The replacement of native dry forests by commercial (exotic) tree plantations could generate changes in rainfall partitioning, which further affects the water cycle. In this study, we determined (i) the rainfall partitioning into interception, throughfall and stemflow, (ii) the role of rainfall event size on rainfall partitioning, (iii) the pH of water channelized as throughfall and stemflow, and (iv) the runoff in Lithraea molleoides (a native species) and Pinus elliottii (an exotic species) stands in the dry Chaco mountain forests, central Argentina. On average, interception, throughfall and stemflow accounted for 19.3%, 79.5% and 1.2% of the gross rainfall in L. molleoides stand, and 32.6%, 66.7% and 0.7% of the gross rainfall in P. elliottii stand, respectively. Amounts of interception, throughfall and stemflow presented positive linear relationships with the increment of rainfall event size for both tree species (P<0.01 in all cases). Percentages of interception, throughfall and stemflow were all related to the increment of rainfall event size, showing different patterns. With increasing rainfall event size, interception exponentially decreased, throughfall asymptotically increased and stemflow linearly increased. Both P. elliottii and L. molleoides stands presented significant differences in the pH values of water channelized as throughfall (6.3 vs. 6.7, respectively; P<0.01) and stemflow (4.5 vs. 5.8, respectively; P<0.01). Runoff occupied only 0.3% of the gross rainfall in P. elliottii stand and was zero in L. molleoides stand. Our results showed that the native species L. molleoides presented 13.6% more water reaching the topsoil (i.e., net rainfall; net rainfall=gross rainfall-interception-runoff) than the exotic species P. elliottii. This study improves our understanding of the effects of native vegetation replacement on the local water balance in the dry forest ecosystems.

Endophytic bacteria of halophytic plants play essential roles in salt stress tolerance. Therefore, an understanding of the true nature of plant-microbe interactions under extreme conditions is essential. The current study aimed to identify cultivable endophytic bacteria associated with the roots and shoots of Seidlitzia rosmarinus Ehrenb. ex Boiss. grown in the salt-affected soil in Uzbekistan and to evaluate their plant beneficial traits related to plant growth stimulation and stress tolerance. Bacteria were isolated from the roots and the shoots of S. rosmarinus using culture-dependent techniques and identified by the 16S rRNA gene. RFLP (Restriction Fragment Length Polymorphism) analysis was conducted to eliminate similar isolates. Results showed that the isolates from the roots of S. rosmarinus belonged to the genera Rothia, Kocuria, Pseudomonas, Staphylococcus, Paenibacillus and Brevibacterium. The bacterial isolates from the shoots of S. rosmarinus belonged to the genera Staphylococcus, Rothia, Stenotrophomonas, Brevibacterium, Halomonas, Planococcus, Planomicrobium and Pseudomonas, which differed from those of the roots. Notably, Staphylococcus, Rothia and Brevibacterium were detected in both roots and shoots, indicating possible migration of some species from roots to shoots. The root-associated bacteria showed higher levels of IAA (indole-3-acetic acid) synthesis compared with those isolated from the shoots, as well as the higher production of ACC (1-aminocyclopropane-1-carboxylate) deaminase. Our findings suggest that halophytic plants are valuable sources for the selection of microbes with a potential to improve plant fitness under saline soils.

