Search

Resilience is the basic attribute of rural regional systems and plays an important role in promoting rural revitalization and high-quality development. Taking 109 administrative villages in Yongchang County, Hexi Corridor, China, as evaluation units, this paper constructed a comprehensive evaluation indicator system of oasis rural resilience from ecological, economic and social dimensions, which comprehensively measures the rural resilience level. We selected typical sample zones, deeply analyzed the differences of rural resilience in "desert-oasis ecotone, oasis core area, oasis-desert-steppe ecotone" and revealed the formation mechanism, and proposed the differentiated oasis rural resilience optimization governance path. The results show that: (1) The mathematical agglomeration characteristics of oasis rural resilience are significant, mainly at high and medium levels. The ecological resilience is relatively high, followed by economic resilience, and social resilience is the lowest; (2) the spatial difference of oasis rural resilience is significant, showing the spatial characteristics of decreasing from oasis core area to oasis edge area. The rural resilience level of the three transects is the oasis core area > oasis-desert-steppe ecotone > desert-oasis ecotone; (3) ecological environment is the leading condition and core factor affecting the resilience of oasis villages. In addition, it is also affected by many factors such as the market economy and government regulation. The improvement of the resilience level of oasis villages requires multiple subjects to participate in the process of rural governance and promote the sustainable development of oasis villages according to local conditions. [ABSTRACT FROM AUTHOR]

Agro-pastoral ecotone of northern China is the prominent area for agricultural production, but it is also the most typical ecological fragile area with frequent drought disasters. Taking Yulin City at Shaanxi Province in China as the case area, the paper aims to investigate the spatio-temporal changes of agricultural vulnerability to drought in China's agro-pastoral ecotone in the period 2000 to 2020. The results show that: 1) the agricultural vulnerability to drought in Yulin City has shifted from high vulnerability in the period 2000–2010 to low vulnerability in the period 2011–2020. 2) There exist obvious spatio-temporal differences of the agricultural vulnerability to drought in Yulin City during the research period. 3) Four sensitive events and 14 resilient events were identified in the research and the crops of Yulin had become more resilient to drought. Finally, the paper put forward with policy implications to make adaptive strategies of agriculture to climate change in China's agro-pastoral ecotone in the future, e.g., carrying out agricultural zoning based on agricultural production conditions, intensifying the construction of disaster prevention and relief system, and integrating with modern agricultural technology to develop new type agriculture. [ABSTRACT FROM AUTHOR]

Drought seriously endangers the development of agro‐pastoral ecotone in arid and semi‐arid regions. However, drought evolution characteristics of semi‐arid sandy grassland and its drivers are not well understood in the complex climate change context. Thus, in this paper, the revised standardized precipitation evaporation indices on one‐month (SPEI‐1) and growing‐season (SPEI‐6) scale, flash drought and dry spells (DS) were calculated as drought indicators, and the temporal variabilities and meteorological drivers of drought in Horqin Sandy Land during the growing period (April–September) from 2007 to 2021 were studied. The results showed that SPEI‐1 and SPEI‐6 exhibited negative trends and periodic change. This drought aggravation was manifested in increased grades and numbers of drought months. Flash droughts can occur every month during the growing season. And its occurrence was not only positively correlated with all drought events in frequency but also synchronized in time. The increased number of DS showed an asymmetrical shift towards 7‐day‐and‐longer DS. SPEI sensitivity to precipitation (P) was noticeably higher than to atmospheric evapotranspiration demand (AED) at both monthly and growing season scales. SPEI sensitivity to AED was modulated by P amounts, which was higher during low P period. Apart from the amounts of P and AED, their temporal variability also strongly determined how they affect the drought severity. P was also the main driver for flash drought and long DS, but AED with larger amount and higher variability is the reason for their aggravation. Our results demonstrate the complexity of drought intensification in semi‐arid sandy grasslands and highlight the important role of AED anomalies in it. [ABSTRACT FROM AUTHOR]

Chinese Farming-pastoral Ecotones (CFPE) is the largest ecologically fragile zone in China. The dynamic prediction and impact factors analysis of landscape ecological risk based on LUCC have an important significance for effectively resolving ecological and environmental risk. In this paper, CA-Markov and BRT models were used to quantitatively analyze dynamic change, evolution characteristics, and influencing factors of landscape ecological risk.The results showed that: (1) LUCC types significantly changed from 2000 to 2040, especially in the bareland regions, which decreased by 1.64 times from 2000 to 2020, mainly transferred out to grassland and farmland. (2) The overall ecological risk showed a trend of increasing first and then decreasing. The highest ecological risk regions reached an area of 192,000 km2 in 2020 and decreased by 1.78 times from 2020 to 2040, these areas showed high spatial correlation and aggregation. (3) Topographical, climate, and socioeconomic factors had certain impacts on landscape ecological risk. Elevation (24.4%) was the most important factor affecting ecological risk, followed by temperature (19.1%), precipitation (15.7%), slope (13.6%) and GDP (8.4%). The study not only proposes a novel method regarding prediction and quantitative assessment of ecological risk based on influencing factors, but also provides a more precise and specific decision-making basis for sustainable development of ecological safety and social economic in the CFPE. [ABSTRACT FROM AUTHOR]

