Net primary production (NPP) is an indicator of rangeland ecosystem function. This research assessed the potential of the Carnegie Ames Stanford Approach (CASA) model for estimating NPP and its spatial and temporal changes in semi-arid rangelands of Semirom County, Iran. Using CASA model, we estimated the NPP values based on monthly climate data and the normalized difference vegetation index (NDVI) obtained from the MODIS sensor. Regression analysis was then applied to compare the estimated production data with observed production data. The spatial and temporal changes in NPP and light utilization efficiency (LUE) were investigated in different rangeland vegetation types. The standardized precipitation index (SPI) was also calculated at different time scales and the correlation of SPI with NPP changes was determined. The results indicated that the estimated NPP values varied from 0.00 to 74.48 g C/(m²?a). The observed and estimated NPP values had different correlations, depending on rangeland conditions and vegetation types. The highest and lowest correlations were respectively observed in Astragalus spp.-Agropyronspp. rangeland (R²=0.75) with good condition and Gundeliaspp.-Cousiniaspp. rangeland (R²=0.36) with poor and very poor conditions. The maximum and minimum LUE values were found in Astragalus spp.-Agropyronspp. rangeland (0.117 g C/MJ) with good condition and annual grasses-annual forbs rangeland (0.010 g C/MJ), respectively. According to the correlations between SPI and NPP changes, the effects of drought periods on NPP depended on vegetation types and rangeland conditions. Annual plants had the highest drought sensitivity while shrubs exhibited the lowest drought sensitivity. The positive effects of wet periods on NPP were less evident in degraded areas where the destructive effects of drought were more prominent. Therefore, determining vegetation types and rangeland conditions is essential in NPP estimation. The findings of this study confirmed the potential of the CASA for estimating rangeland production. Therefore, the model output maps can be used to evaluate, monitor and optimize rangeland management in semi-arid rangelands of Iran where MODIS NPP products are not available.

Remote sensing tools are becoming increasingly important for providing spatial information on water use by different ecosystems. Despite significant advances in remote sensing based evapotranspiration (ET) models in recent years, important information gaps still exist on the accuracy of the models particularly in arid and semi-arid environments. In this study, we evaluated the Penman-Monteith based MOD16 and the modified Priestley-Taylor (PT-JPL) models at the daily time step against three measured ET datasets. We used data from two summer and one winter rainfall sites in South Africa. One site was dominated by native broad leaf and the other by fine leafed deciduous savanna tree species and C₄ grasses. The third site was in the winter rainfall Cape region and had shrubby fynbos vegetation. Actual ET was measured using open-path eddy covariance systems at the summer rainfall sites while a surface energy balance system utilizing the large aperture boundary layer scintillometer was used in the Cape. Model performance varied between sites and between years with the worst estimates (R²<0.50 and RMSE>0.80 mm/d) observed during years with prolonged mid-summer dry spells in the summer rainfall areas. Sensitivity tests on MOD16 showed that the leaf area index, surface conductance and radiation budget parameters had the largest effect on simulated ET. MOD16 ET predictions were improved by: (1) reformulating the emissivity expressions in the net radiation equation; (2) incorporating representative surface conductance values; and (3) including a soil moisture stress function in the transpiration sub-model. Implementing these changes increased the accuracy of MOD16 daily ET predictions at all sites. However, similar adjustments to the PT-JPL model yielded minimal improvements. We conclude that the MOD16 ET model has the potential to accurately predict water use in arid environments provided soil water stress and accurate biome-specific parameters are incorporated.

