Evolution of Land Use Suitability and Adaptation Strategies of the Agro-Pastoral Transitional Zone in northern China under Multiple Climate Change Scenarios

Evolution of Land Use Suitability and Adaptation Strategies of the Agro-Pastoral Transitional Zone in northern China under Multiple Climate Change Scenarios | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Evolution of Land Use Suitability and Adaptation Strategies of the Agro-Pastoral Transitional Zone in northern China under Multiple Climate Change Scenarios Kaige Wang, Yan Xu, Fengrong Zhang, Zengqiang Duan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8518691/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The Agro-Pastoral Transitional Zone in northern China is the tail area of the East Asian summer monsoon, as well as the edge area of crop production. It is also a typical ecologically fragile area, and its agricultural and animal husbandry production conditions and ecological status are highly susceptible to climate change. Climate change has uncertainty in long-term processes in the future, and how it affects the suitability of agricultural and pastoral production in the Agro-Pastoral Transitional Zone constitutes a scientific issue of common concern in climate change research and regional sustainable development research. This study is divided into two parts: multi scenario simulation of climate change and evaluation of land use suitability for agriculture and animal husbandry. The first part first simulates the uncertainty of future climate change and the different paths of international response to climate change by setting low, moderate, and high emission scenarios, and then simulates the spatial distribution of annual precipitation and accumulated temperature elements in the Agro-Pastoral Transitional Zone for three years: 2030 (short-term), 2050 (medium-term), and 2100 (long-term). The second part further constructs an evaluation index system for the suitability of agricultural and animal husbandry land use based on the results of multi scenario simulations of climate change, and comprehensively analyzes the quantity structure and spatial distribution of suitability levels for agriculture and animal husbandry in different years under various scenarios. This study has found that in terms of future climate change, the low and moderate emission scenarios of the Agro-Pastoral Transitional Zone in northern China have similar trends in annual precipitation, while the high emission model has more extreme changes in annual precipitation. The spatial distribution of precipitation has always maintained an overall pattern of "more in the east and less in the west". The precipitation changes in the northern and northwestern sections of the Agro-Pastoral Transitional Zone are relatively small, while the dry and wet changes in the northern and southern parts of the northeastern sections are large; The overall distribution of accumulated temperature shows a spatial characteristic of high in the south and low in the north. The accumulated temperature changes in the low emission mode are relatively stable, while the accumulated temperature changes in the moderate and high emission modes are more extreme. The southern part of the northeast section and the eastern part of the north China section are the key areas of alternating cold and warm changes. The suitability analysis of agriculture and animal husbandry under multiple climate scenarios shows that the response to climate change varies in different regions of the Agro-Pastoral Transitional Zone in northern China. Global warming, under moderate and high emission patterns, can help improve the heat conditions in the central and eastern regions of the agro pastoral transition zone in the medium to long term, thereby enhancing the suitability of agriculture and animal husbandry. However, in the western part of the Agro-Pastoral Transitional Zone in northern China, it will further strengthen the constraints of natural conditions, especially in terms of unstable precipitation, and the suitability of land use for agriculture and animal husbandry cannot achieve long-term stable improvement. This study revealed that in the future climate change of the Agro-Pastoral Transitional Zone in northern China, the heat conditions for agricultural and pastoral production will gradually improve under medium to high emission patterns, but there is no significant trend of increase or decrease in precipitation conditions. Under moderate and high emission modes, the suitability of agricultural and pastoral land use in the central and eastern parts of the Agro-Pastoral Transitional Zone in northern China has been improved, indicating that climate warming is beneficial for enhancing the natural suitability of agricultural and pastoral production in the mid to high latitude regions of the Agro-Pastoral Transitional Zone in northern China. This study further discussed the practical path differences and feasibility between moderate and high emission modes, with moderate emission mode being an important mode path for adapting to future climate change in the Agro-Pastoral Transitional Zone. Earth and environmental sciences/Climate sciences Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences The Agro-Pastoral Transitional Zone in northern China Land use suitability Adaptation strategies Multiple Climate Change Scenarios Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Mitigating and adapting to global climate change is a major challenge currently faced by human society(UNICEF, 2014 ). However, the social ecological effects brought about by climate change vary significantly in different regions of the Earth(Abiodun et al, 2012 ). Focusing on the response of social ecological systems in key areas of the Earth to climate change has become a cutting-edge topic in current geographical research(Dale, 1997 ; Briner et al, 2012 ). The Agro-Pastoral Transitional Zone in northern China is a transitional zone between semi humid and semi-arid regions(Hu 1935 ). It is a coupled development zone between grassland animal husbandry and arable land agriculture, an important ecological security barrier in the central and eastern regions of China, and an important water source conservation zone in the north. It has a unique ecosystem and socio-economic system that is different from pastoral and agricultural areas. On the one hand, as a typical ecologically fragile and climate sensitive area, the Agro-Pastoral Transitional Zone in northern China is prone to ecological degradation due to external disturbances(Zuo et al, 2014 ; Zhao et al, 2017 ). On the other hand, its land use is constrained by climate factors and exhibits significant marginal characteristics, with distinct fluctuations in response to climate change(Erik et al., 2008; Liu, 2017 ). The future global climate change still has strong uncertainty. As an important ecological barrier area, food production area, and forage supply base, the research area will be affected by differentiated climate change, and the exploration of this scientific issue constitutes the focus of climate change and regional geography research(Wang et al., 1999 ; Pradhan et al., 2017 ; Li et al., 2018 ). The research on climate change effects and land suitability evaluation belong to different disciplinary systems. The former focuses on climate change pattern recognition, species distribution and crop yield, hydrology, carbon flow, and climate change trend simulation research, aiming to clarify the basic characteristics and possible trends of climate change(Fang 1997 ; Justin et al., 2014 ; Fan et al., 2015 ; Newbold et al., 2015 ; Peters et al., 2019 ). At the level of climate change effects, attention is paid to the perspectives of vegetation, hydrology, soil characteristics, and human social welfare(Riha et al., 1996 ; Wheeler et al., 2013; Xie et al., 2020 ). The latter focuses on comprehensive suitability evaluation of target land use, with extensive exploration in land consolidation, crop growth, and potential evaluation(Feng et al., 2014 ; Hua et al., 2015; Jin et al., 2018 ). Current academic research has conducted preliminary explorations between climate change and land suitability assessment, but often limited to regional studies similar to the Qinghai Tibet Plateau, a special natural geographic unit(Liu et al., 2003 ; Liu et al., 2007b ; Wang et al., 2013b ; Liu 2018a ). On the one hand, there is a lack of further comprehensive evaluation index system design in the coupling evaluation method, and there are problems of indicator inconsistency and different data types in the analysis process of climate change assessment models and land use suitability evaluations(Tilman et al., 2002 ; Song et al., 2018 ). Meanwhile, attention should be paid to the uncertainty of global climate change, and how to conduct comparable land use suitability evaluations in multiple scenarios has become a new methodological direction(Karina et al., 2021 ). On the other hand, in the application of research areas, it is necessary to expand to a larger scope of global ecologically fragile areas, identify global climate change sensitive areas, and take more targeted governance measures for mitigating and adapting to climate change(Garnett et al., 2013 ; Schirpke et al., 2017 ). In summary, it is urgent to explore a research path that couples climate change research with land use suitability evaluation(Ostrom 2009 ; Liu et al., 2014a ). Firstly, a basic model of climate change should be established through multi scenario simulations to address the uncertainty of climate change(Zhang et al., 2008). Secondly, it is necessary to strengthen the connection and complementarity of land suitability evaluation indicators and climate change indicators, and to adapt to the needs of short-term, medium-term, and long-term time scale analysis at the regional scale(Wang et al., 2011; Shi et al., 2016 ). To sum up, land suitability assessment needs to gradually expand the new scenarios of climate change application path, and climate change research also needs to further strengthen the connection and support with the traditional land use assessment system. This study combines traditional land use suitability evaluation with climate change simulation results, aiming to answer the scientific question of how land suitability in the Agro-Pastoral Transitional Zone of northern China will change under multiple climate change scenarios in the future. This study analyzes the suitability of agricultural and pastoral land use in the northern ecotone of China under high, moderate, and low emission scenarios based on CMIP6 climate change multi scenario prediction data. The research results can directly serve regional agricultural and animal husbandry development planning and climate resilience construction, while expanding the application scenarios of climate change simulation results, and further enriching the organizational methods and regional research connotations of land use suitability evaluation. 2. Data and Methods 2.1 Data sources The research is conducted based on a multi-source data system, involving various data such as climate, land use, soil, terrain, etc. Here, some data sources will be clarified. In the data preprocessing stage, the raster data is resampled to a spatial resolution of 1km to support comprehensive analysis. Vector data is screened for geometric topology errors and stored as a whole to support comprehensive spatial analysis. Some meteorological station data research uses Kriging interpolation for spatial interpolation processing. The data used in the research institute are all open source data with no confidentiality requirements. Their sources can be traced and downloaded, and they have standardization and scientificity, making them highly applicable to this study. Table.1 Research basic data connotation and source Data name Data content Precision Data sources Data purpose Global land cover/use data Global land cover/use database for the years 2000, 2005, 2010, 2015, and 2020 Spatial resolution 30 meter raster data https://storage.googleapis.com/earthenginepartners-hansen/GLCLU2000-2020/v2/download.html Identification of agro-pastoral ecotone and analysis of land use evolution characteristics Basic data of climate elements Global annual average temperature and precipitation spatial distribution database, china land annual precipitation frequency distribution parameter dataset, china meteorological element average status spatial interpolation dataset (annual precipitation, annual evaporation, annual average temperature) from 1960 to 2020, global coupled model comparison project (CMIP6) data Spatial resolution 1km raster data https://giovanni.gsfc.nasa.gov https://gpm.nasa.gov/data/imerg/precipitation-climatology/ https://www.resdc.cn/DOI/DOI.aspx?DOIID=39 https://pcmdi.llnl.gov/CMIP6/ Supporting the identification of the world's agro pastoral ecotone and the simulation analysis of global climate scenarios Terrain data Spatial distribution data of altitude in China (DEM) Spatial resolution 90 meter raster data https://www.resdc.cn/data.aspx?DATAID=284 Supporting the evaluation of land use suitability Soil data China soil texture distribution database, soil organic matter content database, soil layer thickness database Spatial resolution 1km raster data gisrs.cn/index.html Research on supporting regional scale land suitability evaluation Administrative Divisions and Policy Reports Data from various provinces, cities, and county-level administrative regions in China 2015 Vector data https://www.resdc.cn/ https://www.stats.gov.cn https://www.mnr.gov.cn Assist in delineating the spatial scope of the agricultural pastoral transition zone and conducting spatial statistics 2.2 Identification of research area Based on the comprehensive delineation of climatic and administrative factors, the Agro-Pastoral Transitional Zone in northern China is defined. The climate elements are defined as the northwest and southeast boundaries of the Agro-Pastoral Transitional Zone, with annual precipitation ranging from 250 to 450 mm, dryness index ranging from 1 to 2, and precipitation variability ranging from 15% to 30%. This study overlaid the regions defined by climate with administrative regions, based on the principle of relatively complete administrative regions while ensuring the integrity of social and economic data statistical units. The research area was designated as 793800 square kilometers, spanning 9 provinces (cities or autonomous regions) including inner mongolia autonomous region, heilongjiang province, jilin province, hebei province, beijing, shanxi province, shaanxi province, ningxia hui autonomous region, and gansu province. Due to the significant spatial differentiation of the Agro-Pastoral Transitional Zone in northern China in terms of longitude, the research area will be divided into three parts: the northeast section, the north China section, and the northwest section. Specifically, the administrative boundary between chifeng city and chengde city will be used as the boundary between the northeast and north China sections of the Agro-Pastoral Transitional Zone, and the north China and northwest sections of the Agro-Pastoral Transitional Zone will be divided by the section from Wulateqianqi in the middle reaches of the Yellow River to lvliang in shanxi province. 2.3 Research methods 2.3.1 Multi scenario climate change prediction model This study first predicts the future climate factors in the Agro-Pastoral Transitional Zone in Northern China, and then analyzes the impact of future climate change on land suitability using a land suitability evaluation framework. In terms of climate change simulation, the IMAGE model, MESSAGE model, and REMIND-MAGPIE model are used to simulate the basic situation of climate change under low, moderate, and high emission scenarios(Semenov et al., 2010; Garcia et al., 2014 ; Dong et al., 2018 ). The IMAGE model, also known as the Integrated Model to Assess the Greenhouse Effect, is a comprehensive assessment model for global climate change. Developed by the dutch environmental assessment agency in the 1980s, it is one of the comprehensive models adopted by the intergovernmental panel on climate change's special report on emission scenarios. It includes three modules: energy industry system, land environment system, and atmospheric ocean system. Among them, the greenhouse gas emission scenarios related to energy are calculated based on the Target Image Model of Energy Regional(TIMER). The IMAGE model considers the impact of technological and energy price changes on energy intensity, fuel structure, and non mineral fuel penetration rate, and describes technological changes through spontaneous energy efficiency improvements and price induced energy efficiency improvements. The MESSAGE model, also known as the "Model for Energy Supply System Alternatives and their General Environmental Impact", is a medium-long term dynamic linear programming energy technology model. Developed by the international institute for applied systems analysis, the objective function is to seek cost minimization of energy systems under different constraints. Suitable for medium and long-term energy planning, energy policy scenario analysis, and supporting climate change analysis. This model can obtain the resource technology that meets specific terminal service requirements with the minimum cost when running. The model has incorporated endogenous technological learning into the analysis framework, and the cost of technological investment decreases with the increase of accumulated technological experience. Its parameter settings can adapt to the assessment needs of the long-term energy structure transformation in moderate emission scenarios for climate change effects. The REMIND model, also known as the Regional Model of Investments and Development, is a modular and open-source multi regional model that includes detailed descriptions of the economy, climate system, and energy sectors. It solves the cross temporal and spatial Pareto optimality of economic and energy investment within the model area, fully considering the trade of goods, energy carriers, and emission quotas between regions. REMIND allows for the analysis of technology choices and policy recommendations for climate mitigation. The macroeconomic core of REMIND is the Ramsey type optimal growth model, in which temporal global welfare is optimized under equilibrium constraints. The MAGPIE model, also known as the "Model of Agricultural Production and its Impact on the Environment," is a global local equilibrium model for the land use sector used to assess competition for land and water and the related consequences for sustainable development under future scenarios of food, energy, and material demand, production, climate change impacts, greenhouse gas emissions reduction, and different land related policies. It operates in recursive dynamic mode, providing geographic data about biophysical conditions at a resolution of 0.5 degrees, and incorporating spatially explicit information about biophysical constraints into the economic decision-making process. The land types available in the MAGPIE model include farmland, pastures, forests, other land (including non forest natural vegetation, abandoned agricultural land, and deserts), and settlements. Farmland (rain fed and irrigated), pastures, forests, and other land are endogenously determined, while the area of settlements is assumed to remain constant over time. Farmland includes the cultivation of different crop types (such as temperate and tropical grains, corn, rice, oilseeds, roots), rain fed and irrigation systems, as well as two second-generation bioenergy crop types (herbaceous and woody). The research on predicting future climate factors revolves around precipitation and accumulated temperature greater than or equal to 10 ℃, using meteorological data from 1961 to 2020 as the training base period data, simulating the climate factor conditions in 2030 (short-term), 2050 (medium-term), and 2100 (long-term). The simulation period is divided into low emission interference, moderate emission interference, and high emission interference scenarios: (1) Low emission interference (corresponding to the sustainable model of social ecological system) This scenario was simulated by the Integrated Climate Change Assessment Model (IMAGE 3.0). The scenario parameters are set to stabilize radiation stress at 2.8 W/m 2 by 2100, and the global average temperature rise remains stable at around 1.8 ℃. The social subsystem maintains sustainable population growth, high-speed economic growth, and mechanization and rapid progress of agricultural technology. Traditional fossil fuels have basically achieved sustainable substitution, low-carbon lifestyles have been popularized, biodiversity loss has been effectively alleviated, animal product consumption has decreased, and global sustainable development cooperation is stable in the long run. (2) Moderate emission disturbance (corresponding to limited transition mode of social ecological system) This scenario is based on the simulation of alternative energy supply systems and environmental impact models (MESSAGE). The scenario parameters are set to stabilize radiation stress at 7.3 W/m 2 by 2100, and the global average temperature rise remains stable at around 3.6 ℃. Carbon dioxide emissions have roughly doubled compared to 2020 levels, with emissions and temperatures steadily increasing, and traditional fossil fuels partially replacing them. Population growth remains at a moderate level, low-carbon lifestyles have been partially popularized, and biodiversity loss has been partially alleviated. International competition is becoming increasingly fierce, and sustainable development cooperation is limited. The focus is shifting towards national strategic security and ensuring domestic food supply. (3) High emission interference (corresponding to traditional growth patterns of social ecological systems) Simulate the Regional Investment and Development Model (REMIND) and Agricultural Production and Environmental Impact Model (MAGPIE) for this scenario. The scenario parameters are set to approximately double the carbon dioxide emissions from 2020 levels by 2050. By 2100, the global average temperature will rise by around 4.4 ℃, and radiation stress will remain stable at 8.7 W/m 2 . The global economy is steadily growing, with traditional fossil energy use being replaced at a lower rate, and the growth mode maintaining a fossil energy intensive path. The population maintains a relatively high growth rate, the popularization of low-carbon lifestyles is limited, and the rate of biodiversity loss is fast. The level of international sustainable development cooperation is relatively low, and international competition is fierce. 