With a pace of about twice the observed rate of global warming, the temperature on the Qinghai-Tibetan Plateau (Earth's third pole') has increased by 0.2 degrees C per decade over the past 50years, which results in significant permafrost thawing and glacier retreat. Our review suggested that warming enhanced net primary production and soil respiration, decreased methane (CH4) emissions from wetlands and increased CH4 consumption of meadows, but might increase CH4 emissions from lakes. Warming-induced permafrost thawing and glaciers melting would also result in substantial emission of old carbon dioxide (CO2) and CH4. Nitrous oxide (N2O) emission was not stimulated by warming itself, but might be slightly enhanced by wetting. However, there are many uncertainties in such biogeochemical cycles under climate change. Human activities (e.g. grazing, land cover changes) further modified the biogeochemical cycles and amplified such uncertainties on the plateau. If the projected warming and wetting continues, the future biogeochemical cycles will be more complicated. So facing research in this field is an ongoing challenge of integrating field observations with process-based ecosystem models to predict the impacts of future climate change and human activities at various temporal and spatial scales. To reduce the uncertainties and to improve the precision of the predictions of the impacts of climate change and human activities on biogeochemical cycles, efforts should focus on conducting more field observation studies, integrating data within improved models, and developing new knowledge about coupling among carbon, nitrogen, and phosphorus biogeochemical cycles as well as about the role of microbes in these cycles.

The impacts of climate change and human activities on biogeochemical cycles on the Qinghai-Tibetan Plateau

Limiting the rise in global mean temperatures relies on reducing carbon dioxide (CO2) emissions and on the removal of CO2 by land carbon sinks. China is currently the single largest emitter of CO2, responsible for approximately 27 per cent (2.67 petagrams of carbon per year) of global fossil fuel emissions in 20171. Understanding of Chinese land biosphere fluxes has been hampered by sparse data coverage2–4, which has resulted in a wide range of a posteriori estimates of flux. Here we present recently available data on the atmospheric mole fraction of CO2, measured from six sites across China during 2009 to 2016. Using these data, we estimate a mean Chinese land biosphere sink of −1.11 ± 0.38 petagrams of carbon per year during 2010 to 2016, equivalent to about 45 per cent of our estimate of annual Chinese anthropogenic emissions over that period. Our estimate reflects a previously underestimated land carbon sink over southwest China (Yunnan, Guizhou and Guangxi provinces) throughout the year, and over northeast China (especially Heilongjiang and Jilin provinces) during summer months. These provinces have established a pattern of rapid afforestation of progressively larger regions5,6, with provincial forest areas increasing by between 0.04 million and 0.44 million hectares per year over the past 10 to 15 years. These large-scale changes reflect the expansion of fast-growing plantation forests that contribute to timber exports and the domestic production of paper7. Space-borne observations of vegetation greenness show a large increase with time over this study period, supporting the timing and increase in the land carbon sink over these afforestation regions. Newly available atmospheric carbon dioxide measurements from six sites across China during 2009 to 2016 indicate a larger land carbon sink than previously thought, reflecting increased afforestation.

/pdf/large-chinese-land-carbon-sink-estimated-from-atmospheric-5emndisxzf.pdf

Large Chinese land carbon sink estimated from atmospheric carbon dioxide data.

Grasslands cover one third of the earth’s terrestrial surface and are mainly used for livestock production. The usage type, use intensity and condition of grasslands are often unclear. Remote sensing enables the analysis of grassland production and management on large spatial scales and with high temporal resolution. Despite growing numbers of studies in the field, remote sensing applications in grassland biomes are underrepresented in literature and less streamlined compared to other vegetation types. By reviewing articles within research on satellite-based remote sensing of grassland production traits and management, we describe and evaluate methods and results and reveal spatial and temporal patterns of existing work. In addition, we highlight research gaps and suggest research opportunities. The focus is on managed grasslands and pastures and special emphasize is given to the assessment of studies on grazing intensity and mowing detection based on earth observation data. Grazing and mowing highly influence the production and ecology of grassland and are major grassland management types. In total, 253 research articles were reviewed. The majority of these studies focused on grassland production traits and only 80 articles were about grassland management and use intensity. While the remote sensing-based analysis of grassland production heavily relied on empirical relationships between ground-truth and satellite data or radiation transfer models, the used methods to detect and investigate grassland management differed. In addition, this review identified that studies on grassland production traits with satellite data often lacked including spatial management information into the analyses. Studies focusing on grassland management and use intensity mostly investigated rather small study areas with homogeneous intensity levels among the grassland parcels. Combining grassland production estimations with management information, while accounting for the variability among grasslands, is recommended to facilitate the development of large-scale continuous monitoring and remote sensing grassland products, which have been rare thus far.

