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Article

Impacts of Future Climate and Farmland Changes on the Potential Cultivation Suitability of Apricot in China

by
Huiqing Han
1,*,
Huili Song
2,
Kai Wang
3 and
Yuanju Jian
1
1
School of Architecture and Urban Planning, Guizhou Institute of Technology, Guiyang 550025, China
2
Qiannan Academy of Agricultural Sciences, Duyun 558400, China
3
School of Economics and Management, Guizhou Institute of Technology, Guiyang 550025, China
*
Author to whom correspondence should be addressed.
Horticulturae 2025, 11(11), 1409; https://doi.org/10.3390/horticulturae11111409
Submission received: 24 October 2025 / Revised: 17 November 2025 / Accepted: 20 November 2025 / Published: 20 November 2025
(This article belongs to the Special Issue Effects of Environmental Changes on Fruit Production)
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Abstract

Global climate warming and the evolution of land-use patterns are jointly reshaping the spatial configuration of fruit tree cultivation. Focusing on apricot (Prunus armeniaca L.) in China, this study constructs a comprehensive suitability assessment framework driven by the dual forces of climate change and farmland transformation. By integrating multi-source climate datasets, projected land-use data, and geostatistical analysis, the study evaluates the impacts of climate and farmland changes on the potential cultivation suitability of apricot under four SSP scenarios (SSP126, SSP245, SSP370, and SSP585) during 2021–2100. The results indicate that: (1) climate warming generally expands potential suitable areas, showing a latitudinal shift from low to high regions; (2) under moderate- to high-emission scenarios, moderately suitable areas increase significantly, whereas highly suitable areas degrade in the long term due to excess heat and water stress; (3) farmland transformation exerts a crucial constraint between climatic potential and actual plantability, as resource reduction and spatial mismatch limit development potential; and (4) climate factors contribute approximately 72% to suitability variation, while farmland factors contribute about 28%, with a significant spatial interaction between the two. This study reveals the dynamic evolution of apricot suitability patterns under the dual drivers of climate and land changes, providing a scientific basis for fruit industry optimization and spatial land-use planning.

1. Introduction

Global climate change and the evolution of human land-use patterns are jointly reshaping the structure and function of agricultural ecosystems [1,2]. With the continuous rise in temperature, the increasing uncertainty of spatiotemporal precipitation distribution, and the dynamic transformation of farmland resources, the climatically suitable zones for crop and fruit tree cultivation are undergoing significant spatial reorganization [3,4]. For fresh apricot (Prunus armeniaca L.), which is cultivated primarily for direct consumption, the dependence on specific thermal and moisture conditions is particularly pronounced. Its key phenological stages—flowering, fruit setting, and fruit enlargement—exhibit strong sensitivity to temperature fluctuations and water availability [5]. In recent years, the increasing frequency of extreme climatic events—such as late spring frost, summer drought, heat stress, and abrupt heavy rainfall—has posed severe threats to apricot flowering, pollination, fruit expansion, and yield formation [6]. Meanwhile, the rapid transformation of farmland spatial patterns has also exerted indirect impacts on the potential planting zones of apricot. The quantity, quality, and spatial configuration of farmland not only determine the feasibility of fruit cultivation but also influence the degree of spatial matching between fruit production and the surrounding ecological environment [7]. Therefore, the combined effects of climate and farmland changes have become a critical factor shaping the future suitability patterns of apricot.
Existing studies generally acknowledge that climate change is the dominant driver influencing the spatial distribution of fruit trees [8]. Rising temperatures may lead to earlier blooming, reduced chilling requirements, and disrupted dormancy in apricot trees, consequently increasing the risks of phenological mismatches and frost damage during flowering and fruiting periods [9,10]. Simultaneously, altered precipitation regimes and the growing frequency of droughts can limit the water availability essential for fruit growth, thereby affecting both yield and quality [11]. International research employing species distribution models (such as MaxEnt, CLIMEX, and BIOCLIM) and Geographic Information Systems (GIS) to assess crop suitability under different emission scenarios has revealed a general poleward and altitudinal migration trend of temperate fruit species [12]. However, focusing solely on climatic factors may not fully explain the potential shifts in crop distribution. Recent studies have highlighted the increasing importance of the coupled effects of land-use and climate change in agricultural suitability assessments. On the one hand, climate warming may enhance climatic potential in certain regions, yet reductions in farmland resources or encroachment by built-up areas can constrain the actual cultivation potential. On the other hand, agricultural expansion or land consolidation may create new arable spaces within climatically suitable zones, thereby altering the spatial configuration of areas available for cultivation [13,14].
Apricot has been cultivated in China for centuries and exhibits strong sensitivity to thermal and moisture conditions [15,16]. Fruit quality benefits from adequate heat accumulation and pronounced diurnal temperature variation, whereas heat-limited environments often lead to unstable production [17]. With ongoing climate warming, some mid- to high-latitude regions are expected to experience increased accumulated temperatures, potentially emerging as new suitable areas for apricot cultivation. However, farmland resources have shown a trend of reduction and spatial displacement under the dual impacts of rapid urbanization and ecological restoration policies (e.g., “Grain for Green” programs [18]). This misalignment between suitable climatic zones and available arable land may result in spatial mismatches between climatic potential and land carrying capacity, posing a key constraint to the sustainable spatial layout of the apricot industry.
Although recent studies have attempted to predict changes in apricot suitability from a climatic perspective [17], most have neglected the dynamic role of farmland factors. Predictions based solely on climatic variables often overestimate the actual cultivability of potential suitable areas while overlooking spatial constraints and socio-economic feedbacks associated with land-use changes. Moreover, considerable discrepancies exist among previous studies regarding data sources, temporal scales, and model parameterization, limiting the comparability of their findings. Particularly under the context of climate change, the interactive effects of extreme climatic events and farmland transformation have not yet been systematically quantified. Consequently, a comprehensive understanding of the suitability patterns and spatial risks of apricot under the dual influences of future climate and land-use changes remains insufficient.
In this context, establishing an integrated climate–farmland analytical perspective is crucial for understanding how environmental change reshapes apricot cultivation suitability in China. Climatically, apricot growth depends on a narrow range of thermal and moisture conditions, making it necessary to examine how variations in temperature regimes, precipitation patterns, and extreme events modify its physiological thresholds. From a land-use standpoint, shifts in farmland quantity and spatial configuration determine whether climatically suitable areas can be effectively utilized, thereby influencing the realistic feasibility of future cultivation. Incorporating projections of climate trajectories and land-use transitions under different socio-economic pathways enables a more comprehensive understanding of how these drivers jointly expand, restrict, or redistribute suitable zones. Building on this dual perspective, the present study investigates the combined impacts of climate change and farmland transformation on apricot suitability in China, providing an evidence-based foundation for anticipating spatial risks and supporting adaptive agricultural planning. It aims to address three key scientific questions: (1) Under the current climate and land-use patterns, which climatic factors and land characteristics predominantly determine the spatial distribution of apricot? (2) How will the spatial pattern of suitable areas for apricot cultivation change under future climatic and land-use scenarios? (3) What insights can be drawn from the coupled effects of climate and land factors for apricot industry layout and regional agricultural adaptation strategies? The objective of this study is not only to characterize the direct impacts of future climate change on the potential distribution of apricot but also to elucidate the spatial dynamics and risk patterns of suitable zones under the dual driving mechanisms of climate and land changes. By integrating the dual constraints of natural environments and human activities, the research results provide scientific support for the structural adjustment of China’s fruit industry, agricultural climate risk management, and ecological spatial optimization. Moreover, this study offers a theoretical and methodological reference for future suitability assessments of other temperate fruit crops under the combined impacts of climate change and evolving land-use patterns.

