to decadal scales is fundamentally important because of their measurable impact on the global carbon cycle. This study underscores the need for more long-term measurements of BNPP to improve assessments of the terrestrial carbon sink, particularly in the context of ongoing environmental change.

Timing and magnitude of drought impacts on carbon uptake across a grassland biome

Although drought is known to negatively impact grassland functioning, the timing and magnitude of these impacts within a growing season remain unresolved. Previous small-scale assessments indicate grasslands may only respond to drought during narrow periods within a year; however, large-scale assessments are now needed to uncover the general patterns and determinants of this timing. We combined remote sensing datasets of gross primary productivity and weather to assess the timing and magnitude of grassland responses to drought at 5 km² temporal resolution across two expansive ecoregions of the western US Great Plains biome: the C₄ -dominated shortgrass steppe and the C₃ -dominated northern mixed prairies. Across over 700,000 pixel-year combinations covering more than 600,000 km² , we studied how the driest years between 2003-2020 altered the daily and bi-weekly dynamics of grassland carbon (C) uptake. Reductions to C uptake intensified into the early summer during drought and peaked in mid- and late June in both ecoregions. Stimulation of spring C uptake during drought was small and insufficient to compensate for losses during summer. Thus, total grassland C uptake was consistently reduced by drought across both ecoregions; however, reductions were twice as large across the more southern and warmer shortgrass steppe. Across the biome, increased summer vapor pressure deficit (VPD) was strongly linked to peak reductions in vegetation greenness during drought. Rising VPD will likely exacerbate reductions in C uptake during drought across the western US Great Plains, with these reductions greatest during the warmest months and in the warmest locations. High spatiotemporal resolution analyses of grassland response to drought over large areas provide both generalizable insights and new opportunities for basic and applied ecosystem science in these water-limited ecoregions amid climate change.

Variation in methane uptake by grassland soils in the context of climate change - A review of effects and mechanisms

Grassland soils are climate-dependent ecosystems that have a significant greenhouse gas mitigating function through their ability to store large amounts of carbon (C). However, what is often not recognized is that they can also exhibit a high methane (CH₄) uptake capacity that could be influenced by future increases in atmospheric carbon dioxide (CO₂) concentration and variations in temperature and water availability. While there is a wealth of information on C sequestration in grasslands there is less consensus on how climate change impacts on CH₄ uptake or the underlying mechanisms involved. To address this, we assessed existing knowledge on the impact of climate change components on CH₄ uptake by grassland soils. Increases in precipitation associated with soils with a high background soil moisture content generally resulted in a reduction in CH₄ uptake or even net emissions, while the effect was opposite in soils with a relatively low background moisture content. Initially wet grasslands subject to the combined effects of warming and water deficits may absorb more CH₄, mainly due to increased gas diffusivity. However, in the longer-term heat and drought stress may reduce the activity of methanotrophs when the mean soil moisture content is below the optimum for their survival. Enhanced plant productivity and growth under elevated CO₂, increased soil moisture and changed nutrient concentrations, can differentially affect methanotrophic activity, which is often reduced by increasing N deposition. Our estimations showed that CH₄ uptake in grassland soils can change from -57.7 % to +6.1 % by increased precipitation, from -37.3 % to +85.3 % by elevated temperatures, from +0.87 % to +92.4 % by decreased precipitation, and from -66.7 % to +27.3 % by elevated CO₂. In conclusion, the analysis suggests that grasslands under the influence of warming and drought may absorb even more CH₄, mainly because of reduced soil water contents and increased gas diffusivity.

