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The dry and windy climate and low ground cover in spring in the black soil region of Northeast China make the soil strongly affected by wind erosion, which seriously threatens the food security and ecological security of this region. In this paper, based on the daily observation data of 124 meteorological stations in study area from 1961 to 2020, seasonal and monthly wind erosion climate factor (C) in spring (March to May) were calculated by using the method proposed by the Food and Agriculture Organization of the United Nations (FAO), the wind erosion characterization in spring were systematically analyzed based on C by various statistical analysis methods. The results showed that in the past 60 years, spring wind erosion climate factor (CSp) and monthly C of the whole region and each province (region) all showed highly significant decreasing trend, but they began to show rebounded trend in the middle or late 2000s. CSp of the study area showed a significant upward trend since 2008 with an increase of 4.59 (10a)−1. The main contributors to this upward trend are the changes of C in March and in April. For the four provinces (regions), CSp in Heilongjiang, Jilin, Liaoning and eastern Inner Mongolia all showed rebounded since 2008, 2011, 2008 and 2009, respectively. The rebounded trend of CSp in eastern Inner Mongolia was the most obvious with a tendency rate of 11.27 (10a)−1, and its mutation occurred after 1984. The rebound trend of CSp in Heilongjiang Province takes the second place, with a trend rate of 4.72 (10a)−1, but there's no obvious time mutation characteristics. The spatial characteristics of CSp and monthly C are similar, showing decreasing characteristics centered on the typical black soil belt of Northeast China. Compared with 1961–1990, in the period from 1991 to 2020, the proportion of high value areas (CSp>35, monthly C>10) has decreased to varying degrees, while the proportion of low value areas (CSp ≤10, monthly C ≤4) has increased. The trends of seasonal and monthly C in 82.2%∼87.7% of the stations show significant decreases at 95% confidence level. CSp is closely related to wind speed at 2m height, temperature difference, minimum temperature and precipitation in the same period, of which the correlation between CSp and wind speed is the strongest, indicating that the main control factor for CSp in the study area is wind speed, but the impact of the change of temperature and precipitation on CSp cannot be ignored. [ABSTRACT FROM AUTHOR]

Land cover change (LCC) significantly changed the local/regional temperature. This paper attempts to reveal the effects of cropland expansion in different ways on temperature change from the 1900s to 2010s in Heilongjiang Province. To reach this goal, we conducted four simulation research schemes with the coupled Weather Research and Forecast (WRF)-Noah model to investigate the warming/cooling effect of cropland expansion. The results show that cropland expansion exerted different effects with different land-use type conversions. In the last century, the areas with grassland-to-cropland and wetland-to-cropland transition show the warming effect, and the average surface temperature in Heilongjiang Province increased by 0.023 ℃ and 0.024 ℃, respectively. The areas with forest-to-cropland transition show the cooling effect, in which the average temperature decreased by 0.103 ℃. The variation of air temperature is mainly caused by the variation of surface reflectance and surface net radiation flux. The results provide evidence that cropland expansion changes to biophysical landscape characteristics, warming/cooling the land surface and thus enhancing/reducing the temperature, and lead to regional climate change eventually. [ABSTRACT FROM AUTHOR]

The profound impact of climate change on agricultural production, and the government's fiscal expenditure for agriculture, is considered a crucial means to address this challenge. This study utilizes panel data from all prefecture-level cities in Heilongjiang Province from 2000 to 2020. Drawing upon the Cobb-Douglas production function, an economic climate model is constructed to empirically analyze the impact of climate change on grain yield in Heilongjiang Province. Furthermore, the role of fiscal expenditure for agriculture in mitigating the effects of climate change on grain yield is explored. Feasible Generalized Least Squares (FGLS) estimation is employed to address issues of "heteroscedasticity," "autocorrelation within groups," and "cross-sectional contemporaneous correlation" present in the model. The results indicate that climate change has a positive impact on rice and corn yields, while exhibiting a negative impact on wheat yield. The influence of climate change on crop yield is both linear and nonlinear. Specifically, temperature demonstrates a linear relationship with rice and corn yields, whereas precipitation shows a significant inverted U-shaped relationship with rice and corn yields. The impact of climate change on grain production in Heilongjiang Province varies significantly across regions. Fiscal expenditure for agriculture has a significant positive effect on the yield of major grain crops in Heilongjiang Province. In addressing the impact of climate change on grain production, agricultural fiscal expenditure enhances the positive effect of precipitation on rice and corn yields, while diminishing the positive impact of temperature on corn yield. [ABSTRACT FROM AUTHOR]

