理解土地利用方式转变过程影响生态系统生物地球化学循环及温室气体排放的机理,并利用模型模拟土地利用方式转变过程对温室气体通量的影响是一项长期、艰巨的科学任务.本研究基于国际上广泛应用的生物地球化学过程模型(DNDC模型),结合气象、土壤和管理措施等数据,模拟了旱田转水田土地利用方式转变后稻田CH4、CO2和N2O三种温室气体的通量和常年种植水稻的稻田温室气体通量,并将模拟值与观测值进行比较.结果 表明:DNDC模型能够较好地模拟新、老稻田温室气体通量的季节变化,但对老稻田温室气体的排放通量模拟效果(R2＞0.89,n=40,P＜0.01)优于新转稻田(R2 ＞0.79,n=265,P＜0.01),且对CH4和CO2的模拟效果优于对N2O的模拟效果;根据田间观测数据,改变模型模拟土地利用方式转换前后土壤SOC浓度和pH值,并不能完全模拟土地利用变化对温室气体的影响,微生物群落在土地利用方式转变过程中可能发生较大变化,需要在模型中进一步体现.通过模型模拟土地利用方式改变对温室气体排放的影响,可为国家温室气体、碳排放清单的编制及管理政策的制定提供参考依据.

: Agricultural production activities are one of the main sources of atmospheric greenhouse gases. Different crop cultivation systems and management methods will affect greenhouse gas emissions. There have been a lot of researches on the laws and control mechanisms of agricultural greenhouse gas emissions at home and abroad, but there are relatively few studies on the laws and influence mechanisms of greenhouse gas emissions. In this study, greenhouse gas fluxes new paddy fields (just converted from paddy fields to rice fields) in 2013- 2016 and old paddy(which have been rice fields for the past 20 years) fields in 2016 as well as soil micro-meteorological and other physical and chemical properties were observed using a field plot experiment at the Qianyanzhou Ecological Station of the Chinese Academy Sciences in southern China. Then, seasonal and annual variation of greenhouse gas fluxes and the main factors that impacting greenhouse gas fluxes were analyzed. Based on the analysis, the dynamic changes of greenhouse gas emissions in rice fields are predicted. The results show that in the first four years after land-use conversion, CH 4 emission fluxes in the new paddy fields were significantly lower than that in the old paddy fields, and annual emission increased with the extension of farming period, while the CH 4 emission rate of old rice fields is not obvious, whereas the difference in emission of the greenhouse gases CO 2 and N 2 O were not significant. Moreover, soil pH and the soil organic carbon content of new rice fields were lower than that of old paddy fields. The model simulation results show that shortening paddy field rotation (water- dry rotation) period (less than 7 years) can effectively reduce CH 4 and total greenhouse gas emissions in paddy fields. The results suggest that using the CH 4 emission coefficient of old rice fields may significantly overestimate CH 4 emissions from new rice fields. This study may provide new insights for understanding the impact of land- use change on greenhouse gas emissions, and provide a basis for accurate estimation of regional agricultural greenhouse gas emissions and the development of emission reduction policies.

As the largest carbon pool of terrestrial ecosystems,soils constitute important sources and sinks of global CO2 balance.Soil respiration is an important pathway of carbon fluxes between the atmosphere and terrestrial ecosystems.Further,soil respiration can also influence terrestrial carbon cycling through climate feedbacks,specifically temperature sensitivity (Q10)-Oil tea (Camellia oleifera) is an important native woody oil crop,and has been widely developed in south China in recent years.High-level fertilization has been widely adopted to increase growth of oil tea trees and maintain soil fertility.In this study,the effects of fertilization on soil respiration,heterotrophic respiration and temperature sensitivity in an oil tea plantation were examined.Static chambers and gas chromatography were used to collect and analyze gas samples.To differentiate soil respiration and soil heterotrophic respiration,the trenching method was used.There were four treatments in this study:oil tea plots with fertilization (OF),oil tea plots without fertilization (CK),trenching plots with fertilization (OF-T),and trenching plots without fertilization (CK-T).The results showed that fertilization had no significant effects on either soil respiration or heterotrophic respiration.Soil CO2 effluxes in different treatments (OF,CK,OF-T,CK-T) were 77.91±2.59,73.71±0.97,66.82±1.02,and 66.84±3.94 mg C m-2 h-1,respectively.The temperature sensitivity of soil CO2 effluxes was 1.77±0.01,1.75±0.03,1.96±0.01,1.79±0.03 in OF,CK,OF-T,and CK-T respectively.Fertilization significantly increased temperature sensitivity of soil heterotrophic respiration,with the Q10 values in the OF-T plots significantly higher than those in the CK-T plots.In addition,fertilization significantly increased soil NH4+-N and NO3--N contents in the surface layer (0-10cm).We also found significant linear relationships between the Q10 of soil CO2 effluxes and soil NH4+-N,as well as NO3--N contents.Our findings may provide basic data for greenhouse gas inventories and understanding their responses to climate change in a typical cash crop plantation in south China.

