Spatiotemporal changes of gross primary productivity and its response to drought in the Mongolian Plateau under climate change

Gross primary productivity(GPP)of vegetation is an important constituent of the terrestrial carbon sinks and is significantly influenced by drought.Understanding the impact of droughts on different types of vegetation GPP provides insight into the spatiotemporal variation of terrestrial carbon sinks,aiding efforts to mitigate the detrimental effects of climate change.In this study,we utilized the precipitation and temperature data from the Climatic Research Unit,the standardized precipitation evapotranspiration index(SPEI),the standardized precipitation index(SPI),and the simulated vegetation GPP using the eddy covariance-light use efficiency(EC-LUE)model to analyze the spatiotemporal change of GPP and its response to different drought indices in the Mongolian Plateau during 1982-2018.The main findings indicated that vegetation GPP decreased in 50.53% of the plateau,mainly in its northern and northeastern parts,while it increased in the remaining 49.47%area.Specifically,meadow steppe(78.92%)and deciduous forest(79.46%)witnessed a significant decrease in vegetation GPP,while alpine steppe(75.08%),cropland(76.27%),and sandy vegetation(87.88%)recovered well.Warming aridification areas accounted for 71.39% of the affected areas,while 28.53% of the areas underwent severe aridification,mainly located in the south and central regions.Notably,the warming aridification areas of desert steppe(92.68%)and sandy vegetation(90.24%)were significant.Climate warming was found to amplify the sensitivity of coniferous forest,deciduous forest,meadow steppe,and alpine steppe GPP to drought.Additionally,the drought sensitivity of vegetation GPP in the Mongolian Plateau gradually decreased as altitude increased.The cumulative effect of drought on vegetation GPP persisted for 3.00-8.00 months.The findings of this study will improve the understanding of how drought influences vegetation in arid and semi-arid areas.

The multiple roles of crop structural change in productivity,nutrition and environment in China:A decomposition analysis

China's crop structure has undergone significant changes in the last two decades since 2000,with an increase in the share of cereals,vegetables,and fruit,squeezing out other crops.As a result,land productivity,nutrient supply,and carbon emissions have changed.How to reallocate limited farmland among crops to achieve the multiple goals of agrifood systems becomes an important issue.This study explores the sources of land productivity and nutrition supply growth and carbon emissions reduction,and identifies the multiple roles of crop structural change from 2003 to 2020 based on a decomposition analysis.The results reveal that the growth within crops is still the primary driver in land productivity and nutrition supply and the reduction in carbon emissions.However,structural change also plays various roles at different periods.From 2003 to 2010,crop structural change increased the total calorie supply but lowered land productivity and contributed at least 70%of the total growth of carbon emissions.The crop structure was relatively stable,and their effects were modest from 2010 to 2015.From 2015 to 2020,the crop structural change began to play a greater role and generate synergistic effects in improving land productivity,micronutrient supply,and reducing carbon emissions,contributing to approximately a quarter of the growth of land productivity and 30%of total carbon emissions reduction.These results suggest that strategies for crop structural change should comprehensively consider its multiple impacts,aiming to achieve co-benefits while minimizing trade-offs.

Analysis of Spatiotemporal Changes in Integrated Land Productivity in Chongqing from 1997 to 2023