Long-Term Seed Dispersal within an Asymmetric Lizard-Plant Interaction

During the last 24 years, the mutualistic interaction between the dead horse arum, Helicodiceros muscivorus, and the Balearic lizard, Podarcis lilfordi, was studied on Aire Island (Balearic Islands, Spain). From a small population of a hundred plants, the dead horse arum expanded extraordinarily throughout the island, reaching the highest known densities of the species and occupying areas of the island where it was not previously present. The current abundance of plants is a direct effect of the frugivorous activity of the Balearic lizard, which is the main, if not the only, effective seed disperser of the plant on Aire Island. However, abiotic factors predominated over biotic factors in driving abundance of plants. Over the years, plant densities varied significantly depending on the aridity of the island, with higher densities recorded in drier years. Lizards’ frugivorous activity and dispersal intensity was inversely correlated with annual rainfall. We found higher dispersal intensity in years with lower rainfall. We propose that the years of lower rainfall are those in which there is a lower prey availability. In such years, lizards compensate the shortage of other trophic resources with a more intense consumption of dead horse arum fruits. The mutualistic interaction is therefore asymmetric, since there is a greater influence of the frugivorous activity of the lizards on the plants than of the plants on lizards. It is, in short, a system chronically out of balance.

Responses of a semiarid grassland to recurrent drought are linked to community functional composition

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

Traits that distinguish dominant species across aridity gradients differ from those that respond to soil moisture

Many plant traits respond to changes in water availability and might be useful for understanding ecosystem properties such as net primary production (NPP). This is especially evident in grasslands where NPP is water-limited and primarily determined by the traits of dominant species. We measured root and shoot morphology, leaf hydraulic traits, and NPP of four dominant North American prairie grasses in response to four levels of soil moisture in a greenhouse experiment. We expected that traits of species from drier regions would be more responsive to reduced water availability and that this would make these species more resistant to low soil moisture than species from wetter regions. All four species grew taller, produced more biomass, and increased total root length in wetter treatments. Each species reduced its leaf turgor loss point (TLP) in drier conditions, but only two species (one xeric, one mesic) maintained leaf water potential above TLP. We identified a suite of traits that clearly distinguished species from one another, but, surprisingly, these traits were relatively unresponsive to reduced soil moisture. Specifically, more xeric species produced thinner roots with higher specific root length and had a lower root mass fraction. This suggest that root traits are critical for distinguishing species from one another but might not respond strongly to changing water availability, though this warrants further investigation in the field. Overall, we found that NPP of these dominant grass species responded similarly to varying levels of soil moisture despite differences in species morphology, physiology, and habitat of origin.

Soil moisture drives the spatiotemporal patterns of asymmetry in vegetation productivity responses across China

Increasingly drastic global change is expected to cause hydroclimatic changes, which will influence vegetation productivity and pose a threat to the terrestrial carbon sink. Asymmetry represents an imbalance between vegetation growth and loss of growth during dry and wet periods, respectively. However, the mechanisms of asymmetric plant responses to hydrological changes remain poorly understood. Here, we examined the spatiotemporal patterns of asymmetric responses of vegetation productivity across terrestrial ecosystems in China. We analyzed several observational and satellite-based datasets of plant productivity and several reanalyzed datasets of hydroclimatic variables from 2001 to 2020, and used a random forest model to assess the importance of hydroclimatic variables for these responses. Our results showed that the productivity of >50 % of China's vegetated areas showed a more positive asymmetry (2.3 ± 9.4 %) over the study period, which were distributed broadly in northwest China (mainly grasslands and sparse vegetation ecosystems). Negative asymmetries were most common in forest ecosystems in northeast China. We demonstrated that one-third of vegetated areas tended to exhibit significant changes in asymmetry during 2001-2020. The trend towards stronger positive asymmetry (0.95 % yr^-1) was higher than that towards stronger negative asymmetry (-0.55 % yr^-1), which is beneficial for the carbon sink. We further showed that in China, soil moisture was a more important driver of spatiotemporal changes in asymmetric productivity than precipitation. We identified thresholds of surface soil moisture (20-30 %, volume water content) and root-zone soil moisture (200-350 mm, equivalent water height) that were associated with changes in asymmetry. Our findings highlight the necessity of considering the dynamic responses of vegetation to hydrological factors in order to fully understand the physiological growth processes of plants and avoid the possible loss of productivity due to future climate change.