Desertification is showing a trend of overall reversal and partial expansion in the agro-pastoral ecotone in northern China (APENC). Dune–interdune is the typical micro-topography in APENC and is the expansion area of desertification. Research on anti-desertification strategy at dune–interdune is of great significance to further anti-desertification. This paper studies the vertical differentiation of land use and ecosystem service intensities at dune–interdune in APENC. The fundamental reason of the vertical differentiation of land use and ecosystem service intensities is explored with monitoring data of soil moisture at different locations of dune–interdune. Cultivated land is mainly distributed in areas with an elevation < 241 m. Grain provisioning ecosystem service intensity (GPESI) and maize leaf provisioning ecosystem service intensity (MLPESI) show a downward trend with the increase in elevation at dune–interdune. GPESI has a tipping point at the elevation of 241 m. Forage provisioning ecosystem service intensity and sand fixation regulating ecosystem service intensity are high in areas with low or high elevations while low in the central area. Groundwater depth is the root cause for vertical differentiation of land use and ecosystem service intensities at dune–interdune. According to vertical changes of land use and ecosystem service intensities, and groundwater level, cultivated land with an elevation greater than 241 m should be stopped for cultivation to anti-desertification. The area of dune–interdune within 6 m of groundwater depth can be used as cultivated land. The conclusion has an important reference for other similar regions in the world. [ABSTRACT FROM AUTHOR]

Farming-pastoral Ecotones in China (FPEC) is one of the most fragile ecological area in China. Landscape ecological risk assessment of FPEC based on terrain gradients has important strategic significance for ensuring national ecological security and the sustainable development of social economy. Based on the 30 × 30 m land use data and DEM data of FPEC in 1980, 1990, 2000, 2010 and 2020, this paper constructs a landscape ecological risk assessment model, and uses the methods of spatial autocorrelation analysis and terrain distribution index to appraise the dynamic change law and influential factors of FPEC landscape ecological risk on various terrain gradients. The results showed that: (1) In recent 40 years, land use/land cover changes (LUCC) has significantly changed, and the farmland area has increased continuously, mainly transferred from grassland, forest and bare land, particularly the bare land converted into grassland in recent 10 years, which leads to substantial increase in grassland area. (2) The overall ecological risk of the study area showed an upward trend, and the area of highest risk regions has increased more than twice during the study period, mainly distributed in the regions of "interference of human activities in low terrain" and "change of natural high terrain environment," these regions showed a high spatial concentration. (3) Ecological risk along with terrain gradient distribution is mainly limited by climate and terrain factors, the interference of human activities and natural environment change are the main influential factors of ecological risk increase in low and high terrain, respectively. Therefore, it is necessary to adapt to local conditions, and low terrain should rationally develop and utilize natural resources to reduce the interference of unreasonable production and human activities. In order to promote the sustainable and healthy development of FPEC, the policy of closing hillsides to facilitate afforestation should be adopted in the high terrain to reduce the impact of natural environment changes. [ABSTRACT FROM AUTHOR]

The farming–pastoral ecotone in northern China is an ecologically vulnerable area with low-quality arable land, and cash crops are an important economic source for local farmers. Although local governments have introduced supportive policies, there are still several factors that hinder the implementation of the policies: there is a lack of sufficient research on the distribution of specialty crops, and the driving factors for agricultural planting structure adjustment are not yet clear. In this study, the specialty cash crop of the daylily planting industry in Yunzhou District, in the Farming–Pastoral Ecotone in northern China, was selected as the research object. Field surveys were conducted to collect sample points and village-level survey data, which were further combined with Sentinel-1 and Sentinel-2 data, and vegetation indices. Support vector machine (SVM) and random forest (RF) classifiers were utilized to identify daylilies and compare the accuracy using different combinations of input data. Furthermore, the classification results were counted by village, and spatial autocorrelation was used to analyze the spatial distribution pattern of daylilies. Finally, in conjunction with the village-level survey data, Spearman correlation analysis, multiple regression trees (MRT), and random forests were employed to explore the driving factors of daylily cultivation. The results indicate that using an RF classification tree of 300 resulted in the optimal method, as it achieved the highest accuracy for crop classification. The overall accuracy and daylily classification accuracy were 94.6% and 94.75%, respectively. Daylily distributions were mainly concentrated near the Sanggan River, urban areas, and the tourism industry. The distribution area of daylilies in each village was concentrated in 13.4–38.8 hm2. Spatial clustering showed more aggregation of low–low and high–high types. Labor force and daylily yield were identified as the most significant influencing factors. Further analysis of the different regions revealed the importance of industry support policies and technical training. This study provides data to support the distribution of specialty crops in Yunzhou District and a technical basis for adjusting agricultural planting structures. [ABSTRACT FROM AUTHOR]