[Objectives]Integrated land productivity can reflect the comprehensive utilization of land and the overall output level,which is the most basic and commonly used indicator in assessing land use efficiency.This thesis aims to analyze the spatial and temporal changes of integrated land productivity in Chongqing from 1997 to 2023 in order to assess its land use efficiency.[Methods]This study measured the integrated land productivity of Chongqing Municipality,the only municipality directly under the central government in the western part of China,over the past 26 years(1997-2023)through relevant surveys and statistical data,and analyzed in depth the integrated land productivity of the 38 districts and counties under the jurisdiction of Chongqing,as well as the functional sub-districts of the"one district and two clusters"and the"one district and two clusters"in Chongqing.It also analyzes the characteristics of spatial and temporal differences in land productivity in 38 districts and counties under the jurisdiction of Chongqing and"one district and two clusters".[Results]The results of the study show that over the past 26 years,the integrated land productivity of Chongqing has shown an annual growth trend,and the integrated land productivity of the 38 districts and counties and the functional subregions of"one district and two clusters"has also increased significantly,but the average annual growth rate of the integrated land productivity varies among different regions.From the perspective of spatial differences,there are significant differences in land productivity among the 38 districts and counties of Chongqing and the functional subregions of"one district and two clusters",which are mainly due to the different natural conditions,economic development levels and functional positioning of each region.[Conclusions]Based on the results of the study and the actual situation of Chongqing,this paper puts forward the leading measures to improve the integrated land productivity,with a view to providing a reference basis for Chongqing to improve the efficiency of land use and promote the sustainable use of land resources.

Assessment of Climate Change Impact on Water Requirement and Rice Productivity

Assessing the impact of climate change(CC)on agricultural production systems is mainly done using crop models associated with climate model outputs.This review is one of the few,with the main objective of providing a recent compendium of CC impact studies on irrigation needs and rice yields for a better understanding and use of climate and crop models.We discuss the strengths and weaknesses of climate impact studies on agricultural production systems,with a particular focus on uncertainty and sensitivity analyses of crop models.Although the new generation global climate models(GCMs)are more robust than previous ones,there is still a need to consider the effect of climate uncertainty on estimates when using them.Current GCMs cannot directly simulate the agro-climatic variables of interest for future irrigation assessment,hence the use of intelligent climate tools.Therefore,sensitivity and uncertainty analyses must be applied to crop models,especially for their calibration under different conditions.The impacts of CC on irrigation needs and rice yields vary across regions,seasons,varieties and crop models.Finally,integrated assessments,the use of remote sensing data,climate smart tools,CO_(2)enrichment experiments,consideration of changing crop management practices and multi-scale crop modeling,seem to be the approaches to be pursued for future climate impact assessments for agricultural systems。

Exploring the Forest Cover Changes and Influential Factors of Dongsithouane National Production Forest Area, Savannakhet Province, Lao PDR

The Dongsithouane National Production Forest (DNPF) is one of the largest natural forest areas in Savannakhet, Lao PDR, which has been a vital support for the local community’s livelihood, Recently, significant changes in land use and land cover (LULC) have been observed in this area, leading to a reduction of natural forests. There were two separate methods of this study: firstly, to identify LULC changes across three different periods, spectral imagery from the Landsat 5 Thematic Mapper (TM) for the years 2001 and 2011, and the Landsat 8 Operational Land Imager (OLI) for 2021 were used as the primary data sources. The satellite images were preprocessed for various forest classes, including pretreatment of the top of atmosphere reflectance by using QGIS software’s semi-automatic classification plug-in (SCP), and ArcGIS was used for post-classification. A supervised classification approach was applied to the satellite images from 2001, 2011, and 2021 to generate diverse maps of LULC. Secondly, a household survey dataset was used to investigate influential factors. Approximately 220 households were interviewed in order to collect socio-economic information (including data on population growth, increased business activities, location of the area, agriculture land expansion, and need for settlement land). Household survey data was analyzed by using SPSS. Descriptive statistics, including frequency distributions and percentages, were applied to observe characteristics. Additionally, a binary logistic regression model was used to analyze the socioeconomic factors related to LULC change in DNPF. Key findings indicated a decline in natural forest areas within the study site. Specifically, both dry dipterocarp forest (−11.35%) and mixed deciduous forest (−0.18%) decreased from 2001 to 2021. The overall accuracy of the LULC maps was 94%, 86%, and 89% for the years 2001, 2011, and 2021 respectively. In contrast, agricultural land increased significantly by 155.70%, while built-up land, and water bodies increased by 65.54% and 35.33%, respectively. The results also highlighted a significant increase in construction land, up to 65.54%. Furthermore, the study found a correlation between agricultural expansion and a reduction of forest areas, along with an increase in built-up land along the forest areas’ boundaries. Timber exploitation and charcoal production also contributed to the decline in forest cover. The logistic regression model identified significant determinants of LULC change, including the area’s location, agricultural land expansion, increased business activity, and the need for settlement land. These factors have influenced the management of DNPF. Urgent sustainable management practices and actions, including forest ecosystem protection, village agricultural zoning, water source and watershed protection and public awareness, are required to preserve the forest areas of DNPF.

