Search

Climate change is one of the most important meteorological phenomena that has had a lot of impacts on different sections with different spatial scales. In recent decades, climate changes affected by various factors especially human activities have had various impacts in different sections such as melting glaciers, various flood occurrence, occurrence of different droughts and etc. UNEP aridity Index (UNEP) and Modified De-Martonne index (MDM) are two more used indices to evaluate climate conditions in various regions of the world. In this paper; 1) the temporal trend of changes in climate conditions based on UNEP and MDM indices using climatological data (from 1967 to 2017) of 16 meteorological stations using parametric and non-parametric statistical tests were evaluated 2) the accuracy of UNEP and MDM indices were compared to assess climate conditions, based on the correlation between mentioned indices and percent of annual yield loss (AYL) in rain-fed winter wheat using simple and multiple Generalizes Estimation Equation (GEE) methods (for help managers to select more suitable and more accurate index to assess climate condition). Results showed, based on UNEP and MDM indices, climate indices in 93.75% and 87.5% of stations had a decreasing trend, but decreasing trend only in 56.25% and 50% of stations were significant at 5% level (respectively). The evaluation of the accuracy of UNEP and MDM indices showed that, in all stations, |B| coefficients between calculated AYL and UNEP and MDM indices and R2 coefficients between simulated AYL using AquaCrop model and predicted AYL using simple and multiple GEE methods in UNEP aridity index were more than MDM index. So, it is recommended to use UNEP aridity index to assess the climate conditions in different regions.

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.

Fuel moisture limits the availability of fuel to wildfires in many forest areas worldwide, but the effects of climate change on moisture constraints remain largely unknown. Here we addressed how climate affects fuel moisture in pine stands from Catalonia, NE Spain, and the potential effects of increasing climate aridity on burned area in the Pyrenees, a mesic mountainous area where fire is currently rare. We first quantified variation in fuel moisture in six sites distributed across an altitudinal gradient where the long-term mean annual temperature and precipitation vary by 6-15 °C and 395-933 mm, respectively. We observed significant spatial variation in live (78-162%) and dead (10-15%) fuel moisture across sites. The pattern of variation was negatively linked (r = |0.6|-|0.9|) to increases in vapor pressure deficit (VPD) and in the Aridity Index. Using seasonal fire records over 2006-2020, we observed that summer burned area in the Mediterranean forests of Northeast Spain and Southern France was strongly dependent on VPD (r = 0.93), the major driver (and predictor) of dead fuel moisture content (DFMC) at our sites. Based on the difference between VPD thresholds associated with large wildfire seasons in the Mediterranean (3.6 kPa) and the maximum VPD observed in surrounding Pyrenean mountains (3.1 kPa), we quantified the "safety margin" for Pyrenean forests (difference between actual VPD and that associated with large wildfires) at 0.5 kPa. The effects of live fuel moisture content (LFMC) on burned area were not significant under current conditions, a situation that may change with projected increases in climate aridity. Overall, our results indicate that DFMC in currently fire-free areas in Europe, like the Pyrenees, with vast amounts of fuel in many forest stands, may reach critical dryness thresholds beyond the safety margin and experience large wildfires after only mild increases in VPD, although LFMC can modulate the response.

Ecosystems in the arid/humid transition zone (AHTZ) of northern China are highly sensitive to climate change and human activities. Accurately assessing the impact of climate change on these ecosystems is important for effectively reducing the risks faced by them under future climate change. In this study, the leaf area index during the selected growing season (LAIGS) was used as an indicator for vegetation activity. After comparison different potential indicators, the growing season temperature (TGS) was used to indicate temperature, and the growing season aridity index (AIGS), which considers the regional water budget, was used to indicate moisture rather than precipitation, which is used more commonly. Correlation analysis and residual trends were used to study the influence of climatic and non-climatic factors on vegetation activity in the AHTZ from 1982 to 2016. The results for regions where LAIGS increased significantly (0.037/10 yr, 53.58% of the study area), the regions where LAIGS dominated by non-climatic factors (18.40%) was larger than areas dominated by climatic factors (9.61%). However, most (25.57%) of the regions in the selected study area were mainly driven by both climatic and non-climatic factors. In about half (49.73%) of the climate-affected regions, significant changes in LAIGS were driven jointly by TGS and AIGS. These regions were mainly in the northern and western Loess Plateau. The regions where changes were driven mainly by AIGS, and those where changes were driven mainly by TGS, each accounted for nearly a quarter of climate-affected regions (24.87% and 25.40%, respectively). The former regions were on the western Songliao Plain, the northern North China Plain, and the northern Loess Plateau, and the latter regions were in the northern Greater Khingan Mountains, on the southern North China Plain, in the western mountains of North China, and on the southern Loess Plateau.