The hollowing out of the rural population is one of the main reasons for declining rural areas. Studying the hollowing out of the rural population is of great significance in promoting the integrated development of urban and rural areas in the new era. This paper presents the mechanism of the rural development process and divides it into four stages: primary equilibrium, differentiation and divestment, decline or transformation, and urban-rural integration. This paper provides the spatial and temporal evolution patterns and driving factors of rural population hollowing out by analyzing spatial changes of 87 administrative villages in Yanchi County, Ningxia Province with ArcGIS. The results show that: (1) the degree of population hollowing out is unevenly distributed spatially, with highly hollowed areas mainly concentrated in the north where transportation is convenient, and the hollowed areas develop over time from point to linear along transportation routes; (2) the degree of population hollowing out is increasing, but the rate has slowed down; (3) rural population hollowing is influenced by physical geography, basic service facilities, and socio-economic, changing over time. This paper concludes that population hollowing out in rural villages is inevitable in the process of transition from a smallholder economy to modern agriculture. Hollowing out has resulted in rural land use changes, and may bring opportunities for large-scale agricultural operation and advances the development of urban-rural integration, under appropriate policy design and guidance. In the future, more attention should be paid to the new trends of return migration. • Hollowing out is inevitable in transition from smallholder economy to modern agriculture. • Hollowing out advances large-scale agriculture and urban-rural integration. • Compress the hollowing out stage cycle through policy innovation. [ABSTRACT FROM AUTHOR]

The agro-pastoral ecotone in northern China is the main production area of agriculture and animal husbandry, in which agricultural development relies entirely on groundwater. Due to the increasing water consumption of groundwater year by year, groundwater resources are becoming increasingly scarce. The substantial water demand and low germination rate in the first year are the main characteristics of alfalfa (Medicago sativa L.) yield in the agro-pastoral ecotone in northern China. Due to unscientific irrigation, water resources are seriously wasted, which restricts the development of local agriculture and animal husbandry. The study constructed the Dssat-Forages-Alfalfa model and used soil water content, leaf area index, and yield data collected with in situ observation experiments in 2022 and 2023 to calibrate and validate the parameters. The study found ARE < 10%, ENRMS < 15%, and R2 ≥ 0.85. The model simulation accuracy was acceptable. The study revealed that the water consumption at the surface soil layer (0–20 cm) was more than 6~12% and 13~31% than that at the 20–40 cm and 40–60 cm soil layers, respectively. The study showed when the irrigation quota was 30 mm, the annual yield of alfalfa (Medicago sativa L.) (7435 kg/ha) was consistent with that of the irrigation quota of 33 mm, and increased by 3.99% to 5.34% and 6.86% to 10.67% compared with that of irrigation quotas of 27 mm and 24 mm, respectively. To ensure the germination rate of alfalfa (Medicago sativa L.), it is recommended to control the initial soil water content at 0.8 θfc~1.0 θfc, with an irrigation quota of 30 mm, which was the best scheme for water-use efficiency and economic yield. The study aimed to provide technological support for the rational utilization of groundwater and the scientific improvement of alfalfa yield in the agro-pastoral ecotone in northern China. [ABSTRACT FROM AUTHOR]

Soil erosion, considered a major environmental and social problem, leads to the loss of soil nutrients and the degradation of soil structure and impacts plant growth. However, data on the effects of land use changes caused by vegetation restoration on soil nutrients and erodibility for different slope aspects are limited. This study was conducted to detect the response of soil nutrients and erodibility to slope aspect in a typical watershed in the northern agro-pastoral ecotone in China. The following indexes were used to determine the improvement in soil nutrients and erodibility through a weighted summation method: the comprehensive soil nutrient index and the comprehensive soil erodibility index. The results showed that the vegetation types with the highest comprehensive soil quality index (CSQI) values on western, northern, southern, and eastern slopes were Pinus sylvestris and Astragalus melilotoides (1.45), Caragana korshinskii and Capillipedium parviflorum (2.35), Astragalus melilotoides (4.78), and Caragana korshinskii and Lespedeza bicolor (5.00), respectively. Slope aspect had a significant effect on understory vegetation characteristics, soil nutrients, and soil erodibility. Understory vegetation and soil characteristics explained 50.86 %–74.56 % of the total variance in soil nutrients and the erodibility. Mean weight diameter and total phosphorus were the main factors that affected the CSQI for different slope aspects. Our study suggests that the combinations of species, such as C. korshinskii and L. bicolor, were the optimal selection to improve soil nutrients and soil erodibility for any slope aspect. [ABSTRACT FROM AUTHOR]

In order to accurately estimate the water consumption of a Minqin desert Haloxylon ammodendron sand fixation forest, we used thermal equilibrium stem flow measurement to monitor the stem flow dynamics of Minqin desert H. ammodendron (5, 10, 15, and 20 years old, respectively, denoted as H5, H10, H15, and H20). In this study, we chose the growth index of assimilated branches (expressed as Ab in the following text) as the scalar quantity for expansion, and then estimated the water consumption of the H. ammodendron sand fixation forest by fitting the correlation between the water consumption of single H. ammodendron plants and the surface area and dry weight of single Ab. The results showed that the growth of assimilated H. ammodendron branches and the plant's monthly water consumption were synchronized, and that the growth of Ab and water consumption were significantly higher during the fast-growth period of H. ammodendron (July) compared to during the leaf-expanding (May) and leaf-falling periods (October). After correlation analysis, it was determined that there was a linear function between the surface area and dry weight of Ab and water consumption in H. ammodendron. The simulated water consumption values (kg) of H. ammodendron sand fixation forests were greatly affected by stand density and branching configuration, and the simulated values of H. ammodendron assimilated branch growth (cm) were slightly smaller than the measured values for forests of different ages, while the simulated values of assimilated branch surface area (cm2) had a much smaller relative error (8.92%) on average. Therefore, it is feasible to use the surface area and dry weight of Ab to calculate the water consumption of H. ammodendron sand fixation forests. This can enable the reliable estimation of the water consumption of H. ammodendron forests and provide a reference for desert vegetation sand fixation afforestation and its ecological water management. [ABSTRACT FROM AUTHOR]

