Articles | Volume 15, issue 1
https://doi.org/10.5194/essd-15-25-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/essd-15-25-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
03 Jan 2023
Data description paper |
| 03 Jan 2023
| 03 Jan 2023
TiP-Leaf: a dataset of leaf traits across vegetation types on the Tibetan Plateau
Yili Jin
College of Chemistry and Life Sciences, Zhejiang Normal University,
Jinhua 321004, China
Haoyan Wang
College of Chemistry and Life Sciences, Zhejiang Normal University,
Jinhua 321004, China
Jie Xia
College of Chemistry and Life Sciences, Zhejiang Normal University,
Jinhua 321004, China
College of Chemistry and Life Sciences, Zhejiang Normal University,
Jinhua 321004, China
Kai Li
College of Chemistry and Life Sciences, Zhejiang Normal University,
Jinhua 321004, China
Ying Hou
College of Chemistry and Life Sciences, Zhejiang Normal University,
Jinhua 321004, China
Jing Hu
College of Chemistry and Life Sciences, Zhejiang Normal University,
Jinhua 321004, China
Linfeng Wei
College of Chemistry and Life Sciences, Zhejiang Normal University,
Jinhua 321004, China
Kai Wu
College of Chemistry and Life Sciences, Zhejiang Normal University,
Jinhua 321004, China
Haojun Xia
College of Chemistry and Life Sciences, Zhejiang Normal University,
Jinhua 321004, China
Borui Zhou
College of Chemistry and Life Sciences, Zhejiang Normal University,
Jinhua 321004, China
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Chenzhi Li, Anne Dallmeyer, Jian Ni, Manuel Chevalier, Matteo Willeit, Andrei A. Andreev, Xianyong Cao, Laura Schild, Birgit Heim, Mareike Wieczorek, and Ulrike Herzschuh
Clim. Past, 21, 1001–1024, https://doi.org/10.5194/cp-21-1001-2025, https://doi.org/10.5194/cp-21-1001-2025, 2025
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We present global megabiome dynamics and distributions derived from pollen-based reconstructions over the last 21 000 years, which are suitable for the evaluation of Earth-system-model-based paleo-megabiome simulations. We identified strong deviations between pollen- and model-derived megabiome distributions in the circum-Arctic and Tibetan Plateau areas during the Last Glacial Maximum and early deglaciation and in northern Africa and the Mediterranean region during the Holocene.
Mengna Liao, Kai Li, Yili Jin, Lina Liu, Xianyong Cao, and Jian Ni
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-71, https://doi.org/10.5194/essd-2025-71, 2025
Revised manuscript under review for ESSD
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We present a modern pollen dataset of 555 pollen count records from 307 sites on the Tibetan Plateau (28–40° N and 75–103° E). Our open-access dataset holds various potential applications in paleoecological and paleoclimatic researches. It offers a scientific foundation for reconstructing changes in climate and vegetation over time and enables the assessment of the reliability of pollen assemblages in representing the dynamics of vegetation cover, functional traits, and plant diversity.
Furong Li, Marie-José Gaillard, Xianyong Cao, Ulrike Herzschuh, Shinya Sugita, Jian Ni, Yan Zhao, Chengbang An, Xiaozhong Huang, Yu Li, Hongyan Liu, Aizhi Sun, and Yifeng Yao
Earth Syst. Sci. Data, 15, 95–112, https://doi.org/10.5194/essd-15-95-2023, https://doi.org/10.5194/essd-15-95-2023, 2023
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The objective of this study is present the first gridded and temporally continuous quantitative plant-cover reconstruction for temperate and northern subtropical China over the last 12 millennia. The reconstructions are based on 94 pollen records and include estimates for 27 plant taxa, 10 plant functional types, and 3 land-cover types. The dataset is suitable for palaeoclimate modelling and the evaluation of simulated past vegetation cover and anthropogenic land-cover change from models.
Ulrike Herzschuh, Chenzhi Li, Thomas Böhmer, Alexander K. Postl, Birgit Heim, Andrei A. Andreev, Xianyong Cao, Mareike Wieczorek, and Jian Ni
Earth Syst. Sci. Data, 14, 3213–3227, https://doi.org/10.5194/essd-14-3213-2022, https://doi.org/10.5194/essd-14-3213-2022, 2022
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Pollen preserved in environmental archives such as lake sediments and bogs are extensively used for reconstructions of past vegetation and climate. Here we present LegacyPollen 1.0, a dataset of 2831 fossil pollen records from all over the globe that were collected from publicly available databases. We harmonized the names of the pollen taxa so that all datasets can be jointly investigated. LegacyPollen 1.0 is available as an open-access dataset.
Mengna Liao, Kai Li, Weiwei Sun, and Jian Ni
Clim. Past, 17, 2291–2303, https://doi.org/10.5194/cp-17-2291-2021, https://doi.org/10.5194/cp-17-2291-2021, 2021
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The long-term trajectories of precipitation, hydrological balance and soil moisture are not completely consistent in southwest China. Hydrological balance was more sensitive to temperature change on a millennial scale. For soil moisture, plant processes also played a big role in addition to precipitation and temperature. Under future climate warming, surface water shortage in southwest China can be even more serious and efforts at reforestation may bring some relief to the soil moisture deficit.
Xianyong Cao, Fang Tian, Kai Li, Jian Ni, Xiaoshan Yu, Lina Liu, and Nannan Wang
Earth Syst. Sci. Data, 13, 3525–3537, https://doi.org/10.5194/essd-13-3525-2021, https://doi.org/10.5194/essd-13-3525-2021, 2021
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The Tibetan Plateau is quite remote, and it is difficult to collect samples on it; the previous modern pollen data are located on a nearby road, and there is a large geographic gap in the eastern and central Tibetan Plateau. Our novel pollen data can fill the gap and will be valuable in establishing a complete dataset covering the entire Tibetan Plateau, thus helping us to get a comprehensive understanding. In addition, the dataset can also be used to investigate plant species distribution.
Xianyong Cao, Fang Tian, Andrei Andreev, Patricia M. Anderson, Anatoly V. Lozhkin, Elena Bezrukova, Jian Ni, Natalia Rudaya, Astrid Stobbe, Mareike Wieczorek, and Ulrike Herzschuh
Earth Syst. Sci. Data, 12, 119–135, https://doi.org/10.5194/essd-12-119-2020, https://doi.org/10.5194/essd-12-119-2020, 2020
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Pollen percentages in spectra cannot be utilized to indicate past plant abundance directly because of the different pollen productivities among plants. In this paper, we applied relative pollen productivity estimates (PPEs) to calibrate plant abundances during the last 40 kyr using pollen counts from 203 pollen spectra in northern Asia. Results indicate the vegetation are generally stable during the Holocene and that climate change is the primary factor.
