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Article

Climate Change Affects Crop Production Potential in Semi-Arid Regions: A Case Study in Dingxi, Northwest China, in Recent 30 Years

by
Qiong Jia
1,
Mengfei Li
2,* and
Xuecheng Dou
1,2,*
1
College of Agronomy, Gansu Agricultural University, Lanzhou 730070, China
2
State Key Laboratory of Aridland Crop Science, Gansu Agricultural University, Lanzhou 730070, China
*
Authors to whom correspondence should be addressed.
Sustainability 2022, 14(6), 3578; https://doi.org/10.3390/su14063578
Submission received: 16 February 2022 / Revised: 10 March 2022 / Accepted: 17 March 2022 / Published: 18 March 2022
(This article belongs to the Special Issue Sustainable Agricultural Land Management: Co-benefits and Challenges in 21st Century)
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Abstract

:
Crop production potential (CPP) is profoundly affected by the change in climate factors (e.g., precipitation, temperature, and solar radiation) brought about by climate change, which ultimately affects the quantity and yield of crops. In China, arid and semi-arid regions are mainly located in the western regions and occupy around 59% of the land area. In order to identify the most important climatic factors restricting the increase in CPP and planting systems in the arid and semi-arid regions of northwest China, the changes in climate factors, CPP, and their correlation and planting systems were analyzed based on a representative semi-arid location, Dingxi, of Gansu province, from 1989 to 2019. The results showed that the temperature and precipitation increased by 0.89 °C and 26.61 mm, respectively, whereas solar radiation decreased by 5–6 d. The standard CPP of five crops (wheat, corn, potato, Chinese herbal medicines, and vegetables) increased by 655.09 kg/ha (1.09-fold), and precipitation played a more important role in improving CPP than other climate factors. Although there were positive correlations between the standard CPP and the five crops’ actual yields, no significant relationships were observed. The total cultivation area of the five crops showed a 215.55 × 103 ha (1.75-fold) increase with a 8.91-, 2.33-, 8.73- and 3.10-fold increase for corn, potato, Chinese herbal medicines, and vegetables, respectively, plus a 2.58-fold decrease for wheat. The agricultural ecosystem’s adaptability presented an obvious increase, especially from 2013 to 2019, although the agricultural natural environment factor maintained a low level. These findings provide scientific and technological support for the adjustment of planting structure, optimization of agricultural arrangement and development of water-saving agriculture in arid and semi-arid regions of northwest China.

1. Introduction

Crop production potential (CPP) indicates the maximum production of a certain crop in one year under the restriction of climate factors (e.g., temperature, precipitation, and solar radiation) and in the absence of pests, diseases, and other factors [1]. Over the past 100 years, the global climate has undergone a significant change characterized by warming, with the mean global temperature increasing by 0.85 °C from 1880 to 2012 [2,3]. The change in global climate has caused changes in agro-climatic resources (i.e., light, heat, water, air, and wind resources), which has brought further changes in agricultural production potential, agricultural production layout, and planting systems, ultimately affecting the safety of global food production [4,5,6,7].
Extensive research has demonstrated that climate change significantly reduces the production potential of different crops at different scales (i.e., global, regional, and local scales). For example, globally, the production potentials of wheat and corn were reduced by roughly 6% and 4%, respectively, from 1980 to 2008 [8,9]. The production potential of many crops including winter wheat, spring barley, maize, winter rapeseed, potato, sugar beet, pulses, and sunflower, was significantly affected as a consequence of climate change from 1976 to 2005 in Europe [10]. The production potential of wheat declined from 1960 to 2010 in China [11].
China, one of the largest food consumers in the world, is currently experiencing obvious impacts of climate change [11]. Scientific research and observation data show that climate change has had a significant impact on China’s agriculture and the yield of crops such as wheat, corn and rice [12]. In China, arid and semi-arid regions are mainly located in the western regions (e.g., Gansu, Ningxia, and Xinjiang) and occupy around 59% of the total land area. Their agricultural productivity is lower than that of coastal regions (e.g., Shandong, Jiangsu, and Fujian) [13,14]. Many previous studies have found that climate warming significantly affects the yield and quality of major food crops, economic crops and special fruit trees, farmland ecological environments, agricultural meteorological disasters as well as plant diseases and insect pests [15,16]. There is mounting evidence that crop yields in arid and semi-arid regions are particularly affected by climate change, especially via aridification, which greatly restricts agricultural development [17,18,19].
The Dingxi region (34°26′–35°35′ N, 103°52′–105°13′ E) is located in the central parts of Gansu province at the intersection of the Loess Plateau and high-altitude West Qinling Mountains. It is a typical ecologically fragile and dry-farming area due to its temperate, continental, arid climate; currently, its agricultural acreage is around 520,000 ha [20,21]. Although various kinds of crops including food crops (i.e., wheat, corn, and potato) and economic crops (i.e., Chinese herbal medicines and vegetables) have been traditionally cultivated in the Dingxi region, economic development is still slow due to its harsh natural environment [21,22], which may be affected by the climate change. In order to increase the CPP in the Dingxi region, some researchers have reported that the grassland agricultural production mode is more effective and suitable than the traditional cultivated land agricultural production mode, because the former can provide products, conserve soil, regulate climate, sequestrate carbon, and produce oxygen [21]. Other researchers have reported that the crops of Chinese herbal medicines, potato, and flowers have a comparative advantage over other crops in the Dingxi region [22]. To date, the effects of climate change on CCP in the arid and semi-arid regions of northwest China, especially in the semi-arid Dingxi region of Gansu province, have not been studied. Thus, it is of great necessity to identify the most important climatic factors restricting the increase in CPP in the arid and semi-arid regions in order to increase CPP in the Dingxi region.