2.3.2 Land use suitability assessment method The land use suitability assessment method is an evaluation of the suitability of land for a certain use under certain purposes(FAO, 1984 ). It usually uses the comprehensive indicator method to study the suitability, suitability, and limitations of land for the intended use based on its natural and socio-economic attributes. The basic principle of land suitability evaluation is to combine the natural and socio-economic elements of land as identification indicators under the existing level of productivity management and specific land use conditions(Wu et al., 2008a ; Wu et al., 2008b ). By examining and comprehensively analyzing the suitability, quality, and limitations of land for various purposes, the land's use and quality can be classified and graded(Medeiros et al., 2021 ). Land use is based on the natural resource background(Wang et al., 2010 ). As a composite land use area, climate change significantly affects the potential characteristics and spatial distribution of land use in the Agro-Pastoral Transitional Zone. Analyzing the impact of climate change on land suitability can provide a basic reference for scientific planning of national land space and adjustment of agricultural and pastoral structure, and enhance the climate resilience of agricultural and pastoral production in the Agro-Pastoral Transitional Zone. Based on the basic characteristics of the transitional zone between agriculture and animal husbandry in northern China, a suitability evaluation system for agriculture and animal husbandry is established according to local conditions to support future trend analysis of agricultural and animal husbandry suitability under climate factor changes. Table.2 Evaluation system for land use suitability of the Agro-Pastoral Transitional Zone in Northern China Type of suitability Grade Climatic conditions Topographic conditions Soil conditions Annual average precipitation (mm) Accumulated temperature ≥ 10 ℃ (℃) Slope (°) Altitude (m) Soil texture (silt content,%) Soil organic matter content (g/kg) Effective soil layer thickness (cm) Agriculture 1 ≧ 600 ≧ 3000 ≤ 2 ≦ 200 60–65 ≧ 30 ≧ 100 2 500–600 2800–3000 2–6 200–500 50–60, 65–70 20–30 50–100 3 400–500 2500–2800 6–15 500–1000 40–50, 70–75 10–20 30–50 4 350–400 2000–2500 15–25 1000–2500 < 40, 75–80 6–10 20–30 5 < 350 25 ≥ 2500 ≧ 80 < 6 < 20 Livestock farming 1 ≧ 500 ≧ 2500 1–3 ≦ 200 60–70 ≧ 25 ≧ 80 2 400–500 2200–2500 ≦ 1,3–6 200–800 50–60, 70–75 15–25 50–80 3 300–400 2000–2200 6–15 800–1200 40–50, 75–80 10–15 30–50 4 200–300 1500–2000 15–25 1200–3000 < 40, 80–90 2–10 15–30 5 < 200 25 > 3000 ≧ 90 < 2 < 15 Table.3 Connotation of suitability level for agricultural and pastoral land use of the Agro-Pastoral Transitional Zone in Northern China Suitability type Suitability level Suitability characteristics Agricultural land use 1 Completely suitable. The land is flat, the soil layer is deep and fertile, and the water and heat are extremely good. It can be stably used for rain fed crop planting and cultivation without the need for special land protection measures. 2 Highly suitable. The land is generally flat, with thick and fertile soil layers, excellent water and heat conditions, and can be stably used for rain fed crop planting and cultivation without the need for special land protection measures. 3 Moderate suitability. Individual natural factors have a certain degree of constraint. The land is relatively flat, the soil layer thickness is average, the fertility is average, and the water and heat conditions are average. It can be used for rain fed crop planting and cultivation, but certain land protection measures need to be taken. 4 Basically suitable. There are one or more limiting factors, such as a certain slope of the land, relatively thin soil layers or lack of nutrients, insufficient water and heat conditions, which can be limited for rain fed crop planting and cultivation, and poor stability. Strict land protection measures are required for land use. 5 Not suitable. There are one or more serious limiting factors that prevent the planting and cultivation of rain fed crops. Avoid damaging natural vegetation. livestock farming land use 1 Completely suitable. The land is flat, the soil layer is deep and fertile, the water and heat are extremely good, and it can be stably used for natural grass growth. It has a large livestock carrying capacity and does not require special land protection measures. 2 Highly suitable. The land is generally flat, with thick and fertile soil layers, excellent water and heat conditions, and can be stably used for natural grass growth and grazing. It has a large carrying capacity and does not require special land protection measures. 3 Moderate suitability. Individual natural factors have a certain degree of constraint. The land is relatively flat, the soil layer thickness is average, the fertility is average, and the water and heat conditions are average. It can be used for natural grass growth and grazing, and the carrying capacity is average. Therefore, certain land protection measures need to be taken. 4 Basically suitable. There are one or more limiting factors, such as a certain slope of the land, relatively thin soil layers or lack of nutrients, insufficient water and heat conditions, limited use for natural grass growth and grazing, limited carrying capacity, and poor stability. Strict land protection measures need to be taken. 5 Not suitable. There are one or more serious limiting factors that prevent the growth of natural grass. Avoid damaging natural vegetation. 3. Result analysis 3.1 Analysis of multi scenario climate change in the Agro-Pastoral Transitional Zone in northern China In terms of annual average precipitation, under the low emission scenario, the average precipitation in the Agro-Pastoral Transitional Zone of northern China in 2030, 2050, and 2100 is 322.16mm, 433.33mm, and 287.49mm, respectively, showing a trend of first increasing and then decreasing, and the overall average precipitation tends to decrease. In terms of spatial distribution, the average precipitation in the northeast and north China segments shows a regional increase from 2030 to 2050. The 400mm precipitation contour line expands westward as a whole, while the 400mm precipitation contour line shrinks significantly eastward from 2050 to 2100. The aridification characteristics of the northwest and north China segments of the Agro-Pastoral Transitional Zone are evident In terms of spatial distribution, the average precipitation in the northeast and north China segments shows a regional increase from 2030 to 2050. The 400mm precipitation contour line expands westward as a whole, while the 400mm precipitation contour line shrinks significantly eastward from 2050 to 2100. The aridification characteristics of the northwest and north China segments of the Agro-Pastoral Transitional Zone are evident. Under the moderate emission scenario, the average precipitation in the Agro-Pastoral Transitional Zone of northern China in 2030, 2050, and 2100 is 386.39mm, 515.42mm, and 446.44mm, respectively, showing a trend of first increasing and then decreasing, and the overall average precipitation tends to increase. In terms of spatial distribution, the average precipitation in the northeast and north China sections shows a regional increase from 2030 to 2050. The 400mm precipitation contour line expands westward as a whole, while the precipitation in the Greater Khingan Range of the northeast section and the Yanshan area of the north China section increases overall. From 2050 to 2100, the 400mm precipitation contour line shrinks slightly eastward and stabilizes in the central part of the north China section, namely the Yinshan-Yanshan line. The wetting characteristics of the northeast and north China sections are obvious. Under the scenario of high emissions, the average precipitation in the Agro-Pastoral Transitional Zone of northern China in 2030, 2050, and 2100 is 491.74mm, 337.10mm, and 422.32mm, respectively, showing a trend of first decreasing and then increasing. The overall average precipitation tends to decrease. In terms of spatial distribution, the northeastern and eastern parts of the Agro-Pastoral Transitional Zone in 2030 will show obvious wetting characteristics, while the 400mm precipitation line will remain stable in the central part of the North China section. In 2050, the southern part of the Northeast section and the northern part of the North China section will show aridification characteristics. The southern part of the North China section and the southern part of the Northwest section near the southern boundary of the Agro-Pastoral Transitional Zone will show obvious wetting characteristics. The 400mm and other precipitation lines will show a multi-stage distribution pattern, and the wetting areas will be divided into two parts: the north and south. In 2100, the southern part of the Northeast The northern part of the section exhibits wetting characteristics, with precipitation lines of 400mm and others connected as a whole, distributed along the western foothills of the Greater Khingan Range, Yanshan Mountains, and Yinshan Mountains. Overall, the future trend of annual precipitation in the low and moderate emission scenarios of the Agro-Pastoral Transitional Zone in northern China is relatively similar, with the highest difference in average precipitation observed in the high emission model; In terms of spatial distribution, precipitation has always maintained an overall pattern of "more in the east and less in the west". The precipitation changes in the northern and northwestern sections of the Agro-Pastoral Transitional Zone are relatively small, while the dry and wet changes in the northern and southern parts of the northeastern sections are large. (a. 2030; b. 2050; c. 2100), moderate emission scenario (d. 2030; e. 2050; f. 2100), high emission scenario (g. 2030; h. 2050; i. 2100) distribution map of annual precipitation forecast(mm) In terms of accumulated temperature greater than or equal to 10℃, under low emission scenario, the average accumulated temperature greater than or equal to 10℃ in the Agro-Pastoral Transitional Zone of northern China in 2030, 2050, and 2100 is 2374.23℃, 2575℃, and 2494.56℃, respectively. The accumulated temperature changes show an increasing and then decreasing trend, and the average accumulated temperature overall shows an increasing characteristic. In terms of spatial distribution, the 2000℃ accumulated temperature line continues to shrink northward from 2030 to 2050, and there is a slight southward expansion of the 2000℃ accumulated temperature line in the southern part of the northeast section from 2050 to 2100, while the accumulated temperature in the northwest section remains stable above 3000℃. Under the moderate emission scenario, the average accumulated temperature greater than or equal to 10 ℃ in the Agro-Pastoral Transitional Zone of northern China in 2030, 2050, and 2100 is 2273.10℃, 2376.96℃, and 2948.46℃, respectively. The accumulated temperature changes show a continuous increasing trend, and the overall average accumulated temperature shows a significant increase. In terms of spatial distribution, the 2000℃ accumulated temperature line continuously shrinks in the southern part of the northeast section and the eastern part of the north China section from 2030 to 2050, and most areas in the northeast section are occupied by areas with accumulated temperatures below 2000℃. However, between 2050 and 2100, the 2000℃ accumulated temperature line shrinks significantly to the north, and the areas with accumulated temperatures greater than 2000℃ expand significantly in the western part of the north China section and the eastern foot of the Greater Khingan Range. Under the high emission scenario, the average accumulated temperature greater than or equal to 10℃ in the Agro-Pastoral Transitional Zone of northern China in 2030, 2050, and 2100 is 2130℃, 2081.38℃, and 3047.42℃, respectively. The accumulated temperature changes show a trend of first decreasing and then increasing, and the overall average accumulated temperature shows a significant increase. In terms of spatial distribution, the 2000℃ accumulated temperature line will be stably distributed along the Agro-Pastoral Transitional Zone-Yanshan-Yinshan line from 2030 to 2050, and the area of accumulated temperature below 1500℃ will continue to expand in the northeast section, while the area of accumulated temperature above 3000℃ in the northwest section will significantly decrease. From 2050 to 2100, the 2000℃ accumulated temperature line will shrink northward to the northernmost part of Hulunbuir region. Except for the Greater Khingan Range, Yanshan, and Yinshan areas, most of the Agro-Pastoral Transitional Zone, except for the Greater Khingan Range. The accumulated temperature in the region is above 3000℃. Overall, the accumulated temperature distribution in the Agro-Pastoral Transitional Zone of northern China presents a spatial characteristic of high in the south and low in the north. The accumulated temperature changes in the low emission mode are relatively stable, while the accumulated temperature changes in the moderate and high emission modes are more extreme. The southern part of the northeast section and the eastern part of the north China section are the key areas of alternating cold and warm changes. Based on the changes in the dual factors of precipitation and accumulated temperature, it can be seen that in the low emission scenario of 2100, an increase in accumulated temperature and a decrease in precipitation will occur simultaneously, and the process of drying and heating is prone to cause drought disasters. The overall performance of the moderate emission scenario is a warming and humidification process. The high emission scenario is prone to dry and cool processes in the north China region by 2050, and will exhibit warm and humid processes by 2100. 3.2 Analysis of land suitability evolution in the Agro-Pastoral Transitional Zone in northern China under multiple climate change scenarios Based on the evaluation results of land use suitability for agriculture and animal husbandry in the Agro-Pastoral Transitional Zone of Northern China, there are differences in the quantity and spatial distribution of land suitability levels for agriculture and animal husbandry under different scenarios in the three time periods of 2030, 2050, and 2100, as follows: In terms of agricultural land suitability, under the low emission scenario, the proportion of land area unsuitable for agricultural land use in the three time periods of 2030, 2050, and 2100 shows a quantitative structural change characteristic of "first decreasing and then increasing", and the proportion of land area unsuitable for agricultural land use in 2100 is the highest in previous years. In terms of spatial distribution, the areas suitable for agricultural land use are concentrated in the central eastern part of the Agro-Pastoral Transitional Zone, near the southern boundary. By 2050, the suitable agricultural areas will expand to a certain extent, but by 2100, they will sharply shrink and be concentrated in the eastern part of the Agro-Pastoral Transitional Zone, east of the Greater Khingan Range. The rest of the areas are not suitable for agricultural land use. Under the moderate emission scenario, the proportion of land area unsuitable for agricultural land use in the three time periods of 2030, 2050, and 2100 shows a "continuous decrease" in quantity and structural changes, and the proportion of land area unsuitable for agricultural land use in 2100 is the smallest in previous years, while the proportion of land area suitable for moderate use has increased significantly. In terms of spatial distribution, there will be a large-scale expansion of suitable agricultural areas in the central and eastern regions of the Agro-Pastoral Transitional Zone in 2050 and 2100. Due to the improvement of heat conditions, the suitability of agricultural land use in the northeastern Greater Khingan Range region and the Hulunbeir Plateau region of the Agro-Pastoral Transitional Zone will increase significantly. The western region of the Agro-Pastoral Transitional Zone has long been in an agricultural unsuitable area. Under the high emission scenario, the proportion of land area unsuitable for agricultural land use in the three time periods of 2030, 2050, and 2100 shows a "continuous decrease" in quantity and structural changes. In addition, the proportion of land area unsuitable for agricultural land use in 2100 is the smallest in previous years, while the proportion of areas suitable for moderate and basic use has increased significantly. In terms of spatial distribution, the expansion of agricultural suitable areas from 2030 to 2050 is mainly concentrated on the southern side of the central and western regions of the Agro-Pastoral Transitional Zone, as well as some areas in the northeast. By 2100, the scope of agricultural suitable areas in the western part of the Agro-Pastoral Transitional Zone will significantly shrink, while there will be a large-scale expansion of agricultural suitable areas in the central and eastern regions. Overall, in terms of the quantity structure of agricultural suitability, the proportion of suitable agricultural areas in the