Anne Dallmeyer, Martin Claussen, Jian Ni, Xianyong Cao, Yongbo Wang, Nils Fischer, Madlene Pfeiffer, Liya Jin, Vyacheslav Khon, Sebastian Wagner, Kerstin Haberkorn, and Ulrike Herzschuh
Clim. Past, 13, 107–134, https://doi.org/10.5194/cp-13-107-2017, https://doi.org/10.5194/cp-13-107-2017, 2017
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The vegetation distribution in eastern Asia is supposed to be very sensitive to climate change. Since proxy records are scarce, hitherto a mechanistic understanding of the past spatio-temporal climate–vegetation relationship is lacking. To assess the Holocene vegetation change, we forced the diagnostic biome model BIOME4 with climate anomalies of different transient climate simulations.
T.-T. Meng, H. Wang, S. P. Harrison, I. C. Prentice, J. Ni, and G. Wang
Biogeosciences, 12, 5339–5352, https://doi.org/10.5194/bg-12-5339-2015, https://doi.org/10.5194/bg-12-5339-2015, 2015
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By analysing the quantitative leaf-traits along extensive temperature and moisture gradients with generalized linear models, we found that metabolism-related traits are universally acclimated to environmental conditions, rather than being fixed within plant functional types. The results strongly support a move towards Dynamic Global Vegetation Models in which continuous, adaptive trait variation provides the fundamental mechanism for changes in ecosystem properties along environmental gradients.
J. Ni, D. H. Luo, J. Xia, Z. H. Zhang, and G. Hu
Solid Earth, 6, 799–810, https://doi.org/10.5194/se-6-799-2015, https://doi.org/10.5194/se-6-799-2015, 2015
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The root biomass study of karst (limestone and dolomite) vegetation in southwestern China and even in the word’s karst regions is rarely investigated. The mixed evergreen and deciduous broadleaved forest in karst terrain of SW China has higher root biomass, but very high ratio of root to aboveground biomass compared to non-karst subtropical evergreen broadleaved forests. Such findings have significant ecological meanings for vegetation restoration and carbon increment.
H. Wang, I. C. Prentice, and J. Ni
Biogeosciences, 10, 5817–5830, https://doi.org/10.5194/bg-10-5817-2013, https://doi.org/10.5194/bg-10-5817-2013, 2013
Related subject area
Domain: ESSD – Land | Subject: Biogeosciences and biodiversity
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Crop-specific management history of phosphorus fertilizer input (CMH-P) in the croplands of the United States: reconciliation of top-down and bottom-up data sources
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Rong Shang, Xudong Lin, Jing M. Chen, Yunjian Liang, Keyan Fang, Mingzhu Xu, Yulin Yan, Weimin Ju, Guirui Yu, Nianpeng He, Li Xu, Liangyun Liu, Jing Li, Wang Li, Jun Zhai, and Zhongmin Hu
Earth Syst. Sci. Data, 17, 3219–3241, https://doi.org/10.5194/essd-17-3219-2025, https://doi.org/10.5194/essd-17-3219-2025, 2025
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Forest age is critical for carbon cycle modeling and effective forest management. Existing datasets, however, have low spatial resolutions or limited temporal coverage. This study introduces China's annual forest age dataset (CAFA), spanning 1986–2022 at a 30 m resolution. By tracking forest disturbances, we annually update ages. Validation shows small errors for disturbed forests and larger errors for undisturbed forests. CAFA can enhance carbon cycle modeling and forest management in China.
Yanghui Kang, Maoya Bassiouni, Max Gaber, Xinchen Lu, and Trevor F. Keenan
Earth Syst. Sci. Data, 17, 3009–3046, https://doi.org/10.5194/essd-17-3009-2025, https://doi.org/10.5194/essd-17-3009-2025, 2025
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CEDAR-GPP provides spatiotemporally upscaled estimates of gross primary productivity (GPP) globally, uniquely incorporating the direct effect of elevated atmospheric CO2 on photosynthesis. This dataset was produced by upscaling eddy covariance data with machine learning and a broad range of satellite and climate variables. Available at monthly and 0.05° resolution from 1982 to 2020, CEDAR-GPP offers critical insights into ecosystem–climate interactions and the global carbon cycle.
Anna C. Talucci, Michael M. Loranty, Jean E. Holloway, Brendan M. Rogers, Heather D. Alexander, Natalie Baillargeon, Jennifer L. Baltzer, Logan T. Berner, Amy Breen, Leya Brodt, Brian Buma, Jacqueline Dean, Clement J. F. Delcourt, Lucas R. Diaz, Catherine M. Dieleman, Thomas A. Douglas, Gerald V. Frost, Benjamin V. Gaglioti, Rebecca E. Hewitt, Teresa Hollingsworth, M. Torre Jorgenson, Mark J. Lara, Rachel A. Loehman, Michelle C. Mack, Kristen L. Manies, Christina Minions, Susan M. Natali, Jonathan A. O'Donnell, David Olefeldt, Alison K. Paulson, Adrian V. Rocha, Lisa B. Saperstein, Tatiana A. Shestakova, Seeta Sistla, Oleg Sizov, Andrey Soromotin, Merritt R. Turetsky, Sander Veraverbeke, and Michelle A. Walvoord
Earth Syst. Sci. Data, 17, 2887–2909, https://doi.org/10.5194/essd-17-2887-2025, https://doi.org/10.5194/essd-17-2887-2025, 2025
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Wildfires have the potential to accelerate permafrost thaw and the associated feedbacks to climate change. We assembled a dataset of permafrost thaw depth measurements from burned and unburned sites contributed by researchers from across the northern high-latitude region. We estimated maximum thaw depth for each measurement, which addresses a key challenge: the ability to assess impacts of wildfire on maximum thaw depth when measurement timing varies.
Tianjing Ren and Andong Cai
Earth Syst. Sci. Data, 17, 2873–2885, https://doi.org/10.5194/essd-17-2873-2025, https://doi.org/10.5194/essd-17-2873-2025, 2025
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This study compiles a global database of soil dissolved organic carbon (DOC) concentrations, a key factor in soil health and climate change. Using machine learning, it identifies the most influential factors affecting soil DOC levels and maps global DOC patterns. The findings help guide soil management and climate strategies, with the dataset available for further research.