Low-carbon economic development is a strategy that is emerging in response to global climate change. Being the third-largest energy base in the world, Central Asia should adopt rational and efficient energy utilization to achieve the sustainable economic development. In this study, the logarithmic mean Divisia index (LMDI) decomposition method was used to explore the influence factors of CO₂ emissions in Central Asia (including Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan and Turkmenistan) during the period 1992-2014. Moreover, decoupling elasticity and decoupling index based on the LMDI decomposition results were employed to explore the relationship between economic growth and CO₂ emissions during the study period. Our results show that the total CO₂ emissions decreased during the period 1992-1998, influenced by the collapse of the Soviet Union in 1991 and the subsequent financial crisis. After 1998, the total CO₂ emissions started to increase slowly along with the economic growth after the market economic reform. Energy-related CO₂ emissions increased in Central Asia, mainly driven by economic activity effect and population effect, while energy intensity effect and energy carbon structure effect were the primary factors inhibiting CO₂ emissions. The contribution percentages of these four factors (economic activity effect, population effect, energy intensity effect and energy carbon structure effect) to the total CO₂ emissions were 11.80%, 39.08%, -44.82% and -4.32%, respectively, during the study period. Kazakhstan, Uzbekistan and Turkmenistan released great quantities of CO₂ with the annual average emissions of 189.69×10⁶, 45.55×10⁶ and 115.38×10⁶ t, respectively. In fact, their economic developments depended on high-carbon energies. The decoupling indices clarified the relationship between CO₂ emissions and economic growth, highlighting the occurrence of a ''weak decoupling'' between these two variables in Central Asia. In conclusion, our results indicate that CO₂ emissions are still not completely decoupled from economic growth in Central Asia. Based on these results, we suggest four key policy suggestions in this paper to help Central Asia to reduce CO₂ emissions and build a resource-conserving and environment-friendly society.

Riverine sand dunes develop as a result of fluvial-aeolian interactions. The primarily barchan dune chains along the Xiangshui River (a branch of the Xar Moron River in the western part of the Horqin Sandy Land of China) form a typical riverine dune field. We collected a series of samples from the riverine sand dunes parallel to the direction of the prevailing wind and investigated the sand sources and formation mechanisms of these dunes by determining the grain size, heavy mineral content and optically stimulated luminescence (OSL) of the samples. The sand of the near-river dunes was coarser than the sand of the dunes distant from the river, indicating that coarse sand of the valley mainly deposited on near-river dunes. The heavy mineral analysis suggested that wind-sand activity levels were intense on the upwind dunes, but relatively weak on the downwind dunes. This indicated that the sand sources for the near-river dunes were more abundant than those of the distant dunes. Our OSL analysis of samples suggested that the deposition rates on dunes near the river were greater than the deposition rates on dunes distant from the river. The development of dunes along the river indicated that the river played an important role in dune formation and development. In addition, airflow fluctuation and the formation of the waveform dunes had a type of feedback relationship. Grain size, heavy mineral and OSL analyses are widely used methods in wind-sand research. Sand dune grain size characteristics reflect the effects of airflow on the transport and separation of sand materials, as well as the physical characteristics of the sand sources. Heavy mineral characteristics are often used to investigate the relationships between sediments and sand sources. OSL indicates dune age, revealing formation of dunes. Therefore, it is useful to explore dune sand sources, as well as the mechanisms underlying dune formation, by determining grain size, heavy mineral content and OSL. This study investigated the sand sources of riverine dunes and provided new information about riverine dune formation and development.

Mountain glaciers are highly sensitive to climate change. In this paper, we systematically analyzed and discussed the responses of glaciers to climate change during 1960-2017 in western China by the methods of least squares and correlation analysis. Results show that the maximum temperature, minimum temperature, average temperature, and precipitation significantly increased in western China at the rates of 0.32°C/10a, 0.48°C/10a, 0.39°C/10a, and 11.20 mm/10a, respectively. However, the wind speed, hours of sunshine, snowfall, and snowy days displayed decreasing trends at the rates of -0.53 m/(s?10a), 3.72 h/10a, -2.90 mm/10a, and -0.10 d/10a, respectively. The annual percentage of glacier area decreased by approximately 0.42%, and the average glacier area decreased by 2.76 km²/a. Meanwhile, glacial shrinkages were greater in the Altay Mountains, Tanggula Mountains, and Qilian Mountains than in the other mountainous regions. Glacier accumulation decreased while melt volume increased at a rate of 2.7×10⁴ m³/a. The area of melt volume was 1.3 times that of the glacier accumulation area. The glacier mass balance (GMB) decreased substantially at a rate of -14.0 mm/a, whereas the equilibrium line altitude (ELA) showed an increasing trend at a rate of 0.5 mm/a. After 1997, the mass was smaller than -500.0 mm, indicating a huge loss in glaciers. Furthermore, relationships between ELA and GMB and various climatic factors were established. Temperature and precipitation demonstrated a significantly negative correlation, whereas wind speed and snowy days had significantly positive correlations with GMB. Snowy days also exhibited a remarkably negative correlation with ELA. The strong warming trend and less snowy days were thought to be the main factors leading to glacial melting, whereas the increase in precipitation, and reductions of sunshine hours and wind speed might slow glacial melting.