The implementation of the "Belt and Road" strategy not only promotes the coordinated development of China's regional economy but also generates a large amount of greenhouse gas emissions. The research and policy recommendations on agricultural carbon emissions are of great significance for China toward engendering sustainable agricultural development and appreciably contributing to the alleviation of global climate change. In this paper, agricultural carbon emissions in the Belt and Road region of China from 2003-2018 are calculated, and its spatial-temporal characteristics are analyzed. Then, we modified the logarithmic mean Divisia index model from the original four factors to six to analyze the drivers of agricultural carbon emissions. The research results obtained are as follows: (1) Total carbon emission reached a peak of 26.6326 million tons in 2016, representing a 54.53% increase from the 17.2342 million tons in 2003. Moreover, it indicated a downward trend in 2017 and dropped by approximately 4% to 25.5685 million tons in 2018. (2) Spatially, agricultural carbon emission varies greatly, with the highest value recorded in Heilongjiang and the lowest in Tibet, thereby exhibiting the characteristics of "northwest>northeast>southwest>southeast." (3) Overall, the economic factor was the most important driving factor, whereas the subsidy factor was the strongest inhibiting factor for the growth of agricultural carbon emissions. Notably, the foreign trade factor had both promoting and inhibiting effects on it. [ABSTRACT FROM AUTHOR]

The objective of this study is to examine the impact of climate change on forestry efficiency (FRE) and total factor productivity change (TFPC) in 31 provinces of China for a study period of 2001–2020. Additionally, the study aims to evaluate the success level of governmental initiatives used to mitigate climate change. Using the DEA-SBM, this study estimates the forestry efficiency for 31 Chinese provinces and seven regions. Results indicate that the average forestry efficiency score obtained is 0.7155. After considering climatic factors, the efficiency level is 0.5412. East China demonstrates the highest average efficiency with a value of 0.9247, while the lowest score of 0.2473 is observed in Northwest China. Heilongjiang, Anhui, Yunnan, and Tibet exhibit the highest efficiency scores. Mongolia, Heilongjiang, Sichuan, Hebei, and Hunan are the five provinces most affected by climate change. This study's findings indicate that the average total factor forestry productivity (TFPC) is 1.0480, representing an increase of 4.80%. The primary determinant for change is technology change (TC), which surpasses efficiency change (EC). Including climate variables reduces total factor productivity change (TFPC) to 1.0205, mainly driven by a decrease in TC. The region of South China exhibits the highest total factor productivity change (TFPC) with a value of 1.087, whereas both Northeast China and Central China observe falls below 1 in TFPC. The Mann–Whitney U test provides evidence of statistically significant disparities in forestry efficiency and TFPC scores when estimated with and without incorporating climate factors. Kruskal–Wallis found a statistically significant difference in FRE and TFPC among seven regions. [ABSTRACT FROM AUTHOR]

This paper summarises environmental monitoring activities and small plot research in agriculture as practiced in the Heilongjiang province located northeast in China and in Norway. For both countries, there is a need to recommend efficient mitigation measures to farmers and monitor the environmental effect of agricultural systems and management practices. Climate change scenarios predict changes in precipitation which potentially can influence agricultural practices as well as lead to changes in run-off and related to land use as well as the environment losses. As such, cooperation in the further development of monitoring programmes and related techniques will be useful in documenting both present and future, climate change-induced changes, related land use as well as the environmental. [ABSTRACT FROM AUTHOR]

The Heilongjiang-Amur River Basin is one of the largest and most complex aquatic systems in Asia, comprising diverse wetland resources. The wetland vegetation in mid-high latitude areas has high natural value and is sensitive to climate changes. In this study, we investigated the wetland vegetation cover changes and associated responses to climate change in the Heilongjiang-Amur River Basin from 2000 to 2018 based on the growing season (May to September) climate and LAI data. Our results indicated that the wetland LAI increased at 0.014 m²·m-2/yr across Heilongjiang-Amur River Basin with the regional climate showed wetting and warming trends. On a regional scale, wetland vegetation in China and Russia had positive partial correlation with solar radiation and minimum air temperature, with precipitation showing a slight lag effect. In contrast, wetland vegetation in Mongolia had positive partial correlation with precipitation. These correlations were further investigated at different climate intervals. We found the precipitation is positively correlated with LAI in the warm regions while is negatively correlated with LAI in the wet regions, indicating an increase in precipitation is beneficial for the growth of wetland vegetation in heat sufficient areas, and when precipitation exceeds a certain threshold, it will hinder the growth of wetland vegetation. In the cold regions, we found solar radiation and minimum air temperature are positively correlated with LAI, suggesting SR and minimum air temperature instead of mean air temperature and maximum air temperature play more important roles in affecting the wetland vegetation growth in the heat limited areas. The LAI was found to be negatively correlated with maximum air temperature in the arid areas, indicating excessive temperature would inhibit the wetland vegetation growth when the water is limited. Our investigation can provide a scientific foundation for the trilateral region in wetland ecosystem protection and is beneficial for a more comprehensive understanding of the responses of wetlands in the middle and high latitudes to climate change. [ABSTRACT FROM AUTHOR]