2. Materials and Methods

2.1. Research Sites

In the Dingxi region of Gansu province, there are seven counties, which are Anding, Tongwei, Longxi, Zhangxian, Weiyuan, Minxian, and Lintao. In this study, the former six counties were selected as research sites.

2.2. Data Resources of Climatic Factors and Crops Yield

Climate factors including temperature, precipitation, and sunlight were authorized by the Meteorological Bureau of Dingxi city, Gansu province, China, and the crops’ yield, cultivation area, and patterns were collected from statistical yearbooks Gansu Statistical Yearbook, Gansu Rural Yearbook and Dingxi Statistical Yearbook from 1989 to 2019. The statistical results showed that the crops were predominantly wheat, corn, potato, Chinese herbal medicines, and vegetables in the Dingxi region. Therefore, this study focused on the production potential of these five crops.

2.3. Research Methods

2.3.1. Estimation of Crop Production Potential (CPP)

The CPP was estimated using the Miami and Thornthwaite Memorial models based on climate factors [23,24]. The Miami and Thornthwaite Memorial models, typical statistical relation-based models, can not only predict the impact of climate on CPP by establishing the correlation between climate factors and crops production, but are also simple in format and easy to perform [25]. Currently, the two models have been widely used in different regions [26,27]. In the Miami model, the specific climate factors are described in the following:
WT = 30,000/[1 + exp (1.315 − 0.119 T)]
WP = 30,000 [1 − exp (−0.000664 P)]
where T and P represent mean temperature (°C) and mean precipitation (mm), respectively; and WT and WP represent the dry-matter yield (kg/hm2) of plants that were determined by T and P, respectively.
In the Thornthwaite Memorial model, the specific climate factors are described in the following:
WE = 30,000 [1 − exp [−0.0009695 (E − 20)]]
E = 1.05 P/[1 + (1.05 P/L)2]
L = 300 + 25 T + 0.05 T3
where WE represents the dry-matter yield (kg/hm2) of plants that were determined by E; T and P represent mean temperature (°C) and mean precipitation (mm), respectively; and E and L represent mean actual evapotranspiration (mm) and mean maximum evapotranspiration (mm), respectively. Herein, the Formula (5) can be used if P > 0.3161 L; if not, P = E.
Finally, the standard CPP was evaluated based on the Liebig’s law of minimum [23]; its value can be calculated as follows:
WS = min (WT, WP, WE)

2.3.2. Correlation Analysis of Standard CPP with Climate Factors and Actual Crop Yield

The correlation of standard CPP with climate factors and actual crop yield was analyzed in SPSS 22.0 with a 2-tailed test of significance and p < 0.05 level used as the basis for significance. Herein, a higher value of correlation coefficient (r) indicates a more significant correlation between standard CPP with climate factors and actual crop yield, as well as the changes in cultivation area and agricultural ecosystem adaptability with different planting years.

2.3.3. Establishment of Index System of Agricultural Ecosystem Adaptability

Agricultural ecosystem adaptability consists of three factors: agricultural environment, agricultural production, and agricultural economy, based on the Intergovernmental Panel on Climate Change (IPCC) [28,29]. In this study, the agricultural environment factor contained positive indices, including annual mean temperature, annual mean precipitation, and annual solar radiation hours. Drought-affected area was selected as a negative index. The agricultural production factor contained positive indices including cultivated land per capita, irrigated area, total power of agricultural machinery, and grain–economy ratio. Population density was selected as a negative index. The agricultural economy factor contained positive indices including the proportion of agriculture, forestry, animal husbandry, and fishery in GDP, per capita GDP and per capita net income of farmers, and negative indices including the average use of chemical fertilizer and usage of plastic film.