Context: Forest–grassland ecotones, the transitional zones between forests and grasslands, often harbor high levels of biodiversity. According to the portfolio theory, communities with such high biodiversity should exhibit high stability in ecosystem functioning. On the contrary, the theory of 'bi-stability' or 'multistability' predicts that ecosystems exhibiting multiple states or regimes (e.g. forest and grassland) are less stable. Understanding the stability of forest–grassland ecotone has broad implications for forest management and restoration. Objectives: In this study, by quantifying landscape heterogeneity and temporal invariability of regional climatic and vegetational metrics, we aimed to reveal how landscape diversity influences the stability of ecosystem functioning in the forest–grassland ecotone. Methods: We focused on the forest–grassland ecotone in northern China (i.e. from the forest belt in the Greater Khingan Mountains to the steppe grassland in Inner Mongolia) and used remote sensing data of land cover dynamics from 1992 to 2015 to analyze the landscape diversity and ecosystem dynamics at different grain sizes. To measure the temporal stability of climatic variables and vegetational dynamics, we calculated the interannual variation of temperature (T), wind speed (WS), precipitation (P), and the net primary productivity (NPP) on the grided sampling cells at different spatial scale over the same period. Results: Our results showed that landscape diversity across this forest–grassland ecotone was positively related to the stability of T and NPP, but negatively related to that of WS and P. These opposite patterns may be explained by the differential nature of ecosystem variables, namely whether they involve transporting substance across space (WS and P) or not (T and NPP). We also found that as the spatial scale increases, the diversity-stability relationships strengthened for all three climatic variables (i.e., T, P, WS). However, the stabilizing effects of landscape diversity on NPP first increased but then decreased with increasing grain size, peaking at ~ 30 km. Conclusions: Our empirical analyses demonstrate strong, but context-dependent diversity-stability relationships, shedding light on the paradox in the stability of ecosystem functioning in the ecotone. These findings also have implications for the management of landscape resources to maintain the sustainability of forest–grassland ecotones. [ABSTRACT FROM AUTHOR]

The agro-pastoral ecotone serves as an important ecological transition zone between grassland and cropland. It plays a crucial role in providing forage and maintaining the ecological security of Northern China. China has initiated many ecological restoration projects in the agro-pastoral ecotone. Separating the affecting factors of anthropogenic activities and natural factors change on grassland may help guide future ecological restoration projects. This study investigated the grassland change over the agro-pastoral ecotone in Inner Mongolia (APEI) using land use data, vegetation index, and monthly climate data, social and economic data from 2010 to 2020. Two indicators were introduced to evaluate the grassland change in quality and quantity. The average annual maximum NDVI of grassland within each sample was used as a proxy for grassland quality, and the proportion of grassland within each sample was used as a proxy for grassland quantity. The driving mechanisms of grassland quality were examined on different types of grassland. The results showed that (1) from 2010 to 2020, the quantity of grassland in APEI slightly decreased while the quality of the grassland significantly improved; (2) the change in grassland quality was jointly caused by natural factors and human activities, with 66.77% being attributed to natural factors and 33.23% to human activities. In some areas, the alteration in grassland quality was solely determined by either the impacts of natural factors or human-induced disturbances; and (3) temperature and precipitation played different roles in affecting grassland quality among different types of grassland. In some areas, anthropogenic activities, such as farmland and population, would affect grassland quality. The findings of this study would contribute to the understanding of the mechanism of ecological environmental changes in the agro-pastoral ecotone and guide the planning and implementation of future ecological restoration projects in agro-pastoral areas. [ABSTRACT FROM AUTHOR]

As part of the ecological barrier and an essential element of food security, the agro-pastoral ecotone is vital in northern China. Since soil fertility in northern China is low due to frequent surface disturbances, it is necessary to improve the properties of the soil. This study aims to examine the impact of fungal residue return on soil properties based on six treatments (CK: 0 kg/40 m2; R3: 90 kg/40 m2; R5: 150 kg/40 m2; R7: 210 kg/40 m2; R9: 270 kg/40 m2; R11: 330 kg/40 m2;) of fungal residue return concentration experimental data from 0 to 30 cm soil depth. The results showed that the effect of fungal residue returning on soil habits was greater at 0–10 cm of the surface layer. The bulk density can be reduced to 25.83% of CK, and water content can be increased up to 26.26%. Adding fungal residue to the field led to a greater increase in soil parameters (SOM and AP), and this characteristic effect continued as the return concentration increased. The number of soil bacteria and actinomycetes remained stable, and the amount of fungi was at its lowest. Compared with CK, the number of bacteria, fungi, and actinomycetes increased by 1.94 times, 1.46 times, and 1.71 times, respectively. After the residue was returned to the field, AK had the strongest correlation with other factors (p < 0.01), and microorganism and enzyme activities were strongly correlated (p < 0.01). In conclusion, this study presents a new method of resource utilization of downstream wastes in the food industry while simultaneously providing natural, pollution-free improvements to the soil, which is very beneficial to increasing crop yield. [ABSTRACT FROM AUTHOR]