Optimality principles explaining divergent responses of alpine vegetation to environmental change

Recent increases in vegetation greenness over much of the world reflect increasing CO₂ globally and warming in cold areas. However, the strength of the response to both CO₂ and warming in those areas appears to be declining for unclear reasons, contributing to large uncertainties in predicting how vegetation will respond to future global changes. Here, we investigated the changes of satellite-observed peak season absorbed photosynthetically active radiation (F_max ) on the Tibetan Plateau between 1982 and 2016. Although climate trends are similar across the Plateau, we identified robust divergent responses (a greening of 0.31 ± 0.14% year^-1 in drier regions and a browning of 0.12 ± 0.08% year^-1 in wetter regions). Using an eco-evolutionary optimality (EEO) concept of plant acclimation/adaptation, we propose a parsimonious modelling framework that quantitatively explains these changes in terms of water and energy limitations. Our model captured the variations in F_max with a correlation coefficient (r) of .76 and a root mean squared error of .12 and predicted the divergent trends of greening (0.32 ± 0.19% year^-1 ) and browning (0.07 ± 0.06% year^-1 ). We also predicted the observed reduced sensitivities of F_max to precipitation and temperature. The model allows us to explain these changes: Enhanced growing season cumulative radiation has opposite effects on water use and energy uptake. Increased precipitation has an overwhelmingly positive effect in drier regions, whereas warming reduces F_max in wetter regions by increasing the cost of building and maintaining leaf area. Rising CO₂ stimulates vegetation growth by enhancing water-use efficiency, but its effect on photosynthesis saturates. The large decrease in the sensitivity of vegetation to climate reflects a shift from water to energy limitation. Our study demonstrates the potential of EEO approaches to reveal the mechanisms underlying recent trends in vegetation greenness and provides further insight into the response of alpine ecosystems to ongoing climate change.

Responses of grassland productivity to mowing intensity and precipitation variability in a temperate steppe

Mowing for hay is an important land use in grasslands that is affected by precipitation variability, due to the water-limited nature of these ecosystems. Past land use and precipitation conditions can have legacy effects on ecosystem functions, potentially altering responses to both mowing and precipitation. Nonetheless, it is still unclear how natural variation in precipitation will affect plant responses to changes in mowing intensity. We conducted a seven-year field experiment with three mowing intensity treatments compared to the traditional mowing intensity (5 cm stubble height) as a control: increased mowing (2 cm stubble), decreased mowing (8 cm stubble) and ceased mowing. Decreased mowing increased both plant aboveground net primary productivity [ANPP] and forage yield across the whole community, driven by increases in graminoids, mainly owing to the positive response of plants to precipitation. Both mowing disturbance and precipitation variability had legacy effects on plant ANPP; however, these responses differed among the whole community, graminoid, and forb levels. Current-year community-wide ANPP [ANPP_n] was positively associated with current-year precipitation [PPT_n] in all mowing treatments, driven by positive precipitation responses of the dominant graminoids. For forbs, however, ANPP_n was negatively associated with prior-year growing season precipitation [PPT_n-1] across mowing treatments, potentially due to lagged competition with the dominant graminoids. Our results suggest that the response of the dominant graminoids is the primary factor determining the response of ANPP to mowing and precipitation variability in these grassland ecosystems, and highlight that decreasing mowing intensity may maximize both herder's income and grassland sustainability.

Using functional indicators to detect state changes in terrestrial ecosystems

Indicators to predict ecosystem state change are urgently needed to cope with the degradation of ecosystem services caused by global change. With the development of new technologies for measuring ecosystem function with fine spatiotemporal resolution over broad areas, we are in the era of 'big data'. However, it is unclear how large, emerging datasets can be used to anticipate ecosystem state change. We propose the construction of indicators based on functional variables (flows) and state variables (pools) to predict future ecosystem state changes. The indicators identified here may be useful signals for doing so. In addition, functional indicators have explicit ecological meanings that can identify the ecological mechanism that is causing state changes, and can thus be used to improve ecosystem models.