Spatio-temporal distribution of net primary productivity along the northeast China transect and its response to climatic change

An improved Carnegie Ames Stanford Approach model （CASA model） was used to estimate the net primary productivity （NPP） of the Northeast China Transect （NECT） every month from 1982 to 2000. The spatial-temporal distribution of NPP along NECT and its response to climatic change were also analyzed. Results showed that the change tendency of NPP spatial distribution in NECT is quite similar to that of precipitation and their spatial correlation coefficient is up to 0.84 （P 〈 0.01）. The inter-annual variation of NPP in NECT is mainly affected by the change of the aestival NPP every year, which accounts for 67.6% of the inter-annual increase in NPP and their spatial correlation coefficient is 0.95 （P 〈 0.01）. The NPP in NECT is mainly cumulated between May and September, which accounts for 89.8% of the annual NPP. The NPP in summer （June to August） accounts for 65.9% of the annual NPP and is the lowest in winter. Recent climate changes have enhanced plant growth in NECT. The mean NPP increased 14.3% from 1980s to 1990s. The inter-annual linear trend of NPP is 4.6 gC·m^-2·a^-1, and the relative trend is 1.17%, which owns mainly to the increasing temperature.

Environmental Regulation,Pollution Treatment Productivity,and Industrial Environmental TFP in China

Amidst growing environmental protection intensity by the Chinese government, this paper investigates the effects of environmental regulation on China＇s industrial pollution treatment productivity and environmental TFP. By estimating China＇s pollution treatment productivity between 2001 and 2008 and analyzing environmental regulation intensity and the effects of the relevant factors and pollution treatment productivity using panel data, this paper discovers that （1） pollution treatment productivity contributed a significant share of about 40% to industrial environmental TFP during the investigation period; （2） environmental regulation may not necessarily cause adverse impacts on pollution treatment efficiency and productivity but demonstrates a U-shaped relationship： when the share of pollution treatment cost in industrial value-added is above the range of 3.8%-5.1%, environmental regulation is likely to promote pollution treatment productivity and thus environmental TFP Judging by the estimation result, enhancing environmental protection and expediting the development of ecological civilization are conducive to China ＂s economic transition towards an intensive, efficient, circular, and sustainable development pattern. China＇s current industrial development has the capacity to tolerate a rather demanding level of pollution treatment and management and China needs to further rely on energy conservation and the environmental production industries to promote the progress of pollution treatment technologies.

Transportation Infrastructure and Productivity Growth:Effects of Railway Speed-Up on Firm's TFP in China

Improvement of transportation infrastructure quality will lead to more sufficient market competition and promote the flow of resources with greater efficiency. This paper considers China's railway speed-up in 2007 as a quasi-natural experiment on China's transportation infrastructure quality improvement. With the initial operation of electric multiple units(EMUs) as the basis of grouping, this research examines the effect of railway speed-up on corporate total factor productivity(TFP) growth by the differencein-differences(DID) method. Overally, the results reveal positive effects both on firms' technological change and efficiency improvement, which lead to the increase of TFP. Based on subsamples divided by different regions and types of enterprises, further analysis indicates that the productivity of exporter, non-state and coastal firms has been mostly affected by the railway speed-up. These conclusions are verified by a placebo test. Besides, firms within "one-hour economic circle" have been shown more sensitive to the effect of railway speed increase.