Sandy grassland in northern China is a fragile ecosystem with poor soil fertility. Exploring how plant species regulate growth and nutrient absorption under the background of nitrogen (N) deposition is crucial for the management of the sandy grassland ecosystem. We carried out a field experiment with six N levels in the Hulunbuir Sandy Land of China from 2014 to 2016 and explored the Agropyron michnoi Roshev. responses of both aboveground and belowground biomasses and carbon (C), N and phosphorus (P) concentrations in the plant tissues and soil. With increasing N addition, both aboveground and belowground biomasses and C, N and P concentrations in the plant tissues increased and exhibited a single-peak curve. C:N and C:P ratios of the plant tissues first decreased but then increased, while the trend for N:P ratio was opposite. The peak values of aboveground biomass, belowground biomass and C concentration in the plant tissues occurred at the level of 20 g N/(m²·a), while those of N and P concentrations in the plant tissues occurred at the level of 15 g N/(m²·a). The maximum growth percentages of aboveground and belowground biomasses were 324.2% and 75.9%, respectively, and the root to shoot ratio (RSR) decreased with the addition of N. N and P concentrations in the plant tissues were ranked in the order of leaves>roots>stems, while C concentration was ranked as roots>leaves>stems. The increase in N concentration in the plant tissues was the largest (from 34% to 162%), followed by the increase in P (from 10% to 33%) and C (from 8% to 24%) concentrations. The aboveground biomass was positively and linearly correlated with leaf C, N and P, and soil C and N concentrations, while the belowground biomass was positively and linearly correlated with leaf N and soil C concentrations. These results showed that the accumulation of N and P in the leaves caused the increase in the aboveground biomass, while the accumulation of leaf N resulted in the increase in the belowground biomass. N deposition can alter the allocation of C, N and P stoichiometry in the plant tissues and has a high potential for increasing plant biomass, which is conducive to the restoration of sandy grassland.

Effects of mowing on the composition and diversity of grasslands varied with climate change (e.g., precipitation and temperature). However, the interactive effects of long-term mowing and climate change on the diversity and stability of leguminous and non-leguminous species in the semi-arid grasslands are largely unknown. Here, we used in situ monitoring data from 1982 to 2011 to examine the effects of continuous mowing and climate change on the plant biomass and diversity of leguminous and non-leguminous species, and soil total nitrogen in the typical semi-arid grasslands of northern China. Results showed that the biomass and diversity of leguminous species significantly decreased with the increasing in the biomass and diversity of non-leguminous species during the 30-a period. Variations in biomass were mainly affected by the long-term mowing, while variations in diversity were mainly explained by the climate change. Moreover, the normalized change rates of diversity in leguminous species were significantly higher than those in non-leguminous species. Mowing and temperature together contributed to the diversity changes of leguminous species, with mowing accounting for 50.0% and temperature 28.0%. Temporal stability of leguminous species was substantially lower than that of non-leguminous species. Consequently, soil total nitrogen decreased in the 2000s compared with the 1980s. These findings demonstrated that leguminous species were more sensitive to the long-term mowing and climate change than non-leguminous species in the semi-arid grasslands. Thus, reseeding appropriate leguminous plants when mowing in the semi-arid grasslands may be a better strategy to improve nitrogen levels of grassland ecosystems and maintain ecosystem biodiversity.

Persian oak (Quercus brantii var. persica) is a dominant tree species of Zagros forests in a semi-arid area, western Iran. However, the capacity of biomass and carbon stocks of these forests is not well studied. We selected three types of oak, i.e., seed-originated oak, coppice oak and mixed (seed-originated and coppice) oak of Zagros forests in Dalab valley, Ilam Province, Iran to survey the capacity of biomass and carbon stocks in 2018. Thirty plots with an area of 1000 m² were systematically and randomly assigned to each type of oak. Quantitative characteristics of trees, such as diameter at breast height (DBH), height, crown diameter and the number of sprouts in each plot were measured. Then, aboveground biomass (AGB), belowground biomass (BGB), aboveground carbon stock (AGCS) and belowground carbon stock (BGCS) of each tree in plots were calculated using allometric equations. The litterfall biomass (LFB) and litterfall carbon stock (LFCS) were measured in a quadrat with 1 m×1 m in each plot. One-way analysis of variance and Duncan's test were performed to detect the differences in biomass and carbon stocks among three types of oak. Results showed that AGB, BGB and BGCS were significantly different among three types of oak. The highest values of AGB, AGCS, BGB and BGCS in seed-originated oak were 76,043.25, 14,725.55, 36,737.79 and 7362.77 kg/hm², respectively. Also, the highest values of LFB and LFCS in seed-originated oak were 3298.33 and 1520.48 kg/hm², respectively, which were significantly higher than those of the other two types of oak. The results imply the significant role of seed-originated oak for the regeneration of Zagros forests. Further conservation strategy of seed-originated oak is an important step in the sustainable management of Zagros forests in Iran.