Under the threat of global climate change, China has proposed a dual carbon goal of peak carbon and carbon neutrality. As the vital carrier for territorial spatial planning, production–living–ecological (PLE) spaces drive carbon emissions and are important to the dual carbon goals. In this study, carbon emissions and sinks of PLE spaces in cities in Heilongjiang Province from 2005 to 2020 were calculated and spatial–temporal changes were analyzed. The carbon emission structure was analyzed in segmentation sectors. The land use changes and socioeconomic factors on carbon emissions were analyzed, and emission reduction strategies were implemented. The results show the following: (1) Carbon emissions from production and living spaces increased yearly. Carbon sinks were smaller than emissions, but capacity was stable. (2) Higher-emission cities were concentrated in southwest Heilongjiang, and carbon emission differences between regions gradually increased. (3) Among carbon emission sectors, agricultural and household made up smaller proportions, while animal husbandry, industrial, transportation, and traffic travel contributed most. Carbon emission structures were transformed by adjusting urban development and industrial structure. (4) For most cities, industrial space was the main emission space, but agricultural production and urban–rural living spaces dominated in some cities. (5) GDP, urbanization rate, and area of city paved roads suppressed emissions in cities with decreased carbon emission grades. The industrial structure and coal consumption inhibited emissions in cities with maintaining and increasing carbon emissions grades. [ABSTRACT FROM AUTHOR]

In this study, instrument-measured evaporation and conventional meteorological observations from 80 stations in Heilongjiang Province from 1961 to 2020 were collected. Using these data, methods such as linear trend estimation, cumulative anomaly, multiple linear regression, and Morlet wavelet analysis were employed to analyze the changes of instrument-measured evaporation annually and seasonally in Heilongjiang Province. Additionally, we analyzed its response to climate change. The results showed that from 1961 to 2020, annual pan evaporation in Heilongjiang Province showed a significant downward trend, decreasing at 10.5 mm per decade. Evaporation decreased significantly in spring, while the magnitude of this decrease in summer and autumn was relatively small, and evaporation increased significantly in winter. In the periodic change, annual and seasonal evaporation have significant periods on short time scales Among them, and mainly have a short period of 3–4 years, has short periods of about 3 years and 6 years, mainly has short periods of 2 years and 3 years, and mainly has short periods of about 4 years. The geographical correlation of evaporation was significant, with evaporation decreasing as latitude, longitude and altitude increased. Additionally, we found that changes in annual and seasonal pan evaporation were positively correlated to changes in average temperature, hours of sunshine, and wind speed, and negatively correlated to changes relative humidity. Our analysis indicates that a significant decrease in wind speed and hours of sunshine is the dominant factor leading to the decrease in evaporation throughout the year as well as in spring, summer and autumn, while higher temperatures and lower relative humidity may lead to a significant increase in evaporation in winter. [ABSTRACT FROM AUTHOR]

Global climate change is projected to increase the probability of occurrence and severity of droughts. Increased CO2 concentration drives partial closure of plant stomata and reduces evapotranspiration. However, the impact of reduced evapotranspiration due to CO2 on future droughts characteristics in China is unclear. In this study, we have used the Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate model simulations (GCMs) under historical period, and four shared socioeconomic pathway scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5) to estimate drought. We used a widely applicable drought index (i.e., the self‐calibrating Palmer Drought Severity Index [scPDSI]) to evaluate the historical and future drought conditions, using the Penman–Monteith formula with and without the CO2 concentrations. The results show that the increasing trend of scPDSI slows down when the CO2 effect is considered in all scenarios, especially in Heilongjiang, northern Xinjiang, and the Qinghai–Tibet Plateau. The divergence in the slowdown trend among the different scenarios becomes greater after 2030, with higher emission scenarios implying a greater slowdown in the increasing trend of scPDSI. After considering CO2, drought characteristics such as the drought frequency, intensity, and drought area decrease. Increased CO2 concentration on vegetation physiological processes could mitigate future drought. Therefore, the effects of CO2 on plant physiology should be considered in studies of future drought trends to develop more realistic response and adaptation policies to future drought changes. [ABSTRACT FROM AUTHOR]

