Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning.

Annual gross primary productivity (AGPP) is the basis for grain production and terrestrial carbon sequestration. Mapping regional AGPP from site measurements provides methodological support for analysing AGPP spatiotemporal variations thereby ensures regional food security and mitigates climate change. Based on 641 site-year eddy covariance measuring AGPP from China, we built an AGPP mapping scheme based on its formation and selected the optimal mapping way, which was conducted through analysing the predicting performances of divergent mapping tools, variable combinations, and mapping approaches in predicting observed AGPP variations. The reasonability of the selected optimal scheme was confirmed by assessing the consistency between its generating AGPP and previous products in spatiotemporal variations and total amount. Random forest regression tree explained 85 % of observed AGPP variations, outperforming other machine learning algorithms and classical statistical methods. Variable combinations containing climate, soil, and biological factors showed superior performance to other variable combinations. Mapping AGPP through predicting AGPP per leaf area (PAGPP) explained 86 % of AGPP variations, which was superior to other approaches. The optimal scheme was thus using a random forest regression tree, combining climate, soil, and biological variables, and predicting PAGPP. The optimal scheme generating AGPP of Chinese terrestrial ecosystems decreased from southeast to northwest, which was highly consistent with previous products. The interannual trend and interannual variation of our generating AGPP showed a decreasing trend from east to west and from southeast to northwest, respectively, which was consistent with data-oriented products. The mean total amount of generated AGPP was 7.03 ± 0.45 PgC yr-1 falling into the range of previous works. Considering the consistency between the generated AGPP and previous products, our optimal mapping way was suitable for mapping AGPP from site measurements. Our results provided a methodological support for mapping regional AGPP and other fluxes.

[Innovative design of global change network control experiment: A case design of water and heat factors of grassland ecosystem in China]. / å ¨çƒå˜åŒ–è”ç½‘æŽ§åˆ¶å®žéªŒçš„åˆ›æ–°æ€§è®¾è®¡:ä»¥æˆ‘å›½è‰åœ°ç”Ÿæ€ç³»ç»Ÿæ°´çƒ­è¦ç´ è”ç½‘æŽ§åˆ¶å®žéªŒä¸ºä¾‹.

Global changes have profound impacts on the structure and function of terrestrial ecosystems. It is a prerequisite to realize the sustainable use of ecosystem to clarify the response and adaptation mechanism of ecosystems to global changes. Network of control experiment is an important way to understand the response and adaptation of the structure and function of ecosystems to global change factors at regional and global scales. The scientific top-level design is conducive to the integration, comparison and analysis of integrative network-data, and then supports the development of universal ecological theory. We comprehensively expounded the theoretical basis, methodological principles and brand-new concepts of experimental network design for future global change control experiment networks design from several aspects, such as research progress, development needs, innovative design and research prospects. Taking Chinese grassland ecosystems as an example, based on the concept of space reference points (mean point of water and heat), the innovative design technology system of China's grassland ecosystem networking experiment was proposed, in order to promote the development of networking research of control experiments at both regional and global scales in the future.

[Ecosystem carbon uptake was co-limited by nitrogen and phosphorus in alpine meadow on the Qinghai-Tibet Plateau]. / æ°®ç£·å ±é™åˆ¶é’è—é«˜åŽŸé«˜å¯’è‰ç”¸ç”Ÿæ€ç³»ç»Ÿç¢³å¸æ”¶.