Emma Rehn, Haidee Cadd, Scott Mooney, Tim J. Cohen, Henry Munack, Alexandru T. Codilean, Matthew Adeleye, Kristen K. Beck, Mark Constantine IV, Chris Gouramanis, Johanna M. Hanson, Penelope J. Jones, A. Peter Kershaw, Lydia Mackenzie, Maame Maisie, Michela Mariani, Kia Matley, David McWethy, Keely Mills, Patrick Moss, Nicholas R. Patton, Cassandra Rowe, Janelle Stevenson, John Tibby, and Janet Wilmshurst
Earth Syst. Sci. Data, 17, 2681–2692, https://doi.org/10.5194/essd-17-2681-2025, https://doi.org/10.5194/essd-17-2681-2025, 2025
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This paper presents SahulCHAR, a new collection of palaeofire (ancient fire) records from Australia, New Guinea, and New Zealand. SahulCHAR version 1 contains 687 records of sedimentary charcoal or black carbon, including digitized data, records from existing databases, and original author-submitted data. SahulCHAR is a much-needed update to past charcoal compilations that will also provide greater representation of records from this region in future global syntheses to understand past fire.
Judith Vogt, Martijn M. T. A. Pallandt, Luana S. Basso, Abdullah Bolek, Kseniia Ivanova, Mark Schlutow, Gerardo Celis, McKenzie Kuhn, Marguerite Mauritz, Edward A. G. Schuur, Kyle Arndt, Anna-Maria Virkkala, Isabel Wargowsky, and Mathias Göckede
Earth Syst. Sci. Data, 17, 2553–2573, https://doi.org/10.5194/essd-17-2553-2025, https://doi.org/10.5194/essd-17-2553-2025, 2025
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We present a meta-dataset of greenhouse gas observations in the Arctic and boreal regions, including information on sites where greenhouse gases have been measured using different measurement techniques. We provide a novel repository of metadata to facilitate synthesis efforts for regions undergoing rapid environmental change. The meta-dataset shows where measurements are missing and will be updated as new measurements are published.
Qing Ying, Benjamin Poulter, Jennifer D. Watts, Kyle A. Arndt, Anna-Maria Virkkala, Lori Bruhwiler, Youmi Oh, Brendan M. Rogers, Susan M. Natali, Hilary Sullivan, Amanda Armstrong, Eric J. Ward, Luke D. Schiferl, Clayton D. Elder, Olli Peltola, Annett Bartsch, Ankur R. Desai, Eugénie Euskirchen, Mathias Göckede, Bernhard Lehner, Mats B. Nilsson, Matthias Peichl, Oliver Sonnentag, Eeva-Stiina Tuittila, Torsten Sachs, Aram Kalhori, Masahito Ueyama, and Zhen Zhang
Earth Syst. Sci. Data, 17, 2507–2534, https://doi.org/10.5194/essd-17-2507-2025, https://doi.org/10.5194/essd-17-2507-2025, 2025
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We present daily methane (CH4) fluxes of northern wetlands at 10 km resolution during 2016–2022 (WetCH4) derived from a novel machine learning framework. We estimated an average annual CH4 emission of 22.8 ± 2.4 Tg CH4 yr−1 (15.7–51.6 Tg CH4 yr−1). Emissions were intensified in 2016, 2020, and 2022, with the largest interannual variation coming from Western Siberia. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH4 upscaling.
Alba Viana-Soto and Cornelius Senf
Earth Syst. Sci. Data, 17, 2373–2404, https://doi.org/10.5194/essd-17-2373-2025, https://doi.org/10.5194/essd-17-2373-2025, 2025
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Europe's forests are undergoing complex changes in response to increasing disturbances driven by climate and land use changes. Here, we present the European Forest Disturbance Atlas, a satellite-based approach for mapping annual forest disturbances across continental Europe from 1985 onwards. Maps provide insights into the year of disturbance occurrence, the actual frequency of disturbances, severity and the underlying causal agent, thus contributing to a future monitoring system envisioned for Europe.
Katharina Jentzsch, Lona van Delden, Matthias Fuchs, and Claire C. Treat
Earth Syst. Sci. Data, 17, 2331–2372, https://doi.org/10.5194/essd-17-2331-2025, https://doi.org/10.5194/essd-17-2331-2025, 2025
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Methane is a greenhouse gas that contributes to global warming, but we do not fully understand how much is released from natural sources like wetlands. To measure methane over large areas, many measurements are needed, often from small chambers that are placed on the ground. However, different researchers use different measurement setups, making it hard to combine data. We surveyed 36 researchers about their methods, summarized the responses, and identified ways to make the data more comparable.
Laura Schild, Peter Ewald, Chenzhi Li, Raphaël Hébert, Thomas Laepple, and Ulrike Herzschuh
Earth Syst. Sci. Data, 17, 2007–2033, https://doi.org/10.5194/essd-17-2007-2025, https://doi.org/10.5194/essd-17-2007-2025, 2025
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This study reconstructed vegetation and tree cover in the Northern Hemisphere from a harmonized dataset of pollen counts from sediment and peat cores for the past 14 000 years. A model was applied to correct for differences in pollen production between different plants, and modern remote-sensing forest cover was used to validate the reconstructed tree cover. Accurate data on past vegetation are invaluable for the investigation of vegetation–climate dynamics and the validation of vegetation models.
Simeon Lisovski, Alexandra Runge, Iuliia Shevtsova, Nele Landgraf, Anne Morgenstern, Ronald Reagan Okoth, Matthias Fuchs, Nikolay Lashchinskiy, Carl Stadie, Alison Beamish, Ulrike Herzschuh, Guido Grosse, and Birgit Heim
Earth Syst. Sci. Data, 17, 1707–1730, https://doi.org/10.5194/essd-17-1707-2025, https://doi.org/10.5194/essd-17-1707-2025, 2025
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The Lena Delta is the largest river delta in the Arctic and represents a biodiversity hotspot. Here, we describe multiple field datasets and a detailed habitat classification map for the Lena Delta. We present context and methods of these openly available datasets and show how they can improve our understanding of the rapidly changing Arctic tundra system.
Sijia Li and Hongliang Fang
Earth Syst. Sci. Data, 17, 1347–1366, https://doi.org/10.5194/essd-17-1347-2025, https://doi.org/10.5194/essd-17-1347-2025, 2025
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Leaf inclination angle (LIA) is a vital trait in radiative transfer, rainfall interception, evapotranspiration, photosynthesis, and hydrological processes. However, global LIA knowledge is still lacking. This study generated the first global 500 m LIA products by gap-filling LIA measurement data. The global LIA is 41.47° ± 9.55° and increases with latitude. LIA products could enhance our understanding of global LIA and assist remote sensing retrieval and land surface modeling studies.
