Climatic controls of aboveground net primary production in semi-arid grasslands along a latitudinal gradient portend low sensitivity to warming

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.

Impacts of Climate Change and Land Use/Cover Change on the Net Primary Productivity of Vegetation in the Qinghai Lake Basin

The Qinghai Lake Basin acts as a natural barrier, preventing the western desert from spreading eastward. This is an important link in preserving the ecological stability of the northeastern region of the Qinghai-Tibet Plateau (QTP). Therefore, quantitative research into the net primary productivity (NPP) of vegetation and its driving force in the Qinghai Lake Basin is required. The effects of land use/cover change (LUCC) and climate change on NPP in the Qinghai Lake Basin were studied using R-contribution ratio and partial correlation analysis methods using MOD17A3H products, Land Use/Land Cover (LULC) data, and meteorological data. (1) The LULC of the Qinghai Lake Basin showed a trend that "the area of grassland, cultivated land, and unused land continued to decrease, while the area of other LULC types increased" from 2000 to 2020, according to the study's findings. Grassland, water bodies, construction land, and unused land dominated the mutual transformation of LULC types. (2) The NPP of the basin showed a growing trend, with a growth rate of 3.93 gC·m^-2·a^-1 before 2010 and 0.88 gC·m^-2·a^-1 after 2010. Significant regional heterogeneity was found in NPP, with gradients decreasing from southeast to northwest. (3) The impact of LUCC on overall NPP changes had gradually increased. Climate change has been the primary driver of NPP changes in the Qinghai Lake Basin over the last 20 years.

Effects of climate change and human activities on gross primary productivity in the Heihe River Basin, China

As the primary source of carbon dioxide fixation, vegetation is critical to the carbon sink process. In this paper, the Net Primary Productivity (NPP) and the Gross Primary Productivity (GPP) were simulated using the Carnegie-Ames-Stanford Approach (CASA) model and the Vegetation Photosynthesis Model (VPM), respectively, and then the Potential Gross Primary Productivity (PGPP) and the GPP affected by human activities (AGPP) were simulated by combining Potential Net Primary Productivity (PNPP), and then the impact of climate change and human activities on GPP was assessed in the Heihe River Basin (HRB). The results showed that the GPP of grassland and Bare or Sparse Vegetation (BSV) exhibited a fluctuation rise, with increases of 0.709 gCm^-2 a^-1 and 0.115 gCm^-2 a^-1, respectively, whereas the GPP of cropland showed a fluctuation reduction, with a decline rate of -0.465 gCm^-2 a^-1. Climate change and human activity are both positive for vegetation growth, and human activity being the primary factor influencing GPP change. Human-dominated vegetation restoration accounted for 56.1% of the overall restoration area, with grassland GPP being the most visible response to human activities. The GPP changes in crop and grassland had a positive correlation with precipitation but a negative correlation with temperature among climate change factors, whereas the GPP changes in BSV had a negative correlation with both precipitation and temperature. Quantitative analyses of climate change and human activities' dynamic contributions to vegetation can give scientific and theoretical insight for dealing with global climate change.

Aboveground biomass of marshes in Northeast China: Spatial pattern and annual changes responding to climate change

Examining vegetation aboveground biomass (AGB) changes is important to understanding wetland carbon sequestration. Here, we combined the field-measured AGB data (458 samples) from 2009 to 2021, moderate resolution imaging spectroradiometer reflectance products, and climatic data to reveal the AGB variations of marshes in Northeast China by comparing various models driven by different indicators. The results indicated that random forest model driven by six vegetation indices, land surface temperature, and land surface water index achieved accurate marsh AGB estimation with R2 being 0.78 and relative error being 16.71%. The mean marsh AGB in Northeast China from 2000 to 2021 was 682.89 ± 31.69 g·m−2, which generally increased from north to south in space. Temporally, annual marsh AGB declined slowly at a rate of 3.45 g·m−2·year−1 during the past 21 years driven mainly by the decrease in summer mean temperature that was characterized by a significantly positive correlation between them. Nevertheless, we highlighted that the temporal changes of marsh AGB spatially varied in response to inconsistent climate change, thus place-based measures are required for sustainable management of marshes.