Spatio-temporal Pattern of Net Primary Productivity in Hengduan Mountains area, China： Impacts of Climate Change and Human Activities

Net primary productivity(NPP), a metric used to define and identify changes in plant communities, is greatly affected by climate change, human activities and other factors. Here, we used the Carnegie-Ames-Stanford Approach(CASA) model to estimate the NPP of plant communities in Hengduan Mountains area of China, and to explore the relationship between NPP and altitude in this region. We examined the mechanisms underlying vegetation growth responses to climate change and quantitatively assessed the effects of ecological protection measures by partitioning the contributions of climate change and human activities to NPP changes. The results demonstrated that: 1) the average total and annual NPP values over the years were 209.15 Tg C and 468.06 g C/(m2·yr), respectively. Their trend increasingly fluctuated, with spatial distribution strongly linked to altitude(i.e., lower and higher NPP in high altitude and low altitude areas, respectively) and 2400 m represented the marginal altitude for vegetation differentiation; 2) areas where climate was the main factor affecting NPP accounted for 18.2% of the total research area, whereas human activities were the primary factor influencing NPP in 81.8% of the total research area, which indicated that human activity was the main force driving changes in NPP. Areas where climatic factors(i.e., temperature and precipitation) were the main driving factors occupied 13.6%(temperature) and 6.0%(precipitation) of the total research area, respectively. Therefore, the effect of temperature on NPP changes was stronger than that of precipitation; and 3) the majority of NPP residuals from 2001 to 2014 were positive, with human activities playing an active role in determining regional vegetation growth, possibly due to the return of farmland back to forest and natural forest protection. However, this positive trend is decreasing. This clearly shows the periodical nature of ecological projects and a lack of long-term effectiveness.

Impacts of Climate Change on Net Primary Productivity in Arid and Semiarid Regions of China

In recent years, with the constant change in the global climate, the effect of climate factors on net primary productivity(NPP) has become a hot research topic. However, two opposing views have been presented in this research area: global NPP increases with global warming, and global NPP decreases with global warming. The main reasons for these two opposite results are the tremendous differences among seasonal and annual climate variables, and the growth of plants in accordance with these climate variables. Therefore, it will fail to fully clarify the relation between vegetation growth and climate changes by research that relies solely on annual data. With seasonal climate variables, we may clarify the relation between vegetation growth and climate changes more accurately. Our research examined the arid and semiarid areas in China(ASAC), which account for one quarter of the total area of China. The ecological environment of these areas is fragile and easily affected by human activities. We analyzed the influence of climate changes, especially the changes in seasonal climate variables, on NPP, with Climatic Research Unit(CRU) climatic data and Moderate Resolution Imaging Spectroradiometer(MODIS) satellite remote data, for the years 2000–2010. The results indicate that: for annual climatic data, the percentage of the ASAC in which NPP is positively correlated with temperature is 66.11%, and 91.47% of the ASAC demonstrates a positive correlation between NPP and precipitation. Precipitation is more positively correlated with NPP than temperature in the ASAC. For seasonal climatic data, the correlation between NPP and spring temperature shows significant regional differences. Positive correlation areas are concentrated in the eastern portion of the ASAC, while the western section of the ASAC generally shows a negative correlation. However, in summer, most areas in the ASAC show a negative correlation between NPP and temperature. In autumn, precipitation is less important in the west, as opposed to the east, in which it is critically important. Temperatures in winter are a limiting factor for NPP throughout the region. The findings of this research not only underline the importance of seasonal climate variables for vegetation growth, but also suggest that the effects of seasonal climate variables on NPP should be explored further in related research in the future.

Carbon Productivity Analysis to Address Global Climate Change

Developing low-carbon economy and enhancing carbon productivity are basic approaches to coordinating economic development and protecting global environment, which are also the major ways to address climate change under the framework of sustainable development. In this paper, the authors analyze the annual rate of carbon productivity growth, the differences of carbon productivity of different countries, and the factors for enhancing carbon productivity. Consequently, the authors clarify their viewpoint that the annual rate of carbon productivity growth can be used to weigh the efforts that a country takes to address climate change, and propose policies and suggestions on promoting carbon production.