moderate emission scenario in the near future (2030) is the best, the proportion of suitable agricultural areas in the low emission scenario in the medium term (2050) is the best, and the proportion of suitable agricultural areas in the moderate emission scenario in the long term (2100) is the best. In terms of spatial distribution, the southern central region of the Agro-Pastoral Transitional Zone, as well as the eastern Greater Khingan Range and Kerqin regions, are the areas with the strongest fluctuations in agricultural suitability, making them the most sensitive to climate impacts on agricultural land use. In terms of land suitability for animal husbandry, under the low emission scenario, the proportion of land area unsuitable for animal husbandry land use in the three time periods of 2030, 2050, and 2100 shows a quantitative structural change characteristic of "first decreasing and then increasing", and the proportion of land area unsuitable for animal husbandry land use in 2100 is the highest in previous years. In terms of spatial distribution, there are a large number of contiguous suitable areas for animal husbandry concentrated in the southern and central parts of the Agro-Pastoral Transitional Zone, as well as in the eastern foothills of the Greater Khingan Range. In 2050, the central and western regions of the Agro-Pastoral Transitional Zone will show a slight expansion of suitable areas for animal husbandry, while the eastern region will mainly see an improvement in the level of suitability for animal husbandry. By 2100, the basic suitable areas for animal husbandry in the central and western regions of the Agro-Pastoral Transitional Zone will significantly shrink, while the suitable levels in the eastern region will show a significant decline. Under the moderate emission scenario, the proportion of land area unsuitable for animal husbandry land use in the three time series of 2030, 2050, and 2100 shows a "continuous decrease" in quantity and structural changes. In addition, the proportion of land area unsuitable for animal husbandry land use in 2100 is the smallest in previous years, and the proportion of medium and basic suitable areas for animal husbandry has increased significantly. In terms of spatial distribution, the suitable areas for animal husbandry land use show an overall characteristic of "expanding north and extending west" from 2030 to 2100. By 2100, except for the western part of the Agro-Pastoral Transitional Zone, which is still in the unsuitable area for animal husbandry land use, all other areas are suitable for animal husbandry land use. The suitability level for animal husbandry in most areas of the southern and eastern parts of the Agro-Pastoral Transitional Zone continues to improve, and the suitable range has reached the largest in previous years. Under the high emission scenario, the proportion of land area unsuitable for animal husbandry land use in the three time periods of 2030, 2050, and 2100 shows a "continuous decrease" in quantity and structural changes. In addition, the proportion of land area unsuitable for animal husbandry land use in 2100 is the smallest in previous years, and the proportion of medium and basic suitable areas for animal husbandry has increased significantly. In terms of spatial distribution, the suitable areas for land use in animal husbandry exhibit an overall characteristic of "expanding north and extending west" from 2030 to 2100. The speed and scale of expansion of the suitable areas towards the western part of the Agro-Pastoral Transitional Zone are greater than those of the moderate emission mode, while the unsuitable areas for animal husbandry shrink to the northern and central parts of the Agro-Pastoral Transitional Zone. Overall, in terms of the quantity structure of suitability for animal husbandry, the proportion of suitable agricultural areas in the moderate emission scenario in the near future (2030) is the best, the proportion of suitable agricultural areas in the low emission scenario in the medium term (2050) is the best, and the proportion of suitable agricultural areas in the high emission scenario in the long term (2100) is the best. The moderate emission model has a slightly lower proportion of suitable agricultural areas than the high emission model, but has more advantages in suitability levels. In terms of spatial distribution, the southern western region, central hinterland region, and eastern Greater Khingan Range region of the Agro-Pastoral Transitional Zone are the areas with the strongest fluctuations in pastoral suitability, that is, the areas where pastoral land use is most sensitive to climate impact. Based on the comprehensive evaluation of the suitability of agriculture and animal husbandry, the climate sensitive area for agricultural land use suitability is generally located south of the climate sensitive area for animal husbandry land use suitability in terms of spatial position. The climate sensitive area for agricultural land use suitability is a long-term stable suitable area for animal husbandry land use. Therefore, the agricultural land use with strong fluctuations in the edge zone and the animal husbandry land use with natural stability form a highly overlapping area in the central southern part of the Agro-Pastoral Transitional Zone and the eastern Kerqin region, forming a long-term competition and mosaic distribution pattern for agricultural and animal husbandry land use. Climate change is related to the natural conditions of land use around the world. Overall, due to the fact that the Agro-Pastoral Transitional Zone in northern China is located in a mid latitude arid and semi-arid region, global warming can help improve the heat conditions in the central and eastern parts of the ecotone under moderate and high emission patterns, thereby enhancing the suitability of agriculture and animal husbandry. However, in the western part of the ecotone, natural conditions will further strengthen the constraints, and the suitability of agricultural and animal husbandry land use cannot achieve long-term stable improvement. From the perspective of global climate governance, the Paris Climate Agreement proposes that the main goal of controlling global warming is to keep the average global temperature rise within 2℃ before industrialization, preferably within 1.5℃, by the end of the 21st century. This goal is comparable to the low emission model set in research. According to this goal, by 2100, there will be a large-scale shrinkage in the suitability of agricultural and pastoral land use in the Agro-Pastoral Transitional Zone in northern China, with reduced precipitation being the main driving force behind this phenomenon. In the process of achieving this goal, 2030 and 2050 will require more reference to moderate emission models for climate governance. For agricultural climate sensitive areas, future land use should be optimized and implemented in conjunction with terrain zoning. Strengthen the construction of irrigation and drainage facilities in the valley area to enhance its ability to resist natural climate disasters. Mountainous and hilly areas should focus on rain fed agriculture with irrigation as a supplement, and build rainwater storage facilities such as water cellars to enhance the climate resilience of agricultural production. Climate sensitive areas in animal husbandry need to increase the construction of artificial grasslands, develop grassland irrigation and water storage systems according to local conditions, in order to improve and stabilize grassland carrying capacity and enhance the stability of grassland production under drought conditions. The dual climate sensitive areas of agriculture and animal husbandry need to strictly control the development of arable land, designate ecological protection areas, and construct ecological barrier belts to enhance the interception function of sandstorms and the conservation function of river water sources. Table.4 Proportion of agricultural suitability evaluation at different levels in the Agro-Pastoral Transitional Zone in northern China Agricultural suitability evaluation Low emission scenario Completely suitable Highly suitable Moderate suitability Basically suitable Unsuitable 2030 0.00% 0.01% 1.73% 9.78% 88.49% 2050 0.00% 0.00% 6.59% 28.80% 64.60% 2100 0.00% 0.00% 2.39% 4.90% 92.72% Agricultural suitability evaluation Moderate emission scenario Completely suitable Highly suitable Moderate suitability Basically suitable Unsuitable 2030 0.00% 0.00% 3.26% 12.21% 84.53% 2050 0.00% 0.00% 4.99% 21.88% 73.13% 2100 0.00% 0.20% 29.49% 32.89% 37.42% Agricultural suitability evaluation High emission scenario Completely suitable Highly suitable Moderate suitability Basically suitable Unsuitable 2030 0.00% 0.00% 1.59% 9.59% 88.81% 2050 0.00% 0.00% 3.86% 20.65% 75.49% 2100 0.00% 0.24% 25.38% 28.03% 46.35% Table.5 Proportion of animal husbandry suitability evaluation at different levels in the Agro-Pastoral Transitional Zone in northern China Animal husbandry suitability evaluation Low emission scenario Completely suitable Highly suitable Moderate suitability Basically suitable Unsuitable 2030 0.00% 0.80% 12.31% 33.78% 53.12% 2050 0.00% 1.96% 19.41% 44.22% 34.41% 2100 0.00% 1.28% 5.14% 28.51% 65.07% Animal husbandry suitability evaluation Moderate emission scenario Completely suitable Highly suitable Moderate suitability Basically suitable Unsuitable 2030 0.00% 1.42% 12.05% 33.41% 53.11% 2050 0.00% 1.66% 9.60% 41.93% 46.81% 2100 0.00% 3.44% 36.12% 46.86% 13.58% Animal husbandry suitability evaluation High emission scenario Completely suitable Highly suitable Moderate suitability Basically suitable Unsuitable 2030 0.00% 1.09% 6.76% 30.58% 61.57% 2050 0.00% 1.78% 15.17% 48.32% 34.72% 2100 0.00% 3.23% 33.18% 50.55% 13.04% 3. Discussion The Agro-Pastoral Transitional Zone in northern China is located in the tail area affected by the summer monsoon, and its agricultural and animal husbandry production is highly marginalized due to the criticality of climatic factors. There are significant differences in the suitability of agricultural and pastoral production in the transitional zone between agriculture and animal husbandry in northern China under future differentiated climate change scenarios. Overall, the suitability of agricultural and pastoral land use has been greatly improved under moderate emission scenarios, while the improvement in suitability of agricultural and pastoral land use is relatively low under low emission scenarios. The Agro-Pastoral Transitional Zone in northern China is located in the temperate zone of the northern hemisphere, which benefits from the improvement of heat conditions caused by global climate change and promotes the optimization of agricultural and animal husbandry production conditions. The improvement degree of agricultural and animal husbandry production conditions is relatively high under moderate and high emission scenarios. The average proportion of unsuitable agricultural areas under moderate emission mode is 65.03%, the average proportion of unsuitable animal husbandry areas is 37.83%, the average proportion of unsuitable agricultural areas under high emission mode is 70.22%, and the average proportion of unsuitable animal husbandry areas is 36.44%. However, under the high emission mode, the global trend towards traditional fossil energy growth is clearly not in line with the action goals adopted by international climate change cooperation. Therefore, the high emission mode lacks practicality in the international community. Under the low emission mode, the average proportion of unsuitable areas for agriculture is 81.94%, and the average proportion of unsuitable areas for animal husbandry is 50.87%. There has been no significant improvement in the suitability of agricultural and animal husbandry production, and the proportion of unsuitable areas is higher than that under the moderate and high emission modes. Therefore, for the Agro-Pastoral Transitional Zone in northern China, both low and high emission modes are not the optimal models for improving agricultural and animal husbandry production conditions. The moderate emission mode can achieve the maximum improvement in agricultural production conditions, while also matching the basic reality of global climate governance practices. Under the scenario of differentiated climate change in the future, different regions in the Agro-Pastoral Transitional Zone in northern China exhibit differentiated responses to climate change. The eastern region of the Agro-Pastoral Transitional Zone benefits from the improvement of accumulated temperature conditions, which enhances its suitability for agricultural and pastoral production. However, the western region of the Agro-Pastoral Transitional Zone, which has abundant heat but scarce precipitation, will experience a decrease in suitability for agricultural and pastoral production. The agricultural climate sensitive areas are concentrated in the southeastern part of the Agro-Pastoral Transitional Zone. The development of agriculture in this region needs to strengthen the construction of agricultural facilities according to local conditions. In the valley areas, the construction of agricultural irrigation and drainage facilities should be strengthened to enhance resilience against uncertain factors of climate change. Moderately promote dryland agriculture in mountainous and hilly areas, plant drought tolerant crops and characteristic grains, build facilities such as rainwater cellars to efficiently utilize and store natural precipitation, and form a characteristic agricultural production model with "rain fed as the main source and irrigation as the auxiliary", continuously playing the role of food security guarantee. The climate sensitive areas for animal husbandry are concentrated in the western part of the Agro-Pastoral Transitional Zone, which is susceptible to fluctuations in suitability due to unstable precipitation. Therefore, in the future, when carrying out animal husbandry production, it is necessary to increase the construction of artificial grasslands, develop grassland irrigation and water storage systems according to local conditions, ensure stable grassland production in dry years, and continue to play the role of ensuring the production of animal husbandry products. The dual climate sensitive areas of agriculture and animal husbandry are the key areas of focus for future Agro-Pastoral Transitional Zone. This area is most significantly affected by climate change, and is currently mostly covered by forest land. Due to low accumulated temperature, large-scale agricultural and animal husbandry production cannot be carried out. In the future, the suitability of agricultural and animal husbandry production in this area will be improved during the process of climate warming. In the future, this region needs to establish a land use pattern dominated by forests and grasslands, strictly control farmland cultivation and agricultural development, strengthen regional forest and grassland management and protection through the designation of national parks and ecological protection areas, and build an important ecological barrier zone in northern China. The analysis of climate change in research is based on the annual average precipitation and accumulated temperature indicators, which are relatively macroscopic and do not include other climate indicators in the analysis framework. On the one hand, it is limited by the availability of data, and on the other hand, precipitation and accumulated temperature are the most important critical climate elements in the Agro-Pastoral Transitional Zone. The analysis of these two indicators is more suitable for the regional characteristics of the Agro-Pastoral Transitional Zone. When conducting suitability evaluation, the principle of limiting factors is adopted, and the worst level of multiple indicators is used as the final level. However, the limiting ability of climate, terrain, and soil on suitability is different. Whether it is necessary to define the priority order of limiting factors is the focus of subsequent analysis in this study. Future research can add evaluation objects in global regional comparative analysis to enhance global scenario comparison, and further conduct zoning studies within the study area to highlight regional differentiation characteristics and guide regional land use planning and agricultural and animal husbandry production factor allocation. 4. Conclusion In terms of future climate change, the low emission scenario and moderate emission scenario in the Agro-Pastoral Transitional Zone of northern China show similar trends in annual precipitation, with the highest range of precipitation observed in the high emission model. In terms of spatial distribution, precipitation has always maintained an overall pattern of "more in the east and less in the west". The precipitation changes in the northern and northwestern sections of the Agro-Pastoral Transitional Zone are relatively small, while the dry and wet changes in the northern and southern parts of the northeastern and northeastern sections are significant. The overall distribution of accumulated temperature shows a spatial characteristic of high in the south and low in the north. The accumulated temperature changes in the low emission mode are relatively stable, while the accumulated temperature changes in the moderate and high emission modes are more extreme. The southern part of the northeast section and the eastern part of the north China section are the key areas of alternating cold and warm changes. In the low emission scenario of 2100, both the increase in accumulated temperature and the decrease in precipitation will occur simultaneously, and the drying and heating process is prone to cause drought disasters; The overall performance of the moderate emission scenario is a warming and humidification process; The high emission scenario is prone to dry and cool processes in the North China region by 2050, and will exhibit warm and humid processes by 2100. The analysis of land use suitability for agriculture and animal husbandry under multiple climate scenarios found that the climate sensitive area of agricultural land use suitability is generally located south of the climate sensitive area of animal husbandry land use suitability in terms of spatial location. The climate sensitive area of agricultural land use suitability is a suitable area for long-term stable pastoral land use. Therefore, the highly volatile agricultural land use in the marginal zone and the naturally stable pastoral land use form a highly overlapping area in the central southern part of the Agro-Pastoral Transitional Zone and the eastern Kerqin region. Due to the fact that the Agro-Pastoral Transitional Zone in northern China is located in a mid latitude arid and semi-arid region, the response of different areas in the Agro-Pastoral Transitional Zone to climate change varies. Global warming, under moderate and high emission patterns, can help improve the heat conditions in the central and eastern regions of the Agro-Pastoral Transitional Zone in the medium to long term, thereby enhancing the suitability of agriculture and animal husbandry. However, in the western part of the Agro-Pastoral Transitional Zone, it will further strengthen the constraints of natural conditions, especially in terms of unstable precipitation, and the suitability of land use for agriculture and animal husbandry cannot achieve long-term stable improvement. Declarations Author Contribution K.W. and Y.X. wrote the main manuscript text and F.Z. checked and visualized all charts. Z.D. provided guidance on research methods and data models. All authors reviewed the manuscript. Acknowledgement This research was supported by the Assessment Project of Benchmark Land Price for Agricultural Land of State-owned Farms and Ranches in Xing'an League, Inner Mongolia Autonomous Region[grant number 69199032]. We are also grateful for the comments and criticisms of the journal's anonymous reviewers and our colleagues. Data Availability All data used in the study are publicly available. New data generated from the study can be made publicly accessible upon request. References Abiodun, B. J., Lawal, K. A., Salami, A. T. & Abatan, A. A. Potential infuences of global warming on future climate and extreme events in Nigeria. Reg. Envriron. Chang. , 1–15. (2012). Briner, S., Elkin, C., Huber, R. & Grêt-Regamey, A. Assessing the impacts of economic and climate changes on land-use in mountain regions: A spatial dynamic modeling approach Vol. 149, 50–63 (Agriculture, Ecosystems & Environment, 2012). Dale, V. H. The relationship between land use change and climate change: Ecological applications. Ecol. Soc. Am. 7 (3), 753–769 (1997). Dong, N. et al. Land use projections in China under global socioeconomic and emission scenarios: utilizing a scenario-based land-use change assessment framework. Glob Environ. Change . 