Xufeng Wang, Tao Che, Jingfeng Xiao, Tonghong Wang, Junlei Tan, Yang Zhang, Zhiguo Ren, Liying Geng, Haibo Wang, Ziwei Xu, Shaomin Liu, and Xin Li
Earth Syst. Sci. Data, 17, 1329–1346, https://doi.org/10.5194/essd-17-1329-2025, https://doi.org/10.5194/essd-17-1329-2025, 2025
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In this study, carbon flux and auxiliary meteorological data are post-processed to create an analysis-ready dataset for 34 sites across six ecosystems in the Heihe River basin. Overall, 18 sites have multi-year observations, while 16 were observed only during the 2012 growing season, totaling 1513 site months. This dataset can be used to explore carbon exchange, assess ecosystem responses to climate change, support upscaling studies, and evaluate carbon cycle models.
Hirofumi Hashimoto, Weile Wang, Taejin Park, Sepideh Khajehei, Kazuhito Ichii, Andrew Michaelis, Alberto Guzman, Ramakrishna Nemani, Margaret Torn, Koong Yi, and Ian Brosnan
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-33, https://doi.org/10.5194/essd-2025-33, 2025
Revised manuscript accepted for ESSD
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We create the GeoNEX Coincident Ground Observations dataset (GeCGO) by extracting point data at observational network sites across Americas from the gridded GeoNEX products. The GeoNEX dataset is the high temporal frequent dataset of the latest geostationary satellites observations. We also release the software, GeoNEXTools, that helps handling the GeCGO data. GeCGO data and GeoNEXTools could help scientists use geostationary satellite data at their interested ground observational sites.
Masooma Batool, Fanny J. Sarrazin, and Rohini Kumar
Earth Syst. Sci. Data, 17, 881–916, https://doi.org/10.5194/essd-17-881-2025, https://doi.org/10.5194/essd-17-881-2025, 2025
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Our paper presents a reconstruction and analysis of the gridded P surplus in European landscapes from 1850 to 2019 at a 5 arcmin resolution. By utilizing 48 different estimates, we account for uncertainties in major components of the P surplus. Our findings highlight substantial historical changes, with the total P surplus in the EU 27 tripling over 170 years. Our dataset enables flexible aggregation at various spatial scales, providing critical insights for land and water management strategies.
Thomas Dirnböck, Michael Bahn, Eugenio Diaz-Pines, Ika Djukic, Michael Englisch, Karl Gartner, Günther Gollobich, Johannes Ingrisch, Barbara Kitzler, Karl Knaebel, Johannes Kobler, Andreas Maier, Armin Malli, Ivo Offenthaler, Johannes Peterseil, Gisela Pröll, Sarah Venier, Christoph Wohner, Sophie Zechmeister-Boltenstern, Anita Zolles, and Stephan Glatzel
Earth Syst. Sci. Data, 17, 685–702, https://doi.org/10.5194/essd-17-685-2025, https://doi.org/10.5194/essd-17-685-2025, 2025
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Long-term observation sites have been established in six Austrian locations, covering major ecosystem types such as forests, grasslands, and wetlands. The purpose of these observations is to measure baselines for assessing the impacts of extreme climate events on the carbon cycle. The collected datasets include meteorological variables, soil temperature and moisture, carbon dioxide fluxes, and tree stem growth in forests at a resolution of 15–60 min between 2019 and 2021.
Xueqin Yang, Qingling Sun, Liusheng Han, Wenping Yuan, Jie Tian, Liyang Liu, Wei Zheng, Mei Wang, Yunpeng Wang, and Xiuzhi Chen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-64, https://doi.org/10.5194/essd-2025-64, 2025
Revised manuscript accepted for ESSD
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Understanding how leaves absorb carbon from the atmosphere is essential for predicting changes in global forests. Young leaves play a key role in this process, but their efficiency has been difficult to measure at large scales. Using satellite data, we developed a new method to track the seasonal patterns of young leaves’ photosynthetic capacity from 2001 to 2018. Our dataset helps scientists better understand forest growth and how ecosystems respond to climate change.
Masahito Ueyama, Yuta Takao, Hiromi Yazawa, Makiko Tanaka, Hironori Yabuki, Tomo’omi Kumagai, Hiroki Iwata, Md. Abdul Awal, Mingyuan Du, Yoshinobu Harazono, Yoshiaki Hata, Takashi Hirano, Tsutom Hiura, Reiko Ide, Sachinobu Ishida, Mamoru Ishikawa, Kenzo Kitamura, Yuji Kominami, Shujiro Komiya, Ayumi Kotani, Yuta Inoue, Takashi Machimura, Kazuho Matsumoto, Yojiro Matsuura, Yasuko Mizoguchi, Shohei Murayama, Hirohiko Nagano, Taro Nakai, Tatsuro Nakaji, Ko Nakaya, Shinjiro Ohkubo, Takeshi Ohta, Keisuke Ono, Taku M. Saitoh, Ayaka Sakabe, Takanori Shimizu, Seiji Shimoda, Michiaki Sugita, Kentaro Takagi, Yoshiyuki Takahashi, Naoya Takamura, Satoru Takanashi, Takahiro Takimoto, Yukio Yasuda, Qinxue Wang, Jun Asanuma, Hideo Hasegawa, Tetsuya Hiyama, Yoshihiro Iijima, Shigeyuki Ishidoya, Masayuki Itoh, Tomomichi Kato, Hiroaki Kondo, Yoshiko Kosugi, Tomonori Kume, Takahisa Maeda, Trofim Maximov, Ryo Moriwaki, Hiroyuki Muraoka, Roman Petrov, Jun Suzuki, Shingo Taniguchi, and Kazuhito Ichii
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-615, https://doi.org/10.5194/essd-2024-615, 2025
Revised manuscript accepted for ESSD
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The JapanFlux2024 dataset, created through collaboration across Japan and East Asia, includes eddy covariance data from 79 sites spanning 652 site-years (1990–2023). This comprehensive dataset offers valuable insights into energy, water, and CO2 fluxes, supporting research on land-atmosphere interactions and process models. Compatible with FLUXNET, it fosters global collaboration and advances research in environmental science and regional climate dynamics.