With global warming, previous studies have found nonuniformity responses of precipitation because of regional differences. However, climate change affects the mean, extreme, and data structure of precipitation. Quantile regression, which can reflect every part of the trends of data, was used to detect responses of each part of precipitation in China. The V2.0 dataset of daily precipitation grid data (0.5° × 0.5°) from 1961 to 2020 in China was used as practical observation data. Daily precipitation in 2015–2100 from the China Model BCC-CSM2-MR of scenarios SSP2-4.5 and SSP5-8.5 were chosen as future climate changes with moderate and high radiative forcing, respectively. On the basis of the sign consistency of the slope coefficients with quantile regression, the results of quantiles q = 0.3, 0.5, 0.7 and 0.9 were selected to represent low, median, high and flood precipitation, respectively. Precipitation in four seasons was separately analyzed to observe seasonal characteristics in China. For the observation data, precipitation had obviously different responses in the low and high percentiles and was present in mainly spring and summer. In spring, in the middle and lower Yangtze Plains, the low and median precipitation increased, whereas the high and flood precipitation significantly decreased. In summer, Heilongjiang Province and northern Inner Mongolia showed decreasing trends in the low quantile and increasing trends in the high quantile, indicating a completely opposite trend adjustment. These regions deserve more attention. However, obviously different responses in low and high percentiles were not so evident in future climate changes. Self-consistency in model data may weaken the heteroscedastic characteristics of precipitation. [ABSTRACT FROM AUTHOR]

Climate change refers to the statistically significant changes in the mean and dispersion values of meteorological factors. Characterizing potential evapotranspiration (ET0) and its climatic causes will contribute to the estimation of the atmospheric water cycle under climate change. In this study, based on daily meteorological data from 26 meteorological stations in Heilongjiang Province from 1960 to 2019, ET0 was calculated by the Penman–Monteith formula, linear regression method and the Mann–Kendall trend test were used to reveal the seasonal and inter-annual changing trend of ET0. The sensitivity-contribution rate method was used to clarify the climatic factors affecting ET0. The results showed that: (1) From 1960 to 2019, the maximum temperature (Tmax), minimum temperature (Tmin) and average temperature (Tmean) showed an increasing trend, with climate tendency rate of 0.22 °C per decade (10a), 0.49 °C/(10a), 0.36 °C/(10a), respectively. The relative humidity (RH), wind speed (U) and net radiation (Rn) showed a decreasing trend, with a climate tendency rate of −0.42%/(10a), −0.18 m/s/(10a), −0.08 MJ/m2/(10a), respectively. (2) ET0 showed a decreasing trend on seasonal and inter-annual scales. Inter-annually, the average climate tendency rate of ET0 was −8.69 mm/(10a). seasonally, the lowest climate tendency rate was −6.33 mm/(10a) in spring. (3) ET0 was negatively sensitive to Tmin, and RH, while positively sensitive to Tmax, TmeanU and Rn, its sensitivity coefficient of U was the highest, which was 1.22. (4) The contribution rate of U to ET0 was the highest on an inter-annual scale as well as in spring and autumn, which were −8.96%, −9.79% and −13.14%, respectively, and the highest contribution rate to ET0 were Rn and Tmin in summer and winter, whose contribution rates were −4.37% and −11.46%, respectively. This study provides an understanding on the response of evapotranspiration to climatic change and further provides support on the optimal allocation of regional water resource and agricultural water management under climate change. [ABSTRACT FROM AUTHOR]

Understanding future changes in water supply and requirement under climate change is of great significance for long-term water resource management and agricultural planning. In this study, daily minimum temperature (Tmin), maximum temperature (Tmax), solar radiation (Rad), and precipitation for 26 meteorological stations under RCP4.5 and RCP8.5 of MIRCO5 for the future period 2021–2080 were downscaled by the LARS-WG model, daily average relative humidity (RH) was estimated using the method recommended by FAO-56, and reference crop evapotranspiration (ET0), crop water requirement (ETc), irrigation water requirement (Ir), effective precipitation (Pe), and coupling degree of ETc and Pe (CD) for soybean during the growth period were calculated by the CROPWAT model in Heilongjiang Province, China. The spatial and temporal distribution of these variables and meteorological factors were analyzed, and the response of soybean water supply and requirement to climate change was explored. The result showed that the average Tmin, Tmax, and Rad under RCP4.5 and RCP8.5 increased by 0.2656 and 0.5368 °C, 0.3509 and 0.5897 °C, and 0.0830 and 0.0465 MJ/m², respectively, while the average RH decreased by 0.0920% and 0.0870% per decade from 2021 to 2080. The annual average ET0, ETc, Pe, and Ir under RCP4.5 for 2021–2080 were 542.89, 414.35, 354.10, and 102.44 mm, respectively, and they increased by 1.92%, 1.64%, 2.33%, and −2.12% under the RCP8.5, respectively. The ranges of CD under RCP4.5 and RCP8.5 were 0.66–0.95 and 0.66–0.96, respectively, with an average value of 0.84 for 2021–2080. Spatially, the CD showed a general trend of increasing first and then decreasing from west to east. In addition, ET0, ETc, and Pe increased by 9.55, 7.16, and 8.77 mm per decade, respectively, under RCP8.5, while Ir decreased by 0.65 mm per decade. Under RCP4.5 and RCP8.5, ETc, Pe, and Ir showed an overall increasing trend from 2021 to 2080. This study provides a basis for water resources management policy in Heilongjiang Province, China. [ABSTRACT FROM AUTHOR]