Remote Sensing of Grassland Production and Management—A Review

[1] Net primary productivity (NPP) is a key flux in the terrestrial ecosystem carbon balance, as it summarizes the autotrophic input into the system. Forest NPP varies predictably with stand age, and quantitative information on the NPP-age relationship for different regions and forest types is therefore fundamentally important for forest carbon cycle modeling. We used four terms to calculate NPP: annual accumulation of live biomass, annual mortality of aboveground and belowground biomass, foliage turnover to soil, and fine root turnover in soil. For U.S. forests the first two terms can be reliably estimated from the Forest Inventory and Analysis (FIA) data. Although the last two terms make up more than 50% of total NPP, direct estimates of these fluxes are highly uncertain due to limited availability of empirical relationships between aboveground biomass and foliage or fine root biomass. To resolve this problem, we developed a new approach using maps of leaf area index (LAI) and forest age at 1 km resolution to derive LAI-age relationships for 18 major forest type groups in the USA. These relationships were then used to derive foliage turnover estimates using species-specific trait data for leaf specific area and longevity. These turnover estimates were also used to derive the fine root turnover based on reliable relationships between fine root and foliage turnover. This combination of FIA data, remote sensing, and plant trait information allows for the first empirical and reliable NPP-age relationships for different forest types in the USA. The relationships show a general temporal pattern of rapid increase in NPP in the young ages of forest type groups, peak growth in the middle ages, and slow decline in the mature ages. The predicted patterns are influenced by climate conditions and can be affected by forest management. These relationships were further generalized to three major forest biomes for use by continentalscale carbon cycle models in conjunction with remotely sensed land cover types. Citation: He, L., J. M. Chen, Y. Pan, R. Birdsey, and J. Kattge (2012), Relationships between net primary productivity and forest stand age in U.S. forests, Global Biogeochem. Cycles, 26, GB3009, doi:10.1029/2010GB003942.

/pdf/relationships-between-net-primary-productivity-and-forest-3j2znxwmvv.pdf

Relationships between net primary productivity and forest stand age in U.S. forests

Maintaining high rates of carbon storage in old forests: A mechanism linking canopy structure to forest function

http://faculty.geog.utoronto.ca/Chen/Chen's%20homepage/PDFfiles2/JEM-2011-Wang.pdf

Relationships between net primary productivity and stand age for several forest types and their influence on China's carbon balance

Background and aims
SOC inventory and soil δ13C were widely used to access the size of soil C pool and to indicate the dynamics of C input and output. The effects of climatic factors and soil physical characteristics and plant litter input on SOC inventory and soil δ13C were analyzed to better understand the dynamics of carbon cycling across ecosystems on the Qinghai-Tibetan Plateau.

http://www.chinaflux.org/manage/eWebEditor/uploadfile/2012101810258613.pdf

Patterns of SOC and soil 13 C and their relations to climatic factors and soil characteristics on the Qinghai- Tibetan Plateau

Carbon fluxes in temperate grassland ecosystems are characterized by large inter-annual variations due to fluctuations in precipitation and land water availability. Since an eddy flux tower has been in operation in the Xilin Gol grassland, which belongs to typical temperate grassland in North China, in this study, observed eddy covariance flux data were used to critically evaluate the biophysical performance of different remote sensing vegetation indices in relation to carbon fluxes. Furthermore, vegetation photosynthesis model (VPM) was introduced to estimate gross primary production (GPP) of the grassland ecosystem for assessing its dependability. As defined by the input variables of VPM, Moderate Resolution Imaging Spectroradimeter (MODIS) and standard data product MOD09A1 were downloaded for calculating enhanced vegetation index (EVI) and land surface water index (LSWI). Measured air temperature (Ta) and photosynthetically active radiation (PAR) data were also included for model simulating. Field CO2 flux data, during the period from May, 2003 to September, 2005, were used to estimate the “observed” GPP (GPP
 obs) for validation. The seasonal dynamics of GPP predicted from VPM (GPP
 VPM) was compared quite well (R
 2=0.903, N=111, p<0.0001) with the observed GPP. The aggregate GPP
 VPM for the study period was 641.5 g C·m−2, representing a ∼6% over-estimation, compared with GPP
 obs. Additionally, GPP predicted from other two typical production efficiency model (PEM) represents either higher overestimation or lower underestimation to GPP
 obs. Results of this study demonstrate that VPM has potential for estimating site-level or regional grassland GPP, and might be an effective tool for scaling-up carbon fluxes.

/pdf/modeling-gross-primary-production-of-a-temperate-grassland-2w15zh9rx5.pdf

Modeling gross primary production of a temperate grassland ecosystem in Inner Mongolia, China, using MODIS imagery and climate data

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Relationships between net primary productivity and stand age for several forest types and their influence on China's carbon balance

Patterns of SOC and soil 13 C and their relations to climatic factors and soil characteristics on the Qinghai- Tibetan Plateau

Modeling gross primary production of a temperate grassland ecosystem in Inner Mongolia, China, using MODIS imagery and climate data