Gudeta Weldesemayat Sileshi, Edmundo Barrios, Johannes Lehmann, and Francesco Nicola Tubiello
Earth Syst. Sci. Data, 17, 369–391, https://doi.org/10.5194/essd-17-369-2025, https://doi.org/10.5194/essd-17-369-2025, 2025
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Agricultural, fishery, forestry and agro-processing activities produce large quantities of residues, by-products and waste materials every year. Here, we present a global organic matter database (OMD), the first of its kind, consolidating estimates of residues and by-products potentially available for use in a circular bio-economy. It also provides definitions, typologies and methods to aid consistent classification, estimation and reporting of the various residues and by-products.
Kelly S. Aho, Kaelin M. Cawley, Robert T. Hensley, Robert O. Hall Jr., Walter K. Dodds, and Keli J. Goodman
Earth Syst. Sci. Data, 16, 5563–5578, https://doi.org/10.5194/essd-16-5563-2024, https://doi.org/10.5194/essd-16-5563-2024, 2024
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Gas exchange is fundamental to many biogeochemical processes in streams and depends on the degree of gas saturation and the gas transfer velocity (k). Currently, k is harder to measure than concentration. Here, we present a processing pipeline to estimate k from tracer-gas experiments conducted in 22 streams by the National Ecological Observatory Network. The processed dataset (n = 339) represents the largest compilation of standardized k estimates available.
Yifang Shi and W. Daniel Kissling
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-488, https://doi.org/10.5194/essd-2024-488, 2024
Revised manuscript accepted for ESSD
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We present a new set of multi-temporal LiDAR metrics of ecosystem structure derived from four national ALS surveys of the Netherlands (AHN1–AHN4), capturing vegetation height, cover, and structural variability over the past two decades (1998–2022). Around 70 TB point clouds have been processed to read-to-use raster layers at 10 m resolution (~ 59 GB), enabling a wide use and uptake of ecosystem structure information in biodiversity and habitat monitoring, ecosystem and carbon dynamic modelling.
Miina Rautiainen, Aarne Hovi, Daniel Schraik, Jan Hanuš, Petr Lukeš, Zuzana Lhotáková, and Lucie Homolová
Earth Syst. Sci. Data, 16, 5069–5087, https://doi.org/10.5194/essd-16-5069-2024, https://doi.org/10.5194/essd-16-5069-2024, 2024
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Radiative transfer models play a key role in monitoring vegetation using remote sensing data such as satellite or airborne images. The development of these models has been hindered by a lack of comprehensive ground reference data on structural and spectral characteristics of forests. Here, we reported datasets on the structural and spectral properties of temperate, hemiboreal, and boreal European forest stands. We anticipate that these data will have wide use in remote sensing applications.
Ruxandra-Maria Zotta, Leander Moesinger, Robin van der Schalie, Mariette Vreugdenhil, Wolfgang Preimesberger, Thomas Frederikse, Richard de Jeu, and Wouter Dorigo
Earth Syst. Sci. Data, 16, 4573–4617, https://doi.org/10.5194/essd-16-4573-2024, https://doi.org/10.5194/essd-16-4573-2024, 2024
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VODCA v2 is a dataset providing vegetation indicators for long-term ecosystem monitoring. VODCA v2 comprises two products: VODCA CXKu, spanning 34 years of observations (1987–2021), suitable for monitoring upper canopy dynamics, and VODCA L (2010–2021), for above-ground biomass monitoring. VODCA v2 has lower noise levels than the previous product version and provides valuable insights into plant water dynamics and biomass changes, even in areas where optical data are limited.
Peiyu Cao, Bo Yi, Franco Bilotto, Carlos Gonzalez Fischer, Mario Herrero, and Chaoqun Lu
Earth Syst. Sci. Data, 16, 4557–4572, https://doi.org/10.5194/essd-16-4557-2024, https://doi.org/10.5194/essd-16-4557-2024, 2024
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This article presents a spatially explicit time series dataset reconstructing crop-specific phosphorus fertilizer application rates, timing, and methods at a 4 km × 4 km resolution in the United States from 1850 to 2022. We comprehensively characterized the spatio-temporal dynamics of P fertilizer management over the last 170 years by considering cross-crop variations. This dataset will greatly contribute to the field of agricultural sustainability assessment and Earth system modeling.
Chad A. Burton, Sami W. Rifai, Luigi J. Renzullo, and Albert I. J. M. Van Dijk
Earth Syst. Sci. Data, 16, 4389–4416, https://doi.org/10.5194/essd-16-4389-2024, https://doi.org/10.5194/essd-16-4389-2024, 2024
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Understanding vegetation response to environmental change requires accurate, long-term data on vegetation condition (VC). We evaluated existing satellite VC datasets over Australia and found them lacking, so we developed a new VC dataset for Australia, AusENDVI. It can be used for studying Australia's changing vegetation dynamics and downstream impacts on the carbon and water cycles, and it provides a reliable foundation for further research into the drivers of vegetation change.
Xiaoran Zhu, Dong Chen, Maruko Kogure, Elizabeth Hoy, Logan T. Berner, Amy L. Breen, Abhishek Chatterjee, Scott J. Davidson, Gerald V. Frost, Teresa N. Hollingsworth, Go Iwahana, Randi R. Jandt, Anja N. Kade, Tatiana V. Loboda, Matt J. Macander, Michelle Mack, Charles E. Miller, Eric A. Miller, Susan M. Natali, Martha K. Raynolds, Adrian V. Rocha, Shiro Tsuyuzaki, Craig E. Tweedie, Donald A. Walker, Mathew Williams, Xin Xu, Yingtong Zhang, Nancy French, and Scott Goetz
Earth Syst. Sci. Data, 16, 3687–3703, https://doi.org/10.5194/essd-16-3687-2024, https://doi.org/10.5194/essd-16-3687-2024, 2024
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The Arctic tundra is experiencing widespread physical and biological changes, largely in response to warming, yet scientific understanding of tundra ecology and change remains limited due to relatively limited accessibility and studies compared to other terrestrial biomes. To support synthesis research and inform future studies, we created the Synthesized Alaskan Tundra Field Dataset (SATFiD), which brings together field datasets and includes vegetation, active-layer, and fire properties.
Yishuo Cui, Shouzhi Chen, Yufeng Gong, Mingwei Li, Zitong Jia, Yuyu Zhou, and Yongshuo H. Fu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-225, https://doi.org/10.5194/essd-2024-225, 2024
Revised manuscript accepted for ESSD
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Global changes have significantly altered vegetation phenology, affecting terrestrial carbon cycle. While various remote-sensing-based phenology datasets exist, they often suffer from inconsistencies and uncertainties. To address this, we developed a new phenology dataset spanning 1982 to 2022 using a reliability ensemble averaging method. Validated against ground data, our dataset demonstrates substantially improved accuracy, providing a novel and reliable source for global ecological studies.