Under a changing environment, the effect of climate change and human activities on maize yield is vital for ensuring food security and efficient socio-economic development. The time series of maize yield is generally non-stationary and contains different frequency components, such as long- and short-term oscillations. Nevertheless, there is no adequate understanding of the relative importance of climate change. In addition, human activities on maize yield at multiple timescales remain unclear, which help in further improving maize yield prediction. Based on the ensemble empirical mode decomposition method (EEMD), the method of dependent variable variance decomposition (DVVD) and the Sen-slope method, the effect of climate change including growing-season precipitation and temperature (i.e., GSP, GEP, CDD, GST, GSMAT, and GSMT) and human activities including effective irrigation area (EIA) and the consumption of chemical fertilizers (CCF) on maize yield were explored at multiple timescales during 1979–2015. The Heilongjiang Province, a highly important maize production area in China, was selected as a case study. The results of this work indicate the following: (1) The original maize yield series was divided into 3.1-, 7.4-, 18.5-, and 37-year timescale oscillations and a residual series with an increasing trend, where the 3.1-year timescale (IMF1), the 18.5-year timescale (IMF3), and the increasing trend (R) were dominant; (2) the original sequence was mainly affected by human activities; (3) climate change and human activities had different effects on maize yield at different timescales: The short-term oscillation (IMF1) of maize yield was primarily affected by climate change. However, human activities dominated the mid- and long-term oscillations (IMF3 and R) of maize yield. This study sheds new insight into multiple timescale analysis of the role of climate and human activities on maize yield dynamics. [ABSTRACT FROM AUTHOR]

Predicting the impact of future climate change on food security has important implications for sustainable food production. The 26 meteorological stations' future climate data in the study area are assembled from four global climate models under two representative concentration pathways (RCP4.5 and RCP8.5). The future maize yield, actual crop evapotranspiration (ETa), and water use efficiency (WUE) were predicted by calibrated AquaCrop model under two deficit irrigation (the regulated deficit irrigation (RDI) at jointing stage(W1), filling stage(W2)), and full irrigation (W3) during the three periods (2021–2040, 2041–2060, and 2061–2080). The result showed that the maize yields under W1, W2, and W3 of RCP4.5 were 2.8%, 2.9%, and 2.5% lower than those in RCP8.5, respectively. In RCP8.5, the yield of W3 was 1.9% and 1.4% higher than W1 and W2, respectively. Under the RCP4.5, the ETa of W1, W2, and W3 was 481.32 mm, 484.94 mm, and 489.12 mm, respectively. Moreover, the ETa of W1 was significantly lower than W2 under the RCP4.5 and RCP8.5 (p > 0.05). In conclusion, regulated deficit irrigation at the maize jointing stage is recommended in the study area when considering WUE. [ABSTRACT FROM AUTHOR]

Heilongjiang Province is under the pressure of a water shortage due to climate change, population growth and economic development. To effectively manage regional land and water resources, this paper describes a system dynamics model that was built to simulate the interaction between land and water resources and socioeconomic factors, as well as the evolution of regional land and water resources in different climates in Heilongjiang Province. The results show that the declining trend of unused land area and the water supply–demand ratio will not stop, even under the most optimistic (e.g., humid climate) climate conditions, if the current land use patterns continue. Therefore, measures should be taken to manage the unreasonable usage patterns of land and water resources in this region. This study simulated the evolution of regional land and water resources for five scenarios under an arid climate by changing the net irrigation quota for paddy fields, the water quota for industrial use, forestland area, annual change rate of farmland area, and the growth rate of the gross industrial output value. Further, a combined scenario that can maximally reduce the regional land and water resource sustainable risk was identified. The simulation of the combined scenario showed that it can effectively increase the degree of regional land and water resource use in the region, as well as reduce the risks that threaten these resources. This study provides theoretical support for the efficient use of land and water resources in the future. [ABSTRACT FROM AUTHOR]