Climate change evidence in tree growth and stand productivity at the upper treeline ecotone in the Polar Ural Mountains

Background:Recent warming is affecting species composition and species areal distribution of many regions.However,although most treeline studies have estimated the rates of forest expansion into tundra,still little is known about the long-term dynamic of stand productivity at the forest-tundra intersection.Here,we make use of tree-ring data from 350 larch(Larix sibirica Ledeb.)and spruce(Picea obovata Ledeb.)sampled along the singular altitudinal treeline ecotone at the Polar Urals to assess the dynamic of stand establishment and productivity,and link the results with meteorological observations to identify the main environmental drivers.Results:The analysis of stand instalment indicated that more than 90%of the living trees appeared after 1900.During this period,the stand became denser and moved 50m upward,while in recent decades the trees of both species grew faster.The maximum afforestation occurred in the last decades of the twentieth century,and the large number of encountered saplings indicates that the forest is still expanding.The upward shift coincided with a slight increase of May-August and nearly doubling of September-April precipitation while the increase in growth matched with an early growth season warming(June+0.27°C per decade since 1901).This increase in radial growth combined with the stand densification led to a 6-90 times increase of biomass since 1950.Conclusion:Tree-ring based twentieth century reconstruction at the treeline ecotone shows an ongoing forest densification and expansion accompanied by an increased growth.These changes are driven by climate change mechanism,whereby the leading factors are the significant increase in May-June temperatures and precipitation during the dormant period.Exploring of phytomass accumulation mechanisms within treeline ecotone is valuable for improving our understanding of carbon dynamics and the overall climate balance in current treeline ecosystems and for predicting how these will be altered by global change.

Contributions of climate change, land use change and CO2 to changes in the gross primary productivity of the Tibetan Plateau

The ecosystems on the Tibetan Plateau(TP) are highly vulnerable to climate change, rising CO2 concentration, and land-use and land-cover change(LULCC), but their contributions to changes in the gross primary productivity(GPP) of the TP are not clearly understood. In this study, the role of these three factors on the interannual variations(IAVs) and trends of the TP’s GPP were investigated using 12 terrestrial biosphere models. The ensemble simulations showed that climate change can explain most of the changes in the GPP, while the direct effect of LULCC and rising CO2(mainly fertilization effect) contributed 10% and-14% to the mean GPP values, 37% and -20% to the IAV, and 52% and -24% to the GPP’s trend, respectively. The LULCC showed higher contributions to the significant positive trend in the annual GPP of the TP. However, the results from different model simulations showed that considerable uncertainties were associated with the effects of LULCC on the GPP of the TP.

Assessing the vulnerability of ecosystems to climate change based on climate exposure, vegetation stability and productivity

Background: Global warming has brought many negative impacts on terrestrial ecosystems, which makes the vulnerability of ecosystems one of the hot issues in current ecological research. Here, we proposed an assessment method based on the IPCC definition of vulnerability. The exposure to future climate was characterized using a moisture index(MI) that integrates the effects of temperature and precipitation. Vegetation stability, defined as the proportion of intact natural vegetation that remains unchanged under changing climate, was used together with vegetation productivity trend to represent the sensitivity and adaptability of ecosystems. Using this method, we evaluated the vulnerability of ecosystems in Southwestern China under two future representative concentration pathways(RCP 4.5 and RCP 8.5) with MC2 dynamic global vegetation model.Results:(1) Future(2017–2100) climate change will leave 7.4%(under RCP 4.5) and 57.4% of(under RCP 8.5) of areas under high or very high vulnerable climate exposure;(2) in terms of vegetation stability, nearly 45% of the study area will show high or very high vulnerability under both RCPs. Beside the impacts of human disturbance on natural vegetation coverage(vegetation intactness), climate change will cause obvious latitudinal movements in vegetation distribution, but the direction of movements under two RCPs were opposite due to the difference in water availability;(3) vegetation productivity in most areas will generally increase and remain a low vulnerability in the future;(4) an assessment based on the above three aspects together indicated that future climate change will generally have an adverse impact on all ecosystems in Southwestern China, with non-vulnerable areas account for only about 3% of the study area under both RCPs. However, compared with RCP 4.5, the areas with mid-and highvulnerability under RCP 8.5 scenario increased by 13% and 16%, respectively.Conclusion: Analyses of future climate exposure and projected vegetation distribution indicate widespread vulnerability of ecosystems in Southwestern China, while vegetation productivity in most areas will show an increasing trend to the end of twenty-first century. Based on new climate indicators and improved vulnerability assessment rules, our method provides an extra option for a more comprehensive evaluation of ecosystem vulnerability, and should be further tested at larger spatial scales in order to provide references for regional, or even global, ecosystem conservation works.