2. Research Methods

2.1. Overview of the Study Area

China is one of the major centers of origin for apricot and possesses the richest germplasm resources of this species worldwide [19]. The national apricot cultivation belt is mainly distributed between 33–45° N and 85–125° E, encompassing regions such as North China, Northeast China, Northwest China, and the Loess Plateau. Representative provinces include Hebei, Shanxi, Shaanxi, Gansu, Shandong, Liaoning, Xinjiang, Ningxia, Inner Mongolia, and northern Henan [20]. Most of these regions lie within temperate semi-arid to semi-humid climatic zones, characterized by abundant sunshine and large diurnal temperature variations—conditions favorable for the formation of desirable flavor profiles and high sugar accumulation in apricot fruits. However, notable spatial heterogeneity exists across regions due to differences in climatic and land-use conditions. The uneven distribution of thermal, water, and soil resources results in pronounced spatial differentiation of suitable zones for apricot cultivation [21]. Moreover, hman-induced land-use changes have significantly altered both the quantity and spatial configuration of farmland resources, with certain areas experiencing a reduction in arable land and expansion of construction land [22]. Given the high climatic sensitivity of apricot trees and their stage-specific physiological requirements—such as spring warming, summer precipitation, and winter chilling accumulation—the species serves as a representative case for investigating the interactive impacts of climate change and farmland transformation. Based on the research requirements, China is divided into seven regions (Figure 1).

2.2. Data Sources

The climate data used in this study consist of two components: historical climate data and future climate scenario data. The historical climate data were obtained from the National Meteorological Information Center (NMIC) of the China Meteorological Administration, covering more than 2700 ground-based meteorological observation stations across China for the period 1991–2010. The key meteorological variables include daily maximum temperature, minimum temperature, mean temperature, and precipitation (https://www.nmic.cn/data/detail/dataCode/A.0012.0001.S011.html (accessed on 19 November 2025)). To ensure consistency with future climate data, spatial interpolation (Kriging interpolation) was employed to convert station-based observations into gridded data with a spatial resolution of 1 km × 1 km. Future climate data were derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model ensemble (MME) outputs. High-performance global climate models (e.g., BCC-CSM2-MR, CanESM5, MPI-ESM1-2-LR) that best represent regional climatic characteristics were selected for ensemble averaging to minimize the uncertainty associated with individual models [23]. The ensemble data were spatially resampled using bilinear interpolation, and bias correction techniques were applied to adjust systematic deviations in model outputs, ensuring consistency between simulated and observed climate means and variabilities over China. The future climate scenarios were classified according to the Shared Socioeconomic Pathway–Representative Concentration Pathway (SSP–RCP) framework into three time slices: near future (2021–2040), mid-century (2051–2070), and late century (2081–2100), representing climate change trends under different combinations of socioeconomic development trajectories and greenhouse gas emission levels.
Land-use data included both historical and future datasets. Historical land-use data were obtained from the Resource and Environmental Science Data Center (RESDC) of the Chinese Academy of Sciences, consisting of 30 m resolution land-use/land-cover classification data for the year 2000 (https://www.resdc.cn/). Future land-use projections were derived from the high-resolution (1 km spatial resolution) dataset developed by Liao et al. [24], which simulated land-use dynamics from 2015 to 2100 under multiple SSP scenarios using the Future Land Use Simulation (FLUS) model. This dataset has been validated for its accuracy and extensively applied in recent studies [25,26]. Land-use maps for the years 2030, 2060, and 2090 were selected to represent future land-use conditions in the near-, mid-, and long-term periods, respectively.

2.3. Research Methods

2.3.1. Research Framework

This study aims to evaluate the combined effects of future climate change and farmland pattern evolution on the potential planting suitability of apricot in China. The overall research framework comprises three key components: (i) constructing a climatic suitability model for apricot based on historical climate data; (ii) predicting the spatiotemporal dynamics of potential distribution under future climate scenarios; and (iii) integrating farmland spatial change scenarios to comprehensively assess the distribution pattern of apricot suitability under the dual constraints of climate and land-use change. Through the integration of climate modeling, geostatistical analysis, and spatial overlay operations, this study enables dynamic simulation and optimization of climatic suitability zoning.