Small effects of livestock grazing intensification on diversity, abundance, and composition in a dryland plant community

Livestock grazing is a globally important land use and has the potential to significantly influence plant community structure and ecosystem function, yet several critical knowledge gaps remain on the direction and magnitude of grazing impacts. Furthermore, much of our understanding of the long-term effects on plant community composition and structure are based on grazer exclusion experiments, which explicitly avoid characterizing effects along grazing intensity gradients. We sampled big sagebrush plant communities using 68 plots located along grazing intensity gradients to determine how grazing intensity influences multiple aspects of plant community structure over time. This was accomplished by sampling plant communities at different distances from 17 artificial watering sources, using distance from water and cow dung density as proxies for grazing intensity at individual plots. Total vegetation cover and total grass cover were negatively related to grazing intensity, and cover of annual forbs, exotic cover, and exotic richness were positively related to grazing intensity. In contrast, species richness and composition, bunchgrass biomass, shrub density and size, percentage cover of bare ground, litter, and biological soil crusts did not vary along our grazing intensity gradients, in spite of our expectations to the contrary. Our results suggest that the effects of livestock grazing over multiple decades (mean = 46 years) in our sites are relatively small, especially for native perennial species, and that the big sagebrush plant communities we sampled are somewhat resistant to livestock grazing. Collectively, our findings are consistent with existing evidence that indicates the stability of the big sagebrush plant functional type composition under current grazing management regimes.

Emergence of the physiological effects of elevated CO2 on land-atmosphere exchange of carbon and water

Elevated atmospheric CO₂ (eCO₂ ) influences the carbon assimilation rate and stomatal conductance of plants, thereby affecting the global cycles of carbon and water. Yet, the detection of these physiological effects of eCO₂ in observational data remains challenging, because natural variations and confounding factors (e.g., warming) can overshadow the eCO₂ effects in observational data of real-world ecosystems. In this study, we aim at developing a method to detect the emergence of the physiological CO₂ effects on various variables related to carbon and water fluxes. We mimic the observational setting in ecosystems using a comprehensive process-based land surface model QUINCY to simulate the leaf-level effects of increasing atmospheric CO₂ concentrations and their century-long propagation through the terrestrial carbon and water cycles across different climate regimes and biomes. We then develop a statistical method based on the signal-to-noise ratio to detect the emergence of the eCO₂ effects. The eCO₂ effect on gross primary productivity (GPP) emerges at relatively low CO₂ increase (∆[CO₂ ] ~ 20 ppm) where the leaf area index is relatively high. Compared to GPP, the eCO₂ effect causing reduced transpiration water flux (normalized to leaf area) emerges only at relatively high CO₂ increase (∆[CO₂ ] >> 40 ppm), due to the high sensitivity to climate variability and thus lower signal-to-noise ratio. In general, the response to eCO₂ is detectable earlier for variables related to the carbon cycle than the water cycle, when plant productivity is not limited by climatic constraints, and stronger in forest-dominated rather than in grass-dominated ecosystems. Our results provide a step toward when and where we expect to detect physiological CO₂ effects in in-situ flux measurements, how to detect them and encourage future efforts to improve the understanding and quantification of these effects in observations of terrestrial carbon and water dynamics.

