Grain-producing Areas In China Research Articles

Temporal and spatial evolution of drought in Haihe River Basin from 1960 to 2020

The Haihe River Basin is an important grain-producing area in China. It is of great significance to explore and grasp the temporal and spatial evolution of drought for drought prevention and disaster mitigation, water security, and food security. In this study, based on the standardized precipitation evapotranspiration index (SPEI), gravity center model, standard deviation ellipse, and other methods, we analyzed the temporal and spatial evolution of drought in Haihe River Basin from 1960 to 2020. The results showed that during 1960 ∼ 2020, the frequency of drought in the Haihe River Basin had an upward trend, and light drought and moderate drought occurred frequently. Light drought was prone to occur in winter (January, February, December), and moderate drought mainly occurred in March (The first month of spring). The frequency of severe drought and extreme drought has increased significantly since 1990, and the monthly impact is spreading. The annual drought barycenters are distributed in plain areas such as Beijing, Hebei province, and showed a northeast to southwest zonal distribution in the basin, with a general trend of moving toward southwest. The monthly drought barycenters are mainly distributed in the central part of the basin around Baoding, and their migratory direction is mainly northeast and southwest.

Analysis of Current and Qualified Major Grain Producing Areas in China in the Last 30 Years

China’s grain production has been on a pathway parallel to urbanization in the last 30 years. When the balance between the grain supply and demand is considered, contradiction between farming suitability and actual deviation provides warning of a crisis regarding China’s food security. In this study, we constructed a set of topologic maps to summarize the basic distribution of the farming conditions in China, and Kernel density and Local Moran’s I analyses were con-ducted to investigate the spatial-temporal pattern of China’s regional grain production based on the grain output at the county level from 1985 to 2019. The results show that the high-output zones were concentrated in the regions with superior physical conditions in 1985, and by 2019, the high-output zones had increased in the northern regions (i.e., Northeast China Plain) and decreased in the southern regions (i.e., Southern China). The surplus zones of per capita grain output were concentrated in the regions with high total outputs during 1985–2019. The shortage zones were distributed in the regions with low total outputs and low total outputs or large populations. Based on the above three results, several typical commodity grain bases have lost their dominant role (i.e., the Pearl River Delta); furthermore, the qualified commodity grain bases were compiled at both the national and regional level based on overlay analysis (i.e., the Tarbagatay Prefecture as well as eastern and central Inner Mongolia).

Spatial–temporal characteristics and scenario simulation of carbon emissions from energy consumption based on multiscale in the affected areas of the lower Yellow River

Abstract The future development of the world is threatened due to global warming and climate change mainly driven by carbon emissions. Conducting an extensive study on the influencing factors of regional energy consumption and prediction through scenario simulation is of great significance for China in order to meet its aim of achieving carbon peak by 2030. The affected areas of the lower Yellow River are one of the main grain-producing areas in China, and it is facing a strong demand for urbanization and rapid economic development. Based on the night light data, this study demonstrates that the carbon emissions from energy consumption in the study area showed an upward trend from 2000 to 2018 with obvious spatial distribution differences. Economic development had a significant positive effect on the increase in carbon emissions from energy consumption; energy consumption intensity showed a significant negative effect. The study area achieves the carbon peak target in 2027 only under the low-carbon scenario. This study is helpful to realize ecological protection and high-quality development in the Yellow River Basin and also has reference significance for other developing countries.