2.3.2. Temporal Scale Division and Scenario Selection

To explore the long-term trends of climate and farmland change, the study period was divided into four stages: the historical baseline (1991–2010), near future (2021–2040), mid-century (2051–2070), and late century (2081–2100). Future climate data were obtained under the widely used Shared Socioeconomic Pathways–Representative Concentration Pathways (SSP–RCP) framework, which couples socioeconomic development narratives with greenhouse gas emission trajectories. This framework captures plausible futures by integrating demographic, technological, and economic trends (SSPs) with corresponding radiative forcing levels (RCPs). In this study, four combined scenarios—SSP126, SSP245, SSP370, and SSP585—were selected to represent low-, intermediate-, medium–high-, and high-emission pathways. Together, they encompass a broad spectrum of potential climate futures and enable a comprehensive assessment of apricot suitability under varying socioeconomic and emission conditions [27].

2.3.3. Construction of the Climatic Suitability Evaluation Index System and Evaluation Method

Following previous studies, a climatic suitability evaluation system comprising five indicators was developed based on the biological requirements of apricot for climate factors and its sensitivity to thermal and moisture conditions (Table 1) [28,29]. The selected climatic variables include: annual precipitation, spring frost probability, mean temperature of the coldest month, number of days with mean daily temperature between 0–7 °C during December–March (representing chilling requirement), and accumulated temperature ≥10 °C. Indicator weights were determined using the Analytic Hierarchy Process (AHP) [30]. Annual precipitation, spring frost probability, and mean temperature of the coldest month received the highest weights (0.32, 0.26, and 0.23, respectively), reflecting the dominant roles of hydrothermal conditions and frost risk in determining apricot distribution. Suitability levels were classified into four categories—highly suitable, moderately suitable, lowly suitable, and unsuitable—and assigned values of 3, 2, 1, and 0, respectively. Classification thresholds for each variable were established based on literature references [31].
The Weighted Overlay Method was employed to construct the climate suitability evaluation model [32]. The calculation formula is expressed as follows:
C S I = ∑ i = 1 n W i × S i
where Wi denotes the weight of the i-th climatic factor, Si represents the standardized suitability score of that factor, and n is the total number of indicators. The final Climate Suitability Index (CSI) values range from 0 to 3 and are classified into four suitability levels using the quantile method: highly suitable (CSI ≥ 2.6), moderately suitable (2.2 ≤ CSI < 2.6), low suitable (1.8 ≤ CSI < 2.2), and unsuitable (CSI ≤ 1.8). To validate the model’s reliability, current occurrence data of apricot were obtained from the GeoNames database (http://www.geonames.org) for accuracy assessment. The model’s discriminative performance was evaluated through the receiver operating characteristic curve, by calculating the area under the curve (AUC) value. An AUC ≥ 0.85 indicates that the model possesses high reliability and strong predictive capability.

2.3.4. Integration of Cultivated Land Constraints and Spatial Analysis

To further elucidate the restricting role of land resources on climate suitability patterns, this study incorporated cultivated land and slope constraints into the analysis, thereby integrating the influences of natural terrain conditions and cultivated land use policies on the spatial distribution of potential apricot planting areas. Under China’s stringent farmland protection policy, basic farmland—characterized by low slopes and flat topography—serves as the core area ensuring stable grain production and is therefore unsuitable for conversion to economic tree crops. In contrast, moderately sloping lands, due to their limited mechanization potential and lower grain yields, are more appropriate for fruit tree cultivation, contributing to the land-use optimization goal of achieving a coordinated “grain–economic–ecological” spatial structure [33]. Accordingly, slope farmland was considered a key spatial constraint in identifying potential areas suitable for apricot cultivation under climate–land dual constraints, while maintaining national food security. Specifically, slope information across China was extracted from the Digital Elevation Model (DEM) to generate slope raster data. Cultivated land was then classified according to slope characteristics to quantify the impact of topography on planting suitability [34]. Based on agricultural engineering standards and fruit cultivation practices [35,36], slope farmlands were categorized into four suitability levels (Table 2). Based on these classifications, the spatial patterns of slope farmland in different future periods were masked and filtered to retain only those cultivated land units with potential suitability for apricot plantation development.

2.3.5. Comprehensive Evaluation

The results of the climate suitability assessment were spatially overlaid with future cultivated land distribution layers using Overlay Analysis to generate a spatial map of comprehensive suitability under dual constraints of climate and land use [37]. The workflow included the following steps: (i) reclassification and spatial resolution unification of the climate suitability results; (ii) identification of slope farmland distribution based on slope thresholds; and (iii) utilization of raster algebra and spatial overlay functions in ArcGIS v10.1 and ENVI v5.3 platforms to delineate areas that are simultaneously suitable in terms of both climate and land use. On this basis, suitability distribution results for different time periods were subjected to classification statistics and spatial visualization, allowing for the analysis of spatial transfer, contraction, and expansion patterns of suitable areas under various scenarios. By comparing the spatial distribution between historical and future periods, this study elucidates the dynamic evolution of apricot suitability zones under the combined influence of future climate change and farmland transformation.