The growing population and northward shifts in the center of grain production collectively contribute to the arising farmland use intensity of the farming–pastoral ecotone of Northern China (FPENC). Consequently, it poses a great threat to the vulnerable ecosystem of FPENC. Thus, farmland use intensity monitoring is a top priority to practice sustainable farming. In this study, we establish an indicator system designed to evaluate farmland use intensity in Ulanqab, located in the central part of FPENC. This system includes three single-year indicators (the degree of coupling between effective rainfall and crop water requirement (Dcrr), irrigation intensity (Iri) and crop duration (Cd)) and two multi-year indicators (the frequency of adopting the green-depressing cropping system (Gf) and rotation frequency (Rf)). We mapped five farmland use intensity indicators in Ulanqab from 2010 to 2019 using satellite imagery and other ancillary data. Then, the farmland use patterns were recognized by applying the self-organizing map algorithm. Our results suggest that the mapping results of crop types, center pivot irrigation (CPI), and irrigated areas are reasonably accurate. Iri, Cd, and Rf experienced an increase of 31 m3/hm2, 1 day, and 0.06 in Ulanqab from 2010 to 2019, respectively, while Dcrr and Gf witnessed a decrease of 0.002 and 0.004, respectively. That is, farmers are progressively inclined to higher farmland use intensity. Moreover, spatial heterogeneity analysis shows that Northern Ulanqab owned higher Dcrr, Iri, Cd, and Rf, and lower Gf than the southern part. We conclude the paper by discussing the implications of the results for areas with different farmland use intensity patterns. [ABSTRACT FROM AUTHOR]

The North China agro–pastoral zone is a large, ecologically fragile zone in the arid and semi-arid regions. Quantitative remote sensing inversion of soil organic carbon (SOC) in this region can facilitate understanding of the current status of degraded land restoration and provide data support for carbon cycling research in the region. Deep learning (DNN) for SOC inversion has been W.a hot topic over the past decade, but there have been few studies at the regional scale in the arid and semi-arid zones. In this study, a DNN model with five hidden layers and five skip connections was established using 644 spatially distributed SOC samples and Landsat 8 OLI imagery. The model was compared with the random forest algorithm in terms of generalization ability. The main conclusions were as follows: 1. The DNN algorithm can establish a high-precision SOC inversion model (R2 = 0.52, RMSE = 0.7), with 90% of errors concentrated in the range of −2.5 to 2.5 kg·C/m2; 2. the Boruta variable-screening algorithm can effectively improve the model accuracy of the random forest algorithm, but due to the DNN's better ability to mine hidden information in the data, the improvement effect on the DNN model accuracy is limited; 3. the SOC samples in arid and semi-arid areas are highly positively skewed, with a significant impact on the modeling accuracy of DNN, and conversion is required to obtain a model with better generalization ability; and 4. in arid and semi-arid regions, SOC has a weak correlation with vegetation indices but a stronger correlation with temperature, elevation, and aridity. This study established a reliable deep learning model for SOC density in a large arid and semi-arid region, providing a reference and framework for the establishment of SOC inversion models in other regions. [ABSTRACT FROM AUTHOR]

Water security in the ecotone between semi-humid and semi-arid regions (EHA) is very vulnerable and sensitive to climate change and human interferences. Urban turf irrigation is a primary consumer of urban water resources in the EHA, which places huge pressures on water security by substantial irrigated water use due to the expansion of urban turf planting. Based on a 2-year (2020–2021) turf experiment in Zhangjiakou City, a typical water-deficit city in the EHA of northern China, the water budget for turf was measured and analyzed. Furthermore, the Root Zone Water Quality Model (RZWQM2) was employed to evaluate the optimal irrigation scheme for turf. The results showed that the average volumetric water content in the 0–40 cm soil layer was maintained above 23% in 2020–2021. The evapotranspiration in growth period of turf accounted for more than 70% of the annual evapotranspiration, and the deep seepage in turf soil accounted for 49.67% and 60.28% of the total precipitation and irrigation in 2020 and 2021, respectively, during the vigorous growth period of the turf from May to September. The calibrated RZWQM2 showed a robust ability to simulate the water changes in turf. The d-values (consistency index) between the simulated and observed volumetric water contents and evapotranspiration were both greater than 0.90. In the aspects of irrigation scenarios, the T60%-12 scenario (TA-B, where A is 100%, 80%, 60% or 40% of the total irrigation amount and B is the number of irrigation events corresponding to A) was determined as the best irrigation schedule in our study area because of lower evapotranspiration, seepage and higher turf soil water storage under this irrigation scenario, also resulting from the comparison of different irrigation scenarios using the entropy-weight-TOPSIS method. In such an optimal scenario, T60%-12 irrigation treatment reduced the irrigated water requirement of turf by 40% (142.06 mm) and the seepage amount by 28.07% (39.05 mm), and had the lowest negative impacts on the turf growth. [ABSTRACT FROM AUTHOR]