50 , 164–177 (2018). Erik, L. & Ding, C. R. Assessing farmland protection policy in China. Land. Use Policy . 25 , 59e68 (2008). Fan, X., Ma, Z., Yang, Q., Han, Y. & Mahmood, R. Land use/land cover changes and regional climate over the loess plateau during 2001–2009, Part II: Interrelationship from observations. Clim. Change . 129 (3), 441–455 (2015). Fang, X. Q. Decline of pre-historical agriculture and formation of farming grazing transitional zone in north China: a view from climatic changes. J. Nat. Resour. 14 (3), 212e218 (1997). FAO. Guidelines: Land Evaluation for Rainfed Agriculture. Soils Bulletin No. 32, Food and Agriculture Organisation of the United Nations, Rome, Italy, 249 pp. (1984). Feng, T. et al. Spatial distribution of prime farmland based on cultivated land quality comprehensive evaluation at county scale. Tran Chin. Soc. Agri Eng. 30 (1), 200–210 (2014). (in Chinese with English abstract). Garcia, R. A. et al. Multiple dimensions of climate change and their implications for biodiversity. Science 344 , 486–496 (2014). Garnett, T. et al. Sustainable intensifcation in agriculture: premises and policies. Science 341 , 33–34 (2013). Hu, H. Y. Population distribution in China-attached statistical tables and density maps. Acta Geogr. Sin. 2 , 33–74 (1935). (in Chinese with English abstract). Hua, L. & Squires, V. R. Managing China’s pastoral lands: current problems and future prospects. Land. Use Policy . 43 , 129–137 (2015). Jin, J. J., He, R., Wang, W. Y. & Gong, H. Z. Valuing cultivated land protection: a contingent valuation and choice experiment study in China. Land. Use Policy . 74 , 214–219 (2018). Justin, A. J. et al. Global agriculture and carbon tradeoffs. PNAS 111 (34), 12342–12347 (2014). Karina, W., Richard, F., Mark, R. & Martin, H. Global land use changes are four times greater than previously estimated. Nat. Commun. 12 , 2501 (2021). Li, S. J. et al. Changing patterns in farming-pastoral ecotones in China between 1990 and 2010. Ecol. Ind. 89 , 110–117 (2018). Liu, J. Integration across a metacoupled world. Ecol. Soc. 22 (4), 29 (2017). Liu, J. et al. Complexity of coupled human and natural systems. Science 317 , 1513–1516 (2007b). Liu, J. Y., Liu, M. L., Zhuang, D. F., Zhang, Z. & Deng, X. Z. Study on spatial pattern of land-use change in China during 1995e2000. Sci. China Ser. D: Earth Sci. 46 , 373e384 (2003). Liu, Y. Introduction to land use and rural sustainability in China. Land. Use Policy . 74 (5), 1–4 (2018a). Liu, Y., Fang, F. & Li, Y. Key issues of land use in China and implications for policy Making. Land. Use Policy . 40 , 6–12 (2014a). Medeiros, A., Fernandes, C., Gonçalves, J. F. & Farinha-Marques, P. Research trends on integrative landscape assessment using indicators–a systematic review. Ecol. Ind. 129. (2021). Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520 (7545), 45–50 (2015). Ostrom, E. A general framework for analyzing sustainability of social-ecological systems. Science 325 , 419–422 (2009). Peters, M. K. et al. Climate-land-use interactions shape tropical mountain biodiversity and ecosystem functions. Nature 568 (7750), 88–92 (2019). Pradhan, P. et al. A systematic study of Sustainable Development Goal (SDG) interactions. Earths Future . 5 (11), 1169–1179 (2017). Riha, S. J., Wilks, D. W. & Simoens, P. Impact of temperature and precipitation variability on crop model predictions. Clim. Chang. 32 (3), 293–311 (1996). Schirpke, U. et al. Future impacts of changing land-use and climate on ecosystem services of mountain grassland and their resilience. Ecosyst. Serv. 26 (A), 79–94 (2017). Semenov, M. A. & Stratonovitch, S. Use of multi-model ensembles from global climate models for assessment of climate change impacts. Clim. Res. 41 , 1–14 (2010). Shi, X., Wang, W. & Shi, W. Progress on quantitative assessment of the impacts of climate change and human activities on cropland change. J. Geog. Sci. 26 (3), 339–354 (2016). Song, X. P. et al. Global land change from 1982 to 2016. Nature 560 , 639–643 (2018). Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R. & Polasky, S. Agricultural sustainability and intensive production practices. Nature 418 , 671–677 (2002). UNICEF. The millennium development goals report 2015. Midwifery 30 , 1043–1044 (2014). Wang, G. Q. & Yun, W. J. A brieffy review and prospects on the land quality evaluation research. China Land. Sci. 25 (7), 92–96 (2011). (in Chinese with English abstract). Wang, J. L., Xu, X. & Liu, P. F. Land use and land carrying capacity in ecotone between agriculture and animal husbandry in Northern China. Resour. Sci. 21 (5), 19e24 (1999). Wang, L., An, P., Pan, Z., He, D. & Dong, Z. Cultivated land quality change of Wuchuan county in Inner Mongolia under background of climate change in semi-arid regions during recent 20 years. Tran Chin. Soc. Agri Eng. 29 (11), 224–231 (2013b). (in Chinese with English abstract). Wang, S. Y., Liu, J. S. & Ma, T. B. Dynamics and changes in spatial patterns of land use in Yellow River Basin, China. Land. Use Policy . 27 , 313e323 (2010). Wheeler, T. & Von Braun, J. Climate change impacts on global food security. Science 341 , 508–513 (2013). Wu, K. et al. Comprehensive productivity of agricultural land based on the agricultural land classiffcation. Trans. CSAE . 24 (11), 51–56 (2008b). (in Chinese with English abstract). Wu, K. et al. Framework of the arable-land quality dynamic monitoring sites through national gathering of standard farmland. Trans. CSAE . 10 (24), 74–79 (2008a). (in Chinese with English abstract). Xie, H. L. et al. Warning of negative effects of land-use changes on ecological security based on GIS. Sci. Total Environ. 704 , 9 (2020). Zhang, Q. & Li, W. Distributed overgrazing: a neglected cause of grassland degradation in Inner Mongolia. J. Arid Land. Resour. Environ. 22 (12), 8–16 (2008). Zhao, W. et al. Comparison of surface energy budgets and feedbacks to microclimate among different land use types in an agro-pastoral ecotone of northern China. Sci. Total Environ. 599 , 891–898 (2017). Zuo, L. et al. Multitemporal analysis of cropland transition in a climate-sensitive area: A case study of the arid and semiarid region of northwest China. Reg. Envriron. Chang. 14 (1), 75–89 (2014). Additional Declarations No competing interests reported. Supplementary Files GraphicalAbstractforreview.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8518691","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":595802064,"identity":"67a01420-ec42-4ea7-b493-c0d870e27b9c","order_by":0,"name":"Kaige Wang","email":"","orcid":"","institution":"China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Kaige","middleName":"","lastName":"Wang","suffix":""},{"id":595802065,"identity":"247f49d5-b080-4d65-87a4-3abfe0413569","order_by":1,"name":"Yan Xu","email":"","orcid":"","institution":"China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Xu","suffix":""},{"id":595802066,"identity":"0c6be08c-15b4-4a1d-a0a5-efbc824875d5","order_by":2,"name":"Fengrong Zhang","email":"","orcid":"","institution":"China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Fengrong","middleName":"","lastName":"Zhang","suffix":""},{"id":595802067,"identity":"ea357315-90cf-464f-b78d-45eccc5c43ae","order_by":3,"name":"Zengqiang Duan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwklEQVRIiWNgGAWjYDCCA2DSBsLhIUFLGulaDpOghe9G8rOHP8rOy/PPSGB88LaNQd6ckBbJG2nmBhLnbhvOuJHAbDi3jcFwZwMBLQY3EswkDNtuJzDcSGCT5m1jSDA4QFBL+jeJxLZzCfI3Eth/E6klx0ziYNuBBKB1bMxEaZE886ZMsuFcsuHGMw+bJeeckzDcQEgL3/H0bZI/yuzk5Y4nH/zwpsxGnqAtEMAGIhgbgIQEUephWkbBKBgFo2AU4AAAx+ZA10K9Zs8AAAAASUVORK5CYII=","orcid":"","institution":"China Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Zengqiang","middleName":"","lastName":"Duan","suffix":""}],"badges":[],"createdAt":"2026-01-05 08:23:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8518691/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8518691/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103397975,"identity":"b06d4e56-fa03-462d-b922-99f7f6474f75","added_by":"auto","created_at":"2026-02-25 08:58:32","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":307405,"visible":true,"origin":"","legend":"\u003cp\u003eRegional Map of the Agro-Pastoral Transitional Zone in Northern China\u003c/p\u003e","description":"","filename":"1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8518691/v1/7e685376f66e5aa0f19bfb28.jpeg"},{"id":103397977,"identity":"42b81523-0a48-40fe-8bcf-859c946f09ab","added_by":"auto","created_at":"2026-02-25 08:58:32","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":927685,"visible":true,"origin":"","legend":"\u003cp\u003eLow emission scenario in the Agro-Pastoral Transitional Zone in Northern China\u003c/p\u003e\n\u003cp\u003e(a. 2030; b. 2050; c. 2100), moderate emission scenario (d. 2030; e. 2050; f. 2100), high emission scenario (g. 2030; h. 2050; i. 2100) distribution map of annual precipitation forecast(mm)\u003c/p\u003e","description":"","filename":"2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8518691/v1/33e8c0f030f55071e2eb1e03.jpeg"},{"id":103398116,"identity":"5ee4b087-f029-403f-a540-a247aae2590d","added_by":"auto","created_at":"2026-02-25 08:58:49","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":495654,"visible":true,"origin":"","legend":"\u003cp\u003eLow emission scenario in the Agro-Pastoral Transitional Zone in Northern China (a. 2030; b. 2050; c. 2100), moderate emission scenario (d. 2030; e. 2050; f. 2100), high emission scenario (g. 2030; h. 2050; i. 2100) forecast distribution map of accumulated temperature greater than or equal to 10℃\u003c/p\u003e","description":"","filename":"3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8518691/v1/9976ce84ec95579f39fd8620.jpeg"},{"id":103398152,"identity":"4550a238-284f-4d86-954c-a674a1588356","added_by":"auto","created_at":"2026-02-25 08:58:59","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":242470,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of climate sensitive areas for agricultural and pastoral land use in the future climate change scenario in the Agro-Pastoral Transitional Zone in northern China\u003c/p\u003e","description":"","filename":"4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8518691/v1/ede11d3b382f9fd84e200d1e.jpeg"},{"id":103398021,"identity":"54484f8d-0783-49dd-a683-077b21511017","added_by":"auto","created_at":"2026-02-25 08:58:42","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":547974,"visible":true,"origin":"","legend":"\u003cp\u003eLow emission scenario in the Agro-Pastoral Transitional Zone of northern China (a. 2030; b. 2050; c. 2100), moderate emission scenario (d. 2030; e. 2050; f. 2100), high emission scenario (g. 2030; h. 2050; i. 2100 )distribution map of agricultural suitability assessment grades\u003c/p\u003e","description":"","filename":"5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8518691/v1/2194bba6291cdb35ae20159b.jpeg"},{"id":103506555,"identity":"499c3069-24cc-4934-93a5-00706418b7d2","added_by":"auto","created_at":"2026-02-26 13:37:36","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":629724,"visible":true,"origin":"","legend":"\u003cp\u003eLow emission scenario in the Agro-Pastoral Transitional Zone of northern China (a. 2030; b. 2050; c. 2100), moderate emission scenario (d. 2030; e. 2050; f. 2100), high emission scenario (g. 2030; h. 2050; i. 2100) distribution map of suitability evaluation levels for animal husbandry\u003c/p\u003e","description":"","filename":"6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8518691/v1/7b7a93ff4bb30cc478099bbb.jpeg"},{"id":108402797,"identity":"7ed77be7-7209-41d7-a201-c95dcc7bb896","added_by":"auto","created_at":"2026-05-04 09:11:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3631034,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8518691/v1/8ef5a8e0-3002-421e-8bcc-0202b8e1036a.pdf"},{"id":103397980,"identity":"90fbcefb-9963-4fa1-a2f1-3a664db67451","added_by":"auto","created_at":"2026-02-25 08:58:34","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":217080,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstractforreview.docx","url":"https://assets-eu.researchsquare.com/files/rs-8518691/v1/4c0e5e8af64b15ec65592ae5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evolution of Land Use Suitability and Adaptation Strategies of the Agro-Pastoral Transitional Zone in northern China under Multiple Climate Change Scenarios","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMitigating and adapting to global climate change is a major challenge currently faced by human society(UNICEF, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). However, the social ecological effects brought about by climate change vary significantly in different regions of the Earth(Abiodun et al, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Focusing on the response of social ecological systems in key areas of the Earth to climate change has become a cutting-edge topic in current geographical research(Dale, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Briner et al, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The Agro-Pastoral Transitional Zone in northern China is a transitional zone between semi humid and semi-arid regions(Hu \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1935\u003c/span\u003e). It is a coupled development zone between grassland animal husbandry and arable land agriculture, an important ecological security barrier in the central and eastern regions of China, and an important water source conservation zone in the north. It has a unique ecosystem and socio-economic system that is different from pastoral and agricultural areas. On the one hand, as a typical ecologically fragile and climate sensitive area, the Agro-Pastoral Transitional Zone in northern China is prone to ecological degradation due to external disturbances(Zuo et al, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Zhao et al, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). On the other hand, its land use is constrained by climate factors and exhibits significant marginal characteristics, with distinct fluctuations in response to climate change(Erik et al., 2008; Liu, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The future global climate change still has strong uncertainty. As an important ecological barrier area, food production area, and forage supply base, the research area will be affected by differentiated climate change, and the exploration of this scientific issue constitutes the focus of climate change and regional geography research(Wang et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Pradhan et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe research on climate change effects and land suitability evaluation belong to different disciplinary systems. The former focuses on climate change pattern recognition, species distribution and crop yield, hydrology, carbon flow, and climate change trend simulation research, aiming to clarify the basic characteristics and possible trends of climate change(Fang \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Justin et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Fan et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Newbold et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Peters et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). At the level of climate change effects, attention is paid to the perspectives of vegetation, hydrology, soil characteristics, and human social welfare(Riha et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Wheeler et al., 2013; Xie et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The latter focuses on comprehensive suitability evaluation of target land use, with extensive exploration in land consolidation, crop growth, and potential evaluation(Feng et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Hua et al., 2015; Jin et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Current academic research has conducted preliminary explorations between climate change and land suitability assessment, but often limited to regional studies similar to the Qinghai Tibet Plateau, a special natural geographic unit(Liu et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2007b\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2013b\u003c/span\u003e; Liu \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e). On the one hand, there is a lack of further comprehensive evaluation index system design in the coupling evaluation method, and there are problems of indicator inconsistency and different data types in the analysis process of climate change assessment models and land use suitability evaluations(Tilman et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Song et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Meanwhile, attention should be paid to the uncertainty of global climate change, and how to conduct comparable land use suitability evaluations in multiple scenarios has become a new methodological direction(Karina et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). On the other hand, in the application of research areas, it is necessary to expand to a larger scope of global ecologically fragile areas, identify global climate change sensitive areas, and take more targeted governance measures for mitigating and adapting to climate change(Garnett et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Schirpke et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In summary, it is urgent to explore a research path that couples climate change research with land use suitability evaluation(Ostrom \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e). Firstly, a basic model of climate change should be established through multi scenario simulations to address the uncertainty of climate change(Zhang et al., 2008). Secondly, it is necessary to strengthen the connection and complementarity of land suitability evaluation indicators and climate change indicators, and to adapt to the needs of short-term, medium-term, and long-term time scale analysis at the regional scale(Wang et al., 2011; Shi et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). To sum up, land suitability assessment needs to gradually expand the new scenarios of climate change application path, and climate change research also needs to further strengthen the connection and support with the traditional land use assessment system.\u003c/p\u003e \u003cp\u003eThis study combines traditional land use suitability evaluation with climate change simulation results, aiming to answer the scientific question of how land suitability in the Agro-Pastoral Transitional Zone of northern China will change under multiple climate change scenarios in the future. This study analyzes the suitability of agricultural and pastoral land use in the northern ecotone of China under high, moderate, and low emission scenarios based on CMIP6 climate change multi scenario prediction data. The research results can directly serve regional agricultural and animal husbandry development planning and climate resilience construction, while expanding the application scenarios of climate change simulation results, and further enriching the organizational methods and regional research connotations of land use suitability evaluation.