Chu Zou, Shanshan Du, Xinjie Liu, and Liangyun Liu
Earth Syst. Sci. Data, 16, 2789–2809, https://doi.org/10.5194/essd-16-2789-2024, https://doi.org/10.5194/essd-16-2789-2024, 2024
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To obtain a temporally consistent satellite solar-induced chlorophyll fluorescence
(SIF) product (TCSIF), we corrected for time degradation of GOME-2A using a pseudo-invariant method. After the correction, the global SIF grew by 0.70 % per year from 2007 to 2021, and 62.91 % of vegetated regions underwent an increase in SIF. The dataset is a promising tool for monitoring global vegetation variation and will advance our understanding of vegetation's photosynthetic activities at a global scale.
(SIF) product (TCSIF), we corrected for time degradation of GOME-2A using a pseudo-invariant method. After the correction, the global SIF grew by 0.70 % per year from 2007 to 2021, and 62.91 % of vegetated regions underwent an increase in SIF. The dataset is a promising tool for monitoring global vegetation variation and will advance our understanding of vegetation's photosynthetic activities at a global scale.
Daju Wang, Peiyang Ren, Xiaosheng Xia, Lei Fan, Zhangcai Qin, Xiuzhi Chen, and Wenping Yuan
Earth Syst. Sci. Data, 16, 2465–2481, https://doi.org/10.5194/essd-16-2465-2024, https://doi.org/10.5194/essd-16-2465-2024, 2024
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This study generated a high-precision dataset, locating forest harvested carbon and quantifying post-harvest wood emissions for various uses. It enhances our understanding of forest harvesting and post-harvest carbon dynamics in China, providing essential data for estimating the forest ecosystem carbon budget and emphasizing wood utilization's impact on carbon emissions.
Nannan An, Nan Lu, Weiliang Chen, Yongzhe Chen, Hao Shi, Fuzhong Wu, and Bojie Fu
Earth Syst. Sci. Data, 16, 1771–1810, https://doi.org/10.5194/essd-16-1771-2024, https://doi.org/10.5194/essd-16-1771-2024, 2024
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This study generated a spatially continuous plant functional trait dataset (~1 km) in China in combination with field observations, environmental variables and vegetation indices using machine learning methods. Results showed that wood density, leaf P concentration and specific leaf area showed good accuracy with an average R2 of higher than 0.45. This dataset could provide data support for development of Earth system models to predict vegetation distribution and ecosystem functions.
Kai Yan, Jingrui Wang, Rui Peng, Kai Yang, Xiuzhi Chen, Gaofei Yin, Jinwei Dong, Marie Weiss, Jiabin Pu, and Ranga B. Myneni
Earth Syst. Sci. Data, 16, 1601–1622, https://doi.org/10.5194/essd-16-1601-2024, https://doi.org/10.5194/essd-16-1601-2024, 2024
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Variations in observational conditions have led to poor spatiotemporal consistency in leaf area index (LAI) time series. Using prior knowledge, we leveraged high-quality observations and spatiotemporal correlation to reprocess MODIS LAI, thereby generating HiQ-LAI, a product that exhibits fewer abnormal fluctuations in time series. Reprocessing was done on Google Earth Engine, providing users with convenient access to this value-added data and facilitating large-scale research and applications.
Fabio Oriani, Gregoire Mariethoz, and Manuel Chevalier
Earth Syst. Sci. Data, 16, 731–742, https://doi.org/10.5194/essd-16-731-2024, https://doi.org/10.5194/essd-16-731-2024, 2024
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Modern and fossil pollen data contain precious information for reconstructing the climate and environment of the past. However, these data are only achieved for single locations with no continuity in space. We present here a systematic atlas of 194 digital maps containing the spatial estimation of contemporary pollen presence over Europe. This dataset constitutes a free and ready-to-use tool to study climate, biodiversity, and environment in time and space.
João Paulo Darela-Filho, Anja Rammig, Katrin Fleischer, Tatiana Reichert, Laynara Figueiredo Lugli, Carlos Alberto Quesada, Luis Carlos Colocho Hurtarte, Mateus Dantas de Paula, and David M. Lapola
Earth Syst. Sci. Data, 16, 715–729, https://doi.org/10.5194/essd-16-715-2024, https://doi.org/10.5194/essd-16-715-2024, 2024
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Phosphorus (P) is crucial for plant growth, and scientists have created models to study how it interacts with carbon cycle in ecosystems. To apply these models, it is important to know the distribution of phosphorus in soil. In this study we estimated the distribution of phosphorus in the Amazon region. The results showed a clear gradient of soil development and P content. These maps can help improve ecosystem models and generate new hypotheses about phosphorus availability in the Amazon.
Mengyao Zhu, Junhu Dai, Huanjiong Wang, Juha M. Alatalo, Wei Liu, Yulong Hao, and Quansheng Ge
Earth Syst. Sci. Data, 16, 277–293, https://doi.org/10.5194/essd-16-277-2024, https://doi.org/10.5194/essd-16-277-2024, 2024
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This study utilized 24,552 in situ phenology observation records from the Chinese Phenology Observation Network to model and map 24 woody plant species phenology and ground forest phenology over China from 1951 to 2020. These phenology maps are the first gridded, independent and reliable phenology data sources for China, offering a high spatial resolution of 0.1° and an average deviation of about 10 days. It contributes to more comprehensive research on plant phenology and climate change.
Jiabin Pu, Kai Yan, Samapriya Roy, Zaichun Zhu, Miina Rautiainen, Yuri Knyazikhin, and Ranga B. Myneni
Earth Syst. Sci. Data, 16, 15–34, https://doi.org/10.5194/essd-16-15-2024, https://doi.org/10.5194/essd-16-15-2024, 2024
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Long-term global LAI/FPAR products provide the fundamental dataset for accessing vegetation dynamics and studying climate change. This study develops a sensor-independent LAI/FPAR climate data record based on the integration of Terra-MODIS/Aqua-MODIS/VIIRS LAI/FPAR standard products and applies advanced gap-filling techniques. The SI LAI/FPAR CDR provides a valuable resource for researchers studying vegetation dynamics and their relationship to climate change in the 21st century.
Wojciech Tylmann, Alicja Bonk, Dariusz Borowiak, Paulina Głowacka, Kamil Nowiński, Joanna Piłczyńska, Agnieszka Szczerba, and Maurycy Żarczyński
Earth Syst. Sci. Data, 15, 5093–5103, https://doi.org/10.5194/essd-15-5093-2023, https://doi.org/10.5194/essd-15-5093-2023, 2023
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We present a dataset from the decade-long monitoring of Lake Żabińskie, a hardwater and eutrophic lake in northeast Poland. The lake contains varved sediments, which form a unique archive of past environmental variability. The monitoring program was designed to capture a pattern of relationships between meteorological conditions, limnological processes, and modern sedimentation and to verify if meteorological and limnological phenomena can be precisely tracked with varves.