Analysis of Agricultural CO2 Emissions in Henan Province, China, Based on EKC and Decoupling

Global warming caused by greenhouse gas emissions is highly concerning. Both the environmental Kuznets curve (EKC) hypothesis and decoupling analysis indicate a dynamic relationship between economic growth and environmental pollution, and each method has its own emphasis. The objective of this paper is to investigate the nexus between grain production and agricultural carbon emissions for the main grain-producing areas in China. Taking Henan Province, the second largest agricultural province, as an example, this paper examines the relationship between grain production and agricultural CO2 emissions during 2000–2019, using the EKC hypothesis and decoupling analysis. The results are as follows: (1) The estimation model of CO2 EKC shows the climbing stage of an inverted U-shaped relationship, which suggests that agricultural economic growth occurred at the cost of an increase in agricultural CO2 emissions in Henan Province during the past 20 years. (2) The results of the decoupling analysis show that incidences of weak decoupling and expansive coupling states took up most of the study period, accompanied by an occasionally strong decoupling state; decoupling and coupling states alternated irregularly, and no clear development trends were observed. (3) Considering the shape of the CO2 EKC and the decoupling state, environmental policies encouraged decoupling, but suffered from time lags and poor continuity; long-term incentives, such as an ecological compensation policy, could perhaps drive carbon emission reduction. On this basis, Chinese agricultural policy should combine environmentally targeted interventions with measures supporting production and farmers’ incomes, and environmental policy should also adapt to economic growth. Only when both supplement each other can sustainable agricultural goals be achieved.

Evaluation of water use efficiency and optimal irrigation quantity of spring maize in Hetao Irrigation District using the Noah-MP Land Surface Model

Hetao Irrigation District (HID), one of the main grain-producing areas in China, is facing the severe challenge of agricultural water shortages. Improving water use efficiency (WUE) is the most appropriate way to achieve sustainable agricultural development and obtain high returns. However, farmers knew little about efficient irrigation strategies for flood-irrigated fields in the HID. In this study, the Noah-MP Land Surface Model (LSM) with dynamic crop and irrigation schemes is used to jointly simulate the maize yield and irrigation amount in the HID from 2003 to 2012. A sensitivity test for ten sets of irrigation setup with different soil moisture (SM) triggering thresholds (CRI=0–1) is conducted, and the corresponding WUE and irrigation water use efficiency (IWUE) are evaluated and analyzed. In addition, irrigation at different crop growth stages affects total irrigation amounts and crop yield. The results show that under rain-fed conditions, the severe SM deficit during the growing season significantly decreases the maize yield in the HID, with almost no harvest in dry years. With traditional flood irrigation, the irrigation amount per unit area exceeds 1000 mm, leading to low WUE and IWUE, while more than 18–25% of irrigation water is wasted as runoff. With the increase of irrigation intensity, both WUE and IWUE show a significant diminishing marginal effect, usually occurring when SM is greater than 0.24–0.27 m3/m3. The optimal WUE is obtained near CRI= 0.6, while the worst WUE is obtained at CRI= 1. In a normal year, efficient irrigation amount is about 390–480 mm, 53–63% less than that in flood irrigation. In this scenario, most irrigation water becomes SM and transpiration, and less than 5% becomes runoff. With effective irrigation in the reproductive stage, only a small amount of irrigation is needed to promote yield formation. Fully considering the maize yield, WUE, ecosystems, and the available water resources in the HID, the recommended irrigation amount is about 600–650 mm to achieve the optimal maize yield and WUE.

Exploring the Influence Mechanism of Farmers’ Organic Fertilizer Application Behaviors Based on the Normative Activation Theory

This paper establishes an analysis framework to investigate the effect of the awareness of consequences and the ascription of responsibility on farmers’ organic fertilizer application behaviors (OFABs). Using questionnaire survey data from Hubei Province, one of the main grain-producing areas in China, this study employed both mediating effects and moderating effect analytical methods to analyze the influencing mechanism of the awareness of consequences and ascription of responsibility on farmers’ OFABs. The results show that, firstly, the awareness of consequences and ascription of responsibility have a significant positive impact on farmers’ OFABs. The improvement in farmers’ awareness of consequences and ascription of responsibility can effectively promote the utilization of organic fertilizers for enhanced ecological production. Secondly, the awareness of consequences and ascription of responsibility have a significant positive impact on farmers’ OFABs through individual farmers’ personal norms. Increasing farmers’ awareness of consequences and ascription of responsibility firstly stimulates their personal norms; then, personal norms have a positive impact on farmers’ OFABs. Thirdly, farmers’ social norms can positively regulate the relationship between personal norms and their OFABs. The higher the social norms of farmers, the more their social norms can have a positive regulating effect on their OFABs. Therefore, in the future, it will be necessary to vigorously promote farmers’ awareness of consequences and ascription of responsibility, in order to enhance farmers’ social norms, and to improve the level of farmers’ social norms, in order to greatly promote farmers’ engagement in OFABs. This will ultimately better promote rural ecological environmental protection and ecological civilization construction.