Seed germination profoundly impacts plant community composition within the plant life cycle. Snow is an important source of water for seed germination in the temperate deserts of Central Asia. Understanding how seed germination responds to variations in snow cover in relation to seed traits and plant ecological characteristics can help predict plant community sustainability and stability in Central Asia under a scenario climate change. This study investigated the seed germination of 35 plant species common to the Gurbantunggut Desert in Central Asia under the three snow treatments: (1) snow addition; (2) ambient snow; and (3) snow removal. Two-way analysis of variance (ANOVA) tests were performed to assess interactions among the impacts of snow treatments, seed traits and plant ecological characteristics on seed germination. Phylogenetic generalized least-squares (PGLS) model was used to test the relationships between seed traits and seed germination. The results demonstrated that snow variations had no significant impacts on seed germination overall. Seed germination under the snow addition treatment was similar with that under the ambient snow treatment, irrespective of seed traits and plant ecological characteristics. Snow removal only had negative impacts on seed germination for certain groups of seed traits and plant ecological characteristics. Seed mass positively affected seed germination, showing a linear increase of arcsin square root-transformed seed germination with log-transformed seed mass. Seed shape also profoundly impacted seed germination, with a higher germination percentage for elongated and flat seeds. Seed germination differed under different plant life forms, with semi-shrub species showing a significantly higher germination percentage. Most importantly, although snow treatments, seed traits and plant ecological characteristics had no interactive effects on seed germination overall, some negative impacts from the snow removal treatment were detected when seeds were categorized on the basis of seed mass and shape. This result suggests that variations of snow cover may change plant community composition in this temperate desert due to their impacts on seed germination.

Amygdalus pedunculata Pall. is a major species that is widely planted in afforested soils with different textures in the transitional zone between Mu Us Desert and Loess Plateau, China. However, the responses of A. pedunculata to increasing intensity of water stress in different textural soils are not clear. Here, we conducted a soil column experiment to evaluate the effects of different textures (sandy and loamy) on water consumption, water use efficiency (WUE), biomass accumulation and ecological adaptability of A. pedunculata under increasing water stress, i.e., 90% (±5%) FC (field capacity), 75% (±5%) FC, 60% (±5%) FC, 45% (±5%) FC and 30% (±5%) FC in 2018. A. pedunculata grown in the sandy soil with the lowest (30% FC) and highest (90% FC) water contents had respectively 21.3%-37.0% and 4.4%-20.4% less transpiration than those with other water treatments (45%-75% FC). In contrast, A. pedunculata transpiration in the loamy soil decreased with decreasing water content. The magnitude of decrease in transpiration increased with increasing level of water deficit (45% and 30% FC). Mean daily and cumulative transpirations of the plant were significantly lower in the sandy soil than in the loamy soil under good water condition (90% FC), but the reverse was noted under water deficit treatments (45% and 30% FC). Plant height, stem diameter and total biomass initially increased with decreasing water content from 90% to 75% FC and then declined under severe water deficit conditions (45% and 30% FC) in the sandy soil. However, these plant parameters decreased with decreasing water content in the loamy soil. WUE in the sandy soil was 7.8%-12.3% higher than that in the loamy soil, which initially increased with decreasing water content from 90% to 75% FC and then declined under water deficit conditions (45% and 30% FC). The study showed that plant transpiration, biomass production and WUE responded differentially to increasing intensity of water stress in the sandy and loamy soils. The contrasting responses of A. pedunculata to water stress in different textural soils can guide future revegetation programs in the northern region of Chinese Loess Plateau by considering plant adaptability to varying soil and water conditions.