The generation of big data technology provides a new way for processing massive data related to ecological environment,as well as monitoring and analyzing global ecological environmental problems.This paper first described the basic concepts of big data,and the concept and feature of ecological environmental big data.Then,considering the system structure of general big data,the architecture of big data platform for ecological environment was designed from four key aspects,including data platform,infrastructure platform,technology platform and application service platform.After the main frame is analyzed,key technologies for building technology platform of ecological environmental big data were elaborated in four parts:data acquisition,data storage and management,data computing pattern and data analysis.Finally,in view of future development and difficulties,we put forward some thinking and proposals.

Lakes are an important natural source of CH4 to the atmosphere. However, the multi-seasonal CH4 efflux from lakes has been rarely studied. In this study, the CH4 efflux from Poyang Hu, the largest freshwater lake in China, was measured monthly over a 4-year period by using the floating-chamber technique. The mean annual CH4 efflux throughout the 4 years was 0.54 mmol m−2 day−1, ranging from 0.47 to 0.60 mmol m−2 day−1. The CH4 efflux had a high seasonal variation with an average summer (June to August) efflux of 1.34 mmol m−2 day−1 and winter (December to February) efflux of merely 0.18 mmol m−2 day−1. The efflux showed no apparent diel pattern, although most of the peak effluxes appeared in the late morning, from 10:00 to 12:00 CST (GMT + 8). Multivariate stepwise regression on a seasonal scale showed that environmental factors, such as sediment temperature, sediment total nitrogen content, dissolved oxygen, and total phosphorus content in the water, mainly regulated the CH4 efflux. However, the CH4 efflux only showed a strong positive linear correlation with wind speed within 1 day on a bihourly scale in the multivariate regression analyses but almost no correlation with wind speed on diurnal and seasonal scales.

With the advance of internet and wireless communication technology, the fields of ecology and environment have entered a new digital era with the amount of data growing explosively and big data technologies attracting more and more attention. The eco-environmental big data is based airborne and space-/land-based observations of ecological and environmental factors and its ultimate goal is to integrate multi-source and multi-scale data for information mining by taking advantages of cloud computation, artificial intelligence, and modeling technologies. In comparison with other fields, the eco-environmental big data has its own characteristics, such as diverse data formats and sources, data collected with various protocols and standards, and serving different clients and organizations with special requirements. Big data technology has been applied worldwide in ecological and environmental fields including global climate prediction, ecological network observation and modeling, and regional air pollution control. The development of eco-environmental big data in China is facing many problems, such as data sharing issues, outdated monitoring facilities and techno-logies, and insufficient data mining capacity. Despite all this, big data technology is critical to solving eco-environmental problems, improving prediction and warning accuracy on eco-environmental catastrophes, and boosting scientific research in the field in China. We expected that the eco-environmental big data would contribute significantly to policy making and environmental services and management, and thus the sustainable development and eco-civilization construction in China in the coming decades.