Empirical analysis on TFP change in Chinese logistics industry： A nonparametric Malmquist index approach

Through a nonparametric Malmquist index approach, this paper analyzes the total factor productivity change in China＇s logistics industry with panel data of logistics listed corporation from 1999 to 2006, which decomposed into technical efficiency and technical progress. The result shows： （1） The average growth rate of Chinese logistics corporations from 1999 to 2006 is 0.4%, which is mainly due to the improvement of technical efficiency; （2） Technical progress which took the negative effect of the decline could not be neglected; （3） The role of technical efficiency and technical progress are different with time varying.

Impacts of climate change on the potential forest productivity based on a climate-driven biophysical model in northeastern China

Climate warming is expected to influence forest growth,composition and distribution.However,accurately estimating and predicting forest biomass,potential productivity or forest growth is still a challenge for forest managers dealing with land-use at the stand to regional levels.In the present study,we predicted the potential productivity(PP)of forest under current and future climate scenarios(RCP2.6,RCP4.5,RCP6.0 and RCP8.5)in Jilin province,northeastern China by using Paterson’s Climate Vegetation and Productivity(CVP)index model.The PP was validated by comparing it with the mean and maximum net primary production calculated from light energy utilization(GLM_PEM).Our results indicated that using the CVP index model is partially valid for predicting the potential forest productivity in northeastern China.PP exhibited obvious spatial heterogeneity varying from 4.6 to 8.9 m3 ha-1 year-1 with an increasing tendency from northwest to southeast driven by the precipitation across the region.The number of vegetation-active months,precipitation and insolation coefficient were identified as the primary factors affecting PP,but no significant relationship was found for warmest temperature or temperature fluctuation.Under future climate scenarios,PP across the Jilin Province is expected to increase from 1.38%(RCP2.6 in 2050)to 15.30%(RCP8.5 in 2070),especially in the eastern Songnen Plain(SE)for the RCP8.5 scenarios.

Productivity Growth, Technological Progress, and Efficiency Change in Vietnamese Manufacturing Industries: A Stochastic Frontier Approach

This study applies a stochastic frontier production approach to decompose the sources of total productivity (TFP) growth into technical progress and changes in technical efficiency of 8057 firms in Vietnamese manufacturing industries during 2003-2007. Using both total manufacturing industry and sub-manufacturing industrial regressions, the analysis focuses on the trend of technological progress (TP) and technical efficiency change (TEC), and the role of productivity change in economic growth. According to the estimated results, the annual technical progress for the manufacturing industry and sub-manufacturing industries are calculated directly from the estimated parameters of the translog stochastic frontier production function by taking a partial derivative of output with respect to time t. The average technical changes in manufacturing industry and sub-manufacturing industries are positive, with an average technical change about 5.2%, 5.8%, 5.4%, 11.8%, 4.6%, 4.1%, 7.3%, 4.8%, 4.8% and 4.8% for total sample, food products & beverages, textile & wearing apparel, footwear, paper & products, industrial chemicals, rubber & plastic products, non- metallic mineral, basic & fabricated metal and other sub-industries, respectively. Total TFP in the manufacturing sector has grown at the annual rate of 0.052, although the rate of growth decreased continuously during the sample period. For the sub-industry estimates during the sample period, TFP grew fastest in the footwear sub-industry, with annual average growth rate of 11.8%, followed by the rubber & plastic products with a rate of 7.3%, and the food products & beverages with a rate of 5.8% per annum.