A comprehensive understanding of the spatial-temporal evolution and driving forces on ecosystem services (ES) is essential for the agro-pastoral ecotone's ecological security in northern China. However, the land-use pattern (LULC) agglomeration with spatial differentiation in the pastoral and agricultural areas has been rarely concerned. Taking distinct LULC (1980–2018) in Chifeng as an example, we compared four crucial categories of ESs with InVEST. Using SEM, we further contrasted the effects of several variables on regional ES variations in pastoral-dominated (North) and agriculture-dominated (South) regions, respectively. Results revealed the conversion between forest and grassland oriented the LULC transformation in the North. In contrast, human-activitiy-oriented land tended to occupy environmentally sensitive places in the South. Similar ES variations were supplied with the North outperforming the South when soil conservation was omitted. As for the impacts of regional ES variations, the natural and LULC policies both showed positive effects, whereas the anthropogenic factors showed positive in the North, which was negative in the South. Therefore, the ecologically-maintained-dominant and ecologically-restored-dominant strategies should be separately adopted in the North and South. Our study provided appropriate regional ecological management suggestions for balancing the LULC-driven conflicts between ecological protection and regional development. [ABSTRACT FROM AUTHOR]

Identifying the spatial changes in farming–pastoral ecotone (FPE) is of utmost importance for the development of strategies for ecological protection in ecologically fragile areas. This study employed spatial autocorrelation and spatial clustering techniques to map FPE at the pixel scale using CLCD data with a spatial resolution of 30 × 30 m in the years 1985, 2000, and 2021, and then analyzed the changes of the FPE in northern China. The results showed that the FPE is mainly located at the border between the Inner Mongolia Autonomous Region and the adjacent provinces, which is along the Hu-line and the 400-mm isohyetal line. The area of the FPE was 63.94 × 104 km2, 62.90 × 104 km2, and 53.81 × 104 km2 in 1985, 2000, and 2021, respectively, accounting for 6.7%, 6.6%, 5.6% of the total land area in China. The FPE boundary moved northwestward during 1985–2021, demonstrating retreating, fragmenting, and shrinking tendencies. The decreased areas and the moving distances of the gravity center are six times and four times greater during 2000–2021 than that during 1985–2000, respectively. Moreover, the discontinuous change in FPE was mainly due to the increase in forest land, especially for the conversion of grassland to forest land. Our findings provide guidance for the construction of ecological civilization and the optimization of ecosystem structure in the farming–pastoral ecotone. [ABSTRACT FROM AUTHOR]

Vegetation phenology is a sensitive indicator of climate change, and can help understand the response of vegetation cycles to climate, which is important for understanding the impact of global climate change on terrestrial ecosystems. In this study, based on the enhanced vegetation index (EVI) time-series data, derived from the moderate-resolution imaging spectroradiometer (MODIS) data, the climate parameters were extracted using the Savitzky–Golay (S–G) filtering method to explore the spatial and temporal variation characteristics of the vegetation phenology in an agro-pasture ecotone in China, from 2000 to 2020. In addition, the response characteristics of the vegetation phenology to the climate elements (temperature and precipitation) were also analyzed. The results showed the following: (1) The start of the growing season (SOS) was widely advanced, and that was caused by climate change. The end of the growing season (EOS) was delayed, and the length of the growing season (LOS) was gradually extended with a large interannual fluctuation in the SOS and the LOS in the region; (2) the SOS showed significant negative correlations with the air temperature and precipitation. Precipitation was mainly positively correlated with the EOS, but there was no significant difference in the correlation between temperature and the EOS. In general, pre-season precipitation is the main driver of the vegetation phenology, while the influence of temperature on the phenology is less obvious; (3) in the semi-arid area and arid area, the phenology was mainly influenced by precipitation. The response of the vegetation phenology to the temperatures in different temperature zones was found to be regular, showing high spatial differences. In general, the higher the cumulus temperature, the lower the negative effect of the temperature on both the SOS and EOS. These results may provide new reference to study the non-systematic changes of the vegetation phenology in response to climate change. [ABSTRACT FROM AUTHOR]

Evaluating the impacts of land-use change (LUC) on ecosystem services (ESs) is necessary for regional sustainable development, especially for the farming–pastoral ecotone of northern China (FPENC), an ecologically sensitive and fragile region. This study aimed to assess the impacts of LUC on the ESs and provide valuable information for regional planning and management in the FPENC. To accomplish this, we assessed LUC in the FPENC from 2010 to 2020 and simulated land-use patterns in 2030 under three plausible scenarios: the business as usual scenario (BAUS), economic development scenario (EDS), and ecological protection scenario (EPS). Then, we quantified five ESs (including crop production, water yield, soil retention, water purification, and carbon storage) for 2020–2030 and analyzed the trade-offs and synergies among ESs in all scenarios. The results show that FPENC experienced expanding farming land and built-up land throughout 2010–2020. Under the BAUS and EDS from 2000 to 2030, especially EDS, the increase in farming land and built-up land will continue. As a result, crop production and water yield will increase, while soil retention, water purification, and carbon storage will decrease. In contrast, EPS will increase soil retention, water purification, and carbon storage at the cost of a decline in crop production and water yield. These results can provide effective reference information for future regional planning and management in the farming–pastoral ecotone. [ABSTRACT FROM AUTHOR]