The scope of this study is to analyze the climatic potential productivity of soybean [Glycine max (L.) Merr.] and explore the impact of climate change on soybean in the frigid region in China by using daily climatic variables from 144 meteorological stations for the period 1971‒2019. The gradually descending model is used to estimate photosynthesis, light-temperature, and climatic potential productivity of soybean. The results show that climate potential productivity of soybean in the frigid region ranges from large to small: Liaoning > Jilin > Heilongjiang > East Four Leagues (four cities in eastern Inner Mongolia), with Heilongjiang and East Four Leagues showing a significant upward trend. Spatially, the climate potential productivity is larger on plains than that on mountains. The Northeast Plain and Sanjiang Plain are areas with high climate potential productivity. Changes in climatic factors have different impacts on the climate potential productivity of soybean. The influence of temperature changes on the climate potential productivity shows a positive effect, and climate warming compensates for the lack of heat in the frigid region. Furthermore, radiation and precipitation are the main climatic factors leading to spatial differences in the climate potential productivity of soybean in the frigid region. Radiation changes have a positive effect on soybean climate potential productivity in plain areas and a negative effect on the mountains. However, precipitation reduction negatively affects most of the frigid region, while it has a positive effect on the two plains of Heilongjiang. Precipitation responses the needs of soybean growth. Our findings recommend that a transition of soybean planting from the mountainous region to plain, that is, from low potential productivity areas to high potential productivity areas, could be an effective strategy for regional optimization for planting structure and rational utilization of irrigation technology. [ABSTRACT FROM AUTHOR]

• GHG emissions and crop water demand under various scenarios were evaluated. • Changes in planting structure in the study area increased water demand and GHG emissions. • The expansion of the planting area is the main reason for increasing water demand and GHG emissions. • Rice has the greatest impact on GWP during the study period in Heilongjiang. The agriculture sector is one of the largest users of water and a significant source of greenhouse gas (GHG) emissions. The development of low-GHG-emission and water-conserving agriculture will inevitably be the trend in the future. Because of the physiological differences among crops and their response efficiency to external changes, changes in planting structure, climate and input of production factors will have an impact on regional agricultural water use and GHG emissions. This paper systematically analyzed the spatial-temporal evolution characteristics of crop planting structure, climate, and production factor inputs in Heilongjiang Province, the main grain-producing region of China, from 2000 to 2015, and quantified the regional agricultural water use and GHG emissions characteristics under different scenarios by using the Penman-Monteith formula and the Denitrification-Decomposition (DNDC) model. The results showed that the global warming potential (GWP) increased by 15% due to the change in planting structure. A large increase in the proportion of rice and corn sown was the main reason. During the study period, regional climate change had a positive impact on the water-saving and emission reduction of the agricultural industry. The annual water demand per unit area decreased by 19%, and the GWP decreased by 12% compared with that in 2000. The input of fertilizer and other means of production will have a significant impact on GHG emissions from farmlands. The increase in N fertilizer input significantly increased N 2 O emissions, with a 5% increase in GWP. Agricultural water consumption and carbon emissions are affected by changes in climate, input of means of production, and planting structure. Therefore, multiple regulatory measures should be taken in combination with regional characteristics to realize a new layout of planting structure with low emissions, water conservation, and sustainability. [ABSTRACT FROM AUTHOR]

Temporal and spatial variations in reference evapotranspiration (ET0) and aridity index (AI) can be used as important indexes for understanding climate change and its effects on ecosystem stability. Thus, in this work, we comprehensively investigated 71 meteorological stations in Northeast China from 1965 to 2017 to analyze the spatial-temporal variation and trend of ET0 and AI using the nonparametric Mann–Kendall test, the linear regression, and the Morlet wavelet methods. The results elucidated that ET0 for Northeast China as a whole exhibited a decrease at a rate of −1.97 mm/yr, AI declined at a rate of −0.01/yr during 1965–2017, and approximately 94% stations showed a decrease trend. Spatially, the high values of AI and ET0 were primarily at the western part of the study area except for the Heilongjiang province, and the stations showing low values were mainly distributed in the central and eastern part. The decreasing trends for AI were more obvious in the eastern part compared with the western part over the study region. The abrupt changes in AI occurred in 2005 and 2007, whereas only one abrupt change for ET0 occurred in 1995. For annual ET0, there were periods of 3, 7, 11, and 15 yr, and there existed periods of 1, 7, 11, and 13 yr for annual AI. The correlation coefficients implied wind speed and precipitation were the dominant meteorological factors resulting in the ET0 and AI decrease, respectively. Additionally, the change of the Indian summer monsoon index (ISMI) may also contribute to the weakened AI in the study area. Nevertheless, further investigation is still required to clarify the mechanisms for AI and ET0 variations in the future. [ABSTRACT FROM AUTHOR]