Impacts of climate change and human activities on different degraded grassland based on NDVI

Grassland degradation has emerged as a serious socio-economic and ecological problem, endangering both long-term usage and the regional biogeochemical cycle. Climate change and human activities are the two leading factors leading to grassland degradation. However, it is unclear what the degradation level caused by these two factors is. Using the normalized difference vegetation index (NDVI) and coefficient of variation of NDVI (CV_NDVI), the spatial distribution features of grassland degradation or restoration were analyzed in Qilian County in the northeast of the Qinghai–Tibet Plateau. The dominant climate variables affecting NDVI variation were selected through the combination of random forest model and stepwise regression method to improve the residual trend analysis, and on this basis, twelve possible scenarios were established to evaluate the driving factors of different degraded grasslands. Finally, used the Hurst index to forecast the trend of grassland degradation or restoration. The results showed that approximately 55.0% of the grassland had been degraded between 2000 and 2019, and the area of slight degradation (NDVI_slope > 0; CV_{NDVI (slope)} > 0; NDVI_value > 0.2) accounted for 48.6%. These regions were centered in the northwest of Qilian County. Climate and human activities had a joint impact on grassland restoration or degradation. Human activities played a leading role in grassland restoration, while climate change was primarily a driver of grassland degradation. The regions with slight degradation or re-growing (NDVI_slope > 0; CV_{NDVI (slope)} > 0), moderate degradation (NDVI_slope < 0; CV_{NDVI (slope)} > 0), and severe degradation or desertification (NDVI_slope < 0; CV_{NDVI (slope)} < 0) were dominated by the joint effects of climate and anthropogenic activity accounted for 34.3%, 3.3%, and 1.3%, respectively, of the total grassland area. Grasslands in most areas of Qilian County are forecasted to continue to degrade, including the previously degraded areas, with continuous degradation areas accounting for 54.78%. Accurately identifying the driving factors of different degraded grassland and predicting the dynamic change trend of grassland in the future is the key to understand the mechanism of grassland degradation and prevent grassland degradation. The findings offer a reference for accurately identifying the driving forces in grassland degradation, as well as providing a scientific basis for the policy-making of grassland ecological management.

Holistic aboveground ecological productivity efficiency modeling using data envelopment analysis in the southeastern U.S

Aboveground net primary productivity (ANPP) of an ecosystem is among the most important metrics of valued ecosystem services. Measuring the efficiency scores of ecological production (ESEP) based on ANPP using relevant variables is valuable for identifying inefficient sites. The efficiency scores computed by the Data Envelopment Analysis (DEA) may be influenced by the number of input variables incorporated into the models and two DEA settings-orientations and returns-to-scales (RTSs). Therefore, the objectives were threefold to: (1) identify soil-environmental variables relevant to ANPP, (2) assess the sensitivity of ESEP to the number of input variables and DEA settings, and (3) assess local management relations with ESEP. The ANPP rates were calculated for pine forests in the southeastern U.S. where 10 management types were used. This was followed by an all-relevant variable selection technique based on 696 variables that cover biotic, pedogenic, climatic, geological, and topographical factors. Five minimal-optimal variable selection techniques were further applied to create five parsimonious sets that contain a different number of variables used as DEA inputs. After setting ANPP as the output variable, two DEA orientations (input/output) and six RTS were applied to compute ESEP. The variable selection methods succeeded in objectively identifying the major factors relevant to ANPP variation. The site index showed the highest correlation with ANPP (r = 0.39), while various precipitation factors were negatively correlated (r = - 0.15~ - 0.29, p < 0.01). Parsimonious ESEP models observed a decrease in score variances as the number of input variables increased. Various RTS produced similar scores across orientations. Of the DEA settings, an output orientation with decreasing RTS produced the most progressive ESEP with large variation. Results also suggested that macro- and micronutrient fertilization is the best combination of management strategies to achieve high ESEP. This holistic benchmark approach can be applied to other ecological functions in diverse regions.

Effect of Nutrient Addition on the Productivity and Species Richness of Grassland Along With an Elevational Gradient in Tajikistan