High crop yield losses induced by potential HONO sources — A modelling study in the North China Plain

Nitrous acid (HONO) is a major source of hydroxyl radicals in the troposphere through its photolysis, and can significantly influence ozone (O3) levels, thereby causing considerable crop yield losses. Previous studies have assessed relative crop yield losses by using exposure-response equations with observed or simulated O3, however, the contribution of enhanced O3 due to potential HONO sources to the crop yield losses has never been quantified. In this study, for the first time, we evaluated the crop yield losses caused by potential HONO sources in the North China Plain (NCP), which is one of the major grain-producing areas in China suffering from heavy O3 pollution, by using the Weather Research and Forecasting/Chemistry (WRF-Chem) model during the wheat and maize growing seasons of 2016. HONO simulations were significantly improved after including six potential HONO sources in the WRF-Chem model. The potential HONO sources produced a daily maximum 8-h O3 enhancement of 8.1/8.2 ppb during the wheat/maize growing seasons, respectively, and led to ~11.4%/3.3% relative yield losses for wheat/maize, respectively, corresponding to approximately US$3.78/0.66 billion losses, respectively, in NCP in 2016. The above results suggest that potential HONO sources play a significant role in O3 formation and could induce high crop yield losses globally.

An Economy-Climate Model for Quantitatively Projecting the Impact of Future Climate Change and Its Application

Quantitatively projecting the impact of future climate change on the socio-economy and exploring its internal mechanism are of great practical significance to adapt to climate change and prevent climate risks. Based on the economy-climate (C-D-C) model, this paper introduces a yield impact of climate change (YICC) model that can quantitatively project the climate change impact. The model is based on the YICC as its core concept and uses the impact ratio of climate change (IRCC) indicator to assess the response of the economic system to climate change over a long period of time. The YICC is defined as the difference between the economic output under changing climate condition and that under assumed invariant climate condition. The IRCC not only reflects the sensitivity of economic output to climate change but also reveals the mechanism of the nonlinear interaction between climate change and non-climatic factors on the socio-economic system. Using the main grain-producing areas in China as a case study, we use the data of the ensemble average of 5 GCMs in CMIP6 to project the possible impact of climate change on grain production in the next 15–30 years under three future scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5). The results indicate that the long-term climate change in the future will have a restraining effect on production in North region and enhance production in South region. From 2021 to 2035, climate change will reduce production by 0.60–2.09% in North region, and increase production by 1.80–9.01% in South region under three future scenarios. From 2021 to 2050, compared with the climate change impact in 2021–2035, the negative impact of climate change on production in North region will weaken, and the positive impact on production in South region will enhance with the increase in emission concentration. Among them, climate change will reduce grain output in North region by 0.52–1.99%, and increase output in South region by 1.35–9.56% under the three future scenarios. The combination of economic results and climate change research is expected to provide scientific support for further revealing the economic mechanism of climate change impacts.

Research on the degree of coupling of the Internet development level and agricultural--Ecological efficiency based on 2009-2018 data from 13 major grain-producing areas in China.