Understanding the effects of degradation on belowground biomass (BGB) is essential for assessment of carbon budget of the alpine meadow ecosystem on the Tibetan Plateau, China. This ecosystem has been undergoing serious degradation owing to climate change and anthropogenic activities. This study examined the response of the vertical distribution of plant BGB to degradation and explored the underlying mechanisms in an alpine meadow on the Tibetan Plateau. A field survey was conducted in an alpine meadow with seven sequential degrees of degradation in the Zoige Plateau on the Tibetan Plateau during the peak growing season of 2018. We measured aboveground biomass (AGB), BGB, soil water content (SWC), soil bulk density (SBD), soil compaction (SCOM), soil organic carbon (SOC), soil total nitrogen (STN), soil total phosphorus (STP), soil available nitrogen (SAN), and soil available phosphorus (STP) in the 0-30 cm soil layers. Our results show that degradation dramatically decreased the BGB in the 0-10 cm soil layer (BGB_0-10) but slightly increased the subsoil BGB. The main reason may be that the physical-chemical properties of surface soil were more sensitive to degradation than those of subsoil, as indicated by the remarked positive associations of the trade-off value of BGB_0-10 with SWC, SCOM, SOC, STN, SAN, and STP, as well as the negative correlation between the trade-off value of BGB_0-10 and SBD in the soil layer of 0-10 cm. In addition, an increase in the proportion of forbs with increasing degradation degree directly affected the BGB vertical distribution. The findings suggest that the decrease in the trade-off value of BGB_0-10 in response to degradation might be an adaptive strategy for the degradation-induced drought and infertile soil conditions. This study can provide theoretical support for assessing the effects of degradation on the carbon budget and sustainable development in the alpine meadow ecosystem on the Tibetan Plateau as well as other similar ecosystems in the world.

To combat the problem of residual film pollution and ensure the sustainable development of agriculture in oasis areas, a field experiment was carried out in 2019 at the Wuyi Farm Corps Irrigation Center Test Station in Urumqi, Northwest China. Four types of biodegradable mulches, traditional plastic mulchs and a control group (bare land; referred to as CK) were compared, including a total of six different treatments. Effects of mulching on soil water and heat conditions as well as the yield and quality of processing tomatoes under drip irrigation were examined. In addition, a comparative analysis of economic benefits of biodegradable mulches was performed. Principal component analysis and gray correlation analysis were used to evaluate suitable mulching varieties for planting processing tomatoes under drip irrigation. Our results show that, compared with CK, biodegradable mulches and traditional plastic mulch have a similar effect on retaining soil moisture at the seedling stage but significantly increase soil moisture by 0.5%-1.5% and 1.5%-3.0% in the middle and late growth periods (P<0.050), respectively. The difference in the thermal insulation effect between biodegradable mulch and plastic mulch gradually reduces as the crop grows. Compared with plastic mulch, the average soil temperature at 5-20 cm depth under biodegradable mulches is significantly lowered by 2.04°C-3.52°C and 0.52°C-0.88°C (P<0.050) at the seedling stage and the full growth period, respectively, and the water use efficiency, average fruit yield, and production-investment ratio under biodegradable mulches were reduced by 0.89%-6.63%, 3.39%-8.69%, and 0.51%-6.33% (P<0.050), respectively. The comprehensive evaluation analysis suggests that the black oxidized biological double-degradation ecological mulch made from eco-benign plastic is the optimal film type under the study condition. Therefore, from the perspective of sustainable development, biodegradable mulch is a competitive alternative to plastic mulch for large-scale tomato production under drip irrigation in the oasis.