2.3.6. Contribution Analysis

To quantitatively determine the relative contributions of future climate change and farmland pattern evolution to variations in apricot climate suitability, this study employed the Contribution Analysis Method [38]. The analysis was conducted in three scenarios: “climate change only,” “farmland change only,” and “combined climate–land change,” with the suitability model run separately for each case to obtain the differential impacts of each driving factor. By comparing changes in the area and spatial shift direction of suitable zones across scenarios, the contribution proportions of single factors and their interaction effects were computed. To reduce model uncertainty, all influencing variables were standardized using Z-scores, ensuring the comparability between climate and land-use effects. The contribution of climate factors was primarily derived from the rate of change in key climatic variables such as annual precipitation, accumulated temperature (≥10 °C), mean temperature of the coldest month, and spring frost frequency. The contribution of land factors was based on the dynamic variation in available cultivated land area. Finally, through overlay analysis combined with an ANOVA-like decomposition approach [39], the relative contributions of the two categories of factors to suitability changes were calculated. This enabled the identification of the spatial heterogeneity of the dual driving mechanisms of climate and land-use change under different Shared Socioeconomic Pathways (SSPs).

3. Results

3.1. Changes in Climate Suitability

The temporal patterns of apricot climate suitability across China under varying climate scenarios are presented in the following illustration (Figure 2). During the historical period, the potential suitable areas for apricot cultivation were predominantly distributed in regions of low and high suitability. Entering the near-term period, the area of low suitability zones expands under most emission scenarios, particularly under SSP126 and SSP585, where the areas increase to approximately 1.6 × 106 km2 and 1.5 × 106 km2, respectively. Meanwhile, the high suitability zone remains relatively stable at around 1.1 × 106 km2, indicating that short-term climate warming exerts only a limited improvement effect on overall suitability patterns. In the mid-term period, the area of moderate suitability zones increases markedly, especially under high-emission scenarios (SSP370 and SSP585), exceeding 1.5 × 106 km2, while low suitability zones also show a slight expansion. This pattern suggests that improvements in key climatic conditions for apricot cultivation—such as rising temperatures in cold-limited areas, increased heat accumulation, and more favorable precipitation patterns—enhance the suitability of certain marginal regions. By the long-term period, differences among emission scenarios become more pronounced. Under SSP585, the moderate suitability zone reaches its maximum extent (approximately 2.5 × 106 km2), representing a nearly 1.6-fold increase compared to the historical period. Conversely, high suitability zones slightly decline under lower-emission scenarios (SSP126 and SSP245), and low suitability zones remain extensive. This indicates that under extreme warming conditions, some traditional core production areas may experience suitability degradation due to excessive heat accumulation or increased moisture stress.
The spatial distribution of climatic suitability for apricot cultivation in China during the historical period and under different future climate scenarios is illustrated in the figure below (Figure 3). During the historical period (1991–2010), highly suitable zones were mainly concentrated in the central and northern parts of the North China Plain and the central-eastern Loess Plateau. Moderately suitable zones were widely distributed, extending southward to regions north of the Yangtze River, while low-suitability zones were sporadically scattered across the southern hills and southwestern mountainous areas. In the near-term future (2021–2040), under all emission scenarios, the overall extent of highly suitable zones shows a slight expansion, particularly in the western Loess Plateau and central Xinjiang, indicating that climate warming helps to alleviate thermal limitations in these regions. Meanwhile, the suitability of southern marginal areas improves moderately, and moderately suitable zones exhibit a northward expansion trend. By the mid-term future (2051–2070), spatial changes in suitability become more pronounced, with a continuous increase in the area of moderately suitable zones, which advance further northward, while highly suitable zones remain relatively stable. In the long-term future (2081–2100), substantial differences emerge among emission scenarios. Under the low-emission scenario (SSP126), the distribution of highly suitable zones remains relatively stable; however, under the high-emission scenario (SSP585), the extent of highly suitable areas declines significantly. This suggests that extreme climatic warming may intensify heat stress and moisture deficits in traditional core production regions, thereby constraining the overall climatic suitability for apricot cultivation.

3.2. Changes in Farmland Suitability

The figure depicts how the area proportions of farmland with different suitability levels for apricot cultivation in China have shifted from the historical period to various future climate scenarios (Figure 4). During the historical period (1991–2010), the highly suitable farmland area accounted for approximately 28,000 km2, representing the largest proportion; the moderately suitable area covered about 9000 km2, while the low-suitability area was less than 5000 km2, suggesting that high-quality farmland played a crucial role in supporting apricot cultivation. In the near-term future (2021–2040), the area of highly suitable farmland remains stable or slightly increases, reaching around 32,000 km2 under the SSP5–8.5 scenario. Meanwhile, both moderately and low-suitability areas decrease further, indicating that climate warming exerts a positive effect on improving farmland suitability. By the mid-term future (2051–2070), the area of highly suitable farmland remains above 25,000 km2 under the SSP2–4.5 and SSP5–8.5 scenarios but decreases substantially under SSP1–2.6 and SSP3–7.0. The moderately suitable area declines slightly, particularly under high-emission conditions (SSP3–7.0), where some regions may experience reduced suitability due to land degradation and excessive thermal accumulation. In the long-term future (2081–2100), the differences among scenarios become more pronounced. Under the low-emission scenario (SSP1–2.6), farmland suitability remains relatively stable, with highly suitable areas continuing to dominate. In contrast, under high-emission scenarios (SSP3–7.0 and SSP5–8.5), the extent of highly suitable farmland declines markedly—especially under SSP3–7.0—while both moderately and low-suitability areas shrink further. These results suggest that intensified heat stress and altered precipitation regimes under extreme warming conditions may exert adverse effects on apricot growth and its land suitability.
The figure displays the spatial distribution patterns of farmland suitability for apricot cultivation in China during the historical period and under projected future climate scenarios (Figure 5). During the historical period (1991–2010), both moderate- and high-suitability zones were significantly concentrated in the northwest and southwest. Moving into the near future (2021–2040), the extent of highly suitable areas slightly expands across all emission scenarios, particularly extending toward the northwest. In the mid-term (2051–2070) and long-term (2081–2100) periods, from SSP126 to SSP585 scenarios, the highly suitable zones continue to strengthen in North and Northwest China, while changes in the southern and southeastern coastal regions remain minimal. Overall, the spatial pattern of farmland suitability for apricot cultivation in China exhibits a “high-in-the-north, low-in-the-south, superior-in-the-west, and stable-in-the-east” configuration.