Grasslands provide key resource for the millions of people who are dependent on livestock in Tajikistan. Productivity and species richness (SR) are important characteristics of grassland ecosystems and are greatly affected by nutrient inputs. The effect that climate change might have on these characteristics remains unclear. Here, an in situ nitrogen (N) and phosphorus (P) fertilization experiment was conducted at four sites along with an elevational gradient (650, 1,100, 1,250, and 2,000 m) in western Tajikistan over 2 years (2018 and 2019) to examine the influences of nutrient availability and climate change on aboveground biomass (AGB) and SR; precipitation and temperature were also considered to analyze the responses. It demonstrated that enrichment with N, P, and their combinations significantly increased AGB along with an elevational gradient (p < 0.05). AGB increased as the concentrations of nutrients added increased. The maximum AGB, which was 2-fold higher compared with control, was observed when 90 kg N ha^-1year^-1 and 30 kg P ha^-1year^-1 were added. In addition, nitrogen addition alone stimulated greater AGB than P addition, although no significant difference was observed between these two treatments. Enrichment with N, P, and their combination had no significant effect on SR; however, SR significantly changed at different elevation. Elevation had direct effect on precipitation and temperature, which, in turn, resulted in variation in AGB and SR. Moreover, both nutrient and elevation had significant effect on AGB and SR, but there was no interaction effect of them. AGB and SR interacted with significant negative correlation. In the high-elevation area, plants grew better in the warmer year (2018); this indicates that grasslands in high mountain areas in Tajikistan might have higher productivity as the climate warms, which will positively affect the economic development of the country.

Effects of glyphosate on soil fungal communities: A field study

The driving forces behind many soil processes are microorganisms and they are able to respond immediately to environmental changes. The soil microbial community impacts on many soil properties. More than one-third of the terrestrial ecosystems are semiarid. However, a limited number of studies have been conducted to characterize soil fungal communities in semiarid grasslands, in particular those of agricultural fields. The aim of this study was to explore changes in the diversity and structure of soil fungal communities in semiarid grasslands, after different doses of glyphosate were applied under field conditions. Changes in soil fungal communities were examined using different approaches including culturing, calcofluor white stain and denaturing gradient gel electrophoresis (DGGE). The different approaches complement each other, revealing different aspects of the effect of glyphosate on soil fungal communities. We demonstrated a negative effect of glyphosate on soil fungal biomass at high doses and an early and transitory stimulatory effect on soil fungal biomass. We also found a negative effect of glyphosate on the species richness of cultivable fungi and changes in the molecular structure of soil fungal communities after double doses or long-term glyphosate application. In summary, our findings demonstrate an overall negative effect of glyphosate on soil fungal communities.

The impact of climate change on livestock production in pastoral areas of China

This study assesses the impacts of climate change on net livestock revenue, grazing intensity, and net revenue per livestock, based on a panel dataset of 959 herder households from 18 counties in three major pastoral provinces in China. The Ricardian model and the Hsiao two-step method are applied to quantify the impacts on household-level livestock production made by long-term changes of temperature and precipitation and short-term occurrence of natural disasters. The results indicate that long-term temperature leads to decreased net livestock revenue and net revenue per livestock, whereas long-term precipitation improves revenue per livestock. Next, both long-term annual temperature and precipitation result in an increase of grazing intensity. A further analysis based on the simulation of future climate change predicts that the future increase in temperature will have a negative influence on both net revenue and net revenue per livestock, while the precipitation increment will have a positive effect on livestock production.

Dew water-uptake pathways in Negev desert plants: a study using stable isotope tracers

Dew is an important water resource for plants in most deserts. The mechanism that allows desert plants to use dew water was studied using an isotopic water tracer approach. Most plants use water directly from the soil; the roots transfer the water to the rest of the plant, where it is required for all metabolic functions. However, many plants can also take up water into their leaves and stems. Examining the dew water uptake pathways in desert plants can lend insight on another all water-use pathways examination. We determined where and how dew water enters plants in the water limited Negev desert. Highly depleted isotopic water was sprayed on three different dominant plant species of the Negev desert-Artemesia sieberi, Salsola inermis and Haloxylon scoparium-and its entry into the plant was followed. Water was sprayed onto the soil only, or on the leaves/stems only (with soil covered to prevent water entry via root uptake). Thereafter, the isotopic composition of water in the roots and stems were measured at various time points. The results show that each plant species used the dew water to a different extent, and we obtained evidence of foliar uptake capacity of dew water that varied depending on the microenvironmental conditions. A. sieberi took up the greatest amount of dew water through both stems and roots, S. inermis took up dew water mainly from the roots, and H. scoparium showed the least dew capture overall.