Latitudinal patterns of leaf stoichiometry and nutrient resorption were not consistent among published studies, likely due to confounding effects from taxonomy (e.g., plant distribution and community composition), and environment, which is also influenced by altitude and longitude. Thus, the latitudinal patterns and environmental mechanism could be best revealed by testing a given species along a latitude gradient with similar altitude and longitude. We determined nitrogen (N) and phosphorus (P) concentrations of green (leaf) and senesced leaves (litter) from eight Metasequoia glyptostroboides forests along the eastern coastline of China, with similar altitude and longitude. Leaf N, P concentrations increased along latitude, mainly driven by mean annual temperature (MAT), mean annual precipitation (MAP), annual evaporation (AE), aridity index (AI), and annual total solar radiation (ATSR); While leaf N:P ratio was stable with no latitudinal pattern. Nitrogen resorption efficiency (NRE) increased along latitude, and was also mainly influenced by MAT, MAP, AE, and AI. Phosphorus resorption efficiency (PRE) first increased and then decreased with latitude, which was impacted by soil available P. These results indicated that only climate (such as heat, water, and light) controlled the shift in leaf stoichiometry and NRE, while soil nutrient was likely responsible for the shift in PRE along eastern China. Our findings also suggested that leaf N, P stoichiometry and NRE displayed similar latitudinal patterns at regional scale when studied for a given species (this study) or multi-species (previous studies).

Satisfying the nutritional needs of a growing population whilst limiting environmental repercussions will require sustainable intensification of agriculture. We argue that intercropping, which is the simultaneous production of multiple crops on the same area of land, could play an essential role in this intensification. We carried out the first global meta-analysis on the multifaceted benefits of intercropping. The objective of this study was to determine the benefits of intercropping in terms of energetic, economic and land-sparing potential through the framework of the stress-gradient hypothesis. We expected more intercropping benefits under stressful abiotic conditions. From 126 studies that were retrieved from the scientific literature, 939 intercropping observations were considered. When compared to the same area of land that was managed in monoculture, intercrops produced 38% more gross energy (mean relative land output of 1.38) and 33% more gross incomes (mean relative land output of 1.33) on average, whilst using 23% less land (mean land equivalent ratio of 1.30). Irrigation and the aridity index in non-irrigated intercrops did not affect land equivalent ratio, thereby indicating that intercropping remains beneficial, both under stressful and non-stressful contexts concerning moisture availability. Fertilisation and intercropping patterns (rows and strips vs. mixed) did not affect land equivalent ratio. Although intercropping offers a great opportunity for intensification of existing agricultural lands, many challenges need to be tackled by experts from multiple disciplines to ensure its feasible implementation.

Forecasting drought and determining relevant data to predict drought are an important topic for decision-makers and planners. It is critical to predicting drought in the south of Fars province, an important agricultural center in Iran located in arid and semi-arid climates. The purpose of this study was to generate a drought map in 2019 using 12 parameters: altitude, aridity index, erosion, groundwater depth, land use, PET (Potential evapotranspiration), precipitation days, precipitation, slope, soil texture, soil salinity, and distance to river, and predict drought maps in 2030 and 2040 using the cellular automata (CA)-Markov model spatially. The fuzzy method was first used to homogenize the data. Next, by evaluating each parameter, the weight of each parameter was calculated using the analytic hierarchy process (AHP), and a map of drought-prone areas was generated. The results of the fuzzy-AHP method showed that the eastern and southeastern regions of the study area were prone to drought. The four most predictive parameters in causing drought, i.e., aridity index, PET, precipitation, and soil texture, were selected using the Best search method and were then chosen as the input to determine drought mapping using the fuzzy and AHP methods. Finally, the CA-Markov model was used to predict future drought maps, and the results showed that in 2030 and 2040 the drought situation in the east and south of the study area would intensify.

Water use efficiency (WUE) is an environmental factor to account for the metabolism of terrestrial ecosystems using various climate systems and vegetation types. It is estimated by the ratio of gross primary productivity (GPP) to evapotranspiration (ET), the largest carbon and water fluxes with respect to plant respiration. In this study, the WUE was calculated using GPP and ET from the community land model version 4.0 (CLM4.0), inclusive of the prognostic carbon-nitrogen model in the community earth system model (CESM). The estimated WUE in East Asia was analyzed for climate zones, land cover types, and water- and energy-limited zones, with aridity index (AI). Spatial variations from 2001 to 2015 in annual WUE gradually increased as latitude decreased, though small year-to-year differences appeared between monthly GPP and ET. Monthly WUE was lower in summer than fall because the water loss rate in summer was higher than the carbon assimilation increase. The WUE under arid conditions (AI