3.3. Coupled Changes in Climate and Farmland Suitability

As shown in Figure 6, the coupled analysis of climate and farmland suitability reveals the dynamic evolution characteristics of the spatial pattern of apricot cultivation in China under different climate scenarios and future periods. During the historical period (1991–2010), regions classified as Class I—characterized by low climatic suitability—accounted for only a small proportion of the total area. Areas with moderate climatic suitability (Class II) represented a larger share (Class II), whereas areas with high climatic suitability (Class III) and suitable farmland areas were the most extensive, indicating the strongest spatial correspondence between climatic conditions and farmland quality and reflecting substantial production potential. In the near future (2021–2040), scenario-specific differences are projected to become apparent. The general trend shows a further expansion of highly suitable areas, particularly under the SSP585 scenario, where the area of high suitability increases by approximately 20% compared with the historical period, while low-suitability areas decrease significantly. This indicates that climate warming and changes in farmland resources jointly enhance the overall potential for apricot cultivation to some extent. By the mid-term period (2051–2070), under scenarios of continued greenhouse gas emissions (e.g., SSP245 and SSP585), the spatial coupling between highly suitable climatic zones and high-quality farmland further strengthens. The area of highly suitable zones continues to expand under most scenarios (except SSP370), with Class III climatic zones showing the most significant improvement. However, some Class II climatic zones experience limited increases in overall suitability due to land resource constraints. In the long-term future (2081–2100), disparities among scenarios become more pronounced. Under low-emission scenarios (SSP126 and SSP245), the distribution of suitable zones remains relatively stable, whereas under higher-emission scenarios (SSP370 and SSP585), the area of highly suitable zones declines markedly.
The figure presents the temporal variations in climate–farmland suitability levels for apricot cultivation across China’s seven major regions during the historical period and under multiple future climate scenarios (Figure 7). In Northeast China, the dominant suitability shifts from Classes I and II during the historical period to a continuous expansion of Class III in the future. North China has consistently been dominated by Class III suitability, with Class I gradually decreasing under all future scenarios. East China shows a high proportion of Class III suitability in the historical period, with limited variation under most future scenarios, though a slight decline occurs under high-emission scenarios. Northwest China was mainly dominated by Class III during the historical period, and this trend intensifies in the near to mid-term (2021–2070) under SSP585, with a significant expansion of Class III and contraction of Class I areas. However, in the far-future high-emission scenarios (SSP370 and SSP585 for 2081–2100), Class Ⅲ suitability declines sharply. In Central China, Class III suitability consistently dominates across all periods, with only minor fluctuations in Classes I and II, indicating a relatively stable pattern. Notably, under the SSP370 scenario, the area of Class III suitability decreases, particularly between 2051 and 2100. In Southwest China, Class II suitability predominates during the historical period, but Class III areas expand in most future scenarios, except under SSP370 for 2051–2100. Finally, South China consistently shows very limited areas of Classes I, II, and III throughout both the historical and future periods, with a general decline in overall suitable zones.

3.4. Contribution Analysis

To further reveal the relative driving effects of future climate change and farmland pattern evolution on the suitability of apricot cultivation in China, a contribution analysis method was employed to quantitatively decompose the influence of the two factors (Table 3). The contributions of climate and farmland factors under different scenarios exhibit pronounced temporal evolution and regional heterogeneity. Overall, climate change remains the dominant driver of suitability variation, with a national average contribution ranging from 62.3% to 69.9%, while the contribution of farmland factors ranges between 37.7% and 30.1%. The interaction between the two factors accounts for approximately 7%. From a temporal perspective, the contribution of climate factors increases steadily with higher emission intensities—from 62.3% in the historical period to 69.9% under the SSP585 scenario—indicating that the warming trend enhances the climatic improvement effect on suitability. Correspondingly, the contribution of farmland factors decreases from 37.7% to 30.1%, suggesting that although farmland structure adjustment still plays a regulatory role, its relative influence is gradually weakening. Regionally, the northern and northwestern regions show the most pronounced climate-driven effects. Under the SSP585 scenario, the climate contribution in Northeast and Northwest China reaches 76.3% and 78.4%, respectively—an increase of about 8–9% compared with the historical period—reflecting that rising temperatures and improved hydrothermal conditions significantly enhance climatic suitability. In contrast, the contribution of farmland factors in these regions declines to 23.7% and 21.6%, respectively. North China also exhibits a climate-dominant pattern, with the climatic contribution increasing from 63.5% to 70.2%, indicating a sustained positive effect of warming on apricot cultivation in the North China Plain. By contrast, East and Central China demonstrate a more prominent influence of farmland factors, where under the SSP585 scenario, farmland contributions remain relatively high—34.9% and 30.9%, respectively—mainly due to farmland structure optimization and improvements in slope conditions. In Southwest and South China, both climatic and land effects coexist, with climatic contributions of 65.4% and 60.5%, and farmland contributions ranging from 34% to 39%, indicating strong interactive effects between the two under complex topographic and climatic gradients. From a scenario comparison perspective, under low-emission scenarios (SSP126 and SSP245), climate contributions exceed those of farmland factors, implying that mild warming favors the northward expansion and enlargement of suitable zones. Under high-emission scenarios (SSP370 and SSP585), although climatic contributions continue to rise, the relative importance of farmland factors increases—particularly in southern and southwestern regions—where land-use adjustments play a greater role in mitigating climatic stress. In summary, climate change remains the dominant force shaping the evolution of apricot suitability across China; however, the relative influence of farmland factors is projected to gradually increase in the medium to long term.