\u003c/p\u003e"},{"header":"2. Data and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data sources\u003c/h2\u003e \u003cp\u003eThe research is conducted based on a multi-source data system, involving various data such as climate, land use, soil, terrain, etc. Here, some data sources will be clarified. In the data preprocessing stage, the raster data is resampled to a spatial resolution of 1km to support comprehensive analysis. Vector data is screened for geometric topology errors and stored as a whole to support comprehensive spatial analysis. Some meteorological station data research uses Kriging interpolation for spatial interpolation processing. The data used in the research institute are all open source data with no confidentiality requirements. Their sources can be traced and downloaded, and they have standardization and scientificity, making them highly applicable to this study.\u003c/p\u003e \u003cp\u003eTable.1 Research basic data connotation and source\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eData name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eData content\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrecision\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eData sources\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eData purpose\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal land cover/use data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGlobal land cover/use database for the years 2000, 2005, 2010, 2015, and 2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpatial resolution 30 meter raster data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://storage.googleapis.com/earthenginepartners-hansen/GLCLU2000-2020/v2/download.html\u003c/span\u003e\u003cspan address=\"https://storage.googleapis.com/earthenginepartners-hansen/GLCLU2000-2020/v2/download.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIdentification of agro-pastoral ecotone and analysis of land use evolution characteristics\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic data of climate elements\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGlobal annual average temperature and precipitation spatial distribution database, china land annual precipitation frequency distribution parameter dataset, china meteorological element average status spatial interpolation dataset (annual precipitation, annual evaporation, annual average temperature) from 1960 to 2020, global coupled model comparison project (CMIP6) data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpatial resolution 1km raster data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://giovanni.gsfc.nasa.gov\u003c/span\u003e\u003cspan address=\"https://giovanni.gsfc.nasa.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gpm.nasa.gov/data/imerg/precipitation-climatology/\u003c/span\u003e\u003cspan address=\"https://gpm.nasa.gov/data/imerg/precipitation-climatology/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.resdc.cn/DOI/DOI.aspx?DOIID=39\u003c/span\u003e\u003cspan address=\"https://www.resdc.cn/DOI/DOI.aspx?DOIID=39\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pcmdi.llnl.gov/CMIP6/\u003c/span\u003e\u003cspan address=\"https://pcmdi.llnl.gov/CMIP6/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSupporting the identification of the world's agro pastoral ecotone and the simulation analysis of global climate scenarios\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTerrain data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpatial distribution data of altitude in China (DEM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpatial resolution 90 meter raster data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.resdc.cn/data.aspx?DATAID=284\u003c/span\u003e\u003cspan address=\"https://www.resdc.cn/data.aspx?DATAID=284\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSupporting the evaluation of land use suitability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoil data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina soil texture distribution database, soil organic matter content database, soil layer thickness database\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpatial resolution 1km raster data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003egisrs.cn/index.html\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eResearch on supporting regional scale land suitability evaluation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdministrative Divisions and Policy Reports\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eData from various provinces, cities, and county-level administrative regions in China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2015 Vector data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.resdc.cn/\u003c/span\u003e\u003cspan address=\"https://www.resdc.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.stats.gov.cn\u003c/span\u003e\u003cspan address=\"https://www.stats.gov.cn\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mnr.gov.cn\u003c/span\u003e\u003cspan address=\"https://www.mnr.gov.cn\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAssist in delineating the spatial scope of the agricultural pastoral transition zone and conducting spatial statistics\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Identification of research area\u003c/h2\u003e \u003cp\u003eBased on the comprehensive delineation of climatic and administrative factors, the Agro-Pastoral Transitional Zone in northern China is defined. The climate elements are defined as the northwest and southeast boundaries of the Agro-Pastoral Transitional Zone, with annual precipitation ranging from 250 to 450 mm, dryness index ranging from 1 to 2, and precipitation variability ranging from 15% to 30%. This study overlaid the regions defined by climate with administrative regions, based on the principle of relatively complete administrative regions while ensuring the integrity of social and economic data statistical units. The research area was designated as 793800 square kilometers, spanning 9 provinces (cities or autonomous regions) including inner mongolia autonomous region, heilongjiang province, jilin province, hebei province, beijing, shanxi province, shaanxi province, ningxia hui autonomous region, and gansu province. Due to the significant spatial differentiation of the Agro-Pastoral Transitional Zone in northern China in terms of longitude, the research area will be divided into three parts: the northeast section, the north China section, and the northwest section. Specifically, the administrative boundary between chifeng city and chengde city will be used as the boundary between the northeast and north China sections of the Agro-Pastoral Transitional Zone, and the north China and northwest sections of the Agro-Pastoral Transitional Zone will be divided by the section from Wulateqianqi in the middle reaches of the Yellow River to lvliang in shanxi province.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Research methods\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Multi scenario climate change prediction model\u003c/h2\u003e \u003cp\u003eThis study first predicts the future climate factors in the Agro-Pastoral Transitional Zone in Northern China, and then analyzes the impact of future climate change on land suitability using a land suitability evaluation framework. In terms of climate change simulation, the IMAGE model, MESSAGE model, and REMIND-MAGPIE model are used to simulate the basic situation of climate change under low, moderate, and high emission scenarios(Semenov et al., 2010; Garcia et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Dong et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe IMAGE model, also known as the Integrated Model to Assess the Greenhouse Effect, is a comprehensive assessment model for global climate change. Developed by the dutch environmental assessment agency in the 1980s, it is one of the comprehensive models adopted by the intergovernmental panel on climate change's special report on emission scenarios. It includes three modules: energy industry system, land environment system, and atmospheric ocean system. Among them, the greenhouse gas emission scenarios related to energy are calculated based on the Target Image Model of Energy Regional(TIMER). The IMAGE model considers the impact of technological and energy price changes on energy intensity, fuel structure, and non mineral fuel penetration rate, and describes technological changes through spontaneous energy efficiency improvements and price induced energy efficiency improvements.\u003c/p\u003e \u003cp\u003eThe MESSAGE model, also known as the \"Model for Energy Supply System Alternatives and their General Environmental Impact\", is a medium-long term dynamic linear programming energy technology model. Developed by the international institute for applied systems analysis, the objective function is to seek cost minimization of energy systems under different constraints. Suitable for medium and long-term energy planning, energy policy scenario analysis, and supporting climate change analysis. This model can obtain the resource technology that meets specific terminal service requirements with the minimum cost when running. The model has incorporated endogenous technological learning into the analysis framework, and the cost of technological investment decreases with the increase of accumulated technological experience. Its parameter settings can adapt to the assessment needs of the long-term energy structure transformation in moderate emission scenarios for climate change effects.\u003c/p\u003e \u003cp\u003eThe REMIND model, also known as the Regional Model of Investments and Development, is a modular and open-source multi regional model that includes detailed descriptions of the economy, climate system, and energy sectors. It solves the cross temporal and spatial Pareto optimality of economic and energy investment within the model area, fully considering the trade of goods, energy carriers, and emission quotas between regions. REMIND allows for the analysis of technology choices and policy recommendations for climate mitigation. The macroeconomic core of REMIND is the Ramsey type optimal growth model, in which temporal global welfare is optimized under equilibrium constraints.\u003c/p\u003e \u003cp\u003eThe MAGPIE model, also known as the \"Model of Agricultural Production and its Impact on the Environment,\" is a global local equilibrium model for the land use sector used to assess competition for land and water and the related consequences for sustainable development under future scenarios of food, energy, and material demand, production, climate change impacts, greenhouse gas emissions reduction, and different land related policies. It operates in recursive dynamic mode, providing geographic data about biophysical conditions at a resolution of 0.5 degrees, and incorporating spatially explicit information about biophysical constraints into the economic decision-making process. The land types available in the MAGPIE model include farmland, pastures, forests, other land (including non forest natural vegetation, abandoned agricultural land, and deserts), and settlements. Farmland (rain fed and irrigated), pastures, forests, and other land are endogenously determined, while the area of settlements is assumed to remain constant over time. Farmland includes the cultivation of different crop types (such as temperate and tropical grains, corn, rice, oilseeds, roots), rain fed and irrigation systems, as well as two second-generation bioenergy crop types (herbaceous and woody).\u003c/p\u003e \u003cp\u003eThe research on predicting future climate factors revolves around precipitation and accumulated temperature greater than or equal to 10 ℃, using meteorological data from 1961 to 2020 as the training base period data, simulating the climate factor conditions in 2030 (short-term), 2050 (medium-term), and 2100 (long-term). The simulation period is divided into low emission interference, moderate emission interference, and high emission interference scenarios:\u003c/p\u003e \u003cp\u003e(1) Low emission interference (corresponding to the sustainable model of social ecological system)\u003c/p\u003e \u003cp\u003eThis scenario was simulated by the Integrated Climate Change Assessment Model (IMAGE 3.0). The scenario parameters are set to stabilize radiation stress at 2.8 W/m\u003csup\u003e2\u003c/sup\u003e by 2100, and the global average temperature rise remains stable at around 1.8 ℃. The social subsystem maintains sustainable population growth, high-speed economic growth, and mechanization and rapid progress of agricultural technology. Traditional fossil fuels have basically achieved sustainable substitution, low-carbon lifestyles have been popularized, biodiversity loss has been effectively alleviated, animal product consumption has decreased, and global sustainable development cooperation is stable in the long run.\u003c/p\u003e \u003cp\u003e(2) Moderate emission disturbance (corresponding to limited transition mode of social ecological system)\u003c/p\u003e \u003cp\u003eThis scenario is based on the simulation of alternative energy supply systems and environmental impact models (MESSAGE). The scenario parameters are set to stabilize radiation stress at 7.3 W/m\u003csup\u003e2\u003c/sup\u003e by 2100, and the global average temperature rise remains stable at around 3.6 ℃. Carbon dioxide emissions have roughly doubled compared to 2020 levels, with emissions and temperatures steadily increasing, and traditional fossil fuels partially replacing them. Population growth remains at a moderate level, low-carbon lifestyles have been partially popularized, and biodiversity loss has been partially alleviated. International competition is becoming increasingly fierce, and sustainable development cooperation is limited. The focus is shifting towards national strategic security and ensuring domestic food supply.\u003c/p\u003e \u003cp\u003e(3) High emission interference (corresponding to traditional growth patterns of social ecological systems)\u003c/p\u003e \u003cp\u003eSimulate the Regional Investment and Development Model (REMIND) and Agricultural Production and Environmental Impact Model (MAGPIE) for this scenario. The scenario parameters are set to approximately double the carbon dioxide emissions from 2020 levels by 2050. By 2100, the global average temperature will rise by around 4.4 ℃, and radiation stress will remain stable at 8.7 W/m\u003csup\u003e2\u003c/sup\u003e. The global economy is steadily growing, with traditional fossil energy use being replaced at a lower rate, and the growth mode maintaining a fossil energy intensive path. The population maintains a relatively high growth rate, the popularization of low-carbon lifestyles is limited, and the rate of biodiversity loss is fast. The level of international sustainable development cooperation is relatively low, and international competition is fierce.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Land use suitability assessment method\u003c/h2\u003e \u003cp\u003eThe land use suitability assessment method is an evaluation of the suitability of land for a certain use under certain purposes(FAO, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). It usually uses the comprehensive indicator method to study the suitability, suitability, and limitations of land for the intended use based on its natural and socio-economic attributes. The basic principle of land suitability evaluation is to combine the natural and socio-economic elements of land as identification indicators under the existing level of productivity management and specific land use conditions(Wu et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2008a\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2008b\u003c/span\u003e). By examining and comprehensively analyzing the suitability, quality, and limitations of land for various purposes, the land's use and quality can be classified and graded(Medeiros et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLand use is based on the natural resource background(Wang et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). As a composite land use area, climate change significantly affects the potential characteristics and spatial distribution of land use in the Agro-Pastoral Transitional Zone. Analyzing the impact of climate change on land suitability can provide a basic reference for scientific planning of national land space and adjustment of agricultural and pastoral structure, and enhance the climate resilience of agricultural and pastoral production in the Agro-Pastoral Transitional Zone. Based on the basic characteristics of the transitional zone between agriculture and animal husbandry in northern China, a suitability evaluation system for agriculture and animal husbandry is established according to local conditions to support future trend analysis of agricultural and animal husbandry suitability under climate factor changes.\u003c/p\u003e \u003cp\u003eTable.2 Evaluation system for land use suitability of the Agro-Pastoral Transitional Zone in Northern China\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eType of suitability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eClimatic conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eTopographic conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eSoil conditions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnnual average precipitation (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAccumulated temperature\u0026thinsp;\u0026ge;\u0026thinsp;10 ℃ (℃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSlope (\u0026deg;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAltitude (m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSoil texture\u003c/p\u003e \u003cp\u003e(silt content,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSoil organic matter content (g/kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEffective soil layer thickness (cm)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eAgriculture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e≧\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e≧\u0026thinsp;3000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e≦\u0026thinsp;200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60\u0026ndash;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e≧\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e≧\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500\u0026ndash;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2800\u0026ndash;3000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e200\u0026ndash;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u0026ndash;60, 65\u0026ndash;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e50\u0026ndash;100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e400\u0026ndash;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2500\u0026ndash;2800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u0026ndash;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e500\u0026ndash;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40\u0026ndash;50, 70\u0026ndash;75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e350\u0026ndash;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2000\u0026ndash;2500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1000\u0026ndash;2500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;40, 75\u0026ndash;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;2500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e≧\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eLivestock farming\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e≧\u0026thinsp;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e≧\u0026thinsp;2500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e≦\u0026thinsp;200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60\u0026ndash;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e≧\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e≧\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e400\u0026ndash;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2200\u0026ndash;2500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e≦\u0026thinsp;1,3\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e200\u0026ndash;800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u0026ndash;60, 70\u0026ndash;75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e50\u0026ndash;80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300\u0026ndash;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2000\u0026ndash;2200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u0026ndash;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e800\u0026ndash;1200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40\u0026ndash;50, 75\u0026ndash;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u0026ndash;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e200\u0026ndash;300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1500\u0026ndash;2000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1200\u0026ndash;3000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;40, 80\u0026ndash;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e≧\u0026thinsp;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable.3 Connotation of suitability level for agricultural and pastoral land use of the Agro-Pastoral Transitional Zone in Northern China\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuitability type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSuitability level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuitability characteristics\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eAgricultural land use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCompletely suitable. The land is flat, the soil layer is deep and fertile, and the water and heat are extremely good. It can be stably used for rain fed crop planting and cultivation without the need for special land protection measures.