3. Results

3.1. Change in Climate Factors in Dingxi City

As shown in Figure 1, there was an obvious change in climate factors in the semi-arid regions. The annual mean temperature, precipitation, and evapotranspiration showed increasing trends with 0.89 °C, 26.61 mm, and 35.45 mm increases, respectively (Figure 1A,B,D). The annual mean solar radiation showed a 128.52 h decrease (Figure 1C) in the initial 10 years (1989 to 1998) compared with the latest 10 years (2010 to 2019).

3.2. Change in Crop Production Potential (CPP) Affected by Climate Factors

The annual CPP affected by climate factors showed increasing trends, with 1.07-, 1.05- and 1.10-fold increases when affected by temperature, precipitation, and evapotranspiration, respectively (Figure 2A–C), from 1989 to 1998 compared with 2010 to 2019. Finally, the annual standard CPP showed a 655.09 kg/ha (1.09-fold) increase from 1989 to 2019 (Figure 2D).

3.3. Correlation of Standard CPP with Climate Factors

The correlation between standard CPP and climate factors was analyzed, since obvious changes in climate factors and CPP were found over the last 30 years. There was a positive correlation between standard CPP and mean minimum temperature, maximum temperature, precipitation and actual evapotranspiration; and mean precipitation and actual evapotranspiration were at a significant level (Figure 3B–D,F). There was a negative correlation between standard CPP and mean temperature and solar radiation (Figure 3A,E). These findings indicate that mean precipitation and actual evapotranspiration significantly contribute to the increase in standard CPP in the semi-arid Dingxi region.

3.4. Correlation between Standard CPP and Actual Crop Yield

In order to identify the contribution of major cultivated crops to CPP, the correlation between standard CPP and the actual yield of five crops (wheat, corn, potato, Chinese herbal medicines, and vegetables) was analyzed. There were positive correlations between the standard CPP and the five crops’ actual yields (Figure 4A–E), as well as between actual mean yield of the crops from 1989 to 2019 (Figure 4F), though no significance level was reached, which indicates that the CPP may depend on not only the climatic conditions but also agricultural practices and management in the semi-arid Dingxi region.

3.5. Change in Cultivation Area of the Five Crops

In order to reveal the change in cultivation area of crops that were affected by climate factors, production, and economic benefit, the specific changes for the five crops were analyzed. The cultivation area of corn, potato, Chinese herbal medicines, and vegetables showed 8.91-, 2.33-, 8.73- and 3.10-fold increases, respectively, from 1989 to 1998 compared with 2010 to 2019 (Figure 5B–E). Although the cultivation area of wheat showed a 2.58-fold decrease, there was an increasing trend from 2016 to 2018 (Figure 5A). On the whole, the total cultivation area of the five crops showed a 215.55 × 103 ha (1.75-fold) increase from 1989 to 2019 (Figure 4F).

3.6. Change in Agricultural Ecosystem Adaptability

In order to further reveal the changes in crop yield and cultivation area, agricultural ecosystem adaptability was analyzed in this study. From 1989 to 2007, there was a low level of agricultural ecosystem adaptability parameters including the agricultural environment factor, agricultural production and development factor, agricultural economic benefit factor, and composite index. Although there was no obvious change in the agricultural natural environment factor, an increasing trend in agricultural ecosystem adaptability was observed from 2008 to 2012. From 2013 to 2019, there was a synchronous increase in the agricultural production and development factor, agricultural economic benefit factor, and composite index.