Disentangling the effects of climatic variability and climate extremes on the belowground biomass of C3- and C4-dominated grasslands across five ecoregions

Elucidating the variation in grassland belowground biomass (BGB) and its response to changes in climatic variables are key issues in plant ecology research. In this study, BGB data for five ecoregions (cold steppe, temperate dry steppe, savanna, humid savanna, and humid temperate) were used to examine the effects of climatic variability and extremes on the BGB of C₃- and C₄-dominated grasslands. Results showed that BGB varied significantly across the ecoregions, with the highest levels in cold steppe and the lowest in savanna. The results indicated that growing-season temperature, maximum and minimum temperatures and their interactions had significantly positive effects on the single-harvest BGB of C₃ plants in colder ecoregions (i.e., humid temperate and cold steppe) and of C₄ plants in arid ecoregions (i.e., temperate dry steppe and savanna). The single-harvest BGB of C₃ plants in arid ecoregions and C₄ plants in humid savanna ecoregion declined with increasing temperature during the growing season. Growing-season precipitation exerted significant positive effects on the single-harvest BGB of C₄ plants in arid ecoregions. Annual temperature variables negatively impacted the annual BGB of humid temperate ecoregion, because of the dominance of C₃ plants. Increasing cumulative growing-season precipitation elevated and the mean annual temperature reduced the annual BGB of both categories of plants in arid ecoregions. Compared with normal climates, extreme dry events during the growing season enhanced single-harvest BGB in colder ecoregions. The single-harvest BGB of C₄ plants in savanna tended to increase during extreme wet and decrease during moderate dry events compared to normal climates. This study suggests that the differential effects of climatic variability and extremes on BGB can be explained by differences in plant types, and ecoregions. These findings on the responses of the BGB to climatic variability and extremes constitute important scientific evidence emphasizing the need to maintain ecosystem stability across ecoregions.

Vegetation Productivity Dynamics in Response to Climate Change and Human Activities under Different Topography and Land Cover in Northeast China

Net primary productivity (NPP) is the total amount of organic matter fixed by plants from the atmosphere through photosynthesis and is susceptible to the influences of climate change and human activities. In this study, we employed actual NPP (ANPP), potential NPP (PNPP), and human activity-induced NPP (HNPP) based on the Hurst exponent and statistical analysis to analyze the characteristics of vegetation productivity dynamics and to evaluate the effects of climate and human factors on vegetation productivity in Northeast China (NEC). The increasing trends in ANPP, PNPP, and HNPP accounted for 81.62%, 94.90%, and 89.63% of the total area, respectively, and ANPP in 68.64% of the total area will continue to increase in the future. Climate change played a leading role in vegetation productivity dynamics, which promoted an increase in ANPP in 71.55% of the area, and precipitation was the key climate factor affecting ANPP. The aggravation of human activities, such as increased livestock numbers and intensified agricultural activities, resulted in a decrease in ANPP in the western grasslands, northern Greater Khingan Mountains, and eastern Songnen Plain. In particular, human activities led to a decrease in ANPP in 53.84% of deciduous needleleaf forests. The impact of climate change and human activities varied significantly under different topography, and the percentage of the ANPP increase due to climate change decreased from 71.13% to 53.9% from plains to urgent slopes; however, the percentage of ANPP increase due to human activities increased from 3.44% to 21.74%, and the effect of human activities on the increase of ANPP was more obvious with increasing slope. At different altitudes, the difference in the effect of these two factors was not significant. The results are significant for understanding the factors influencing the vegetation productivity dynamics in NEC and can provide a reference for governments to implement projects to improve the ecosystem.

Spatial-temporal analysis of net primary production (NPP) and its relationship with climatic factors in Iran

Fluctuations of the climate variables have increased in the recent years. These fluctuations are different in each climatic region. Net primary production (NPP) indicating the plant growth and carbon stabilization over period of time is influenced by these fluctuations. Investigation of the variations in the NPP and analysis of its relationship with the climatic and environmental variables can play a key role in determining the effects of fluctuations of climatic variables on the NPP. Therefore, the present study was conducted to investigate the spatiotemporal changes in the NPP and its correlation with precipitation rate and temperature during 2000-2014 based on the annual NPP estimates determined by the moderate resolution imaging spectroradiometer (MODIS) sensor and precipitation and temperature data of the synoptic stations in eight climate regions in Iran. The slope of variations in the NPP was calculated in these climatic regions, and then, the changes in the NPP trend at two confidence levels of 95 and 99% were investigated based on the pixel-based method using the Mann-Kendall test. The sensitivity of NPP to climatic variables of temperature and precipitation was also estimated by calculating the correlation. The results showed the significant spatial distribution of NPP in the whole region under study indicating a declining trend from north to south and from west to east directions. The results also indicated the nonlinear variations in the temporal distribution of NPP. The annual mean NPP was found to follow the climatic boundaries in the climatic regions except for climate region 2, and region with the higher annual mean precipitation had higher annual mean NPP. Analysis of the trend by the Mann-Kendall method revealed that 3.2% of the pixels in the whole region followed a certain trend. Among the pixels, 70% of them followed a negative trend and the remaining 30% followed a positive trend. The greatest number of pixels with a certain trend was found in the Gulf of Oman coast climate region so that 93% of the pixels had a positive trend. The lowest number of pixels with a certain trend was observed in eastern Alborz foothills so that 87% of the pixels showed a negative trend. Slope variations of the NPP in the whole region varied from - 35 to 46 gC m² year^-1. The eastern plateau had the highest negative slope variations among the climate regions, and the highest positive slope variation of 42% was observed in the highlands climate region. In general, the precipitation rate and temperature showed a mean partial coefficient of 0.22 and 0.02, respectively, and the correlation between the NPP and temperature and precipitation was different in each climatic region. The temperature was negatively correlated with the NPP in four climatic regions with higher annual mean temperatures and in other climatic regions; it had a weak positive correlation. Therefore, the sensitivity of NPP to precipitation and temperature was different in each climatic region.