Recently, forest carbon (C) budgets have been significantly affected by climate variability, nitrogen (N) deposition, an increasing global atmospheric CO2 concentration, and disturbances (i.e., harvests, fires, and insect infestations). In this study, we quantitatively simulated the annual carbon balance of forests in Heilongjiang, China, from 1901 to 2013 using the Integrated Terrestrial Ecosystem Carbon (InTEC) model, which integrated the effects of nondisturbance (i.e., atmospheric CO2 concentration, N deposition, and climate variability) and disturbance factors. The average net primary production (NPP) of Heilongjiang was 284 g C m-2 a-1 in 1901 and increased in 1950 to 339 g C m-2 a-1; a rapid increase occurred after 1980, with an increase of 48% in 2013 compared with the NPP in 1901. The average NPP of the entire Heilongjiang region increased significantly and became more stable in 2013. However, the NPP in the northern region of the Xiaoxing'an Mountains was lower than that in the other regions. The fluctuation in average net ecosystem production (NEP) was relatively large because Heilongjiang was a carbon source for many years before the 1930s and again in the early 21st century, due to serious disturbances and intensified human activities. In recent years, NEP began to increase again, and in 2013 the forests became a large carbon sink (188 g C m-2 a-1). The spatial distribution of the average NEP was similar to that of NPP, though the largest increment in the average NEP from 1901 to 2013 was in the Changbai Mountains. [ABSTRACT FROM AUTHOR]

Simple Summary: The Asian corn borer (ACB), Ostrinia furnacalis, is an important economic pest of corn and other crops, and is widely distributed in China. Depending on the climate, ACB may have one or up to seven generations each year, from north to south, respectively. The degree of crop damage is closely related to its phenology and number of generations per year (voltinism). Climate warming may result in an alternation of voltinism in the ACB. In the present study, we investigated the voltinism of different populations under different simulated environments. From the diapause response, both the uni- and multivoltine ecotypes were coexisting in the Harbin (H) population collected from action sites of ACB moths in Harbin, Heilongjiang Province, China. Diapause incidence declined given the climate-warming scenario, which was temporally specific and could be overridden by significantly low daily average temperatures. Elevated CO2 did not directly impact voltinism. On the basis of voltinism, the H population reflected sympatric uni- and multivoltine ecotypes, with multivoltinism being dominant. The univoltinism trait was recessive. Climate warming could significantly override photoperiod effects. Warmer temperatures and declining latitude (reduced daylength), and their interaction, are estimated to drive ACB evolution to increased homogeneity and multivoltinism. In the Asian corn borer (ACB), Ostrinia furnacalis (Guenée), diapause is governed by a multigenetic constitution that responds to daylength and temperature with seasonality. The ACB displays uni- or multivoltinism, depending on its geographic specificity. Hence, warmer temperatures may result in alternation of voltinism in the ACB, which will help in understanding the ecological consequences of climate warming on insects. In the present study, we investigated the voltinism in two natural populations from Harbin (H) and Gongzhuling (G) as well as a laboratory (L) population (established from the H population in 2017) of the ACB, at ambient and elevated atmospheric CO2 (aCO2 390 μL/L and eCO2 750 μL/L) and temperature (aT and Et = At + 2 °C). From the diapause response, both the uni- and multivoltine ecotypes were coexisting in the H population. The neonate occurrence date of 50% individuals that induced diapause was ca. 10 days later in the G population than in the H population, but it was about 10 days earlier than in the L population. Comparing to the dates of onset and the peak of diapause induction, the G and L populations were less variable than the H population in response to a short and/or shortening daylength in the field. The univoltine individuals could not be eliminated completely after 19 generations of selection. Diapause incidence decreased with a climate-warming scenario, which was temporally specific and could be overridden by significantly low daily average temperatures. The eCO2 did not directly impact the voltinism. On the basis of voltinism, the H population was sympatric for uni- and multivoltine ecotypes, with multivoltinism being dominant. The univoltinism trait was recessive. Climate warming could significantly override the effect of photoperiod, which was yearly dependent. Warmer temperatures and a decreased latitude (shortened daylength), and their interaction, would drive ACB evolution toward diapause homogeneity for multivoltinism. [ABSTRACT FROM AUTHOR]