The global decline in the sensitivity of vegetation productivity to precipitation from 2001 to 2018

The sensitivity of vegetation productivity to precipitation (S_ppt ) is a key metric for understanding the variations in vegetation productivity under changing precipitation and predicting future changes in ecosystem functions. However, a comprehensive assessment of S_ppt over all the global land is lacking. Here, we investigated spatial patterns and temporal changes of S_ppt across the global land from 2001 to 2018 with multiple streams of satellite observations. We found consistent spatial patterns of S_ppt with different satellite products: S_ppt was highest in dry regions while low in humid regions. Grassland and shrubland showed the highest S_ppt , and evergreen needle-leaf forest and wetland showed the lowest. Temporally, S_ppt showed a generally declining trend over the past two decades (p < .05), yet with clear spatial heterogeneities. The decline in S_ppt was especially noticeable in North America and Europe, likely due to the increase in precipitation. In central Russia and Australia, however, S_ppt showed an increasing trend. Biome-wise, most ecosystem types exhibited significant decrease in S_ppt , while grassland, evergreen broadleaf forest, and mixed forest showed slight increases or non-significant changes in S_ppt . Our finding of the overall decline in S_ppt implies a potential stabilization mechanism for ecosystem productivity under climate change. However, the revealed S_ppt increase for some regions and ecosystem types, in particular global grasslands, suggests that grasslands might be increasingly vulnerable to climatic variability with continuing global climate change.

Climate disequilibrium dominates uncertainty in long-term projections of primary productivity

Rapid climate change may exceed ecosystems' capacities to respond through processes including phenotypic plasticity, compositional turnover and evolutionary adaption. However, consequences of the resulting climate disequilibria for ecosystem functioning are rarely considered in projections of climate change impacts. Combining statistical models fit to historical climate data and remotely-sensed estimates of herbaceous net primary productivity with an ensemble of climate models, we demonstrate that assumptions concerning the magnitude of climate disequilibrium are a dominant source of uncertainty: models assuming maximum disequilibrium project widespread decreases in productivity in the western US by 2100, while models assuming minimal disequilibrium project productivity increases. Uncertainty related to climate disequilibrium is larger than uncertainties from variation among climate models or emissions pathways. A better understanding of processes that regulate climate disequilibria is essential for improving long-term projections of ecological responses and informing management to maintain ecosystem functioning at historical baselines.

Antecedent climatic conditions spanning several years influence multiple land-surface phenology events in semi-arid environments

Ecological processes are complex, often exhibiting non-linear, interactive, or hierarchical relationships. Furthermore, models identifying drivers of phenology are constrained by uncertainty regarding predictors, interactions across scales, and legacy impacts of prior climate conditions. Nonetheless, measuring and modeling ecosystem processes such as phenology remains critical for management of ecological systems and the social systems they support. We used random forest models to assess which combination of climate, location, edaphic, vegetation composition, and disturbance variables best predict several phenological responses in three dominant land cover types in the U.S. Northwestern Great Plains (NWP). We derived phenological measures from the 25-year series of AVHRR satellite data and characterized climatic predictors (i.e., multiple moisture and/or temperature based variables) over seasonal and annual timeframes within the current year and up to 4 years prior. We found that antecedent conditions, from seasons to years before the current, were strongly associated with phenological measures, apparently mediating the responses of communities to current-year conditions. For example, at least one measure of antecedent-moisture availability [precipitation or vapor pressure deficit (VPD)] over multiple years was a key predictor of all productivity measures. Variables including longer-term lags or prior year sums, such as multi-year-cumulative moisture conditions of maximum VPD, were top predictors for start of season. Productivity measures were also associated with contextual variables such as soil characteristics and vegetation composition. Phenology is a key process that profoundly affects organism-environment relationships, spatio-temporal patterns in ecosystem structure and function, and other ecosystem dynamics. Phenology, however, is complex, and is mediated by lagged effects, interactions, and a diversity of potential drivers; nonetheless, the incorporation of antecedent conditions and contextual variables can improve models of phenology.