Alpine grassland is threatened by the import of chemicals, fertilizers and other external resources with increasing human activities on the Qinghai-Tibet Plateau. It is unclear how carbon cycle of alpine grasslands is affected by the inputs of external resources such as nitrogen, phosphorus, and potassium (N, P, K) and their interactions. We conducted a 3 year experiment on the interactive addition of N, P and K with alpine grassland as the research object to clarify ecosystem carbon exchange process in response to resource addition by measuring community coverage and ecosystem carbon exchange. The results showed the alpine meadow was represented by carbon sequestration during the growing season. The mean value of net ecosystem CO2 exchange (NEE) was -13.0 µmol·m-2·s-1 under the control treatment. NEE, ecosystem respiration (ER), and gross ecosystem productivity (GEP) showed no significant responses when N, P and K were added separately. NEE was significantly increased by 95.3% and 63.9%, GEP was significantly increased by 45.5% and 33.0% under the combined addition of NP and NPK, but ER remained stable. The combined addition of NP or NPK mainly increased NEE and GEP by increasing the coverage of plant communities and affecting ecosystem water use efficiency. Plant community coverage was increased by 18.1% and 21.4%, respectively. The addition of NP increased productivity and autotrophic respiration in alpine meadow. It might cause soil acidification to inhibit heterotrophic respiration, thereby did not change ER due to the two aspects canceling each other out. The addition of N, P, K alone and NK and PK did not change ecosystem carbon exchange, while the combined addition of NP increased NEE and GEP on the nutrient-deficient alpine meadows, indicating that ecosystem carbon uptake was co-limited by N and P in alpine meadow.

[A coordinated three-dimensional network for observing large-scale terrestrial ecosystem status changes and the consequences on resources and environment]. / å¤§å°ºåº¦é™†åœ°ç”Ÿæ€ç³»ç»ŸçŠ¶æ€å˜åŒ–åŠå ¶èµ„æºçŽ¯å¢ƒæ•ˆåº”çš„ç«‹ä½“åŒ–ååŒè”ç½‘è§‚æµ‹.

Co-driven by environmental change and human activity, global ecosystem has been experiencing rapid changes, with cascading effects on resources and environment. The changes of ecosystem status and its spatiotemporal evolution drivers, and the related resource and environmental effects have been recognized as the long standing topics of large-scale terrestrial ecosystem science. The coordinated observation networks distributed across different continents and the globe provide the valuable tools for observing and evaluating ecosystem state change, for revealing and elaborating mechanisms underlying ecosystem response, for cognizing and understanding ecosystem evolution, and for predicting and early-warning of ecosystem change. Committing to serving the continental-scale ecosystem science and supporting regional ecological environmental governance, this review first comprehensively analyzed the current status of ecological environment observation research networks, then proposed their development directions. This review advocated to develop a collaborative observation system with characteristics of multi-element, multi-interface, multi-medium, multi-process, multi-scale and multi-method, and to establish the new generation of continental ecosystem observation-experiment research network composed of high technology integration, regional distribution network, network management intellectualization, long-term observation & experiment, multi-functional model simulations, and remote data integration and resource sharing. We elaborated on the function orientation, design philosophy, design scheme, construction objectives and technical system of the research network. We hoped provide references for the development of terrestrial ecosystem observation network in China.

[Performance evaluation of GIMMS NDVI based on MODIS NDVI and SPOT NDVI data]. / 基于MODIS NDVI、SPOT NDVI数据的GIMMS NDVI性能评价.

The study evaluated GIMMS NDVI based on MODIS NDVI and SPOT NDVI over the same period from 2000 to 2015. We assessed their absolute values, dynamics, trends and cross-relationships between any two of the NDVIs for the national scale, as well as four separate land use types, i.e., paddy field, dry land, forest, and grassland. GIMMS NDVI was numerically greater than MODIS NDVI and SPOT NDVI. The three NDVIs exhibited equal capability of capturing monthly phenological variations. During the study period, the three NDVIs showed increasing trends in most regions, with GIMMS NDVI showing the smallest increment. Pronounced differences were identified in trends between GIMMS NDVI and MODIS NDVI or SPOT NDVI in the northwest, northeast, south-central China, Tibetan Plateau and Yunnan-Guizhou Plateau, implying that GIMMS NDVI trends in these regions should be interpreted with caution. High correlations existed between the three datasets. MODIS NDVI and SPOT NDVI showed stronger correlations at national scale. The GIMMS NDVI and MODIS NDVI were in highest accordance for dry land, while MODIS NDVI and SPOT NDVI were in higher accordance for the paddy field, forest, and grassland than dry lands.