Sen Cao, Muyi Li, Zaichun Zhu, Zhe Wang, Junjun Zha, Weiqing Zhao, Zeyu Duanmu, Jiana Chen, Yaoyao Zheng, Yue Chen, Ranga B. Myneni, and Shilong Piao
Earth Syst. Sci. Data, 15, 4877–4899, https://doi.org/10.5194/essd-15-4877-2023, https://doi.org/10.5194/essd-15-4877-2023, 2023
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The long-term global leaf area index (LAI) products are critical for characterizing vegetation dynamics under environmental changes. This study presents an updated GIMMS LAI product (GIMMS LAI4g; 1982−2020) based on PKU GIMMS NDVI and massive Landsat LAI samples. With higher accuracy than other LAI products, GIMMS LAI4g removes the effects of orbital drift and sensor degradation in AVHRR data. It has better temporal consistency before and after 2000 and a more reasonable global vegetation trend.
Muyi Li, Sen Cao, Zaichun Zhu, Zhe Wang, Ranga B. Myneni, and Shilong Piao
Earth Syst. Sci. Data, 15, 4181–4203, https://doi.org/10.5194/essd-15-4181-2023, https://doi.org/10.5194/essd-15-4181-2023, 2023
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Long-term global Normalized Difference Vegetation Index (NDVI) products support the understanding of changes in vegetation under environmental changes. This study generates a consistent global NDVI product (PKU GIMMS NDVI) from 1982–2022 that eliminates the issue of orbital drift and sensor degradation in Advanced Very High Resolution Radiometer (AVHRR) data. More accurate than its predecessor (GIMMS NDVI3g), it shows high temporal consistency with MODIS NDVI in describing vegetation trends.
Parisa Sarzaeim, Francisco Muñoz-Arriola, Diego Jarquin, Hasnat Aslam, and Natalia De Leon Gatti
Earth Syst. Sci. Data, 15, 3963–3990, https://doi.org/10.5194/essd-15-3963-2023, https://doi.org/10.5194/essd-15-3963-2023, 2023
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A genomic, phenomic, and climate database for maize phenotype predictability in the US and Canada is introduced. The database encompasses climate from multiple sources and OMICS from the Genomes to Fields initiative (G2F) data from 2014 to 2021, including codes for input data quality and consistency controls. Earth system modelers and breeders can use CLIM4OMICS since it interconnects the climate and biological system sciences. CLIM4OMICS is designed to foster phenotype predictability.
Elisabeth Mauclet, Maëlle Villani, Arthur Monhonval, Catherine Hirst, Edward A. G. Schuur, and Sophie Opfergelt
Earth Syst. Sci. Data, 15, 3891–3904, https://doi.org/10.5194/essd-15-3891-2023, https://doi.org/10.5194/essd-15-3891-2023, 2023
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Permafrost ecosystems are limited in nutrients for vegetation development and constrain the biological activity to the active layer. Upon Arctic warming, permafrost degradation exposes organic and mineral soil material that may directly influence the capacity of the soil to retain key nutrients for vegetation growth and development. Here, we demonstrate that the average total exchangeable nutrient density (Ca, K, Mg, and Na) is more than 2 times higher in the permafrost than in the active layer.
Anna G. Boegehold, Ashley M. Burtner, Andrew C. Camilleri, Glenn Carter, Paul DenUyl, David Fanslow, Deanna Fyffe Semenyuk, Casey M. Godwin, Duane Gossiaux, Thomas H. Johengen, Holly Kelchner, Christine Kitchens, Lacey A. Mason, Kelly McCabe, Danna Palladino, Dack Stuart, Henry Vanderploeg, and Reagan Errera
Earth Syst. Sci. Data, 15, 3853–3868, https://doi.org/10.5194/essd-15-3853-2023, https://doi.org/10.5194/essd-15-3853-2023, 2023
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Western Lake Erie suffers from cyanobacterial harmful algal blooms (HABs) despite decades of international management efforts. In response, the US National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) and the Cooperative Institute for Great Lakes Research (CIGLR) created an annual sampling program to detect, monitor, assess, and predict HABs. Here we describe the data collected from this monitoring program from 2012 to 2021.
Akli Benali, Nuno Guiomar, Hugo Gonçalves, Bernardo Mota, Fábio Silva, Paulo M. Fernandes, Carlos Mota, Alexandre Penha, João Santos, José M. C. Pereira, and Ana C. L. Sá
Earth Syst. Sci. Data, 15, 3791–3818, https://doi.org/10.5194/essd-15-3791-2023, https://doi.org/10.5194/essd-15-3791-2023, 2023
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We reconstructed the spread of 80 large wildfires that burned recently in Portugal and calculated metrics that describe how wildfires behave, such as rate of spread, growth rate, and energy released. We describe the fire behaviour distribution using six percentile intervals that can be easily communicated to both research and management communities. The database will help improve our current knowledge on wildfire behaviour and support better decision making.
Yuelong Xiao, Qunming Wang, Xiaohua Tong, and Peter M. Atkinson
Earth Syst. Sci. Data, 15, 3365–3386, https://doi.org/10.5194/essd-15-3365-2023, https://doi.org/10.5194/essd-15-3365-2023, 2023
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Forest age is closely related to forest production, carbon cycles, and other ecosystem services. Existing stand age products in China derived from remote-sensing images are of a coarse spatial resolution and are not suitable for applications at the regional scale. Here, we mapped young forest ages across China at an unprecedented fine spatial resolution of 30 m. The overall accuracy (OA) of the generated map of young forest stand ages across China was 90.28 %.
Emily H. Stanley, Luke C. Loken, Nora J. Casson, Samantha K. Oliver, Ryan A. Sponseller, Marcus B. Wallin, Liwei Zhang, and Gerard Rocher-Ros
Earth Syst. Sci. Data, 15, 2879–2926, https://doi.org/10.5194/essd-15-2879-2023, https://doi.org/10.5194/essd-15-2879-2023, 2023
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The Global River Methane Database (GRiMeDB) presents CH4 concentrations and fluxes for flowing waters and concurrent measures of CO2, N2O, and several physicochemical variables, plus information about sample locations and methods used to measure gas fluxes. GRiMeDB is intended to increase opportunities to understand variation in fluvial CH4, test hypotheses related to greenhouse gas dynamics, and reduce uncertainty in future estimates of gas emissions from world streams and rivers.