Natural soil-forming factors such as landforms, parent materials or biota lead to high variability in soil properties. However, there is not enough research quantifying which environmental factor(s) can be the most relevant to predicting soil properties at the catchment scale in semi-arid areas. Thus, this research aims to investigate the ability of multivariate statistical analyses to distinguish which soil properties follow a clear spatial pattern conditioned by specific environmental characteristics in a semi-arid region of Iran. To achieve this goal, we digitized parent materials and landforms by recent orthophotography. Also, we extracted ten topographical attributes and five remote sensing variables from a digital elevation model (DEM) and the Landsat Enhanced Thematic Mapper (ETM), respectively. These factors were contrasted for 334 soil samples (depth of 0-30 cm). Cluster analysis and soil maps reveal that Cluster 1 comprises of limestones, massive limestones and mixed deposits of conglomerates with low soil organic carbon (SOC) and clay contents, and Cluster 2 is composed of soils that originated from quaternary and early quaternary parent materials such as terraces, alluvial fans, lake deposits, and marls or conglomerates that register the highest SOC content and the lowest sand and silt contents. Further, it is confirmed that soils with the highest SOC and clay contents are located in wetlands, lagoons, alluvial fans and piedmonts, while soils with the lowest SOC and clay contents are located in dissected alluvial fans, eroded hills, rock outcrops and steep hills. The results of principal component analysis using the remote sensing data and topographical attributes identify five main components, which explain 73.3% of the total variability of soil properties. Environmental factors such as hillslope morphology and all of the remote sensing variables can largely explain SOC variability, but no significant correlation is found for soil texture and calcium carbonate equivalent contents. Therefore, we conclude that SOC can be considered as the best-predicted soil property in semi-arid regions.

Soil tillage and straw retention in dryland areas may affect the soil aggregates and the distribution of total organic carbon. The aims of this study were to establish how different tillage and straw retention practices affect the soil aggregates and soil organic carbon (SOC) and total nitrogen (TN) contents in the aggregate fractions based on a long-term (approximately 15 years) field experimentin the semi-arid western Loess Plateau, northwestern China. The experiment included four soil treatments, i.e., conventional tillage with straw removed (T), conventional tillage with straw incorporated (TS), no tillage with straw removed (NT) and no tillage with straw retention (NTS), which were arranged in a complete randomized block design. The wet-sieving method was used to separate four size fractions of aggregates, namely, large macroaggregates (LA, >2000 μm), small macroaggregates (SA, 250-2000 μm), microaggregates (MA, 53-250 μm), and silt and clay (SC, <53 μm). Compared to the conventional tillage practices (including T and TS treatments), the percentages of the macroaggregate fractions (LA and SA) under the conservation tillage practices (including NT and NTS treatments) were increased by 41.2%-56.6%, with the NTS treatment having the greatest effect. For soil layers of 0-5, 5-10 and 10-30 cm, values of the mean weight diameter (MWD) under the TS and NTS treatments were 10.68%, 13.83% and 17.65%, respectively. They were 18.45%, 19.15% and 14.12% higher than those under the T treatment, respectively. The maximum contents of the aggregate-associated SOC and TN were detected in the SA fraction, with the greatest effect being observed for the NTS treatment. The SOC and TN contents were significantly higher under the NTS and TS treatments than under the T treatment. Also, the increases in SOC and TN levels were much higher in the straw-retention plots than in the straw-removed plots. The macroaggregates (including LA and SA fractions) were the major pools for SOC and TN, regardless of tillage practices, storing 3.25-6.81 g C/kg soil and 0.34-0.62 g N/kg soil. Based on the above results, we recommend the NTS treatment as the best option to boost soil aggregates and to reinforce carbon and nitrogen sequestration in soils in the semi-arid western Loess Plateau of northwestern China.