The elevated atmospheric carbon dioxide concentration (CO2), as a key variable linking human activities and climate change, seriously affects the watershed hydrological processes. However, whether and how atmospheric CO2 influences the watershed water-energy balance dynamics at multiple time scales have not been revealed. Based on long-term hydrometeorological data, the variation of non-stationary parameter n series in the Choudhury's equation in the mainstream of the Wei River Basin (WRB), the Jing River Basin (JRB) and Beiluo River Basin (BLRB), three typical Loess Plateau regions in China, was examined. Subsequently, the Empirical Mode Decomposition method was applied to explore the impact of CO2 on watershed water-energy balance dynamics at multiple time scales. Results indicate that (1) in the context of warming and drying condition, annual n series in the WRB displays a significantly increasing trend, while that in the JRB and BLRB presents non-significantly decreasing trends; (2) the non-stationary n series was divided into 3-, 7-, 18-, exceeding 18-year time scale oscillations and a trend residual. In the WRB and BLRB, the overall variation of n was dominated by the residual, whereas in the JRB it was dominated by the 7-year time scale oscillation; (3) the relationship between CO2 concentration and n series was significant in the WRB except for 3-year time scale. In the JRB, CO2 concentration and n series were significantly correlated on the 7- and exceeding 7-year time scales, while in the BLRB, such a significant relationship existed only on the 18- and exceeding 18-year time scales. (4) CO2-driven temperature rise and vegetation greening elevated the aridity index and evaporation ratio, thus impacting watershed water-energy balance dynamics. This study provided a deeper explanation for the possible impact of CO2 concentration on the watershed hydrological processes.

The terrestrial water balance can be represented by the ratio of evapotranspiration to precipitation, which is expressed as a function of the aridity index (ϕ) and the basin characteristics parameter (n) in the Budyko framework. Traditionally n is assumed to be a constant for a catchment, independent to the climatic variables and altered only by changes in land cover and human activities. Another conceptual framework, Climate Change Impact Hypotheses (CCUW), makes similar assumption of constant catchment efficiency for evapotranspiration. In this study, using Variation Infiltration Capacity (VIC) model experiments, we show that the basin characteristics parameter and catchment efficiency are influenced by aridity index, in contrast with the traditional assumption. We also examine the analytical derivation of a functional form of Budyko equation and show that the assumption of n being independent of the climate variables is not valid. Hydrologic simulations with VIC show that the influence of seasonal change in vegetation (in the form of Leaf Area Index) on n is negligible compared to that of aridity, but the intra-seasonal rainfall variability does have impacts. We demonstrate these with a case study on impact of 1.5 °C and 2 °C global warming scenarios on the terrestrial water cycle in the Ganga river basin, one of the large river basins of South Asia with multiple sub-basins. Our findings imply that, with these assumptions, classical conceptual frameworks cannot fully explain the hydrometeorological impacts of climate change. These results highlight the importance of model evaluation and assessment of model assumptions before regional impact assessment studies.

Biocrusts are common biotic components in dryland ecosystems worldwide, they contain diverse soil organisms and effectively enhance soil stability and perform a series of key ecological functions. However, the geographical pattern of microbial communities in biocrusts is rarely assessed, despite it is closely related to the spatial variation of ecosystem functions in drylands. We assessed soil bacterial communities in biocrusts across four ecosystems (Gobi, desert, desert steppe and grassland) in a precipitation gradient (16–566 mm yr−1) in northern China. Bacterial OTU number and phylogenetic diversity did not linearly increase with decreasing aridity, they were significantly lower in Gobi and similar among desert, desert steppe and grassland. Soil bacterial community composition in Gobi and desert were different than those in desert steppe and grassland, and they were similar between Gobi and desert, this suggests the key role of habitat in structuring soil bacterial communities. The geographic pattern of soil bacterial communities was strongly influenced by both geographic distance and environmental factors. The first explanatory factor for the geographic variation of bacterial community dissimilarity differed among four ecosystems, being aridity in Gobi and desert, precipitation in desert steppe, and soil inorganic nitrogen in grassland. The geographic pattern of the bacterial functional group profile showed a similar pattern with community composition across four ecosystems, and the groups of containing mobile elements and gram negative bacteria were more abundant in drier habitats of Gobi and desert. Our results reveal the non-linear changes in diversity, composition and functional group of soil bacterial communities in biocrusts across the precipitation gradient from hyper-arid to semi-humid regions, and suggest that the geographic distance and habitat-specific environmental factors determine the distribution of soil bacterial communities in different ecosystems.