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHighly suitable. The land is generally flat, with thick and fertile soil layers, excellent water and heat conditions, and can be stably used for rain fed crop planting and cultivation without the need for special land protection measures.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate suitability. Individual natural factors have a certain degree of constraint. The land is relatively flat, the soil layer thickness is average, the fertility is average, and the water and heat conditions are average. It can be used for rain fed crop planting and cultivation, but certain land protection measures need to be taken.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBasically suitable. There are one or more limiting factors, such as a certain slope of the land, relatively thin soil layers or lack of nutrients, insufficient water and heat conditions, which can be limited for rain fed crop planting and cultivation, and poor stability. Strict land protection measures are required for land use.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot suitable. There are one or more serious limiting factors that prevent the planting and cultivation of rain fed crops. Avoid damaging natural vegetation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003elivestock farming\u003c/p\u003e \u003cp\u003eland use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCompletely suitable. The land is flat, the soil layer is deep and fertile, the water and heat are extremely good, and it can be stably used for natural grass growth. It has a large livestock carrying capacity and does not require special land protection measures.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHighly suitable. The land is generally flat, with thick and fertile soil layers, excellent water and heat conditions, and can be stably used for natural grass growth and grazing. It has a large carrying capacity and does not require special land protection measures.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate suitability. Individual natural factors have a certain degree of constraint. The land is relatively flat, the soil layer thickness is average, the fertility is average, and the water and heat conditions are average. It can be used for natural grass growth and grazing, and the carrying capacity is average. Therefore, certain land protection measures need to be taken.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBasically suitable. There are one or more limiting factors, such as a certain slope of the land, relatively thin soil layers or lack of nutrients, insufficient water and heat conditions, limited use for natural grass growth and grazing, limited carrying capacity, and poor stability. Strict land protection measures need to be taken.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot suitable. There are one or more serious limiting factors that prevent the growth of natural grass. Avoid damaging natural vegetation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Result analysis","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Analysis of multi scenario climate change in the Agro-Pastoral Transitional Zone in northern China\u003c/h2\u003e \u003cp\u003eIn terms of annual average precipitation, under the low emission scenario, the average precipitation in the Agro-Pastoral Transitional Zone of northern China in 2030, 2050, and 2100 is 322.16mm, 433.33mm, and 287.49mm, respectively, showing a trend of first increasing and then decreasing, and the overall average precipitation tends to decrease.\u003c/p\u003e \u003cp\u003eIn terms of spatial distribution, the average precipitation in the northeast and north China segments shows a regional increase from 2030 to 2050. The 400mm precipitation contour line expands westward as a whole, while the 400mm precipitation contour line shrinks significantly eastward from 2050 to 2100. The aridification characteristics of the northwest and north China segments of the Agro-Pastoral Transitional Zone are evident In terms of spatial distribution, the average precipitation in the northeast and north China segments shows a regional increase from 2030 to 2050. The 400mm precipitation contour line expands westward as a whole, while the 400mm precipitation contour line shrinks significantly eastward from 2050 to 2100. The aridification characteristics of the northwest and north China segments of the Agro-Pastoral Transitional Zone are evident.\u003c/p\u003e \u003cp\u003eUnder the moderate emission scenario, the average precipitation in the Agro-Pastoral Transitional Zone of northern China in 2030, 2050, and 2100 is 386.39mm, 515.42mm, and 446.44mm, respectively, showing a trend of first increasing and then decreasing, and the overall average precipitation tends to increase. In terms of spatial distribution, the average precipitation in the northeast and north China sections shows a regional increase from 2030 to 2050. The 400mm precipitation contour line expands westward as a whole, while the precipitation in the Greater Khingan Range of the northeast section and the Yanshan area of the north China section increases overall. From 2050 to 2100, the 400mm precipitation contour line shrinks slightly eastward and stabilizes in the central part of the north China section, namely the Yinshan-Yanshan line. The wetting characteristics of the northeast and north China sections are obvious.\u003c/p\u003e \u003cp\u003eUnder the scenario of high emissions, the average precipitation in the Agro-Pastoral Transitional Zone of northern China in 2030, 2050, and 2100 is 491.74mm, 337.10mm, and 422.32mm, respectively, showing a trend of first decreasing and then increasing. The overall average precipitation tends to decrease. In terms of spatial distribution, the northeastern and eastern parts of the Agro-Pastoral Transitional Zone in 2030 will show obvious wetting characteristics, while the 400mm precipitation line will remain stable in the central part of the North China section. In 2050, the southern part of the Northeast section and the northern part of the North China section will show aridification characteristics. The southern part of the North China section and the southern part of the Northwest section near the southern boundary of the Agro-Pastoral Transitional Zone will show obvious wetting characteristics. The 400mm and other precipitation lines will show a multi-stage distribution pattern, and the wetting areas will be divided into two parts: the north and south. In 2100, the southern part of the Northeast The northern part of the section exhibits wetting characteristics, with precipitation lines of 400mm and others connected as a whole, distributed along the western foothills of the Greater Khingan Range, Yanshan Mountains, and Yinshan Mountains.\u003c/p\u003e \u003cp\u003eOverall, the future trend of annual precipitation in the low and moderate emission scenarios of the Agro-Pastoral Transitional Zone in northern China is relatively similar, with the highest difference in average precipitation observed in the high emission model; In terms of spatial distribution, precipitation has always maintained an overall pattern of \"more in the east and less in the west\". The precipitation changes in the northern and northwestern sections of the Agro-Pastoral Transitional Zone are relatively small, while the dry and wet changes in the northern and southern parts of the northeastern sections are large.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e(a. 2030; b. 2050; c. 2100), moderate emission scenario (d. 2030; e. 2050; f. 2100), high emission scenario (g. 2030; h. 2050; i. 2100) distribution map of annual precipitation forecast(mm)\u003c/p\u003e \u003cp\u003eIn terms of accumulated temperature greater than or equal to 10℃, under low emission scenario, the average accumulated temperature greater than or equal to 10℃ in the Agro-Pastoral Transitional Zone of northern China in 2030, 2050, and 2100 is 2374.23℃, 2575℃, and 2494.56℃, respectively. The accumulated temperature changes show an increasing and then decreasing trend, and the average accumulated temperature overall shows an increasing characteristic. In terms of spatial distribution, the 2000℃ accumulated temperature line continues to shrink northward from 2030 to 2050, and there is a slight southward expansion of the 2000℃ accumulated temperature line in the southern part of the northeast section from 2050 to 2100, while the accumulated temperature in the northwest section remains stable above 3000℃.\u003c/p\u003e \u003cp\u003eUnder the moderate emission scenario, the average accumulated temperature greater than or equal to 10 ℃ in the Agro-Pastoral Transitional Zone of northern China in 2030, 2050, and 2100 is 2273.10℃, 2376.96℃, and 2948.46℃, respectively. The accumulated temperature changes show a continuous increasing trend, and the overall average accumulated temperature shows a significant increase. In terms of spatial distribution, the 2000℃ accumulated temperature line continuously shrinks in the southern part of the northeast section and the eastern part of the north China section from 2030 to 2050, and most areas in the northeast section are occupied by areas with accumulated temperatures below 2000℃. However, between 2050 and 2100, the 2000℃ accumulated temperature line shrinks significantly to the north, and the areas with accumulated temperatures greater than 2000℃ expand significantly in the western part of the north China section and the eastern foot of the Greater Khingan Range.\u003c/p\u003e \u003cp\u003eUnder the high emission scenario, the average accumulated temperature greater than or equal to 10℃ in the Agro-Pastoral Transitional Zone of northern China in 2030, 2050, and 2100 is 2130℃, 2081.38℃, and 3047.42℃, respectively. The accumulated temperature changes show a trend of first decreasing and then increasing, and the overall average accumulated temperature shows a significant increase. In terms of spatial distribution, the 2000℃ accumulated temperature line will be stably distributed along the Agro-Pastoral Transitional Zone-Yanshan-Yinshan line from 2030 to 2050, and the area of accumulated temperature below 1500℃ will continue to expand in the northeast section, while the area of accumulated temperature above 3000℃ in the northwest section will significantly decrease. From 2050 to 2100, the 2000℃ accumulated temperature line will shrink northward to the northernmost part of Hulunbuir region. Except for the Greater Khingan Range, Yanshan, and Yinshan areas, most of the Agro-Pastoral Transitional Zone, except for the Greater Khingan Range. The accumulated temperature in the region is above 3000℃.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOverall, the accumulated temperature distribution in the Agro-Pastoral Transitional Zone of northern China presents a spatial characteristic of high in the south and low in the north. The accumulated temperature changes in the low emission mode are relatively stable, while the accumulated temperature changes in the moderate and high emission modes are more extreme. The southern part of the northeast section and the eastern part of the north China section are the key areas of alternating cold and warm changes.\u003c/p\u003e \u003cp\u003eBased on the changes in the dual factors of precipitation and accumulated temperature, it can be seen that in the low emission scenario of 2100, an increase in accumulated temperature and a decrease in precipitation will occur simultaneously, and the process of drying and heating is prone to cause drought disasters. The overall performance of the moderate emission scenario is a warming and humidification process. The high emission scenario is prone to dry and cool processes in the north China region by 2050, and will exhibit warm and humid processes by 2100.\u003c/p\u003e \u003cp\u003e3.2 Analysis of land suitability evolution in the Agro-Pastoral Transitional Zone in northern China under multiple climate change scenarios\u003c/p\u003e \u003cp\u003eBased on the evaluation results of land use suitability for agriculture and animal husbandry in the Agro-Pastoral Transitional Zone of Northern China, there are differences in the quantity and spatial distribution of land suitability levels for agriculture and animal husbandry under different scenarios in the three time periods of 2030, 2050, and 2100, as follows:\u003c/p\u003e \u003cp\u003eIn terms of agricultural land suitability, under the low emission scenario, the proportion of land area unsuitable for agricultural land use in the three time periods of 2030, 2050, and 2100 shows a quantitative structural change characteristic of \"first decreasing and then increasing\", and the proportion of land area unsuitable for agricultural land use in 2100 is the highest in previous years. In terms of spatial distribution, the areas suitable for agricultural land use are concentrated in the central eastern part of the Agro-Pastoral Transitional Zone, near the southern boundary. By 2050, the suitable agricultural areas will expand to a certain extent, but by 2100, they will sharply shrink and be concentrated in the eastern part of the Agro-Pastoral Transitional Zone, east of the Greater Khingan Range. The rest of the areas are not suitable for agricultural land use.\u003c/p\u003e \u003cp\u003eUnder the moderate emission scenario, the proportion of land area unsuitable for agricultural land use in the three time periods of 2030, 2050, and 2100 shows a \"continuous decrease\" in quantity and structural changes, and the proportion of land area unsuitable for agricultural land use in 2100 is the smallest in previous years, while the proportion of land area suitable for moderate use has increased significantly. In terms of spatial distribution, there will be a large-scale expansion of suitable agricultural areas in the central and eastern regions of the Agro-Pastoral Transitional Zone in 2050 and 2100. Due to the improvement of heat conditions, the suitability of agricultural land use in the northeastern Greater Khingan Range region and the Hulunbeir Plateau region of the Agro-Pastoral Transitional Zone will increase significantly. The western region of the Agro-Pastoral Transitional Zone has long been in an agricultural unsuitable area.\u003c/p\u003e \u003cp\u003eUnder the high emission scenario, the proportion of land area unsuitable for agricultural land use in the three time periods of 2030, 2050, and 2100 shows a \"continuous decrease\" in quantity and structural changes. In addition, the proportion of land area unsuitable for agricultural land use in 2100 is the smallest in previous years, while the proportion of areas suitable for moderate and basic use has increased significantly. In terms of spatial distribution, the expansion of agricultural suitable areas from 2030 to 2050 is mainly concentrated on the southern side of the central and western regions of the Agro-Pastoral Transitional Zone, as well as some areas in the northeast. By 2100, the scope of agricultural suitable areas in the western part of the Agro-Pastoral Transitional Zone will significantly shrink, while there will be a large-scale expansion of agricultural suitable areas in the central and eastern regions.\u003c/p\u003e \u003cp\u003eOverall, in terms of the quantity structure of agricultural suitability, the proportion of suitable agricultural areas in the moderate emission scenario in the near future (2030) is the best, the proportion of suitable agricultural areas in the low emission scenario in the medium term (2050) is the best, and the proportion of suitable agricultural areas in the moderate emission scenario in the long term (2100) is the best. In terms of spatial distribution, the southern central region of the Agro-Pastoral Transitional Zone, as well as the eastern Greater Khingan Range and Kerqin regions, are the areas with the strongest fluctuations in agricultural suitability, making them the most sensitive to climate impacts on agricultural land use.\u003c/p\u003e \u003cp\u003eIn terms of land suitability for animal husbandry, under the low emission scenario, the proportion of land area unsuitable for animal husbandry land use in the three time periods of 2030, 2050, and 2100 shows a quantitative structural change characteristic of \"first decreasing and then increasing\", and the proportion of land area unsuitable for animal husbandry land use in 2100 is the highest in previous years. In terms of spatial distribution, there are a large number of contiguous suitable areas for animal husbandry concentrated in the southern and central parts of the Agro-Pastoral Transitional Zone, as well as in the eastern foothills of the Greater Khingan Range. In 2050, the central and western regions of the Agro-Pastoral Transitional Zone will show a slight expansion of suitable areas for animal husbandry, while the eastern region will mainly see an improvement in the level of suitability for animal husbandry. By 2100, the basic suitable areas for animal husbandry in the central and western regions of the Agro-Pastoral Transitional Zone will significantly shrink, while the suitable levels in the eastern region will show a significant decline.\u003c/p\u003e \u003cp\u003eUnder the moderate emission scenario, the proportion of land area unsuitable for animal husbandry land use in the three time series of 2030, 2050, and 2100 shows a \"continuous decrease\" in quantity and structural changes. In addition, the proportion of land area unsuitable for animal husbandry land use in 2100 is the smallest in previous years, and the proportion of medium and basic suitable areas for animal husbandry has increased significantly. In terms of spatial distribution, the suitable areas for animal husbandry land use show an overall characteristic of \"expanding north and extending west\" from 2030 to 2100. By 2100, except for the western part of the Agro-Pastoral Transitional Zone, which is still in the unsuitable area for animal husbandry land use, all other areas are suitable for animal husbandry land use. The suitability level for animal husbandry in most areas of the southern and eastern parts of the Agro-Pastoral Transitional Zone continues to improve, and the suitable range has reached the largest in previous years.