Increasing sensitivity of dryland vegetation greenness to precipitation due to rising atmospheric CO2

Water availability plays a critical role in shaping terrestrial ecosystems, particularly in low- and mid-latitude regions. The sensitivity of vegetation growth to precipitation strongly regulates global vegetation dynamics and their responses to drought, yet sensitivity changes in response to climate change remain poorly understood. Here we use long-term satellite observations combined with a dynamic statistical learning approach to examine changes in the sensitivity of vegetation greenness to precipitation over the past four decades. We observe a robust increase in precipitation sensitivity (0.624% yr⁻¹) for drylands, and a decrease (−0.618% yr⁻¹) for wet regions. Using model simulations, we show that the contrasting trends between dry and wet regions are caused by elevated atmospheric CO₂ (eCO₂). eCO₂ universally decreases the precipitation sensitivity by reducing leaf-level transpiration, particularly in wet regions. However, in drylands, this leaf-level transpiration reduction is overridden at the canopy scale by a large proportional increase in leaf area. The increased sensitivity for global drylands implies a potential decrease in ecosystem stability and greater impacts of droughts in these vulnerable ecosystems under continued global change.

Changes in vegetation responses to precipitation may be hydroclimate dependent. Here the authors reveal contrasting trends of vegetation sensitivity to precipitation in drylands vs. wetter ecosystems over the last 4 decades and identify increased CO2 as a major contributing factor.

Biodiversity mediates ecosystem sensitivity to climate variability

A rich body of evidence from local-scale experiments and observational studies has revealed stabilizing effects of biodiversity on ecosystem functioning. However, whether these effects emerge across entire regions and continents remains largely overlooked. Here we combine data on the distribution of more than 57,500 plant species and remote-sensing observations throughout the entire Western Hemisphere to investigate the role of multiple facets of plant diversity (species richness, phylogenetic diversity, and functional diversity) in mediating the sensitivity of ecosystems to climate variability at the regional-scale over the past 20 years. We show that, across multiple biomes, regions of greater plant diversity exhibit lower sensitivity (more stable over time) to temperature variability at the interannual and seasonal-scales. While these areas can display lower sensitivity to interannual variability in precipitation, they emerge as highly sensitive to precipitation seasonality. Conserving landscapes of greater diversity may help stabilize ecosystem functioning under climate change, possibly securing the continuous provisions of productivity-related ecosystem service to people.

With the help of spatial autoregressive models, the relationship between multiple facets of plant biodiversity and ecosystem sensitivity to climate variability is explored on a landscape-scale.

Rainfall pulse regime drives biomass and community composition in biological soil crusts

Future climates will alter the frequency and size of rain events in drylands, potentially affecting soil microbes that generate carbon feedbacks to climate, but field tests are rare. Topsoils in drylands are commonly colonized by biological soil crusts (biocrusts), photosynthesis-based communities that provide services ranging from soil fertilization to stabilization against erosion. We quantified responses of biocrust microbial communities to twelve years of altered rainfall regimes, with 60 mm of additional rain per year delivered either as small (5 mm) weekly rains or large (20 mm) monthly rains during the summer monsoon season. Rain addition promoted microbial diversity, suppressed the dominant cyanobacterium, Microcoleus vaginatus, and enhanced nitrogen-fixing taxa, but did not consistently increase microbial biomass. The addition of many small rain events increased microbial biomass, whereas few, large events did not. These results alter the physiological paradigm that biocrusts are most limited by the amount of rainfall and instead predict that regimes enriched in small rain events will boost cyanobacterial biocrusts and enhance their beneficial services to drylands. This article is protected by copyright. All rights reserved.

Precipitation effects on grassland plant performance are lessened by hay harvest

Climate and human management, such as hay harvest, shape grasslands. With both disturbances co-occurring, understanding how these ecosystems respond to these combined drivers may aid in projecting future changes in grasslands. We used an experimental precipitation gradient combined with mimicked acute hay harvest (clipping once a year) to examine (1) whether hay harvest influences precipitation effects on plant performance (cover and height) and (2) the role of inter-specific responses in influencing plant performance. We found that hay harvest reduced the strength of precipitation effects on plant performance through changes in bare-ground soil cover. Species performance were mainly influenced by change in abiotic factors, often responding negatively, as hay harvest increased bare-ground amount. Conversely, altered precipitation without hay harvest promoted plant species performance through abiotic factors change first, followed by biotic. Most species, including the dominant grass Schizachyrium scoparium, increased their performance with greater leaf area index (proxy for canopy structure). Our experiment demonstrates that plant performance responds directly to abiotic factors with hay harvest, but indirectly without hay harvest. Positive effects of increasing precipitation were likely due to microhabitat amelioration and resource acquisition, thus inclusion of hay harvest as a disturbance lessens positive impacts of biotic variables on species performance to climate change.