Climate conditions can significantly alter the vegetation net primary productivity (NPP) in many of Earth's ecosystems, although specifics of NPP–climate condition interactions, especially time-lag responses on seasonal scales, remain unclear in ecologically sensitive forest–grassland ecotones. Based on the Moderate-Resolution Imaging Spectroradiometer (MODIS) and meteorological datasets, we analyzed the relationship between NPP and precipitation, temperature, and drought during the growing season (April–August), considering the time-lag effect (0–5 months) at the seasonal scale in Hulunbuir, Inner Mongolia, China from 2000 to 2018. The results revealed a delayed NPP response to precipitation and drought throughout the growing season. In April, the precipitation in the 4 months before (i.e., the winter of the previous year) explained the variation in NPP. In August, the NPP in some areas was influenced by the preceding 1~2 months of drought. The time-lag effect varied with vegetation type and soil texture at different spatial patterns. Compared to grass and crop, broadleaf forest and meadow exhibited a longer legacy of precipitation during the growing season. The length of the time-lag effects of drought on NPP increased with increasing soil clay content during the growing season. The interaction of vegetation types and soil textures can explain 37% of the change in the time-lag effect of the NPP response to PPT on spatial pattern. Our findings suggested that preceding precipitation influences vegetation growth at the early stages of growth, while preceding drought influences vegetation growth in the later stages of growth. The spatial pattern of the time lag was significantly influenced by interaction between vegetation type and soil texture factors. This study highlights the importance of considering the time-lag effects of climate conditions and underlying drivers in further improving the prediction accuracy of NPP and carbon sinks in temperate semiarid forest–grassland ecotones. [ABSTRACT FROM AUTHOR]

The 'Returning Farmland to Forest Program' (RFFP) in China has become an essential factor in land cover changes and forest transition, especially in terms of the ecological processes between two adjacent ecosystems. However, accurately delineating ecotones is still a big challenge for vegetation and landscape ecologists. Acquiring high spatial resolution imagery from a small, unmanned aircraft system (UAS) provides new opportunities for studying ecotones at a small scale. This study aims to extract forest-agriculture ecotones by RGB ultrahigh-resolution images from a small UAS and quantify the small biotopes in 3D space. To achieve these objectives, a canopy height model (CHM) is constructed based on a UAS-photogrammetric-derived point cloud, which is derived from the digital surface model (DSM) minus the digital terrain model (DTM). Afterward, according to the difference of plant community height between abandoned farmland ecosystem and forest ecosystem, the ecotones are delineated. A landscape pattern identified with ecotones and other small biotopes at the fine scale. Furthermore, we assess the accuracy of the ecotones' delineation based on the transects method with the previous situ work we carried out and quantify the landscape structure using common landscape metrics to describe its spatial and geometric characteristics. Through transect-based analysis at three transects, the overall accuracy of the width of UAS-derived delineation is greater than 70%, and the detection accuracy for the occurrence location is 100%. Finally, we conclude that ecotones extraction from UAS images would also provide the possibility to gain a comprehensive understanding of the entire ecological process of agricultural abandoned land restoration through continuous investigation and monitoring. [ABSTRACT FROM AUTHOR]

Understanding the impact of climate change on terrestrial wet and dry changes and the relationship between the two is of great significance to the sustainable development of terrestrial ecosystems. The farming-pastoral ecotone of northern China (FPENC) is an area that is sensitive to climate change, suffering from perennial drought and a clear aridification trend. Unlike previous single-factor, single-timescale studies, we identified aridification in the region based on a dataset established by remote sensing and ground-based monitoring stations from a combination of two perspectives: climate and soil. The results show that, in terms of climate, the period from 2000 to 2019 was the driest in the region during the last 120 years , and the summer drought was the most severe and shifted from a summer to spring drought; in terms of soil, the soil aridification trend in the region was severe, with 16.1% of the areas becoming significantly drier (P < 0.1) among the years and 41.6% in spring, respectively. Similar to climate change, soils exhibited recessive aridification due to the counterbalancing effect of the dry and wet seasons within the year. Then the coupling relationship between climate change and soil aridification was established in time and space. Moreover, the spatiotemporal response patterns of both were obtained. The results showed that the frequency of soil drought under meteorological drought conditions showed an increasing trend and that the sensitivity of soil drought occurrence increased. Among them, the effect of precipitation on relative soil moisture (RSM) was immediate, and the effect of prolonged warming on RSM is greater. The area of soil aridification that was caused by climatic aridification in spring accounted for 13.7% of the entire area. The regional aridification research mode proposed in this paper can provide ideas for subsequent studies. [Display omitted] • A comprehensive judgment mode of the regional aridification combining climate elements, soil moisture was established. • Over the last 20 years, the central part of the FPENC showed overall warming and wetting of the climate. • Over the last 20 years, the trend of the soil aridification in the central part of the FPENC remained severe. • The counterbalancing effect of the dry and wet seasons leads to recessive aridification. • The sensitivity of the occurrences of soil drought to the climate drought anomalies continuously became stronger. [ABSTRACT FROM AUTHOR]