Response of vegetation net primary productivity to climate change scenarios in the Loess Plateau of China--A case study of the Yangou watershed

Vegetation net primary productivity(NPP)is a sensitive indicator to characterize the response of terrestrial ecosystems to the climate change.Projections of the NPP changes of the Loess Plateau under future climate scenarios have great significances in revealing the interactions among terrestrial ecosystems and climatic systems,as well as instructing future vegetation construction of this region.Here,we carried out a case study on the Yangou watershed in the Loess Plateau.Using the vegetation-producing process model(VPP)established for such small watersheds,we simulated the NPP of the Yangou watershed under different scenarios of climate changes.The results showed that the NPP significandy increased with the precipitation increasing and evidently decreased with the temperature increasing where the climate change occurred in the whole year or in the summer half year.However,where the climate change occurred in the winter half year,the increased precipitation had little effect on the NPP,and the increased temperature significantly reduced the NPP.There were clear differences among the response sensitivities of different vegetation types with trees and shrubs were more sensitive to the changes in temperature and precipitation than crops and grasses.Currently,the most favourable climate change scenario to the NPP in the Yangou watershed was T0P15 under which the precipitation increased by 15%and the temperature did not changed,in the whole year;in the meantime,the most unfavourable climate change scenarios was T2P-15 under which the precipitation declined by 15%and the temperature increased by 2℃,in the whole year.

A Domain Engineering Approach to Increase Productivity in the Development of a Service for Changes Notification of the Configuration Management Database

This paper presents a domain engineering approach to build a software product line that supports the change notification service in a Configuration Management Database (CMDB) according to the Information Technology Infrastructure Library (ITIL) best practices. For the development of this product line, the proposed approach makes use of a construction of products methodology by analogy: this is a new notation which reports the variability of the products, obtaining metrics as important as the number of products and uses a language that enables, by means of the flexibilization of a product and the development of some generators, to build the rest of the product line. In addition the paper offers a standard for the analysis and design of the CMDB as well. Finally, the paper presents an economic model for the product line, where the profitability and productivity of the proposed solution are analyzed.

Climate Change Impacts on Agroecosystems in China:Processes,Mechanisms and Prospects

Building a more resilient response system to climate change for sustainable development and reducing uncertainty in China’s food markets,requires access to historical research gaps and mapping future research progress for decision making.However,the lack of quantitative and objective analyses to ensure the stability and development of agroecosystems increases the complexity of agro-climatic mechanisms,which leads to uncertainty and undesirable consequences.In this paper,we review the characteristics of climate change in China(1951–2020),reveal the mechanisms of agroecosystem structure in response to climate,and identify challenges and opportunities for future efforts in the context of research progress.The aim is to improve the scientific validity and relevance of future research by clarifying agro-climatic response mechanisms.The results show that surface temperature,precipitation,and frequency of extreme weather events have increased to varying degrees in major agricultural regions of China in 1951–2020.And they have strong geographic variation,which has resulted in droughts in the north and floods in the south.Moreover,climate change has complicated the mechanisms of soil moisture,Net Primary Productivity(NPP),soil carbon pool,and crop pest structure in agroecosystems.This lends to a reduction in soil water holding capacity,NPP,soil carbon content,and the number of natural enemies of diseases and insects,which in turn affects crop yields.However,human interventions can mitigate the deterioration of these factors.We have also realized that the methodology and theory of historical research poses a great challenge to future agroecosystem.Historical and projected climate trends identified current gaps in interdisciplinary integration and multidisciplinary research required to manage diverse spatio-temporal climate change impacts on agroecosystems.Future efforts should highlight integrated management and decision making,multidisciplinary big data coupling,and numerical simulations to ensure sustainable agricultural development,ecological security,and food security in China.