Contribution of unvegetated tidal flats to coastal carbon flux

Unvegetated flats occupy a large area in the intertidal zone. However, compared to vegetated areas, the carbon sequestration of unvegetated tidal flats is rarely quantified, even though these areas are highly threatened by human development and climate change. We determined benthic maximum gross primary production (GPP_m ), net primary production (NPP) and total respiration (TR) during emersion on seven tidal flats along a latitudinal gradient (from 22.48°N to 40.60°N) in winter and summer from 2012 to 2016 to assess the spatial and temporal variability of carbon dioxide flux. In winter, these processes decreased by 89%-104% towards higher latitudes. In summer, however, no clear trend was detected across the latitudinal gradient. Quadratic relationships between GPP_m , NPP and TR and sediment temperature can be described along the latitudinal gradient. These curves showed maximum values of GPP_m and NPP when the sediment temperatures reached 28.7 and 26.6°C respectively. TR increased almost linearly from 0 to 45°C. The maximum daily NPP across the latitudinal gradient averaged 0.24 ± 0.28 g C m^-2  day^-1 , which was only 10%-20% of the global average of NPP of vegetated coastal habitats. Multiplying with the global area of unvegetated tidal flats, our results suggest that the contribution of NPP on unvegetated tidal flats to the coastal carbon cycle is small (11.04 ± 13.32 Tg C/year). If the land cover of vegetated habitats is continuously degraded to unvegetated tidal flats, the carbon sequestration capacity in the intertidal zone is expected to reduce by at least 13.10 Tg C/year, equivalent to 1% of global carbon emissions from land-use change.

The impacts of climate changes and human activities on net primary productivity vary across an ecotone zone in Northwest China

The variations in net primary productivity (NPP) and its controls are critical to understand the mechanisms that maintain ecosystem services under ongoing climate change and human activities. However, such knowledge is still incomplete in ecotone areas where plant species may reach their physiological thresholds. Our study quantified the variations in NPP and its controls resulting from interannual climate variations and human activities in the Qilian Mountain region (QLMR), an ecotone zone in central Asia. To achieve this goal, three indexes, including actual NPP (ANPP), potential NPP (PNPP), and human-induced NPP (HNPP), and their variations during 2001-2012 were estimated by combining the Carnegie-Ames-Stanford approach and a residual trend method. The results showed that the average PNPP, HNPP and ANPP values across the whole QLMR increased at rates of 4.71, 3.08, and 1.63 g C m^-2 yr^-1, respectively. The ANPP increased in 66.8% of the area during 2001-2012. The impacts of climate variations and human activities on NPP varied across the ecotone zone, vegetation types and altitudinal gradient. Climate-derived impacts caused the ANPP to increase in over 53% of the area in all vegetation ecosystems except forests. Climate variations were expected to account for most of the changes in ANPP in high-altitude zones (above 3500 m), while the impacts of human activities on ANPP were concentrated mainly in mid- and low-elevation zones. Our results suggest that increasing precipitation is a dominant factor underlying the increase in ANPP in such semiarid regions, while human activity is the primary reason for declines in NPP even if there is vegetation restoration. To improve the functions of vegetation ecosystems in such ecotones, a holistic strategy that combines spatially distinct measures is urgently needed.