Disturbance to biocrusts decreased cyanobacteria, N-fixer abundance, and grass leaf N but increased fungal abundance

Interactions between plants and soil microbes influence plant nutrient transformations, including nitrogen (N) fixation, nutrient mineralization, and resource exchanges through fungal networks. Physical disturbances to soils can disrupt soil microbes and associated processes that support plant and microbial productivity. In low resource drylands, biological soil crusts ("biocrusts") occupy surface soils and house key autotrophic and diazotrophic bacteria, non-vascular plants, or lichens. Interactions among biocrusts, plants, and fungal networks between them are hypothesized to drive carbon and nutrient dynamics; however, comparisons across ecosystems are needed to generalize how soil disturbances alter microbial communities and their contributions to N pools and transformations. To evaluate linkages among plants, fungi, and biocrusts, we disturbed all unvegetated surfaces with human foot trampling twice yearly in dry conditions from 2013-2019 in cyanobacteria-dominated biocrusts in Chihuahuan Desert grassland and shrubland ecosystems. After five years, disturbance decreased the abundances of cyanobacteria (especially Microcoleus steenstrupii clade) and N-fixers (Scytonema sp., and Schizothrix sp.) by >77% and chlorophyll a by up to 55%, but conversely, increased soil fungal abundance by 50% compared to controls. Responses of root-associated fungi differed between the two dominant plant species and ecosystem types, with a maximum of 80% more aseptate hyphae in disturbed than control plots. Although disturbance did not affect ¹⁵ N tracer transfer from biocrusts to the dominant grass, Bouteloua eriopoda, disturbance increased available soil N by 65% in the shrubland, and decreased leaf N of B. eriopoda up to 16%, suggesting that although rapid N transfer during peak production was not affected by disturbance, over the long term, plant nutrient content was disrupted. Altogether, the shrubland may be more resilient to detrimental changes due to disturbance than grassland, and these results demonstrate that disturbances to soil microbial communities have potential to cause substantial changes in N pools by reducing and reordering biocrust taxa.

Global pattern and associated drivers of grassland productivity sensitivity to precipitation change

Precipitation is a primary climatic determinant of grassland productivity, with many global change experiments manipulating precipitation. Here we examine the impacts of precipitation addition and reduction treatment intensity and duration on grassland above- (ANPP) and below- (BNPP) ground net primary productivity in a large-scale meta-analysis. We tested, 1) the double asymmetry model of sensitivity, specifically whether the sensitivity of productivity decreases with treatment intensity under increased precipitation and increases with treatment intensity under decreased precipitation, 2) whether the sensitivity of productivity to precipitation change decreases with treatment length, and 3) how the sensitivity of productivity changes with climate conditions. ANPP showed higher sensitivity than BNPP under increased precipitation but similar sensitivity to BNPP under decreased precipitation. The sensitivity of ANPP and BNPP decreased with increasing treatment intensity (e.g., percentage change in precipitation, ΔPPT) and leveled off in the long-term. With increased precipitation, the sensitivity of productivity decreased with increasing treatment length (e.g., experimental duration) and leveled off in the long-term, whereas the sensitivity increased with increasing treatment length under reduced precipitation. Furthermore, the sensitivity of productivity to precipitation change decreased with increasing mean annual precipitation and temperature. Finally, our meta-analysis shows that above- and belowground net primary productivity have asymmetric responses to precipitation change. Together these results highlight the complex mechanisms underlying the impacts of precipitation change, particularly the intensity and duration of such changes, on grassland productivity.