\u003c/p\u003e \u003cp\u003eUnder the high emission scenario, the proportion of land area unsuitable for animal husbandry land use in the three time periods of 2030, 2050, and 2100 shows a \"continuous decrease\" in quantity and structural changes. In addition, the proportion of land area unsuitable for animal husbandry land use in 2100 is the smallest in previous years, and the proportion of medium and basic suitable areas for animal husbandry has increased significantly. In terms of spatial distribution, the suitable areas for land use in animal husbandry exhibit an overall characteristic of \"expanding north and extending west\" from 2030 to 2100. The speed and scale of expansion of the suitable areas towards the western part of the Agro-Pastoral Transitional Zone are greater than those of the moderate emission mode, while the unsuitable areas for animal husbandry shrink to the northern and central parts of the Agro-Pastoral Transitional Zone.\u003c/p\u003e \u003cp\u003eOverall, in terms of the quantity structure of suitability for animal husbandry, the proportion of suitable agricultural areas in the moderate emission scenario in the near future (2030) is the best, the proportion of suitable agricultural areas in the low emission scenario in the medium term (2050) is the best, and the proportion of suitable agricultural areas in the high emission scenario in the long term (2100) is the best. The moderate emission model has a slightly lower proportion of suitable agricultural areas than the high emission model, but has more advantages in suitability levels. In terms of spatial distribution, the southern western region, central hinterland region, and eastern Greater Khingan Range region of the Agro-Pastoral Transitional Zone are the areas with the strongest fluctuations in pastoral suitability, that is, the areas where pastoral land use is most sensitive to climate impact.\u003c/p\u003e \u003cp\u003eBased on the comprehensive evaluation of the suitability of agriculture and animal husbandry, the climate sensitive area for agricultural land use suitability is generally located south of the climate sensitive area for animal husbandry land use suitability in terms of spatial position. The climate sensitive area for agricultural land use suitability is a long-term stable suitable area for animal husbandry land use. Therefore, the agricultural land use with strong fluctuations in the edge zone and the animal husbandry land use with natural stability form a highly overlapping area in the central southern part of the Agro-Pastoral Transitional Zone and the eastern Kerqin region, forming a long-term competition and mosaic distribution pattern for agricultural and animal husbandry land use.\u003c/p\u003e \u003cp\u003eClimate change is related to the natural conditions of land use around the world. Overall, due to the fact that the Agro-Pastoral Transitional Zone in northern China is located in a mid latitude arid and semi-arid region, global warming can help improve the heat conditions in the central and eastern parts of the ecotone under moderate and high emission patterns, thereby enhancing the suitability of agriculture and animal husbandry. However, in the western part of the ecotone, natural conditions will further strengthen the constraints, and the suitability of agricultural and animal husbandry land use cannot achieve long-term stable improvement. From the perspective of global climate governance, the Paris Climate Agreement proposes that the main goal of controlling global warming is to keep the average global temperature rise within 2℃ before industrialization, preferably within 1.5℃, by the end of the 21st century. This goal is comparable to the low emission model set in research. According to this goal, by 2100, there will be a large-scale shrinkage in the suitability of agricultural and pastoral land use in the Agro-Pastoral Transitional Zone in northern China, with reduced precipitation being the main driving force behind this phenomenon. In the process of achieving this goal, 2030 and 2050 will require more reference to moderate emission models for climate governance.\u003c/p\u003e \u003cp\u003eFor agricultural climate sensitive areas, future land use should be optimized and implemented in conjunction with terrain zoning. Strengthen the construction of irrigation and drainage facilities in the valley area to enhance its ability to resist natural climate disasters. Mountainous and hilly areas should focus on rain fed agriculture with irrigation as a supplement, and build rainwater storage facilities such as water cellars to enhance the climate resilience of agricultural production. Climate sensitive areas in animal husbandry need to increase the construction of artificial grasslands, develop grassland irrigation and water storage systems according to local conditions, in order to improve and stabilize grassland carrying capacity and enhance the stability of grassland production under drought conditions. The dual climate sensitive areas of agriculture and animal husbandry need to strictly control the development of arable land, designate ecological protection areas, and construct ecological barrier belts to enhance the interception function of sandstorms and the conservation function of river water sources.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable.4 Proportion of agricultural suitability evaluation at different levels in the Agro-Pastoral Transitional Zone in northern China\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabd\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAgricultural suitability evaluation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eLow emission scenario\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompletely suitable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHighly suitable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate suitability\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBasically suitable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUnsuitable\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.73%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88.49%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.59%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64.60%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92.72%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAgricultural suitability evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eModerate emission scenario\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompletely suitable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHighly suitable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate suitability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBasically suitable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUnsuitable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.26%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84.53%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.88%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73.13%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.89%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37.42%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAgricultural suitability evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eHigh emission scenario\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompletely suitable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHighly suitable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate suitability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBasically suitable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUnsuitable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.59%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.59%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88.81%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.86%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.65%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75.49%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.38%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.03%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46.35%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable.5 Proportion of animal husbandry suitability evaluation at different levels in the Agro-Pastoral Transitional Zone in northern China\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabe\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAnimal husbandry suitability evaluation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eLow emission scenario\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompletely suitable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHighly suitable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate suitability\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBasically suitable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUnsuitable\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.31%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.41%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.28%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.14%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.51%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e65.07%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAnimal husbandry suitability evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eModerate emission scenario\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompletely suitable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHighly suitable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate suitability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBasically suitable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUnsuitable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.42%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.05%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.11%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.66%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.93%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46.81%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.44%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.12%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.86%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.58%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAnimal husbandry suitability evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eHigh emission scenario\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompletely suitable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHighly suitable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate suitability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBasically suitable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUnsuitable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.09%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.76%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.58%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61.57%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.32%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.72%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.23%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.04%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Discussion","content":"\u003cp\u003eThe Agro-Pastoral Transitional Zone in northern China is located in the tail area affected by the summer monsoon, and its agricultural and animal husbandry production is highly marginalized due to the criticality of climatic factors. There are significant differences in the suitability of agricultural and pastoral production in the transitional zone between agriculture and animal husbandry in northern China under future differentiated climate change scenarios. Overall, the suitability of agricultural and pastoral land use has been greatly improved under moderate emission scenarios, while the improvement in suitability of agricultural and pastoral land use is relatively low under low emission scenarios. The Agro-Pastoral Transitional Zone in northern China is located in the temperate zone of the northern hemisphere, which benefits from the improvement of heat conditions caused by global climate change and promotes the optimization of agricultural and animal husbandry production conditions. The improvement degree of agricultural and animal husbandry production conditions is relatively high under moderate and high emission scenarios. The average proportion of unsuitable agricultural areas under moderate emission mode is 65.03%, the average proportion of unsuitable animal husbandry areas is 37.83%, the average proportion of unsuitable agricultural areas under high emission mode is 70.22%, and the average proportion of unsuitable animal husbandry areas is 36.44%. However, under the high emission mode, the global trend towards traditional fossil energy growth is clearly not in line with the action goals adopted by international climate change cooperation. Therefore, the high emission mode lacks practicality in the international community. Under the low emission mode, the average proportion of unsuitable areas for agriculture is 81.94%, and the average proportion of unsuitable areas for animal husbandry is 50.87%. There has been no significant improvement in the suitability of agricultural and animal husbandry production, and the proportion of unsuitable areas is higher than that under the moderate and high emission modes. Therefore, for the Agro-Pastoral Transitional Zone in northern China, both low and high emission modes are not the optimal models for improving agricultural and animal husbandry production conditions. The moderate emission mode can achieve the maximum improvement in agricultural production conditions, while also matching the basic reality of global climate governance practices.\u003c/p\u003e \u003cp\u003eUnder the scenario of differentiated climate change in the future, different regions in the Agro-Pastoral Transitional Zone in northern China exhibit differentiated responses to climate change. The eastern region of the Agro-Pastoral Transitional Zone benefits from the improvement of accumulated temperature conditions, which enhances its suitability for agricultural and pastoral production. However, the western region of the Agro-Pastoral Transitional Zone, which has abundant heat but scarce precipitation, will experience a decrease in suitability for agricultural and pastoral production. The agricultural climate sensitive areas are concentrated in the southeastern part of the Agro-Pastoral Transitional Zone. The development of agriculture in this region needs to strengthen the construction of agricultural facilities according to local conditions. In the valley areas, the construction of agricultural irrigation and drainage facilities should be strengthened to enhance resilience against uncertain factors of climate change. Moderately promote dryland agriculture in mountainous and hilly areas, plant drought tolerant crops and characteristic grains, build facilities such as rainwater cellars to efficiently utilize and store natural precipitation, and form a characteristic agricultural production model with \"rain fed as the main source and irrigation as the auxiliary\", continuously playing the role of food security guarantee. The climate sensitive areas for animal husbandry are concentrated in the western part of the Agro-Pastoral Transitional Zone, which is susceptible to fluctuations in suitability due to unstable precipitation. Therefore, in the future, when carrying out animal husbandry production, it is necessary to increase the construction of artificial grasslands, develop grassland irrigation and water storage systems according to local conditions, ensure stable grassland production in dry years, and continue to play the role of ensuring the production of animal husbandry products. The dual climate sensitive areas of agriculture and animal husbandry are the key areas of focus for future Agro-Pastoral Transitional Zone. This area is most significantly affected by climate change, and is currently mostly covered by forest land. Due to low accumulated temperature, large-scale agricultural and animal husbandry production cannot be carried out. In the future, the suitability of agricultural and animal husbandry production in this area will be improved during the process of climate warming. In the future, this region needs to establish a land use pattern dominated by forests and grasslands, strictly control farmland cultivation and agricultural development, strengthen regional forest and grassland management and protection through the designation of national parks and ecological protection areas, and build an important ecological barrier zone in northern China.\u003c/p\u003e \u003cp\u003eThe analysis of climate change in research is based on the annual average precipitation and accumulated temperature indicators, which are relatively macroscopic and do not include other climate indicators in the analysis framework. On the one hand, it is limited by the availability of data, and on the other hand, precipitation and accumulated temperature are the most important critical climate elements in the Agro-Pastoral Transitional Zone. The analysis of these two indicators is more suitable for the regional characteristics of the Agro-Pastoral Transitional Zone. When conducting suitability evaluation, the principle of limiting factors is adopted, and the worst level of multiple indicators is used as the final level. However, the limiting ability of climate, terrain, and soil on suitability is different. Whether it is necessary to define the priority order of limiting factors is the focus of subsequent analysis in this study. Future research can add evaluation objects in global regional comparative analysis to enhance global scenario comparison, and further conduct zoning studies within the study area to highlight regional differentiation characteristics and guide regional land use planning and agricultural and animal husbandry production factor allocation.\u003c/p\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eIn terms of future climate change, the low emission scenario and moderate emission scenario in the Agro-Pastoral Transitional Zone of northern China show similar trends in annual precipitation, with the highest range of precipitation observed in the high emission model. In terms of spatial distribution, precipitation has always maintained an overall pattern of \"more in the east and less in the west\". The precipitation changes in the northern and northwestern sections of the Agro-Pastoral Transitional Zone are relatively small, while the dry and wet changes in the northern and southern parts of the northeastern and northeastern sections are significant. The overall distribution of accumulated temperature shows a spatial characteristic of high in the south and low in the north. The accumulated temperature changes in the low emission mode are relatively stable, while the accumulated temperature changes in the moderate and high emission modes are more extreme. The southern part of the northeast section and the eastern part of the north China section are the key areas of alternating cold and warm changes. In the low emission scenario of 2100, both the increase in accumulated temperature and the decrease in precipitation will occur simultaneously, and the drying and heating process is prone to cause drought disasters; The overall performance of the moderate emission scenario is a warming and humidification process; The high emission scenario is prone to dry and cool processes in the North China region by 2050, and will exhibit warm and humid processes by 2100.