Agricultural informatization and agricultural green development are important components of modern agricultural development, and coordination between the two is an important foundation for achieving sustainable agricultural development. This paper uses data from the 13 major grain producing areas in China from 2009 to 2018 to analyze the coordination of the Internet development level and the agricultural ecological-efficiency, and it further investigates the degree of coupling and coordination between the two. The results of theis study are as follows.(1) The Internet development level of China's 13 main grain production areas has been continuously improving. The average Internet penetration rate increased from 0.25 in 2008 to 0.54 in 2018. (2) The agricultural ecological efficiency of China's main grain production areas has gradually improved. The average value of agricultural ecological efficiency increased from 0.45 in 2009 to 0.79 in 2018. (3) The Internet development level in China's main grain production areas and the continuous improvement of coordination and degree of coupling of the agricultural ecological efficiency show that the interaction between them has led to continuous improvements in the agricultural informatization development and agricultural green development. However, the coordination between the two still has significant room for growth, and there is a certain gap between the different regions.

Evaluation and Future Projection of Extreme Climate Events in the Yellow River Basin and Yangtze River Basin in China Using Ensembled CMIP5 Models Data.

The Yellow River Basin (YLRB) and Yangtze River Basin (YZRB) are heavily populated, important grain-producing areas in China, and they are sensitive to climate change. In order to study the temporal and spatial distribution of extreme climate events in the two river basins, seven extreme temperature indices and seven extreme precipitation indices were projected for the periods of 2010–2039, 2040–2069, and 2070–2099 using data from 16 Coupled Model Intercomparison Project Phase 5 (CMIP5) models, and the delta change and reliability ensemble averaging (REA) methods were applied to obtain more robust ensemble values. First, the present evaluation indicated that the simulations satisfactorily reproduced the spatial distribution of temperature extremes, and the spatial distribution of precipitation extremes was generally suitably captured. Next, the REA values were adopted to conduct projections under different representative concentration pathway (RCP) scenarios (i.e., RCP4.5, and RCP8.5) in the 21st century. Warming extremes were projected to increase while cold events were projected to decrease, particularly on the eastern Tibetan Plateau, the Loess Plateau, and the lower reaches of the YZRB. In addition, the number of wet days (CWD) was projected to decrease in most regions of the two basins, but the highest five-day precipitation (Rx5day) and precipitation intensity (SDII) index values were projected to increase in the YZRB. The number of consecutive dry days (CDD) was projected to decrease in the northern and western regions of the two basins. Specifically, the warming trends in the two basins were correlated with altitude and atmospheric circulation patterns, and the wetting trends were related to the atmospheric water vapor content increases in summer and the strength of external radiative forcing. Notably, the magnitude of the changes in the extreme climate events was projected to increase with increasing warming targets, especially under the RCP8.5 scenario.

Multi-Site Evaluation of Accumulated Temperature and Rainfall for Maize Yield and Disease in Loess Plateau

The Guanzhong region is a typical and important grain-producing area in China. The effect of accumulated temperature and rainfall on maize production is important in the face of global warming. Here, we collected meteorological data from six test sites in the Guanzhong region to study climate change from 1972 to 2018 in this area. A two-year study was conducted at multiple experimental sites to analyze the effect of climatic factors on maize yield and disease in the Guanzhong region. In the past 40 years, average temperatures have significantly increased at all sites, except for Hancheng. Rainfall varied significantly between years at each site, except for Huxian, with an overall declining trend. Accumulated temperature had a significant positive effect on yield (R2 = 0.28, p = 0.041 < 0.05), but rainfall did not affect yield (R2 = 0.0971, p = 0.324 > 0.05). During the growing period, total rainfall had a significant positive correlation with northern leaf blight disease in maize, and rainfall before silking had a significant positive correlation with ear length and row grain number. The demand for accumulated temperature by maize differed between sites. It is predicted that maize yield will increase with increasing temperature in the Guanzhong region. Greater attention should be paid to improve agronomic practices, such as adjustment of sowing dates, straw mulching, deep tillage, and pest control to adapt to future climate change.