Divergent responses of primary production to increasing precipitation variability in global drylands

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) <500 mm year^-1 , using a combined approach of data synthesis and process-based modeling. We found a hump-shaped response of ANPP to precipitation variability along the MAP gradient. The response was positive when MAP < ~300 mm year^-1 and negative when MAP was higher than this threshold, with a positive peak at 140 mm year^-1 . Transpiration and subsoil water content mirrored the response of ANPP to precipitation variability; evaporation responded negatively and water loss through runoff and drainage responded positively to precipitation variability. Mean annual temperature, soil type, and plant physiological traits all altered the magnitude but not the pattern of the response of ANPP to precipitation variability along the MAP gradient. By extrapolating to global drylands (<500 mm year^-1  MAP), we estimated that ANPP would increase by 15.2 ± 6.0 Tg C year^-1 in arid and hyper-arid lands and decrease by 2.1 ± 0.5 Tg C year^-1 in dry sub-humid lands under future changes in interannual precipitation variability. Thus, increases in precipitation variability will enhance primary production in many drylands in the future.

Country-level land carbon sink and its causing components by the middle of the twenty-first century

BACKGROUND

Countries have long been making efforts by reducing greenhouse-gas emissions to mitigate climate change. In the agreements of the United Nations Framework Convention on Climate Change, involved countries have committed to reduction targets. However, carbon (C) sink and its involving processes by natural ecosystems remain difficult to quantify.

METHODS

Using a transient traceability framework, we estimated country-level land C sink and its causing components by 2050 simulated by 12 Earth System Models involved in the Coupled Model Intercomparison Project Phase 5 (CMIP5) under RCP8.5.

RESULTS

The top 20 countries with highest C sink have the potential to sequester 62 Pg C in total, among which, Russia, Canada, USA, China, and Brazil sequester the most. This C sink consists of four components: production-driven change, turnover-driven change, change in instantaneous C storage potential, and interaction between production-driven change and turnover-driven change. The four components account for 49.5%, 28.1%, 14.5%, and 7.9% of the land C sink, respectively.

CONCLUSION

The model-based estimates highlight that land C sink potentially offsets a substantial proportion of greenhouse-gas emissions, especially for countries where net primary production (NPP) likely increases substantially and inherent residence time elongates.

Declines in rodent abundance and diversity track regional climate variability in North American drylands

Regional long-term monitoring can enhance the detection of biodiversity declines associated with climate change, improving future projections by reducing reliance on space-for-time substitution and increasing scalability. Rodents are diverse and important consumers in drylands, regions defined by the scarcity of water that cover 45% of Earth's land surface and face increasingly drier and more variable climates. We analyzed abundance data for 22 rodent species across grassland, shrubland, ecotone, and woodland ecosystems in the southwestern USA. Two time series (1995-2006 and 2004-2013) coincided with phases of the Pacific Decadal Oscillation (PDO), which influences drought in southwestern North America. Regionally, rodent species diversity declined 20%-35%, with greater losses during the later time period. Abundance also declined regionally, but only during 2004-2013, with losses of 5% of animals captured. During the first time series (wetter climate), plant productivity outranked climate variables as the best regional predictor of rodent abundance for 70% of taxa, whereas during the second period (drier climate), climate best explained variation in abundance for 60% of taxa. Temporal dynamics in diversity and abundance differed spatially among ecosystems, with the largest declines in woodlands and shrublands of central New Mexico and Colorado. Which species were winners or losers under increasing drought and amplified interannual variability in drought depended on ecosystem type and the phase of the PDO. Fewer taxa were significant winners (18%) than losers (30%) under drought, but the identities of winners and losers differed among ecosystems for 70% of taxa. Our results suggest that the sensitivities of rodent species to climate contributed to regional declines in diversity and abundance during 1995-2013. Whether these changes portend future declines in drought-sensitive consumers in the southwestern USA will depend on the climate during the next major PDO cycle.