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.
Extreme precipitation should increase with warmer temperatures. Data from tropical regions show that this correlation is obscured by the cooling effect of clouds. When cloud effects are corrected, the increase in extreme precipitation with rising temperatures becomes apparent.
More frequent strong storms are destroying ever larger areas of the Amazon rainforest. Storm damage was mapped between 1985 and 2020. The total area of affected forests roughly quadrupled in the period studied.
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
The Chinese Academy of Sciences (CAS) and the German National Academy of Sciences Leopoldina will hold a joint conference on the challenges of achieving carbon neutrality in Berlin on October 29-30, 2024.
Experts from science, journalism, local authorities and non-governmental organizations consider a change of course in communication on climate issues to be urgently needed. The appeal was published on the occasion of the K3 Congress on Climate Communication with around 400 participants in Graz.
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.
Thuringia is severely affected by climate change, which is already reflected in extreme weather events and rising temperatures. The Climate Council is calling for the consistent implementation and tightening of climate policy targets in order to achieve climate neutrality by 2045. The coming legislative period is crucial for the future of Thuringia.
When it comes to studying climate change, we generally assume that the total amount of carbon emissions determines how much the planet will warm. A new study suggests that not only the amount, but also the timing of those emissions controls the amount of surface warming that occurs on human time-scale.