With the arrival of the era of big data and the rapid development of big data technology,the construction and application of ecological environment big data have been initiated.To comprehensively promote the construction and application of ecological environment big data,we summarize in the present paper the opportunities and advantages presented by ecological environment big data in terms of solving ecological environment problems,and analyze the challenges faced regarding the application of ecological environment big data.We review the concept and basic features of big data and present the particularity and complexity of the characteristics of ecological environment big data,taking into consideration the characteristics of the ecological environment.Subsequently,we primarily analyze the opportunities presented by ecological environment big data in mitigating environmental pollution,ecological degradation,and climate change from the aspects of data storage,data processing,data analysis,data interpretation,and presentation,and compare these with the use of traditional ecological environment data.The advantages of ecological environment big data indicate that this type of data can help us to improve the comprehensive decision-making level of ecological environment management.Although prospects for the applications of ecological environment big data in China are promising,there exist potential difficulties and challenges,such as data sharing,dataassessing,data application innovation,data management,technological innovation and launch,professional personnel training,and capital investment.Finally,we propose the following three priority areas concerning ecological environment big data based on our thorough review:(1) standardization of all types of ecological environment data;(2) building the storage,processing,and analysis platforms of ecological environment big data storage and processing analysis;(3) pushing forward the docking of ecological environment big data at home and abroad.

Methane (CH4) emissions are critical to greenhouse gas (GHG) management in agriculture, especially in areas growing rice (Oryza sativa). However, studies on CH4 emissions and the nitrogen (N) fertilization effect in new rice fields in subtropical regions are still scarce. In this study, we designed a split-plot field experiment in Jiangxi Province, southern China, to examine whether land-use legacies and N fertilization would influence CH4 emissions. Using static chambers and gas chromatography, we measured CH4 fluxes in a newly developed rice paddy and a 10-year-old rice paddy. We also measured climatic factors and soil chemical and physical properties to match the flux measurements. The results showed that annual CH4 emissions in the new rice plots were significantly lower than in the old rice plots regardless of N fertilization. Annual CH4 emissions increased with the land-use years of rice paddies, following the order of 1 year < 2 years < 3 years < 10 years. N fertilization significantly decreased CH4 emissions by 36.9% in the first year after the new rice plots were developed, whereas it had no significant effects on CH4 emissions in the old rice plots or the new rice plots in the second and third years. The results suggest that land-use legacies have significant effects on CH4 emissions and may influence the N fertilization effect on CH4 emissions in rice fields in subtropical regions. The findings suggest that land-use legacies should be considered in managing and estimating GHG emissions in rice-growing regions.

Natural heritages are precious and unrenewable treasures that have been handed down through generations by the nature.They are especially important to the protection of biodiversity,the maintaining of the ecological balance and the harmonious development of human and environment.However,the protection of natural heritage sites mainly focuses on biodiversity and landscape nowadays.Important features that could reflect the evolution history of the earth have been damaged beyond retrieve under the effect of expansive human activities,together with the relatively less research on the protection of geodiversity of natural heritage sites.As a counterpart concept of biodiversity,geodiversity provides scientific fundamental to the geological conservation of natural heritages sites.It has been widely accepted that the geodiversity of natural heritage sites has important scientific values,functional values and aesthetic values and so on.Based on the systematic analysis of the geodiversity elements,four geodiversity areas of the Tomur natural heritage site were recognized,including glacier and periglacial area of the high and extremely high mountains,red bed topography area and medium-mountain area on the south slope and medium-mountain area on the north slope of Tomur Peak,using the spatial overlay analysis of the ArcGIS working environment.In reference to the analysis of existed studies,the composition of the geodiversity values were identified,and subsequently the assessment index system of the integrated values of geodiversity was constructed.The index system is composed of six elements,and subordinately including 18 indexes,which were used to evaluate the natural attributes,scientific values and functional values,aesthetic values,economic values and cultural values of the geodiversity of natural heritage site respectively.After that the rating system of geodiversity conservation areas with different values was defined.The area with a score between 8 and 10 belongs to protected area I,which has intact and the most typical geodiversity features and can only be used for scientific study and environmental monitoring.And areas with a score of 6-8,5-6,3-5 and 1-3 can be classified into protected area II,III,IV and V accordingly.Finally,the author carried out empirical study on the Tomur natural heritage site.It has been concluded as follows:(1) the glacier and periglacial area belongs to protected area I,in which any kind of human activities are forbidden;(2) the red bed topography area belongs to protected area II,in which human activities are controlled,and undamaging activities such as tourism and education are allowed;(3) the medium-mountain areas on the south and north slope both can be classified into protected area III,in which the exploitation of minerals and collection of construction materials with limited scale are permitted.