Analysis on the Agricultural Green Production Efficiency and Driving Factors of Urban Agglomerations in the Middle Reaches of the Yangtze River

As one of the main grain-producing areas in China, urban agglomeration in the middle reaches of the Yangtze River plays an important role in the development of agricultural production for China’s grain supply. The existing studies about agricultural production efficiency lack of regional coordination analysis at both macro and micro levels, and only few studies consider the impact of agricultural production environment pollution and other undesirable outputs. Based on the input–output index system of agricultural green production, Slacks-based model (SBM) was adopted to measure the agricultural green production efficiency of 31 prefecture level cities in the middle reaches of the Yangtze River from 2008 to 2018, and the Tobit model of panel fixed effect was used to analyze the driving effect of external factors that affect the agricultural green production efficiency of urban agglomeration in the middle reaches of the Yangtze River. At the same time, the research methods at both macro and micro levels provide ideas for the research of transregional production efficiency. The results showed that: (1) the agricultural green production efficiency of urban agglomeration in the middle reaches of the Yangtze river is relatively low, with 2009 and 2013 as the inflection points, showing a stable trend of rise and decline; (2) The green agricultural production efficiency of urban agglomeration in the middle reaches of the Yangtze River presents the spatial distribution characteristics of “high in the west and low in the east”. The regional efficiency difference is obvious, the gap gradually expands, develops from the equilibrium to the polarization; (3) Urbanization development and government intervention has a significant restraining effect on the improvement of agricultural green production efficiency, and opening to the outside world produces a remarkable influence on the improvement of agricultural green production efficiency, however, economic development and industrial structure have little impact on the improvement of agricultural green production efficiency. Therefore, it is necessary to increase investment in technological innovation, promote agricultural transformation and upgrading, promote rational factors allocation and promote coordinated development of agriculture based on regional production differences.

Spatiotemporal changes in temperature and precipitation over the Songhua River Basin between 1961 and 2014

The Songhua River Basin is one of the main grain-producing areas in China, and local climate change has had a direct impact on grain production during the past several decades. This study focused on changes in mean and extreme climate conditions in the Songhua River Basin during the period 1961–2014. We founded that the precipitation decreased slightly over most of the basin; however, an increasing occurrence of extreme events was detected in the northern and eastern parts of the basin, especially for the number of very wet days and, correspondingly, how much those days contributed to total precipitation. By contrast, the mean, maximum and minimum temperature values between 1961 and 2014 showed statistically significant positive trends in almost all regions of the basin. The rate of change was greater for minimum temperature than maximum temperature, which resulted in a significant increasing trend for the number of warm nights and an overall decreasing trend in the annual mean diurnal temperature range. Generally, the magnitudes of changes in temperature were more remarkable than the magnitudes of changes in precipitation over the Songhua River Basin. If we take both precipitation and temperature changes into account, the areas sensitive to climate change during the last five decades were in the southern and central parts of the Songhua River Basin.

Incentives or restrictions: policy choices in farmers’ chemical fertilizer reduction and substitution behaviors

Abstract Based on 804 samples of farmers in Hubei Province, a typical major grain-producing area in China, this study empirically analyzed the effects of two different policy tools, i.e. economic incentives (subsidies) and order enforcements (regulatory restrictions), as well as the effects of their interaction, on farmers’ chemical fertilizer reduction and substitution behaviors. Samples were grouped according to the degree of concurrent employment to analyze the effects on different groups. The results show that (1) the influences of these policies on the behaviors were significantly positive; (2) after constructing the interactive variables of the policies, the influence of the order enforcement policy was no longer significant, but the influence of the interaction was significantly positive; (3) the low-degree concurrent employment farmers were more likely to be affected by the order enforcement policy, whereas the high-degree ones were more affected by the economic incentive policy; and (4) the behaviors of the low-degree ones were strongly affected by family management characteristics, whereas the high-degree ones were more affected by the farmers’ individual characteristics.