Knowledge of exchanges of energy and water over terrestrial surfaces is the first step towards understand the ecohydrological mechanisms, particularly in water‐limited ecosystems in dryland environments. However, patterns of energy exchange and evapotranspiration (ET) are not well understood in the oasis‐desert ecotone, which plays an important role in protecting oases against the threat of desertification in arid regions of northwestern China. Here, the continuous measurements of surface energy fluxes were made using eddy covariance in conjunction with auxiliary measurements for 2 years (2014–2015) in an oasis‐desert ecotone mainly covered by phreatophyte shrubs Haloxylon ammodendron, Nitraria tangutorum/sphaerocarpa, and Calligonum mongolicum in arid northwestern China. Based on the collated data for 2 years, statistical analysis on a 30‐min time scale indicated that approximately 50% of daytime net radiation (Rn) in the ecotone was dissipated as H on average, and one‐third of Rn was consumed by soil heat flux (G). Only 9% of Rn was consumed for latent heat flux (λE), which peaked in summer (21% in 2014 and 16% in 2015), corresponding to the highest rainfall season. Daily mean ET was approximately 1 mm days−1 during the growing season of the shrub species. Accumulated annual ET was 195 and 181 mm in 2014 and 2015, respectively, exceeding the corresponding precipitation (P) by approximately 87 and 77 mm, indicating that groundwater may be another important source of water for ET in the ecotone aside from rainfall. Results within provide valuable insights into the mechanisms responsible for sustaining energy and water balance in the ecotone, a potentially groundwater‐dependent ecosystem. These results also offer a foremost ecohydrological implication for water and land resources management and ecotone conservation, such as avoiding heavy groundwater pumping for extensive agricultural irrigation use to sustain groundwater availability for these shrub species in the ecotone. [ABSTRACT FROM AUTHOR]

Large-scale ecological restoration (ER) projects have been implemented in northwest China in recent decades as a means to prevent desertification and improve ecosystem services. However, previous studies have demonstrated adverse impacts in the form of widespread soil water deficit caused by intensive ER activities. Understanding the role of climate change and ER efforts in vegetation dynamics and soil moisture consumption is essential for sustainable ecosystem management. Here, we used the break for additive season and trend (BFAST) method to analyse spatial patterns in the normalized difference vegetation index (NDVI) variation over the agro-pastoral ecotone of northwest China (APENC) for 2000–2015. From the combined use of generalized additive modelling (GAM) and residual-trend analysis (RESTREND), we distinguished and quantified the effects of climate and human management on vegetation and soil water dynamics. Approximately 78% of the area showed vegetation variations representing a significant change in NDVI, of which more than 68% were categorized as abrupt changes. Large areas of the abrupt change type, interrupted increase and monotonic increase in NDVI were observed before 2006, and small areas of the change type of negative reversals were observed after 2012. Anthropogenic activity was found to be the major driving factor of variation in vegetation (contribution rate of 56%) and soil moisture (contribution rate of 78%). The vegetation expansion, which was mainly related to the large number of ER programs that started in 2000, was found to increase soil moisture depletion. By comparing areas where anthropogenic activities had a high contribution rate to vegetation increase and areas where soil moisture consumption was severely increased, we identify and discuss hotspot areas of soil moisture consumption caused by the ER programs. The current methodological workflow and results represent a novel foundation to inform and support water resource management and ecological-restoration-related policy making. [ABSTRACT FROM AUTHOR]

In order to explore the spatiotemporal changes and driving factors of soil organic carbon (SOC) in the agro-pastoral ecotone of northern China, we took Aohan banner, Chifeng City, Inner Mongolia Autonomous Region as the study area, used the random forest (RF) method to predict the SOC from 1989 to 2018, and the geographic detector method (GDM) was applied to analyze quantitatively the natural and anthropogenic factors that are affecting Aohan banner. The results indicated that: (1) After adding the terrain factors, the R2 and residual predictive deviation (RPD) of the RF model increased by 1.178 and 0.39%, with root mean square errors (RMSEs) of 1.42 g/kg and 1.05 g/kg, respectively; (2) The spatial distribution of SOC was higher in the south and lower in the north; the negative growth of SOC accounted for 55.923% of the total area, showing a trend of degradation; (3) Precipitation was the main driving factor of SOC spatial variation in the typical agro-pastoral ecotone of northern China, which was also affected by temperature, elevation, soil type and soil texture (p < 0.01). (4). Anthropogenic factors (carbon input and gross domestic product (GDP)) had a greater impact on SOC than did climate factors (temperature and precipitation), making anthropogenic factors the dominant factors affecting SOC temporal variation (p < 0.01). The results of this work constitute a basis for a regional assessment of the temporal evolution of organic carbon in the soil surface, which is a key tool for monitoring the sustainable development of agropastoral ecotones. [ABSTRACT FROM AUTHOR]