Quantifying the Impacts of Anthropogenic Activities and Climate Variations on Vegetation Productivity Changes in China from 1985 to 2015

Accurate assessment of vegetation dynamics provides important information for ecosystem management. Anthropogenic activities and climate variations are the major factors that primarily influence vegetation ecosystems. This study investigates the spatiotemporal impacts of climate factors and human activities on vegetation productivity changes in China from 1985 to 2015. Actual net primary productivity (ANPP) is used to reflect vegetation dynamics quantitatively. Climate-induced potential net primary productivity (PNPP) is used as an indicator of climate change, whereas the difference between PNPP and ANPP is considered as an indicator of human activities (HNPP). Overall, 91% of the total vegetation cover area shows declining trends for net primary productivity (NPP), while only 9% shows increasing trends before 2000 (base period). However, after 2000 (restoration period), 78.7% of the total vegetation cover area shows increasing trends, whereas 21.3% of the area shows decreasing trends. Moreover, during the base period, the quantitative contribution of climate change to NPP restoration is 0.21 grams carbon per meter square per year (gC m−2 yr−1) and to degradation is 2.41 gC m−2 yr−1, while during the restoration period, climate change contributes 0.56 and 0.29 gC m−2 yr−1 to NPP restoration and degradation, respectively. Human activities contribute 0.36 and 0.72 gC m−2 yr−1 during the base period, and 0.63 and 0.31 gC m−2 yr−1 during the restoration period to NPP restoration and degradation, respectively. The combined effects of climate and human activities restore 0.65 and 1.11 gC m−2 yr−1, and degrade 2.01 and 0.67 gC m−2 yr−1 during the base and restoration periods, respectively. Climate factors affect vegetation cover more than human activities, while precipitation is found to be more sensitive to NPP change than temperature. Unlike the base period, NPP per unit area increases with an increase in the human footprint pressure during the restoration period. Grassland has more variability than other vegetation classes, and the grassland changes are mainly observed in Tibet, Xinjiang, and Inner Mongolia regions. The results may help policy-makers by providing necessary guidelines for the management of forest, grassland, and agricultural activities.

Associations of breeding-bird abundance with climate vary among species and trait-based groups in southern California

The responses of individuals and populations to climate change vary as functions of physiology, ecology, and plasticity. We investigated whether annual variation in seasonal temperature and precipitation was associated with relative abundances of breeding bird species at local and regional levels in southern California, USA, from 1968-2013. We tested our hypotheses that abundances were correlated positively with precipitation and negatively with temperature in this semiarid to arid region. We also examined whether responses to climate varied among groups of species with similar land-cover associations, nesting locations, and migratory patterns. We investigated relations between seasonal climate variables and the relative abundances of 41 species as estimated by the North American Breeding Bird Survey. Associations with climate variables varied among species. Results of models of species associated with arid scrublands or that nest on the ground strongly supported our hypotheses, whereas those of species associated with coniferous forests or that nest in cavities did not. Associations between climate variables and the abundances of other trait-based groups were diverse. Our results suggest that species in arid areas may be negatively affected by increased temperature and aridity, but species in nearby areas that are cooler and less arid may respond positively to those fluctuations in climate. Relations with climate variables can differ among similar species, and such knowledge may inform projections of future abundance trajectories and geographic ranges.

Grassland dynamics in responses to climate variation and human activities in China from 2000 to 2013

Improving our understanding of the impacts of climate variation and human activities on grassland dynamics is heightened by expectations that climate variation and human activities may induce grassland degradation. An accurate evaluation of the respective impacts of climate variation and human activities on grassland dynamics is crucial to understand the grassland degradation mechanism and to control the degraded grassland. In this study, net primary productivity (NPP) was selected as an indicator to reflect grassland dynamics. Meanwhile, the potential NPP (PNPP) and human-induced NPP (HNPP) calculated as the difference of PNPP and actual ANPP (ANPP) were used to assess the relative effects of climate variation and human activities on grassland NPP changes in China during 2000-2013. Results of grassland ANPP showed an overall increase than decrease in productivity (81.21% vs 18.79%) from 2000 to 2013. For the increase of ANPP, the relative contribution of climate variation and human activities to grassland NPP changes were 41.45% and 45.22%, respectively. Climate variation was the dominant factor that induced the increase in ANPP mainly in areas of Sichuan, Gansu, Ningxia and Inner Mongolia. An increase in Human-dominated ANPP mainly occurred in Tibet, Qinghai and Xinjiang. The decrease in ANPP is principally controlled by the effect of human activities than that of climate variation, especially in Inner Mongolia. Meanwhile, climate-dominated ANPP increase and human-dominated ANPP decrease mainly occurred in plain grassland, desert grassland and meadow across the six types of grasslands in China. Furthermore, in alpine sub-alpine meadow and alpine sub-alpine, while climate-dominated ANPP of grassland was found to be decreased, an increase in human-dominated ANPP was detected. The increase in precipitation and the implementation of ecological restoration programs were found to be effective in inducing the noticeable increased grassland ANPP since 2003. The findings of the current research recommend that the Chinese government should continue to implement the prohibiting graze policy across the country and extensively strengthen the implementation of the policy in Inner Mongolia and North Xinjiang, particularly in plain grassland, desert grassland and meadow.