4. Discussion

Climate change has been profoundly affecting crop production potential (CPP) globally for centuries, although it is difficult to determine which climatic factor most strongly affects crop quantity and yield in a region [30,31]. The change in global climate results in changes in climate factors including precipitation and temperature, decreasing crop yields in arid and semi-arid regions [4,5,6,7,17,18,19]; thus, it is urgent to seek strategies to improve CPP, especially in northwest China, where eight provinces and autonomous regions (Gansu, Ningxia, Xinjiang, Inner Mongolia, Tibet, Qinghai, Shanxi and Shaanxi) face extreme environments such as drought, low temperature, and high altitude [14,32]. In this study, the effect of climate change on CPP in a representative semi-arid location, Dingxi, was analyzed from 1989 to 2019. We found that global climate change affected climate factors (e.g., temperature, precipitation, and solar radiation), the CPP of five crops, and planting systems.
Previous studies on climate factors in northwest China have found that temperatures increased by ca. 1.4–3.0 °C, but precipitation significantly decreased in arid and semi-arid regions over the past 50 years [33,34,35]. The decrease in precipitation has inevitably led to increases in both drought frequency and duration, coupled with substantial warming [36]. For example, in the Dingxi region of Gansu province, there has been a significant change in temperature, with days of extreme/highest temperatures, summer days, hot nights, warm days, and warm nights, showing increasing trends from 1955 to 2016 [20]. In this study, the annual mean temperature, precipitation, and evapotranspiration also showed increasing trends, whereas the annual mean solar radiation showed a decreasing trend from 1989 to 2019 (see Figure 1). These changes in climate factors indicate that the CPP and plant systems had to accordingly experience a significant change.
To date, there are inconsistent results on the effect of climate change on CPP. Some studies show that the change in temperature played a more prominent role in CPP than that of precipitation and solar radiation [8,9,37,38]. Other studies found that the change in precipitation presented a more important factor in affecting CPP than that of temperature [39,40]. For example, the increase in temperature led to an increase in wheat, maize, and rice yields in China [12,41] but led to a decrease in wheat and corn yields in Gansu province [12,42,43]. Previous studies reported that the effect of climate warming on agriculture in Gansu province was more negative than positive, largely due to the lack of water resources [15]. In this study, climate change improved CPP on the whole from 1989 to 2019, and climate factors including temperature, precipitation, and evapotranspiration played positive roles in the increase in CPP (see Figure 2). There was a significant correlation between precipitation and standard CPP (see Figure 3), showing that drought is still the most important adverse climate factor restricting the increase in CPP in the semi-arid Dingxi region. Under the background of climate change with drought in the Dingxi region, on the one hand, methods to improve water-use efficiency such as drip irrigation have been widely applied in recent years; on the other hand, the change in planting systems definitely contributes to the increase in CPP under adverse environments (i.e., drought, low temperature, and high altitude).
Extensive studies have found that climate change leads to changes in crop growth duration and planting systems, with earlier seeding for spring crops, later seeding for autumn crops, and accelerated crop growth and reduced mortality for winter crops [32]. For example, the growth duration of winter wheat in Shaanxi and corn in dry-farming areas in southeastern Gansu were shortened by 5–6 d, whereas that of cotton in Hexi Corridor of Gansu was prolonged by 14–16 d [44,45,46]. The planting pattern in the main producing region of spring wheat has changed into that of spring wheat, winter wheat, and potato in semi-arid areas in central Gansu [47]. In this study, the cultivation areas of corn, potato, Chinese herbal medicines, and vegetables significantly increased, whereas those of wheat significantly decreased in the Dingxi region from 1989 to 2019 (see Figure 5), consistent with the greater contributions of potato and Chinese herbal medicines to CPP than wheat (see Figure 4). Several studies have reported that most climate factors, especially in increased temperatures, have a yield-reducing effect on wheat [11,48]. Studies on wheat cultivation in Gansu province found that the decrease in cultivation area was restricted not only by climate change, especially in drought, but also by the low economic benefits [49,50].
Agricultural ecosystem adaptability is the response to external pressures or actions that people make in efforts to reduce the adverse effects caused by global change with the aim of harmoniously inhabiting the environment [51]. Climate change can affect not only the agricultural environment and agricultural production but also agricultural economy, as well as plant diseases, human evolution, and civilization [28,29,52]. In this study, there was an increase in agricultural ecosystem adaptability (i.e., agricultural production and development factor, agricultural economic benefit factor, and composite index) from 1989 to 2019, although the agricultural natural environment factor in Dingxi maintained a low level (see Figure 6). These findings can be well-explained by effective measures such as the adjustment of planting systems, optimization of agricultural arrangement, expansion of thermophilic crops, and development of water-saving agriculture [32]. For example, the increase in the cultivation area of corn (see Figure 5B) largely relies on the development of water-saving agriculture and large-scale application of silage corn [53,54]; the increase in the cultivation area of potato (see Figure 5C) largely relies on planting mechanization, standardization, and improved varieties [55]; and the increase in the cultivation area of Chinese herbal medicines (see Figure 5D) largely relies on abundant medicinal plant resources and high economic benefits [56,57].

5. Conclusions

From the above investigations into the changes in climate factors, CPP, and planting systems in the semi-arid Dingxi region over the past 30 years, we found that climate change significantly affected climate factors, crop yield, planting systems, and agricultural ecosystem adaptability in the region. Precipitation played a more important role in improving CPP than other climate factors. The increases in the cultivation area and yield of potato and Chinese herbal medicines have greater contributions to the standard CPP than corn and wheat in the semi-arid Dingxi region. These findings will provide scientific and technological support for agricultural production in the arid and semi-arid regions of northwest China.