Desert mosses, which are important stabilizers in desert ecosystems, are distributed patchily under and between shrubs. Mosses differ from vascular plants in the ways they take up nutrients. Clarifying their distribution with ecological stoichiometry may be useful in explaining their mechanisms of living in different microhabitats. In this study, Syntrichia caninervis, the dominant moss species of moss crusts in the Gurbantunggut Desert, China, was selected to examine the study of stoichiometric characteristics in three microhabitats (under living shrubs, under dead shrubs and in exposed ground). The stoichiometry and enzyme activity of rhizosphere soil were analyzed. The plant function in the above-ground and below-ground parts of S. caninervis is significantly different, so the stoichiometry of the above-ground and below-ground parts might also be different. Results showed that carbon (C), nitrogen (N) and phosphorus (P) contents in the below-ground parts of S. caninervis were significantly lower than those in the above-ground parts. The highest N and P contents of the two parts were found under living shrubs and the lowest under dead shrubs. The C contents of the two parts did not differ significantly among the three microhabitats. In contrast, the ratios of C:N and C:P in the below-ground parts were higher than those in the above-ground parts in all microhabitats, with significant differences in the microhabitats of exposed ground and under living shrubs. There was an increasing trend in soil organic carbon (SOC), soil total nitrogen (STN), soil available phosphorous (SAP), and C:P and N:P ratios from exposed ground to under living shrubs and to under dead shrubs. No significant differences were found in soil total phosphorous (STP) and soil available nitrogen (SAN), or in ratios of C:N and SAN:SAP. Higher soil urease (SUE) and soil nitrate reductase (SNR) activities were found in soil under dead shrubs, while higher soil sucrase (STC) and soil β-glucosidase (SBG) activities were respectively found in exposed ground and under living shrubs. Soil alkaline phosphatase (AKP) activity reached its lowest value under dead shrubs, and there was no significant difference between the microhabitats of exposed ground and under living shrubs. Results indicated that the photosynthesis-related C of S. caninervis remained stable under the three microhabitats while N and P were mediated by the microhabitats. The growth strategy of S. caninervis varied in different microhabitats because of the different energy cycles and nutrient balances. The changes of stoichiometry in soil were not mirrored in the moss. We conclude that microhabitat could change the growth strategy of moss and nutrients cycling of moss patches.

The community assembly rules and species coexistence have always been interested by ecologists.The community phylogenetic structure is the consequence of the interaction process between the organisms and the abiotic environmentand has been used to explain the relative impactof abiotic and biotic factors on species co-existence. In recent years, grassland degradation and biodiversity loss have become increasingly severe on the Mongolian Plateau,while the drivers for these changes are not clearly explored, especially whether climate change is a main factor is debated in academia. In this study, we examined the phylogenetic structure of grassland communities along five transects of climate aridity on the Mongolian Plateau, and analyzed their relations with environmental factors, with the aims to understand theformation mechanismof the grasslandcommunities and the role of climatic factors.We surveyed grassland communities at 81 sites along the five transects,and calculated theirnet relatedness index (NRI)attwo different quadratscales (smallscale of 1 m² and largescale of 5 m²) to characterize thecommunity phylogenetic structure andanalyzeitsrelationship withthe key 11 environmental factors. We also calculatedthe generalized UniFrac distance (GUniFrac)among the grassland communities to quantify the influence of spatial distance and environmental distance on the phylogenetic β diversity. The results indicated that plant community survey using the largescalequadrat contained sufficient species to represent community compositions. The community phylogenetic structure of grasslandswas significantly overdispersed at both the small and largescales, and the degree of overdispersion was greater at the large scalethan at the smallscale, suggesting that competitive exclusion instead of habitat filtering played a major role in determination of community composition. Altitude was the main factor affecting the community phylogenetic structure, whereas climatic factors, such as precipitation and temperature, had limited influence. Theprincipal component analysis of the 11 environmental factorsrevealed that 94.04% of their variation was accounted by the first four principal components.Moreover only 14.29% and 23.26% of the variation in community phylogenetic structurewere explained by the first four principal componentsat the small and largescales, respectively. Phylogenetic β diversity was slightly significantly correlated with both spatial distance and environmental distance, however,environmental distancehada less explanatory powerthan spatial distance, indicating a limited environmental effect on the community phylogenetic structure of grasslands on the Mongolian Plateau. In view of the limited effect of climatic factors on the community phylogenetic structure of grasslands, climate change may have a smaller impact on grassland degradation than previously thought.