Evaluating the responses of net primary productivity and carbon use efficiency of global grassland to climate variability along an aridity gradient

Net primary productivity (NPP) and carbon use efficiency (CUE) are common ecological indicators for assessing the terrestrial carbon cycle. However, despite their widespread use, considerable uncertainties exist toward the response patterns of NPP and CUE to climate variability along an aridity gradient, especially for grassland ecosystems. The aridity index (AI) was calculated in this study to specify arid-humid zones across the global grassland ecosystem. The dynamics of grassland NPP, CUE, and their dependence on climate under different AI levels from 2000 to 2013 were investigated. Results showed that the NPP and CUE of grasslands demonstrated a slightly increasing trend with regional increasing precipitation in most AI zones, except for arid regions (AR) from 2000 to 2013. The NPP and CUE of grasslands exhibited a remarkable spatial heterogeneity in different AI zones. High NPP values mainly occurred in the dry and sub-humid (DSH) and humid (HU) regions of Southern Hemisphere with warm and wet climate. High CUE values were mostly found in the HU of the Northern Hemisphere with cold and wet climate. In addition, low NPP and CUE values were observed in most parts of AR and semi-AR (SAR) with hot and dry climate. Overall, the NPP and CUE of grasslands were significantly affected by precipitation at the global scale. Specifically, grassland NPP was positively correlated with the mean annual precipitation (MAP) in SAR and AR, but negatively related with the MAP in the HU region. The positive correlation between NPP and mean annual temperature (MAT) was found only for HU regions. Grassland CUE indicated a positive relation with MAP, but a negative relation was observed with MAT in all AI zones. The correlation coefficients between CUE and MAP decreased from AR to HU regions. This finding indicated that grassland CUE was highly sensitive to precipitation in dry areas, but this relationship weakened in HU ecosystems.

Influence of climatic factors on variation in the Normalised Difference Vegetation Index in Mongolian Plateau grasslands

Climate change will affect how the Normalised Difference Vegetation Index (NDVI), which is correlated with climate factors, varies in space and over time. The Mongolian Plateau is an arid and semi-arid area, 64% covered by grassland, which is extremely sensitive to climate change. Its climate has shown a warming and drying trend at both annual and seasonal scales. We analysed NDVI and climate variation characteristics and the relationships between them for Mongolian Plateau grasslands from 1981 to 2013. The results showed spatial and temporal differences in the variation of NDVI. Precipitation showed the strongest correlation with NDVI (43% of plateau area correlated with total annual precipitation and 44% with total precipitation in the growing season, from May to September), followed by potential evapotranspiration (27% annual, and 30% growing season), temperature (7% annual, 16% growing season) and cloud cover (10% annual, 12% growing season). These findings confirm that moisture is the most important limiting factor for grassland vegetation growth on the Mongolian Plateau. Changes in land use help to explain variations in NDVI in 40% of the plateau, where no correlation with climate factors was found. Our results indicate that vegetation primary productivity will decrease if warming and drying trends continue but decreases will be less substantial if further warming, predicted as highly likely, is not accompanied by further drying, for which predictions are less certain. Continuing spatial and temporal variability can be expected, including as a result of land use changes.