There are eight provinces and autonomous regions (Gansu Province, Ningxia Hui Autonomous Region, Xinjiang Uygur Autonomous Region, Inner Mongolia Autonomous Region, Tibet Autonomous Region, Qinghai Province, Shanxi Province, and Shaanxi Province) in Northwest China, most areas of which are located in arid and semi-arid regions (northwest of the 400 mm precipitation line), accounting for 58.74% of the country's land area and sustaining approximately 7.84×10⁶ people. Because of drought conditions and fragile ecology, these regions cannot develop agriculture at the expense of the environment. Given the challenges of global warming, the green total factor productivity (GTFP), taking CO₂ emissions as an undesirable output, is an effective index for measuring the sustainability of agricultural development. Agricultural GTFP can be influenced by both internal production factors (labor force, machinery, land, agricultural plastic film, diesel, pesticide, and fertilizer) and external climate factors (temperature, precipitation, and sunshine duration). In this study, we used the Super-slacks-based measure (Super-SBM) model to measure agricultural GTFP during the period 2000-2016 at the regional level. Our results show that the average agricultural GTFP of most provinces and autonomous regions in arid and semi-arid regions underwent a fluctuating increase during the study period (2000-2016), and the fluctuation was caused by the production factors (input and output factors). To improve agricultural GTFP, Shaanxi, Shanxi, and Gansu should reduce agricultural labor force input; Shaanxi, Inner Mongolia, Gansu, and Shanxi should decrease machinery input; Shaanxi, Inner Mongolia, Xinjiang, and Shanxi should reduce fertilizer input; Shaanxi, Xinjiang, Gansu, and Ningxia should reduce diesel input; Xinjiang and Gansu should decrease plastic film input; and Gansu, Shanxi, and Inner Mongolia should cut pesticide input. Desirable output agricultural earnings should be increased in Qinghai and Tibet, and undesirable output (CO₂ emissions) should be reduced in Inner Mongolia, Xinjiang, Gansu, and Shaanxi. Agricultural GTFP is influenced not only by internal production factors but also by external climate factors. To determine the influence of climate factors on GTFP in these provinces and autonomous regions, we used a Geographical Detector (Geodetector) model to analyze the influence of climate factors (temperature, precipitation, and sunshine duration) and identify the relationships between different climate factors and GTFP. We found that temperature played a significant role in the spatial heterogeneity of GTFP among provinces and autonomous regions in arid and semi-arid regions. For Xinjiang, Inner Mongolia, and Tibet, a suitable average annual temperature would be in the range of 7°C-9°C; for Gansu, Shanxi, and Ningxia, it would be 11°C-13°C; and for Shaanxi, it would be 15°C-17°C. Stable climatic conditions and more efficient production are prerequisites for the development of sustainable agriculture. Hence, in the agricultural production process, reducing the redundancy of input factors is the best way to reduce CO₂ emissions and to maintain temperatures, thereby improving the agricultural GTFP. The significance of this study is that it explores the impact of both internal production factors and external climatic factors on the development of sustainable agriculture in arid and semi-arid regions, identifying an effective way forward for the arid and semi-arid regions of Northwest China.

Global warming is one of the most complicated challenges of our time causing considerable tension on our societies and on the environment. The impacts of global warming are felt unprecedentedly in a wide variety of ways from shifting weather patterns that threatens food production, to rising sea levels that deteriorates the risk of catastrophic flooding. Among all aspects related to global warming, there is a growing concern on water resource management. This field is targeted at preventing future water crisis threatening human beings. The very first stage in such management is to recognize the prospective climate parameters influencing the future water resource conditions. Numerous prediction models, methods and tools, in this case, have been developed and applied so far. In line with trend, the current study intends to compare three optimization algorithms on the platform of a multilayer perceptron (MLP) network to explore any meaningful connection between large-scale climate indices (LSCIs) and precipitation in the capital of Iran, a country which is located in an arid and semi-arid region and suffers from severe water scarcity caused by mismanagement over years and intensified by global warming. This situation has propelled a great deal of population to immigrate towards more developed cities within the country especially towards Tehran. Therefore, the current and future environmental conditions of this city especially its water supply conditions are of great importance. To tackle this complication an outlook for the future precipitation should be provided and appropriate forecasting trajectories compatible with this region's characteristics should be developed. To this end, the present study investigates three training methods namely backpropagation (BP), genetic algorithms (GAs), and particle swarm optimization (PSO) algorithms on a MLP platform. Two frameworks distinguished by their input compositions are denoted in this study: Concurrent Model Framework (CMF) and Integrated Model Framework (IMF). Through these two frameworks, 13 cases are generated: 12 cases within CMF, each of which contains all selected LSCIs in the same lead-times, and one case within IMF that is constituted from the combination of the most correlated LSCIs with Tehran precipitation in each lead-time. Following the evaluation of all model performances through related statistical tests, Taylor diagram is implemented to make comparison among the final selected models in all three optimization algorithms, the best of which is found to be MLP-PSO in IMF.