Boreal forests are important carbon sinks and have tremendous potential to mitigate climate change. Aboveground biomass of Siberian larch (Larix sibirica Ledeb.) stands in the Altay Mountains, Northwest China was studied and allometric equations that are related to the biomass of aboveground components using diameter at breast height (DBH) or both DBH and height (H) as independent variables for L. sibirica trees were derived in this paper. A linear simultaneous equation system by using either DBH or both DBH and H (DBH&H) indices, was used to ensure additivity of the biomass of individual tree components, and was fitted for L. sibirica. Model performance was validated using the jackknifing test. Results indicate that the goodness-of-fit for the regressions was lowest for the needles (R² ranging from 0.696 to 0.756), and highest for the stem wood (R² ranging from 0.984 to 0.997) and the aggregated biomass components (R² ranging from 0.994 to 0.995). The coefficient of determination for each component was only marginally improved in terms of model fit and performance in the biomass equations that used DBH&H as the independent variables compared to that used DBH as the independent variable, and needles yielded an even worse fit. Stem biomass accounted for the largest proportion (87%) of the aboveground biomass. Based on the additive equations that used DBH as the single predicitor in this study, the mean aboveground carbon stock density and the carbon storage values of L. sibirica forests were 74.07 Mg C/hm² and 30.69 Tg C, respectively, in the Altay Mountains. Empirical comparisons of published equations for the same species growing in the Altay Mountains of Mongolia were also presented. The mean aboveground carbon stock density estimated for L. sibirica forests was higher in the Chinese Altay Mountains than in the Mongolian Altay Mountains (66.00 Mg C/hm²).

The water deficit in arid and semi-arid regions is the primary limiting factor for the development of urban greenery and forestation. In addition, planting the species that consume low levels of water is useful in arid and semi-arid regions that have poor water management measures. Leaf water potential (Ψ) is a physiological parameter that can be used to identify drought resistance in various species. Indeed, Ψ is one of the most important properties of a plant that can be measured using a pressure chamber. Drought avoiding or drought resistant species have a lower Ψ than plants that use normal or high levels of water. To determine drought resistance of species that are suitable for afforestation in arid urban regions, we evaluated twenty woody species in the Isfahan City, central Iran. The experimental design was random split-split plots with five replications. The species were planted outdoor in plastic pots and then subjected to treatments that consisted of two soil types and five drip irrigation regimes. To evaluate the resistance of each species to drought, we used the Ψ and the number of survived plants to obtain the drought resistance index (DRI). Then, cluster analysis, dendrogram, and similarity index were used to group the species using DRI. Result indicates that the evaluated species were classified into five groups: (1) high water consuming species (DRI>-60 MPa); (2) above normal water consuming species (-60 MPa≥DRI>-90 MPa); (3) normal water consuming species (-90 MPa≥DRI>-120 MPa); (4) semi-drought resistant species (-120 MPa≥DRI>-150 MPa); and (5) drought resistant species (DRI≤-150 MPa). According to the DRI, Salix babylonica L., Populus alba L., and P. nigra L. are high water consuming species, Platanus orientalis L. and Albizia julibrissin Benth are normal water consuming species, and Quercus infectoria Oliv. and Olea europaea L. can be considered as drought resistant species.