Construction and application of evaluation system for integrated development of agricultural industry in China

In order to expand the channels of increasing farmers' income and change the mode of agricultural development, China has put forward the strategy of integrated development of agricultural industry. Twenty evaluation indicators were confirmed by using hierarchical analysis method and multi-factor comprehensive evaluation method to construct the evaluation system. This system was applied to evaluate the level of integrated development of agricultural industry in Heilongjiang province, the main grain-producing area in China. The results showed that the integrated comprehensive development index of agricultural industry in Heilongjiang province reached 63.2, 63.5, 65.1, 65.3 and 67.8, respectively, from 2013 to 2017, which has entered the growth stage from the initial stage and increased year by year.

Comparing Groundwater Storage Changes in Two Main Grain Producing Areas in China: Implications for Sustainable Agricultural Water Resources Management

Balancing groundwater supply and food production is challenging, especially in large regions where there is often insufficient information on the groundwater budget, such as in the North China Plain (NCP) and the Northeast China Plain (NECP), which are major food producing areas in China. This study aimed to understand this process in a simple but efficient way by using Gravity Recovery and Climate Experiment (GRACE) data, and it focused on historical and projected groundwater storage (GWS) changes in response to changes in grain-sown areas. The results showed that during 2003–2016, the GWS was depleted in the NCP at a rate of −17.2 ± 0.8 mm/yr despite a decrease in groundwater abstraction along with an increase in food production and a stable sown area, while in the NECP, the GWS increased by 2.3 ± 0.7 mm/yr and the groundwater abstraction, food production and the sown area also increased. The scenario simulation using GRACE-derived GWS anomalies during 2003–2016 as the baseline showed that the GWS changes in the NCP can be balanced (i.e., no decreasing trend in storage) by reducing the area of winter wheat and maize by 1.31 × 106 ha and 3.21 × 106 ha, respectively, or by reducing both by 0.93 × 106 ha. In the NECP, the groundwater can sustain an additional area of 0.62 × 106 ha of maize without a decrease in storage. The results also revealed that the current groundwater management policies cannot facilitate the recovery of the GWS in the NCP unless the sown ratio of drought-resistance wheat is increased from 90% to 95%. This study highlights the effectiveness of using GRACE to understanding the nexus between groundwater supply and food production at large scales.

Changes in spatiotemporal drought characteristics over northeast China from 1960 to 2018 based on the modified nested Copula model

Drought forecasting is helpful for understanding the inherent mechanism of hydrological extremes and taking corresponding measures to mitigate drought impacts. Northeast China, which is an important, major grain-producing area in China, has been challenged by substantial losses due to frequent drought. In this study, to predict the spatiotemporal variation in drought events over Northeast China, a model-based simulation framework is proposed based on precipitation data at 70 meteorological stations from 1960 to 2018. The core of the model framework is run theory, modified Copula model- based Bayesian-MCMC, Gibbs sampling, and a new definition of drought intensity center and drought intensity accumulation area. The results showed that a total of 6408 drought events occurred at the 70 meteorological stations in Northeast China over the past 59 years. The empirical distribution functions of longitude, latitude, and time can be used to fit the edge distribution of the original variable. In comparison to the traditional maximum likelihood method, the Bayesian-MCMC method is more accurate for parameter estimation of the Copula model. The Frank Copula is the optimum joint function of longitude and latitude, while the Gaussian Copula is the optimum joint function of location and time. Gibbs sampling can provide a relatively larger sample size for predicting future drought conditions. The spatiotemporal variation in drought in Northeast China changes similarly throughout the year. Drought is mainly concentrated in southwestern Liaoning from February to April. The drought intensity center moves to the northeast from May to September. Western Heilongjiang is the main drought-stricken area from October to November. The drought intensity center moves southwest from December to January of the following year. This study provides a method for effectively predicting drought events and is of great significance to the protection, development, and utilization of water resources.