Soil erosion in the Three-River Headwaters Region (TRHR) of the Qinghai-Tibet Plateau in China has a significant impact on local economic development and ecological environment. Vegetation and precipitation are considered to be the main factors for the variation in soil erosion. However, it is a big challenge to analyze the impacts of precipitation and vegetation respectively as well as their combined effects on soil erosion from the pixel scale. To assess the influences of vegetation and precipitation on the variation of soil erosion from 2005 to 2015, we employed the Revised Universal Soil Loss Equation (RUSLE) model to evaluate soil erosion in the TRHR, and then developed a method using the Logarithmic Mean Divisia Index model (LMDI) which can exponentially decompose the influencing factors, to calculate the contribution values of the vegetation cover factor (C factor) and the rainfall erosivity factor (R factor) to the variation of soil erosion from the pixel scale. In general, soil erosion in the TRHR was alleviated from 2005 to 2015, of which about 54.95% of the area where soil erosion decreased was caused by the combined effects of the C factor and the R factor, and 41.31% was caused by the change in the R factor. There were relatively few areas with increased soil erosion modulus, of which 64.10% of the area where soil erosion increased was caused by the change in the C factor, and 23.88% was caused by the combined effects of the C factor and the R factor. Therefore, the combined effects of the C factor and the R factor were regarded as the main driving force for the decrease of soil erosion, while the C factor was the dominant factor for the increase of soil erosion. The area with decreased soil erosion caused by the C factor (12.10×10³ km²) was larger than the area with increased soil erosion caused by the C factor (8.30×10³ km²), which indicated that vegetation had a positive effect on soil erosion. This study generally put forward a new method for quantitative assessment of the impacts of the influencing factors on soil erosion, and also provided a scientific basis for the regional control of soil erosion.

The seif dune field over the gravel desert surface in the eastern margin of the Kumtagh Desert is a valuable experimental site for the observation of dune formation and dynamics. We used high-resolution remote sensing and station observation approaches, combined with wind and grain size data, to study the characteristics of the aeolian environment and the morphologies of and dynamic changes in seif dunes. We observed the ratio of the resultant drift potential (RDP) to the drift potential (DP), which was 0.37, associated with an obtuse bimodal wind regime. The drift potentials in the west-northwest (WNW) and east-northeast (ENE) directions were dominant, and the angle between the two primary DP directions was 135.00°. The dune orientations ranged from 168.75°-213.75°, which were parallel to the resultant drift direction (186.15°). The dune lengths ranged from 51.68 to 1932.11 m with a mean value of 344.91 m. The spacings of the dunes ranged from 32.34 to 319.77 m with a mean value of 93.39 m. The mean grain size of the sediments became finer, and the sorting became better from upwind tail to downwind tip, which indicated that the sediment of the seif dunes in the study region may be transported from northward to southward. The rate of increase in the length, the mean longitudinal migration rate of the dune tail, and the mean longitudinal extension rate of the dune tip (also called elongation rate) were 4.93, 4.63, and 9.55 m/a, respectively. The mean lateral migration vector of the seif dunes was approximately 0.11 m/a towards the west (-0.11 m/a), while the mean amplitude of lateral migration was 0.53 m/a, ignoring the direction of lateral migration. We found that the seif dune field formed first beside seasonal rivers, which can provide sediment, and then expanded downwind.