4. Discussion

4.1. Comparison with Related Studies and Mechanism Analysis

This study systematically elucidates the mechanisms by which future climate change and farmland evolution influence the potential spatial suitability of apricot cultivation in China through a coupled climate–farmland analysis. The results indicate that climatic factors remain the dominant driver of suitability changes, whereas the relative contribution of farmland factors gradually increases in the medium to long term, with both factors exhibiting pronounced spatial heterogeneity and scenario dependence across regions. These findings are broadly consistent with conclusions from global studies on fruit tree suitability. Previous research has shown that the distribution center of temperate fruit trees is shifting northward under global warming [40], primarily driven by rising temperatures and accumulated heat units. In this study, the northward expansion of climatically suitable areas for apricot is also evident, indicating that warming will temporarily improve thermal conditions in northern China and thereby expand potential cultivation boundaries. However, under high-emission scenarios (SSP585), some historically favorable regions (e.g., East China and central North China) experience decreased suitability, aligning with European studies reporting yield fluctuations of apricot due to heat stress and water deficits [41]. This suggests that excessive heat under extreme warming may offset the positive effects of climate improvement.
Regionally, climate contributions are highest in northern and northwestern China, reaching 76.3% and 78.4%, respectively, highlighting the strong role of warming and improved moisture conditions in enhancing apricot growth environments. These results are consistent with studies on temperate fruit trees [42], indicating that climatic constraints in temperate zones are gradually weakening. In contrast, farmland factors exhibit relatively higher contributions in East and central China (34.9% and 30.9%), reflecting the effects of regional farmland consolidation, soil improvement, and slope optimization policies [43,44]. This underscores the important compensatory role of human land-use interventions in enhancing suitability in mid- to low-latitude regions. In topographically complex regions such as southwestern and southern China, climate and farmland contributions are more balanced (climate ~65%, farmland ~35%), reflecting the significant interactive effects of climate change and land-use adjustment in ecologically fragile areas, where the evolution of suitability is jointly constrained by multiple factors.
From a global comparative perspective, the results confirm the general pattern of “climate-driven—land-regulated” suitability dynamics. Compared with apricot-producing regions in the Mediterranean and southern Europe [45], the climate-driven contribution to suitability in China is slightly higher, while the influence of land factors is relatively more pronounced. This can be attributed to the large topographic variations and uneven farmland distribution in western and northern China, where land-use structural changes play a more prominent role in modulating climate-induced stress. Moreover, policy interventions under different socioeconomic pathways may reshape land-use patterns, thereby indirectly influencing crop responses to climate suitability. For instance, under moderate emission scenarios (SSP126 and SSP245), strengthened ecological conservation and land-consolidation policies tend to improve farmland quality and vegetation cover, which is consistent with the enhanced apricot suitability observed in this study. In contrast, under high-emission scenarios (such as SSP370 or SSP585), the importance of land-related factors increases markedly, highlighting the “buffering effect” of optimized land use in mitigating risks associated with extreme climatic conditions. This pattern is also reflected in other fruit-related studies. For example, Yourek et al. (2023), when evaluating future land availability for grains, vegetables, and fruits under SSP–RCP scenarios, found that fruit-producing areas face intensified land-use competition under the RCP8.5 scenario, resulting in a reduction in suitable production zones [46]. Likewise, suitability analyses for other fruit crops support our findings. Vetharaniam et al. (2022), using RCP2.6 and RCP8.5 scenarios to model the spatial suitability of apples and kiwifruit in New Zealand, reported a substantial expansion of highly suitable areas under low-emission conditions, whereas in high-emission scenarios, despite increased climatic risks, optimized land use and strategic relocation still help maintain relatively high suitability [47].

4.2. Policy Implications

From a management and policy perspective, the findings of this study provide important insights for the future spatial planning of the apricot industry and regional agricultural adaptation strategies. First, potential expansion zones in northern and northwestern China should be prioritized, aligning industrial development with climate trends and land suitability optimization, following a pattern of “priority development in highly suitable areas and guided management in marginal zones [48].” Second, in densely populated regions such as East and Central China, measures to protect farmland and improve soil quality should be strengthened to enhance the productive potential of limited land resources and mitigate potential risks associated with rising temperatures [49]. Third, in regions with complex terrain, such as southern and southwestern China, attention should be paid to microclimate–topography interactions, and site-condition optimization and ecological engineering interventions should be employed to alleviate the adverse impacts of climate variability [50]. Furthermore, at the national level, agricultural climate risk assessment and coordinated land-use planning should be reinforced, incorporating fruit tree industry layouts into regional ecological redlines and grain–fruit balance frameworks, thereby enhancing the climate resilience of agricultural systems.

4.3. Limitations and Future Research Directions

This study systematically elucidates the impacts of future climate change and farmland evolution on the potential suitability of apricot cultivation in China, yet several limitations remain. First, uncertainties in data and models, including biases in climate projections and differences in land data resolution, may affect result accuracy, and the contribution analysis method may not fully capture the complex interactions between climate and land factors [51]. Second, the range of influencing factors considered is limited, as soil properties, irrigation infrastructure, and socio-economic variables were not included, although they may affect suitability [52]. Third, spatial and temporal scales are constrained, limiting the ability to capture short-term impacts of extreme climatic events on apricot suitability. Fourth, a comprehensive assessment integrating ecological and economic benefits is lacking, as yield risk and industrial adaptability have not been incorporated [53]. Future research could integrate multi-model ensembles and high-resolution climate data, combine remote sensing and ground observations to improve parameterization, and develop a comprehensive climate–land–socioeconomic assessment framework [54]. Such approaches would allow deeper exploration of farmer adaptive behavior and policy interventions in regulating the spatial pattern of apricot cultivation, thereby providing a scientific basis for climate-adaptive planning and sustainable development of specialty fruit industries.