The hydrogen isotopic composition of leaf wax-derived n-alkanes (δ2Hn-alkanes) is a widely applied proxy for (paleo)climatic changes. It has been suggested that the coupling with the oxygen isotopic composition of hemicellulose-derived sugars (δ18Osugar) - an approach dubbed 'paleohygrometer' - might allow more robust and quantitative (paleo)hydrological reconstructions. However, the paleohygrometer remains to be evaluated and tested regionally. In this study, topsoil samples from South Africa, covering extensive environmental gradients, are analysed. δ2Hn-alkanes correlates significantly with the isotopic composition of precipitation (δ2Hp), whereas no significant correlation exists between δ18Osugar and δ18Op. The apparent fractionation (eapp) is the difference between δ2Hn-alkanes and δ2Hp (eapp 2H) and δ18Osugar and δ18Op (eapp 18O), respectively, and integrates i) isotopic enrichment due to soil water evaporation, ii) leaf (and xylem) water transpiration and iii) biosynthetic fractionation. We find no correlation of eapp 18O nor for eapp 2H with temperature, and no correlation of eapp 2H with potential evapotranspiration and an aridity index. By contrast, eapp 18O correlates significantly with both potential evapotranspiration and the aridity index. This highlights the strong effect of evapotranspirative enrichment on δ18Osugar. In study areas without plant predominance using Crassulacean Acid Metabolism (CAM), coupling δ18Osugar and δ2Hn-alkanes enables to reconstruct δ2Hp and δ18Op with an offset of Δδ2H = 6 ± 27‰ and Δδ18O = 0.8 ± 3.7‰, respectively, as well as relative humidity (RH) with an offset of ΔRH = 6 ± 17%. The paleohygrometer does, however, not work well for our study areas where CAM plants prevail (reconstructed δ18Op, δ2Hp and RH are off by 3.1‰, 27.2‰ and 31.7%). This probably reflects plant-specific (phenological) adaptations and/or post-photosynthetic exchange reactions related to CAM metabolism. Overall, our findings corroborate that δ2Hn-alkanes and δ18Osugar are valuable proxies, and the paleohygrometer is a promising approach for paleoclimate reconstructions in southern Africa.

The Budyko parameter, which controls the shape of Budyko curve, represents the superimposed impact of various periodic factors (including climatic factors, catchment characteristics, large-scale climate patterns, solar activity and anthropogenic activity) on the watershed water-energy balance dynamics. However, this superimposition is not conducive to identifying the drivers of Budyko parameter dynamics at different time scales, and thus affects parameter estimation. Here we obtain the Budyko parameter ω in the Fu’s equation (one form of the Budyko framework) for the Wei River Basin (WRB), and then adopt the Empirical Mode Decomposition method to reveal the relationships between factors and ω series at multiple time scales by considering the interplay among different influencing factors. Results indicate that (1) ω series are decomposed into 4-, 12-, 20-, exceeding 20-year time scale oscillations and a residual component with an significantly increasing trend in the mainstream of the WRB, a non-significantly decreasing trend in the Jing River Basin and Beiluo River Basin; (2) by analyzing the residual trend component, evaporation ratio, soil moisture and effective irrigated area are found to induce the significant increase of ω in the upstream of the WRB, whereas that in the middle and lower reaches is dominated by baseflow and Nino 3.4; (3) ω dynamics at the 4-year time scale is dominated by evaporation ratio, aridity index, baseflow and soil moisture; baseflow, Pacific Decadal Oscillation (PDO) and sunspots attribute to the dynamics at 12-year time scale; all the factors except baseflow and soil moisture contribute to the dynamics at 20- or exceeding 20-year time scales. The results of this study will help identify the connection between watershed water-energy balance dynamics and changing environment at multiple time scales, and also be beneficial for guiding water resources management and ecological development planning on the Loess Plateau.

Revegetation and afforestation across drylands for establishing sustainable ecosystems requires a comprehensive understanding of the carrying capacity for vegetation (CCV) at the regional scale. To determine the CCV across drylands in northern China, we developed a technical framework based on two measures of leaf area index (LAI): maximum LAI (Max-LAI) and safe LAI (Safe-LAI), and their thresholds, CCVmax and CCVsafe, for six drylands (Horqin, Hulun Buir, Otindag, Mu Us, Tengger, and Junggar) using remote sensing datasets from 2000 to 2014. We also predicted dynamics of CCV of the drylands over the next decade (2015–2024) by establishing optimal prediction models based on environmental factors (temperature, precipitation, potential evapotranspiration, and elevation). According to these models, the Max-LAI threshold (range: 0.36–1.03 m2/m2) and Safe-LAI threshold (0.29–0.70 m2/m2) declined from east to west with decreases in aridity index. Under current climatic variability and anthropogenic disturbances, the CCV in most drylands would have positive increments (approximately 15%), except in the Horqin (approximately −15%) and Tengger (slight changes), during the following decade. This indicates that there is scope for improving vegetation coverage in most drylands, except in the Horqin and Tengger. Our results suggest that revegetation and ecosystem management to prevent ongoing desertification should be carried out at the regional scale. Although it does not account for biocrusts, artificially introduced vegetation, underground water, and other vegetation attributes (e.g., density and biomass), our technical framework and results might nonetheless be valuable in evaluating regional ecological security and guiding vegetation restoration of drylands across northern China.