Determinants and Differences of Grain Production Efficiency Between Main and Non-Main Producing Area in China

This paper investigated the determinants, especially labor transformation, and differences of technical efficiency between main and non-main grain-producing area in China based on a panel data from 30 provinces in the period of 2001–2017. Stochastic frontier production function was used to estimate the level of technical efficiency and the marginal productivity of different inputs. The estimated results showed that land is the most important factor to improve China’s grain output, followed by fertilizers, labor, and machinery inputs. There was a significant 4.6 percent gap of production efficiency between main and non-main producing provinces. Influence of rural labor transformation was confirmed to be positive to improve technical efficiency.

Measuring the Cultivated Land Use Efficiency of the Main Grain-Producing Areas in China under the Constraints of Carbon Emissions and Agricultural Nonpoint Source Pollution

The carbon emissions and agricultural nonpoint source pollution constraints were incorporated into the input–output index system, and the epsilon-based measure (EBM) super efficiency model and global Malmquist–Luenberger (GML) index were used to measure the cultivated land use efficiency and changes in the total factor productivity (TFP) of cultivated land use in the main grain-producing areas in China from 1993–2016. The results indicate that: (1) from 1993 to 2016, the cultivated land use efficiency in the main grain-producing areas in China showed a tendency to fluctuate and increase, with obvious stage characteristics; however, the overall level was not high. (2) There is a significant difference in the cultivated land use efficiency under the constraints of carbon emissions and nonpoint source pollution in the main grain-producing areas in the different provinces, and low-efficiency provinces have higher input redundancy and undesired output redundancy than high-efficiency provinces. It can be observed that input redundancy and undesired output redundancy have a significant negative effect on cultivated land use efficiency. (3) The TFP of cultivated land use under the constraints of carbon emissions and nonpoint source pollution in China’s main grain-producing areas is estimated by the GML index. The results show that the TFP of cultivated land use in the main provinces in the main grain-producing regions is greater than 1, indicating that the productivity levels of all the provinces in China’s main grain-producing areas are increasing. From the perspective of the power sources in each province, global pure technological change (GPTC) and global scale technological change (GSTC) are the main driving forces for the TFP of cultivated land use, while global pure efficiency change (GPEC) and global scale efficiency change (GSEC) are the bottlenecks for increasing the TFP of cultivated land use.

Pollinator diversity in different habitats of the agricultural landscape in the middle and lower reaches of the Yellow River based on the three-color pan trap method

The middle and lower reaches of the Yellow River constitute one of the most important grain-producing areas in China and strategic position for national food security. The maintenance of pollinator diversity in agricultural landscapes is not only meaningful for biodiversity protection, but also a guarantee of food security and crop production. Pollinators have response preferences to the color of nectar and pollen plants in different habitats. The diversity of pollinator in different habitats was analyzed by using multivariable ANOVA. Results showed that a total of 23,264 individuals were captured, which belong to 7 orders and 84 families. The difference individuals of pollinators in two habitats was highly significant (P<0.001). Approximately twice as many individuals were captured in farmland habitat than that in woodland habitat. The values of the Margalef richness index and the Berger-Parker dominance index were also greater in farmland habitat than that in woodland habitat. In both habitats, differences in pollinator diversity were significantly higher for the yellow traps than that for the other two colors (P<0.01); differences in the individual abundance in the yellow traps are highly significantly greater (P<0.001) than that for the other two colors, while there was no significant difference between the white and blue traps. The sensitivity of orders Diptera and Hymenoptera was greatest to yellow traps, followed by that to white and blue traps, while order Coleoptera showed no obvious preference among the three colors. With respect to species richness, white traps could capture the most pollinators in different habitat types; with respect to the individual abundance, yellow traps attracted the most pollinators. The results also show that some species had a specific preference for color. For example, Drosophilidae in both farmland and woodland habitats preferred white, and Eulophidae preferred yellow only in farmland. This is because pollinators respond differently to different intensities, wavelengths, and reflectivity, which is as a result of both innate preferences and learning. Pollinators respond differently to the three colored traps, and these traps could be used in a complementary manner for pollinator capture. Color pan traps can be seen as an effective method to obtain pollinators, which can use in various studies on pollinators in this research area.