Water resources from rivers are essential to humans. The discharge of rivers is demonstrated to be significantly affected by climate change in the literature, particularly in the boreal and subboreal climate zones. The Da Hinggan Mountains in subboreal northeast China form the headwaters of the Heilongjiang River and the Nenjiang River, which are important water resources for irrigation of downstream agriculture and wetlands. In this study, long-term (44 years) hydrologic, climate and forest dynamics data from the Tahe were analyzed using the soil and water assessment tool (SWAT) model to quantify the effects of climate and forest change on runoff depth. Meanwhile, downscaled precipitation and temperature predictions that arose from global climate models (GCMs) under four representative concentration pathways (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5) were forced using the SWAT model to investigate the climate change impacts on the Tahe River flows in the future. The results indicated that compared with the 1972–1982 period, the forest biomass in the 1984–1994 period was reduced by 17.6%, resulting in an increase of 16.6% in mean annual runoff depth. On the contrary, with reforestation from the 1995–2005 period to the 2006–2016 period, the mean forest biomass was increased by 9.8%, resulting in the mean runoff depth reduction of 11.9%. The tree species composition shift reduced mean annual runoff depth of 13.3% between the 1984–1994 period and the 2006–2016 period. Compared with base years (2006–2016), projections of GCM in the middle of the 21st century indicated that both mean annual temperature and precipitation were expected to increase by −0.50 °C and 43 mm under RCP 2.6, 0.38 °C and 23 mm under RCP 4.5, 0.67 °C and 36 mm under RCP 6.0 and 1.00 °C and 10 mm under RCP 8.5. Simulated results of the SWAT model showed that annual runoff depth would increase by 18.1% (RCP 2.6), 11.8% (RCP 4.5), 23.6% (RCP 6.0), and 11.5% (RCP 8.5), compared to the base years. Such increased runoff was mainly attributed to the increase in April, July, August, September and October, which were consistent with the precipitation prediction. We concluded that the future climate change will increase the water resources from the river, thereby offsetting the possible decline in runoff caused by the forest recovery. The findings of this study might be useful for understanding the impacts of climate and forest change on runoff and provide a reasonable strategy for managers and planners to mitigate the impact of future climate change on water resources in the subboreal forested watersheds. [ABSTRACT FROM AUTHOR]

Background: Around the Cretaceous-Paleogene (K-Pg) boundary, an obvious global cooling occurred, which resulted in dramatic changes in terrestrial ecosystems and the evolutionary trends of numerous organisms. However, how plant lineages responded to the cooling has remained unknown until now. Between ca. 70–60 Ma Mesocyparis McIver & Basinger (Cupressaceae), an extinct conifer genus, was distributed from eastern Asia to western North America and provides an excellent opportunity to solve this riddle. Results: Here we report a new species, Mesocyparis sinica from the early Paleocene of Jiayin, Heilongjiang, northeastern China. By integrating lines of evidence from phylogeny and comparative morphology of Mesocyparis, we found that during ca.70–60 Ma, the size of seed cone of Mesocyparis more than doubled, probably driven by the cooling during the K-Pg transition, which might be an effective adaptation for seed dispersal by animals. More importantly, we discovered that the northern limit of this genus, as well as those of two other arboreal taxa Metasequoia Miki ex Hu et Cheng (gymnosperm) and Nordenskioldia Heer (angiosperm), migrated ca.4–5° southward in paleolatitude during this time interval. Conclusions: Our results suggest that the cooling during the K-Pg transition may have been responsible for the increase in size of the seed cone of Mesocyparis and have driven the migration of plants southwards. [ABSTRACT FROM AUTHOR]

Drought is a natural extreme climate event which occurs in most parts of the world. Northeastern China is one of the major agricultural production areas in China and also a typical vulnerable climate zone. To understand the spatio-temporal characteristics of drought over northeastern China, we first assessed the trends of precipitation and temperature. Drought events were then characterized by Standardized Precipitation Evapotranspiration Index over various temporal scales. The Trend Free Prewhitening Mann–Kendall test and distinct empirical orthogonal function, were used to investigate the trends and spatio-temporal patterns of droughts. The results indicate precipitation increasing trends are mostly detected in Heilongjiang and Jinling provinces, however, the majority of the trends are insignificant. Temperature increasing trends are detected over the entire northeastern China and most of them are significant. Decreasing drought trends are observed in Heilongjiang province and some bordering area in Jilin province, whereas increasing trends are noticed in Liaoning province and some bordering area in Jilin province. Two main sub-regions of drought variability—the Liaohe River Plain and the Second Songhua River basin (LS region), and the Songnen Plain and the Lesser Hinggan Mountains (SL region) are identified, and the detected droughts for the two sub-regions correspond well with recorded drought loss. The results will be beneficial for regional water resource management and planning, agriculture production, and ecosystem protection in northeastern China. [ABSTRACT FROM AUTHOR]