5. Conclusions

This study, by integrating future climate change and farmland pattern evolution, elucidates the spatiotemporal dynamics and driving mechanisms of potential suitability zones for apricot cultivation in China. The results indicate that climate warming will generally promote a northward and upward shift of suitable areas, with northern China and the southwestern regions emerging as potential expansion zones. From a land perspective, changes in farmland play a crucial role in mediating between climatic potential and actual land availability. Although some climatically suitable areas are projected to expand, the availability of farmland continues to decline under urban expansion and ecological protection policies, constraining the spatial distribution of highly suitable sloped farmland and resulting in a mismatch between climate potential and land availability. Contribution analysis further confirms that climate change is the dominant driver, whereas farmland changes impose significant spatial constraints on suitability, with the interaction between the two factors being particularly pronounced in northwestern and northern China. Future regional agricultural planning should therefore emphasize comprehensive suitability assessments under combined climate–land constraints, focusing on water resource management and ecological protection in arid and semi-arid northern regions, to promote an integrated fruit industry layout that balances “climatic suitability—land feasibility—ecological security.” The novelty of this study lies in its systematic integration of future climate projections and dynamic land-use data, quantifying their relative contributions to changes in fruit tree suitability, and providing a transferable methodological framework for exploring agricultural spatial pattern evolution under coupled climate–land conditions. Nonetheless, several limitations remain: the model does not account for varietal differences, management practices, or irrigation conditions, and future socio-economic policies and market feedback may also influence suitability projections. Future research should expand in the directions of multi-model ensembles, agronomic adaptation scenarios, and multi-source data integration to enhance the comprehensiveness and practical accuracy of fruit tree climate suitability assessments.

Author Contributions

Software, Writing—original draft, Review and editing, H.H.; Methodology, Data curation, H.S. and K.W.; Resources, Y.J. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Guizhou provincial science and technology Projects (ZK [2023]018), National Natural Science Foundation of China (72264005) and Guizhou Office of Philosophy and Social Science (23GZYB146).

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author(s).