Adams M. Empirical and model-based estimates of spatial and temporal variations in net primary productivity in semi-arid grasslands of Northern China

Spatiotemporal variations in net primary productivity (NPP) reflect the dynamics of water and carbon in the biosphere, and are often closely related to temperature and precipitation. We used the ecosystem model known as the Carnegie-Ames-Stanford Approach (CASA) to estimate NPP of semiarid grassland in northern China counties between 2001 and 2013. Model estimates were strongly linearly correlated with observed values from different counties (slope = 0.76 (p < 0.001), intercept = 34.7 (p < 0.01), R² = 0.67, RMSE = 35 g C·m^-2·year^-1, bias = -0.11 g C·m^-2·year^-1). We also quantified inter-annual changes in NPP over the 13-year study period. NPP varied between 141 and 313 g C·m^-2·year^-1, with a mean of 240 g C·m^-2·year^-1. NPP increased from west to east each year, and mean precipitation in each county was significantly positively correlated with NPP—annually, and in summer and autumn. Mean precipitation was positively related to NPP in spring, but not significantly so. Annual and summer temperatures were mostly negatively correlated with NPP, but temperature was positively correlated with spring and autumn NPP. Spatial correlation and partial correlation analyses at the pixel scale confirmed precipitation is a major driver of NPP. Temperature was negatively correlated with NPP in 99% of the regions at the annual scale, but after removing the effect of precipitation, temperature was positively correlated with the NPP in 77% of the regions. Our data show that temperature effects on production depend heavily on recent precipitation. Results reported here have significant and far-reaching implications for natural resource management, given the enormous size of these grasslands and the numbers of people dependent on them.

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.

Sensitive Indicators of Zonal Stipa Species to Changing Temperature and Precipitation in Inner Mongolia Grassland, China

Climate change often induces shifts in plant functional traits. However, knowledge related to sensitivity of different functional traits and sensitive indicator representing plant growth under hydrothermal change remains unclear. Inner Mongolia grassland is predicted to be one of the terrestrial ecosystems which are most vulnerable to climate change. In this study, we analyzed the response of four zonal Stipa species (S. baicalensis, S. grandis, S. breviflora, and S. bungeana) from Inner Mongolia grassland to changing temperature (control, increased 1.5, 2, 4, and 6°C), precipitation (decreased 30 and 15%, control, increased 15 and 30%) and their combined effects via climate control chambers. The relative change of functional traits in the unit of temperature and precipitation change was regarded as sensitivity coefficient and sensitive indicators were examined by pathway analysis. We found that sensitivity of the four Stipa species to changing temperature and precipitation could be ranked as follows: S. bungeana > S. grandis > S. breviflora > S. baicalensis. In particular, changes in leaf area, specific leaf area and root/shoot ratio could account for 86% of the changes in plant biomass in the four Stipa species. Also these three measurements were more sensitive to hydrothermal changes than the other functional traits. These three functional indicators reflected the combination of plant production capacity (leaf area), adaptive strategy (root/shoot ratio), instantaneous environmental effects (specific leaf area), and cumulative environmental effects (leaf area and root/shoot ratio). Thus, leaf area, specific leaf area and root/shoot ratio were chosen as sensitive indicators in response to changing temperature and precipitation for Stipa species. These results could provide the basis for predicting the influence of climate change on Inner Mongolia grassland based on the magnitude of changes in sensitive indicators.

Impacts of weather on long-term patterns of plant richness and diversity vary with location and management

Better understanding the influence of precipitation and temperature on plant assemblages is needed to predict the effects of climate change. Many studies have examined the relationship between plant productivity and weather (primarily precipitation), but few have directly assessed the relationship between plant richness or diversity and weather despite their increased use as metrics of ecosystem condition. We focus on the grasslands of central North America, which are characterized by high temporal climatic variability. Over the next 100 years, these grasslands are predicted to experience further increased variability in growing season precipitation, as well as increased temperatures, due to global climate change. We assess the portion of interannual variability of richness and diversity explained by weather, how relationships between these metrics and weather vary among plant assemblages, and which aspects of weather best explain temporal variability. We used an information-theoretic approach to assess relationships between long-term plant richness and diversity patterns and a priori weather covariates using six data sets from four grasslands. Weather explained up to 49% and 63% of interannual variability in total plant species richness and diversity, respectively. However, richness and diversity responses to specific weather variables varied both among sites and among experimental treatments within sites. In general, we found many instances in which temperature was of equal or greater importance as precipitation, as well as evidence of the importance of lagged effects and precipitation or temperature variability. Although precipitation has been shown to be a key driver of productivity in grasslands, our results indicate that increasing temperatures alone, without substantial changes in precipitation patterns, could have measurable effects on Great Plains grassland plant assemblages and biodiversity metrics. Our results also suggest that richness and diversity will respond in unique ways to changing climate and management can affect these responses; additional research and monitoring will be essential for further understanding of these complex relationships.