Meng, M.; Ni, J.; Zong, M. J.: Impacts of changes in climate variability on regional vegetation in China: NDVI-based analysis from 1982 to 2000. Ecological Research 26 (2), pp. 421 - 428 (2011)
Ashiq, M. W.; Zhao, C. Y.; Ni, J.; Akhtar, M.: GIS-based high-resolution spatial interpolation of precipitation in mountain-plain areas of Upper Pakistan for regional climate change impact studies. Theoretical and Applied Climatology 99 (3-4), pp. 239 - 253 (2010)
Ni, J.; Yu, G.; Harrison, S. P.; Prentice, I. C.: Palaeovegetation in China during the late Quaternary: Biome reconstructions based on a global scheme of plant functional types. Palaeogeography, Palaeoclimatology, Palaeoecology 289 (1-4), pp. 44 - 61 (2010)
Ni, J.; Wang, G. H.; Bai, Y. F.; Li, X. Z.: Scale-dependent relationships between plant diversity and above-ground biomass in temperate grasslands, south-eastern Mongolia. Journal of Arid Environments 68 (1), pp. 132 - 142 (2007)
Ni, J.; Harrison, S. P.; Prentice, I. C.; Kutzbach, J. E.; Sitch, S.: Impact of climate variability on present and Holocene vegetation: A model-based study. Ecological Modelling 191 (3-4), pp. 469 - 486 (2006)
Wang, G.-H.; Ni, J.: Responses of plant functional types to an environmental gradient on the Northeast China Transect. Ecological Research 20 (5), pp. 563 - 572 (2005)
Wang, Q.; Ni, J.; Tenhunen, J.: Application of a geographically-weighted regression analysis to estimate net primary production of Chinese forest ecosystems. Global Ecology and Biogeography 14 (4), pp. 379 - 393 (2005)
Ni, J.: Corrigendum to "Net primary productivity in forests of China: scaling-up of national inventory data and comparison with model predictions" (Forest Ecology and Management, vol 187 (2003), 485-495). Forest Ecology and Management 194 (1-3), p. 413 (2004)
Ni, J.: Estimating net primary productivity of grasslands from field biomass measurements in temperate northern China. Plant Ecology 174 (2), pp. 217 - 234 (2004)
Ni, J.: Forest productivity of the Altay and Tianshan Mountains in the dryland, northwestern China. Forest Ecology and Management 202 (1-3), pp. 13 - 22 (2004)
Ni, J.: Plant functional types and climate along a precipitation gradient in temperate grasslands, north-east China and south-east Mongolia. Journal of Arid Environments 53 (4), pp. 501 - 516 (2003)
Ni, J.: Net primary productivity in forests of China: scaling-up of national inventory data and comparison with model predictions. Forest Ecology and Management 176 (1-3), pp. 485 - 495 (2003)
Ni, J.; Ding, S.-Y.: Modeling the large-scale distribution of plant diversity: a possibility inferred from climate and productivity. Acta Phytoecologica Sinica 26 (5), pp. 568 - 574 (2002)
Clark, D. A.; Brown, S.; Kicklighter, D. W.; Chambers, J. Q.; Thomlinson, J. R.; Ni, J.: Measuring net primary production in forests: Concepts and field methods. Ecological Applications 11 (2), pp. 356 - 370 (2001)
Clark, D. A.; Brown, S.; Kicklighter, D. W.; Chambers, J. Q.; Thomlinson, J. R.; Ni, J.; Holland, E. A.: NPP in tropical forests: an evaluation and synthesis of existing field data. Ecological Applications 11: 371-384. Appendix 1. Estimates from the literature of net primary productivity in tropical forests. Ecological Archives A011-006-A1, pp. 1 - 19 (2001)
The BIOMASS satellite was successfully launched into orbit on 29 April 2025. The BIOMASS mission is designed to map and monitor global forests. It will map the structure of different forest types and provide data on above-ground biomass.
Thanks to FLUXCOM-X, the next generation of data driven, AI-based earth system models, scientists can now see the Earth’s metabolism at unprecedented detail – assessed everywhere on land and every hour of the day.
The Global Carbon Project shows that fossil CO2 emissions will continue to rise in 2024. There is no sign of the rapid and substantial decline in emissions that would be needed to limit the impact of climate change
A recent study by scientists from the Max Planck Institute for Biogeochemistry and the University of Leipzig suggests that increasing droughts in the tropics and changing carbon cycle responses due to climate change are not primarily responsible for the strong tropical response to rising temperatures. Instead, a few particularly strong El Niño events could be the cause.
EU funds the international research project AI4PEX to further improve Earth system models and thus scientific predictions of climate change. Participating scientists from 9 countries met at the end of May 2024 to launch the project at the MPI for Biogeochemistry in Jena, which is leading the project.
Anthropogenic emissions of nitrous oxide (N2O), a much more potent greenhouse gas per molecule than carbon dioxide or methane, increased by around 40% between 1980 and 2020. In 2020, anthropogenic emissions into the atmosphere reached more than 10 million tons per year, according to the new report "Global Nitrous Oxide Budget 2024" by the Global Carbon Project.
A recent study published in Nature, co-authored by Sönke Zaehle, suggests that eucalyptus trees do not benefit from rising CO2. Increased CO2 levels cause soil microorganisms to hold on to their phosphorus. This soil mineral, which is essential for tree growth, is therefore less available.
Removing a tonne of CO2 from the air and thus undoing a tonne of emissions? Doesn't quite work, says a study. And provides four objections in view of Earth systems.
The new report by the Global Carbon Project shows: Fossil CO2 emissions will reach a record high in 2023. If emissions remain this high, the carbon budget that remains before reaching the 1.5°C limit will probably be used up in seven years. Although emissions from land use are decreasing slightly, they are still too high to be compensated by renewable forests and reforestation.
Storing carbon in the soil can help to mitigate climate change. Soil organic matter bound to minerals in particular can store carbon in the long term. A new study shows that the formation of mineral-associated organic matter depends primarily on the type of mineral, but is also influenced by land use and cultivation intensity.