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Distribution of the regions in China.
Figure 1. Distribution of the regions in China.
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Figure 2. Changes in Climatic Suitability Grades for Apricot Cultivation in China.
Figure 2. Changes in Climatic Suitability Grades for Apricot Cultivation in China.
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Figure 3. Spatial Distribution of Climatic Suitability for Apricot Cultivation in China. (a) 1991–2010, (b) SSP126 2021–2040, (c) SSP126 2051–2070, (d) SSP126 2081–2100, (e) SSP245 2021–2040, (f) SSP245 2051–2070, (g) SSP245 2081–2100,(h) SSP370 2021–2040, (i) SSP370 2051–2070, (j) SSP370 2081–2100, (k) SSP585 2021–2040, (l) SSP585 2051–2070, (m) SSP585 2081–2100.
Figure 3. Spatial Distribution of Climatic Suitability for Apricot Cultivation in China. (a) 1991–2010, (b) SSP126 2021–2040, (c) SSP126 2051–2070, (d) SSP126 2081–2100, (e) SSP245 2021–2040, (f) SSP245 2051–2070, (g) SSP245 2081–2100,(h) SSP370 2021–2040, (i) SSP370 2051–2070, (j) SSP370 2081–2100, (k) SSP585 2021–2040, (l) SSP585 2051–2070, (m) SSP585 2081–2100.
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Figure 4. Changes in farmland suitability levels for apricot cultivation in China.
Figure 4. Changes in farmland suitability levels for apricot cultivation in China.
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Figure 5. Spatial distribution of farmland suitability for apricot cultivation in China. (a) 1991–2010, (b) SSP126 2021–2040, (c) SSP126 2051–2070, (d) SSP126 2081–2100, (e) SSP245 2021–2040, (f) SSP245 2051–2070, (g) SSP245 2081–2100, (h) SSP370 2021–2040, (i) SSP370 2051–2070, (j) SSP370 2081–2100, (k) SSP585 2021–2040, (l) SSP585 2051–2070, (m) SSP585 2081–2100.
Figure 5. Spatial distribution of farmland suitability for apricot cultivation in China. (a) 1991–2010, (b) SSP126 2021–2040, (c) SSP126 2051–2070, (d) SSP126 2081–2100, (e) SSP245 2021–2040, (f) SSP245 2051–2070, (g) SSP245 2081–2100, (h) SSP370 2021–2040, (i) SSP370 2051–2070, (j) SSP370 2081–2100, (k) SSP585 2021–2040, (l) SSP585 2051–2070, (m) SSP585 2081–2100.
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Figure 6. Changes in coupled climate–farmland suitability levels for apricot cultivation in China. (Class I indicates low climatic suitability; Class II indicates moderate climatic suitability; Class III indicates high climatic suitability). (a) Historical period (1991–2010), (b) Near future period (2021–2040), (c) Middle future period (2051-2070), (d) Far future period (2081–2100).
Figure 6. Changes in coupled climate–farmland suitability levels for apricot cultivation in China. (Class I indicates low climatic suitability; Class II indicates moderate climatic suitability; Class III indicates high climatic suitability). (a) Historical period (1991–2010), (b) Near future period (2021–2040), (c) Middle future period (2051-2070), (d) Far future period (2081–2100).
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Figure 7. Regional characteristics of coupled climate–farmland suitability for apricot cultivation in China (Class I indicates low climatic suitability; Class II indicates moderate climatic suitability; Class III indicates high climatic suitability). (a1) Northeast region 1991–2010, (a2) Northeast region 2021–2040, (a3) Northeast region 2051–2070, (a4) Northeast region 2081–2100, (b1) North region 1991–2010, (b2) North region 2021–2040, (b3) North region 2051–2070, (b4) North region 2081–2100, (c1) East region 1991–2010, (c2) East region 2021–2040, (c3) East region 2051–2070, (c4) East region 2081–2100, (d1) Northwest region 1991–2010, (d2) Northwest region 2021–2040, (d3) Northwest region 2051–2070, (d4) Northwest region 2081–2100, (e1) Central region 1991–2010, (e2) Central region 2021–2040, (e3) Central region 2051–2070, (e4) Central region 2081–2100, (f1) Southwest region 1991–2010, (f2) Southwest region 2021–2040, (f3) Southwest region 2051–2070, (f4) Southwest region 2081–2100, (g1) South region 1991–2010, (g2) South region 2021–2040, (g3) South region 2051–2070, (g4) South region 2081–2100.
Figure 7. Regional characteristics of coupled climate–farmland suitability for apricot cultivation in China (Class I indicates low climatic suitability; Class II indicates moderate climatic suitability; Class III indicates high climatic suitability). (a1) Northeast region 1991–2010, (a2) Northeast region 2021–2040, (a3) Northeast region 2051–2070, (a4) Northeast region 2081–2100, (b1) North region 1991–2010, (b2) North region 2021–2040, (b3) North region 2051–2070, (b4) North region 2081–2100, (c1) East region 1991–2010, (c2) East region 2021–2040, (c3) East region 2051–2070, (c4) East region 2081–2100, (d1) Northwest region 1991–2010, (d2) Northwest region 2021–2040, (d3) Northwest region 2051–2070, (d4) Northwest region 2081–2100, (e1) Central region 1991–2010, (e2) Central region 2021–2040, (e3) Central region 2051–2070, (e4) Central region 2081–2100, (f1) Southwest region 1991–2010, (f2) Southwest region 2021–2040, (f3) Southwest region 2051–2070, (f4) Southwest region 2081–2100, (g1) South region 1991–2010, (g2) South region 2021–2040, (g3) South region 2051–2070, (g4) South region 2081–2100.
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Table 1. Climatic suitability evaluation index system.
Table 1. Climatic suitability evaluation index system.
IndicatorWeightClassification Criteria (Assigned Values)
Highly Suitable (3)Moderately Suitable (2)Lowly Suitable
(1)		Unsuitable
(0)
Annual precipitation (mm)0.32440 ≤ R ≤ 990360 ≤ R < 440
or 990 < R ≤ 1300		60 ≤ R < 360
or 1300 < R ≤ 1450		R < 60 or R > 1450
Spring frost probability (%)0.260 ≤ R ≤ 77 < R ≤ 1515 < R ≤ 26R > 26
Mean temperature of the coldest month (°C)0.23−5.2 ≤ R ≤ 2.9−8.9 ≤ R < −5.2 or 2.9 < R ≤ 8.4−13.2 ≤ R < −8.9
or 8.4 < R ≤ 13		R < −13.2 or R > 13
Days with mean temperature 0–7 °C (Dec–Mar)0.11R ≥ 4538 ≤ R < 4530 ≤ R < 38R < 30
Accumulated temperature ≥10 °C (°C·d)0.08R ≥ 42003200 ≤ R < 42002800 ≤ R < 3200R < 2800
Note: R denotes the observed value of each climatic indicator. Weights were derived using the AHP, based on expert scoring and consistency testing, to quantify the relative importance of each indicator in determining apricot climatic suitability.
Table 2. Classification criteria and characteristics of slope farmland.
Table 2. Classification criteria and characteristics of slope farmland.
Slope (°)Suitability LevelDescription
6–10Highly suitableModerate relief, good drainage, high soil permeability, non-overlapping with basic farmland; conducive to root growth and heat accumulation of apricot trees
10–15Moderately suitableSteeper terrain but can be improved through terracing and vegetation stabilization measures
15–25Low suitableSteep slopes, low mechanization, high soil erosion risk
<6 or >25UnsuitableThe former mainly refers to plains, key grain-producing areas that should be protected; the latter are steep and erosion-prone areas unsuitable for cultivation
Table 3. Contributions of climate and farmland factors to changes in apricot cultivation suitability under different SSP scenarios (%).
Table 3. Contributions of climate and farmland factors to changes in apricot cultivation suitability under different SSP scenarios (%).
RegionsHistorical PeriodFuture Periods Under Different Scenarios
SSP126SSP245SSP370SSP585
CCFCCCFCCCFCCCFCCCFC
Northeast China68.431.670.229.872.127.974.525.576.323.7
North China63.536.564.135.965.834.268.731.370.229.8
East China60.439.661.338.763.536.564.835.265.134.9
Northwest China69.830.272.427.674.125.976.823.278.421.6
Central China61.938.163.736.365.234.867.532.569.130.9
Southwest China57.842.259.440.661.238.863.836.265.434.6
Southern China54.245.855.644.457.142.959.340.760.539.5
Nationwide62.337.763.836.265.634.468.032.069.930.1
Note: CC denotes climate contribution; FC denotes farmland contribution.
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Han, H.; Song, H.; Wang, K.; Jian, Y. Impacts of Future Climate and Farmland Changes on the Potential Cultivation Suitability of Apricot in China. Horticulturae 2025, 11, 1409. https://doi.org/10.3390/horticulturae11111409

AMA Style

Han H, Song H, Wang K, Jian Y. Impacts of Future Climate and Farmland Changes on the Potential Cultivation Suitability of Apricot in China. Horticulturae. 2025; 11(11):1409. https://doi.org/10.3390/horticulturae11111409

Chicago/Turabian Style

Han, Huiqing, Huili Song, Kai Wang, and Yuanju Jian. 2025. "Impacts of Future Climate and Farmland Changes on the Potential Cultivation Suitability of Apricot in China" Horticulturae 11, no. 11: 1409. https://doi.org/10.3390/horticulturae11111409

APA Style

Han, H., Song, H., Wang, K., & Jian, Y. (2025). Impacts of Future Climate and Farmland Changes on the Potential Cultivation Suitability of Apricot in China. Horticulturae, 11(11), 1409. https://doi.org/10.3390/horticulturae11111409

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