\u003c/p\u003e \u003cp\u003eThe analysis of land use suitability for agriculture and animal husbandry under multiple climate scenarios found that the climate sensitive area of agricultural land use suitability is generally located south of the climate sensitive area of animal husbandry land use suitability in terms of spatial location. The climate sensitive area of agricultural land use suitability is a suitable area for long-term stable pastoral land use. Therefore, the highly volatile agricultural land use in the marginal zone and the naturally stable pastoral land use form a highly overlapping area in the central southern part of the Agro-Pastoral Transitional Zone and the eastern Kerqin region. Due to the fact that the Agro-Pastoral Transitional Zone in northern China is located in a mid latitude arid and semi-arid region, the response of different areas in the Agro-Pastoral Transitional Zone to climate change varies. Global warming, under moderate and high emission patterns, can help improve the heat conditions in the central and eastern regions of the Agro-Pastoral Transitional Zone in the medium to long term, thereby enhancing the suitability of agriculture and animal husbandry. However, in the western part of the Agro-Pastoral Transitional Zone, it will further strengthen the constraints of natural conditions, especially in terms of unstable precipitation, and the suitability of land use for agriculture and animal husbandry cannot achieve long-term stable improvement.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eK.W. and Y.X. wrote the main manuscript text and F.Z. checked and visualized all charts. Z.D. provided guidance on research methods and data models. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis research was supported by the Assessment Project of Benchmark Land Price for Agricultural Land of State-owned Farms and Ranches in Xing'an League, Inner Mongolia Autonomous Region[grant number 69199032]. We are also grateful for the comments and criticisms of the journal's anonymous reviewers and our colleagues.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data used in the study are publicly available. New data generated from the study can be made publicly accessible upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbiodun, B. J., Lawal, K. A., Salami, A. T. \u0026amp; Abatan, A. A. Potential infuences of global warming on future climate and extreme events in Nigeria. \u003cem\u003eReg. Envriron. Chang.\u003c/em\u003e, 1\u0026ndash;15. (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBriner, S., Elkin, C., Huber, R. \u0026amp; Gr\u0026ecirc;t-Regamey, A. \u003cem\u003eAssessing the impacts of economic and climate changes on land-use in mountain regions: A spatial dynamic modeling approach\u003c/em\u003e Vol. 149, 50\u0026ndash;63 (Agriculture, Ecosystems \u0026amp; Environment, 2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDale, V. H. The relationship between land use change and climate change: Ecological applications. \u003cem\u003eEcol. Soc. Am.\u003c/em\u003e \u003cb\u003e7\u003c/b\u003e (3), 753\u0026ndash;769 (1997).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDong, N. et al. Land use projections in China under global socioeconomic and emission scenarios: utilizing a scenario-based land-use change assessment framework. \u003cem\u003eGlob Environ. Change\u003c/em\u003e. \u003cb\u003e50\u003c/b\u003e, 164\u0026ndash;177 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErik, L. \u0026amp; Ding, C. R. Assessing farmland protection policy in China. \u003cem\u003eLand. Use Policy\u003c/em\u003e. \u003cb\u003e25\u003c/b\u003e, 59e68 (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFan, X., Ma, Z., Yang, Q., Han, Y. \u0026amp; Mahmood, R. Land use/land cover changes and regional climate over the loess plateau during 2001\u0026ndash;2009, Part II: Interrelationship from observations. \u003cem\u003eClim. Change\u003c/em\u003e. \u003cb\u003e129\u003c/b\u003e (3), 441\u0026ndash;455 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFang, X. Q. Decline of pre-historical agriculture and formation of farming grazing transitional zone in north China: a view from climatic changes. \u003cem\u003eJ. Nat. Resour.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e (3), 212e218 (1997).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFAO. Guidelines: Land Evaluation for Rainfed Agriculture. Soils Bulletin No. 32, Food and Agriculture Organisation of the United Nations, Rome, Italy, 249 pp. (1984).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeng, T. et al. Spatial distribution of prime farmland based on cultivated land quality comprehensive evaluation at county scale. \u003cem\u003eTran Chin. Soc. Agri Eng.\u003c/em\u003e \u003cb\u003e30\u003c/b\u003e (1), 200\u0026ndash;210 (2014). (in Chinese with English abstract).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarcia, R. A. et al. Multiple dimensions of climate change and their implications for biodiversity. \u003cem\u003eScience\u003c/em\u003e \u003cb\u003e344\u003c/b\u003e, 486\u0026ndash;496 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarnett, T. et al. Sustainable intensifcation in agriculture: premises and policies. \u003cem\u003eScience\u003c/em\u003e \u003cb\u003e341\u003c/b\u003e, 33\u0026ndash;34 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu, H. Y. Population distribution in China-attached statistical tables and density maps. \u003cem\u003eActa Geogr. Sin.\u003c/em\u003e \u003cb\u003e2\u003c/b\u003e, 33\u0026ndash;74 (1935). (in Chinese with English abstract).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHua, L. \u0026amp; Squires, V. R. Managing China\u0026rsquo;s pastoral lands: current problems and future prospects. \u003cem\u003eLand. Use Policy\u003c/em\u003e. \u003cb\u003e43\u003c/b\u003e, 129\u0026ndash;137 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJin, J. J., He, R., Wang, W. Y. \u0026amp; Gong, H. Z. Valuing cultivated land protection: a contingent valuation and choice experiment study in China. \u003cem\u003eLand. Use Policy\u003c/em\u003e. \u003cb\u003e74\u003c/b\u003e, 214\u0026ndash;219 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJustin, A. J. et al. Global agriculture and carbon tradeoffs. \u003cem\u003ePNAS\u003c/em\u003e \u003cb\u003e111\u003c/b\u003e (34), 12342\u0026ndash;12347 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarina, W., Richard, F., Mark, R. \u0026amp; Martin, H. Global land use changes are four times greater than previously estimated. \u003cem\u003eNat. Commun.\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e, 2501 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi, S. J. et al. Changing patterns in farming-pastoral ecotones in China between 1990 and 2010. \u003cem\u003eEcol. Ind.\u003c/em\u003e \u003cb\u003e89\u003c/b\u003e, 110\u0026ndash;117 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu, J. Integration across a metacoupled world. \u003cem\u003eEcol. Soc.\u003c/em\u003e \u003cb\u003e22\u003c/b\u003e (4), 29 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu, J. et al. Complexity of coupled human and natural systems. \u003cem\u003eScience\u003c/em\u003e \u003cb\u003e317\u003c/b\u003e, 1513\u0026ndash;1516 (2007b).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu, J. Y., Liu, M. L., Zhuang, D. F., Zhang, Z. \u0026amp; Deng, X. Z. Study on spatial pattern of land-use change in China during 1995e2000. \u003cem\u003eSci. China Ser. D: Earth Sci.\u003c/em\u003e \u003cb\u003e46\u003c/b\u003e, 373e384 (2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu, Y. Introduction to land use and rural sustainability in China. \u003cem\u003eLand. Use Policy\u003c/em\u003e. \u003cb\u003e74\u003c/b\u003e (5), 1\u0026ndash;4 (2018a).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu, Y., Fang, F. \u0026amp; Li, Y. Key issues of land use in China and implications for policy Making. \u003cem\u003eLand. Use Policy\u003c/em\u003e. \u003cb\u003e40\u003c/b\u003e, 6\u0026ndash;12 (2014a).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMedeiros, A., Fernandes, C., Gon\u0026ccedil;alves, J. F. \u0026amp; Farinha-Marques, P. Research trends on integrative landscape assessment using indicators\u0026ndash;a systematic review. \u003cem\u003eEcol. Ind.\u003c/em\u003e 129. (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNewbold, T. et al. Global effects of land use on local terrestrial biodiversity. \u003cem\u003eNature\u003c/em\u003e \u003cb\u003e520\u003c/b\u003e (7545), 45\u0026ndash;50 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOstrom, E. A general framework for analyzing sustainability of social-ecological systems. \u003cem\u003eScience\u003c/em\u003e \u003cb\u003e325\u003c/b\u003e, 419\u0026ndash;422 (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeters, M. K. et al. Climate-land-use interactions shape tropical mountain biodiversity and ecosystem functions. \u003cem\u003eNature\u003c/em\u003e \u003cb\u003e568\u003c/b\u003e (7750), 88\u0026ndash;92 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePradhan, P. et al. A systematic study of Sustainable Development Goal (SDG) interactions. \u003cem\u003eEarths Future\u003c/em\u003e. \u003cb\u003e5\u003c/b\u003e (11), 1169\u0026ndash;1179 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRiha, S. J., Wilks, D. W. \u0026amp; Simoens, P. Impact of temperature and precipitation variability on crop model predictions. \u003cem\u003eClim. Chang.\u003c/em\u003e \u003cb\u003e32\u003c/b\u003e (3), 293\u0026ndash;311 (1996).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchirpke, U. et al. Future impacts of changing land-use and climate on ecosystem services of mountain grassland and their resilience. \u003cem\u003eEcosyst. Serv.\u003c/em\u003e \u003cb\u003e26\u003c/b\u003e (A), 79\u0026ndash;94 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSemenov, M. A. \u0026amp; Stratonovitch, S. Use of multi-model ensembles from global climate models for assessment of climate change impacts. \u003cem\u003eClim. Res.\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e, 1\u0026ndash;14 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi, X., Wang, W. \u0026amp; Shi, W. Progress on quantitative assessment of the impacts of climate change and human activities on cropland change. \u003cem\u003eJ. Geog. Sci.\u003c/em\u003e \u003cb\u003e26\u003c/b\u003e (3), 339\u0026ndash;354 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSong, X. P. et al. Global land change from 1982 to 2016. \u003cem\u003eNature\u003c/em\u003e \u003cb\u003e560\u003c/b\u003e, 639\u0026ndash;643 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTilman, D., Cassman, K. G., Matson, P. A., Naylor, R. \u0026amp; Polasky, S. Agricultural sustainability and intensive production practices. \u003cem\u003eNature\u003c/em\u003e \u003cb\u003e418\u003c/b\u003e, 671\u0026ndash;677 (2002).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUNICEF. The millennium development goals report 2015. \u003cem\u003eMidwifery\u003c/em\u003e \u003cb\u003e30\u003c/b\u003e, 1043\u0026ndash;1044 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, G. Q. \u0026amp; Yun, W. J. A brieffy review and prospects on the land quality evaluation research. \u003cem\u003eChina Land. Sci.\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e (7), 92\u0026ndash;96 (2011). (in Chinese with English abstract).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, J. L., Xu, X. \u0026amp; Liu, P. F. Land use and land carrying capacity in ecotone between agriculture and animal husbandry in Northern China. \u003cem\u003eResour. Sci.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e (5), 19e24 (1999).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, L., An, P., Pan, Z., He, D. \u0026amp; Dong, Z. Cultivated land quality change of Wuchuan county in Inner Mongolia under background of climate change in semi-arid regions during recent 20 years. \u003cem\u003eTran Chin. Soc. Agri Eng.\u003c/em\u003e \u003cb\u003e29\u003c/b\u003e (11), 224\u0026ndash;231 (2013b). (in Chinese with English abstract).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, S. Y., Liu, J. S. \u0026amp; Ma, T. B. Dynamics and changes in spatial patterns of land use in Yellow River Basin, China. \u003cem\u003eLand. Use Policy\u003c/em\u003e. \u003cb\u003e27\u003c/b\u003e, 313e323 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWheeler, T. \u0026amp; Von Braun, J. Climate change impacts on global food security. \u003cem\u003eScience\u003c/em\u003e \u003cb\u003e341\u003c/b\u003e, 508\u0026ndash;513 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu, K. et al. Comprehensive productivity of agricultural land based on the agricultural land classiffcation. \u003cem\u003eTrans. CSAE\u003c/em\u003e. \u003cb\u003e24\u003c/b\u003e (11), 51\u0026ndash;56 (2008b). (in Chinese with English abstract).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu, K. et al. Framework of the arable-land quality dynamic monitoring sites through national gathering of standard farmland. \u003cem\u003eTrans. CSAE\u003c/em\u003e. \u003cb\u003e10\u003c/b\u003e (24), 74\u0026ndash;79 (2008a). (in Chinese with English abstract).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie, H. L. et al. Warning of negative effects of land-use changes on ecological security based on GIS. \u003cem\u003eSci. Total Environ.\u003c/em\u003e \u003cb\u003e704\u003c/b\u003e, 9 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang, Q. \u0026amp; Li, W. Distributed overgrazing: a neglected cause of grassland degradation in Inner Mongolia. \u003cem\u003eJ. Arid Land. Resour. Environ.\u003c/em\u003e \u003cb\u003e22\u003c/b\u003e (12), 8\u0026ndash;16 (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao, W. et al. Comparison of surface energy budgets and feedbacks to microclimate among different land use types in an agro-pastoral ecotone of northern China. \u003cem\u003eSci. Total Environ.\u003c/em\u003e \u003cb\u003e599\u003c/b\u003e, 891\u0026ndash;898 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZuo, L. et al. Multitemporal analysis of cropland transition in a climate-sensitive area: A case study of the arid and semiarid region of northwest China. \u003cem\u003eReg. Envriron. Chang.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e (1), 75\u0026ndash;89 (2014).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"The Agro-Pastoral Transitional Zone in northern China, Land use suitability, Adaptation strategies, Multiple Climate Change Scenarios","lastPublishedDoi":"10.21203/rs.3.rs-8518691/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8518691/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Agro-Pastoral Transitional Zone in northern China is the tail area of the East Asian summer monsoon, as well as the edge area of crop production. It is also a typical ecologically fragile area, and its agricultural and animal husbandry production conditions and ecological status are highly susceptible to climate change. Climate change has uncertainty in long-term processes in the future, and how it affects the suitability of agricultural and pastoral production in the Agro-Pastoral Transitional Zone constitutes a scientific issue of common concern in climate change research and regional sustainable development research. This study is divided into two parts: multi scenario simulation of climate change and evaluation of land use suitability for agriculture and animal husbandry. The first part first simulates the uncertainty of future climate change and the different paths of international response to climate change by setting low, moderate, and high emission scenarios, and then simulates the spatial distribution of annual precipitation and accumulated temperature elements in the Agro-Pastoral Transitional Zone for three years: 2030 (short-term), 2050 (medium-term), and 2100 (long-term). The second part further constructs an evaluation index system for the suitability of agricultural and animal husbandry land use based on the results of multi scenario simulations of climate change, and comprehensively analyzes the quantity structure and spatial distribution of suitability levels for agriculture and animal husbandry in different years under various scenarios. This study has found that in terms of future climate change, the low and moderate emission scenarios of the Agro-Pastoral Transitional Zone in northern China have similar trends in annual precipitation, while the high emission model has more extreme changes in annual precipitation. The spatial distribution of precipitation has always maintained an overall pattern of \"more in the east and less in the west\". The precipitation changes in the northern and northwestern sections of the Agro-Pastoral Transitional Zone are relatively small, while the dry and wet changes in the northern and southern parts of the northeastern sections are large; The overall distribution of accumulated temperature shows a spatial characteristic of high in the south and low in the north. The accumulated temperature changes in the low emission mode are relatively stable, while the accumulated temperature changes in the moderate and high emission modes are more extreme. The southern part of the northeast section and the eastern part of the north China section are the key areas of alternating cold and warm changes. The suitability analysis of agriculture and animal husbandry under multiple climate scenarios shows that the response to climate change varies in different regions of the Agro-Pastoral Transitional Zone in northern China. Global warming, under moderate and high emission patterns, can help improve the heat conditions in the central and eastern regions of the agro pastoral transition zone in the medium to long term, thereby enhancing the suitability of agriculture and animal husbandry. However, in the western part of the Agro-Pastoral Transitional Zone in northern China, it will further strengthen the constraints of natural conditions, especially in terms of unstable precipitation, and the suitability of land use for agriculture and animal husbandry cannot achieve long-term stable improvement. This study revealed that in the future climate change of the Agro-Pastoral Transitional Zone in northern China, the heat conditions for agricultural and pastoral production will gradually improve under medium to high emission patterns, but there is no significant trend of increase or decrease in precipitation conditions. Under moderate and high emission modes, the suitability of agricultural and pastoral land use in the central and eastern parts of the Agro-Pastoral Transitional Zone in northern China has been improved, indicating that climate warming is beneficial for enhancing the natural suitability of agricultural and pastoral production in the mid to high latitude regions of the Agro-Pastoral Transitional Zone in northern China. This study further discussed the practical path differences and feasibility between moderate and high emission modes, with moderate emission mode being an important mode path for adapting to future climate change in the Agro-Pastoral Transitional Zone.\u003c/p\u003e","manuscriptTitle":"Evolution of Land Use Suitability and Adaptation Strategies of the Agro-Pastoral Transitional Zone in northern China under Multiple Climate Change Scenarios","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-25 08:56:30","doi":"10.21203/rs.3.rs-8518691/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9bf840f1-c4b0-48c1-9d5b-647ec835e408","owner":[],"postedDate":"February 25th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-04T08:52:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-01T15:18:13+00:00","index":117,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":63397640,"name":"Earth and environmental sciences/Climate sciences"},{"id":63397641,"name":"Biological sciences/Ecology"},{"id":63397642,"name":"Earth and environmental sciences/Ecology"},{"id":63397643,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2026-05-04T09:10:03+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-25 08:56:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8518691","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8518691","identity":"rs-8518691","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}