Author Contributions

Q.J.: data curation, formal analysis and software; M.L.: conceptualization, methodology and writing—review and editing; X.D.: funding acquisition, project administration and supervision. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the State Key Laboratory of Aridland Crop Science/Gansu Agricultural University (GSCS-2021-Z03), National Social Science Fund of China (13xjy018); and Technological innovation and guidance program of Gansu Province, China (20CX9ZA012).

Data Availability Statement

Not applicable.

Conflicts of Interest

All the authors declare no conflict of interest.

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Figure 1. Linear changing trend in temperature, precipitation, solar radiation, and evapotranspiration from 1989 to 2019. Images (A–D) represent the change in annual mean temperature, precipitation, solar radiation, and evapotranspiration, respectively.
Figure 1. Linear changing trend in temperature, precipitation, solar radiation, and evapotranspiration from 1989 to 2019. Images (A–D) represent the change in annual mean temperature, precipitation, solar radiation, and evapotranspiration, respectively.
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Figure 2. Linear changing trend in crop production potential (CPP) affected by temperature (T), precipitation (P), evapotranspiration (E), and standard CPP from 1989 to 2019. Images (A–D) represent the change in CPP affected by T, P, E and standard CPP, respectively.
Figure 2. Linear changing trend in crop production potential (CPP) affected by temperature (T), precipitation (P), evapotranspiration (E), and standard CPP from 1989 to 2019. Images (A–D) represent the change in CPP affected by T, P, E and standard CPP, respectively.
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Figure 3. Correlation between standard CPP and climate factors in Dingxi region. Images (A–F) represent the correlation between standard CPP and mean temperature, mean minimum temperature, mean maximum temperature, mean precipitation, mean solar radiation, and mean actual evapotranspiration, respectively. The r was analyzed using a two-tailed test at p < 0.05 level. The “*” indicates that the correlation is significant at p < 0.05 level.
Figure 3. Correlation between standard CPP and climate factors in Dingxi region. Images (A–F) represent the correlation between standard CPP and mean temperature, mean minimum temperature, mean maximum temperature, mean precipitation, mean solar radiation, and mean actual evapotranspiration, respectively. The r was analyzed using a two-tailed test at p < 0.05 level. The “*” indicates that the correlation is significant at p < 0.05 level.
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Figure 4. Correlation between standard CPP and actual crop yield in Dingxi city. Images (A–F) represent the correlation of standard CPP with wheat, corn, potato, Chinese herbal medicines, vegetables, and mean yield of the above five crops, respectively.
Figure 4. Correlation between standard CPP and actual crop yield in Dingxi city. Images (A–F) represent the correlation of standard CPP with wheat, corn, potato, Chinese herbal medicines, vegetables, and mean yield of the above five crops, respectively.
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Figure 5. Change in cultivation area of the five crops in Dingxi region from 1989 to 2019. Images (A–F) represent the changes in wheat, corn, potato, Chinese herbal medicines, vegetables, and total area, respectively. The r was analyzed using a two-tailed test at p < 0.05 level. The “*” indicates that the correlation is significant at p < 0.05 level.
Figure 5. Change in cultivation area of the five crops in Dingxi region from 1989 to 2019. Images (A–F) represent the changes in wheat, corn, potato, Chinese herbal medicines, vegetables, and total area, respectively. The r was analyzed using a two-tailed test at p < 0.05 level. The “*” indicates that the correlation is significant at p < 0.05 level.
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Figure 6. Evolution of agricultural ecosystem adaptability in Dingxi region from 1991 to 2019.
Figure 6. Evolution of agricultural ecosystem adaptability in Dingxi region from 1991 to 2019.
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Jia, Q.; Li, M.; Dou, X. Climate Change Affects Crop Production Potential in Semi-Arid Regions: A Case Study in Dingxi, Northwest China, in Recent 30 Years. Sustainability 2022, 14, 3578. https://doi.org/10.3390/su14063578

AMA Style

Jia Q, Li M, Dou X. Climate Change Affects Crop Production Potential in Semi-Arid Regions: A Case Study in Dingxi, Northwest China, in Recent 30 Years. Sustainability. 2022; 14(6):3578. https://doi.org/10.3390/su14063578

Chicago/Turabian Style

Jia, Qiong, Mengfei Li, and Xuecheng Dou. 2022. "Climate Change Affects Crop Production Potential in Semi-Arid Regions: A Case Study in Dingxi, Northwest China, in Recent 30 Years" Sustainability 14, no. 6: 3578. https://doi.org/10.3390/su14063578

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