Xueqin Yang, Xiuzhi Chen, Jiashun Ren, Wenping Yuan, Liyang Liu, Juxiu Liu, Dexiang Chen, Yihua Xiao, Qinghai Song, Yanjun Du, Shengbiao Wu, Lei Fan, Xiaoai Dai, Yunpeng Wang, and Yongxian Su
Earth Syst. Sci. Data, 15, 2601–2622, https://doi.org/10.5194/essd-15-2601-2023, https://doi.org/10.5194/essd-15-2601-2023, 2023
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We developed the first time-mapped, continental-scale gridded dataset of monthly leaf area index (LAI) in three leaf age cohorts (i.e., young, mature, and old) from 2001–2018 data (referred to as Lad-LAI). The seasonality of three LAI cohorts from the new Lad-LAI product agrees well at eight sites with very fine-scale collections of monthly LAI. The proposed satellite-based approaches can provide references for mapping finer spatiotemporal-resolution LAI products with different leaf age cohorts.
Yann Quilcaille, Fulden Batibeniz, Andreia F. S. Ribeiro, Ryan S. Padrón, and Sonia I. Seneviratne
Earth Syst. Sci. Data, 15, 2153–2177, https://doi.org/10.5194/essd-15-2153-2023, https://doi.org/10.5194/essd-15-2153-2023, 2023
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We present a new database of four annual fire weather indicators over 1850–2100 and over all land areas. In a 3°C warmer world with respect to preindustrial times, the mean fire weather would increase on average by at least 66% in both intensity and duration and even triple for 1-in-10-year events. The dataset is a freely available resource for fire danger studies and beyond, highlighting that the best course of action would require limiting global warming as much as possible.
Beatriz P. Cazorla, Javier Cabello, Andrés Reyes, Emilio Guirado, Julio Peñas, Antonio J. Pérez-Luque, and Domingo Alcaraz-Segura
Earth Syst. Sci. Data, 15, 1871–1887, https://doi.org/10.5194/essd-15-1871-2023, https://doi.org/10.5194/essd-15-1871-2023, 2023
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This dataset provides scientists, environmental managers, and the public in general with valuable information on the first characterization of ecosystem functional diversity based on primary production developed in the Sierra Nevada (Spain), a biodiversity hotspot in the Mediterranean basin and an exceptional natural laboratory for ecological research within the Long-Term Social-Ecological Research (LTSER) network.
Shengli Tao, Zurui Ao, Jean-Pierre Wigneron, Sassan Saatchi, Philippe Ciais, Jérôme Chave, Thuy Le Toan, Pierre-Louis Frison, Xiaomei Hu, Chi Chen, Lei Fan, Mengjia Wang, Jiangling Zhu, Xia Zhao, Xiaojun Li, Xiangzhuo Liu, Yanjun Su, Tianyu Hu, Qinghua Guo, Zhiheng Wang, Zhiyao Tang, Yi Y. Liu, and Jingyun Fang
Earth Syst. Sci. Data, 15, 1577–1596, https://doi.org/10.5194/essd-15-1577-2023, https://doi.org/10.5194/essd-15-1577-2023, 2023
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We provide the first long-term (since 1992), high-resolution (8.9 km) satellite radar backscatter data set (LHScat) with a C-band (5.3 GHz) signal dynamic for global lands. LHScat was created by fusing signals from ERS (1992–2001; C-band), QSCAT (1999–2009; Ku-band), and ASCAT (since 2007; C-band). LHScat has been validated against independent ERS-2 signals. It could be used in a variety of studies, such as vegetation monitoring and hydrological modelling.
Jose V. Moris, Pedro Álvarez-Álvarez, Marco Conedera, Annalie Dorph, Thomas D. Hessilt, Hugh G. P. Hunt, Renata Libonati, Lucas S. Menezes, Mortimer M. Müller, Francisco J. Pérez-Invernón, Gianni B. Pezzatti, Nicolau Pineda, Rebecca C. Scholten, Sander Veraverbeke, B. Mike Wotton, and Davide Ascoli
Earth Syst. Sci. Data, 15, 1151–1163, https://doi.org/10.5194/essd-15-1151-2023, https://doi.org/10.5194/essd-15-1151-2023, 2023
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This work describes a database on holdover times of lightning-ignited wildfires (LIWs). Holdover time is defined as the time between lightning-induced fire ignition and fire detection. The database contains 42 datasets built with data on more than 152 375 LIWs from 13 countries in five continents from 1921 to 2020. This database is the first freely-available, harmonized and ready-to-use global source of holdover time data, which may be used to investigate LIWs and model the holdover phenomenon.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Cited articles
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classification for the orders and families of flowering plants: APG IV, Bot.
J. Linn. Soc., 181, 1–20, https://doi.org/10.1111/boj.12385, 2016.
Berzaghi, F., Wright, I. J., Kramer, K., Oddou-Muratorio, S., Bohn, F. J.,
Reyer, C. P. O., Sabate, S., Sanders, T. G. M., and Hartig, F.: Towards a
New Generation of Trait-Flexible Vegetation Models, Trends Ecol. Evol., 35,
191–205, https://doi.org/10.1016/j.tree.2019.11.006, 2020.
Butler, E. E., Datta, A., Flores-Moreno, H., Chen, M., Wythers, K. R.,
Fazayeli, F., Banerjee, A., Atkin, O. K., Kattge, J., Amiaud, B., Blonder,
B., Boenisch, G., Bond-Lamberty, B., Brown, K. A., Byun, C., Campetella, G.,
Cerabolini, B. E. L., Cornelissen, J. H. C., Craine, J. M., Craven, D., de
Vries, F. T., Diaz, S., Domingues, T. F., Forey, E., Gonzalez-Melo, A.,
Gross, N., Han, W. X., Hattingh, W. N., Hickler, T., Jansen, S., Kramer, K.,
Kraft, N. J. B., Kurokawa, H., Laughlin, D. C., Meir, P., Minden, V.,
Niinemets, U., Onoda, Y., Penuelas, J., Read, Q., Sack, L., Schamp, B.,
Soudzilovskaia, N. A., Spasojevic, M. J., Sosinski, E., Thornton, P. E.,
Valladares, F., van Bodegom, P. M., Williams, M., Wirth, C., and Reich, P.
B.: Mapping local and global variability in plant trait distributions, P. Natl. Acad. Sci. USA,
114, E10937–E10946, https://doi.org/10.1073/pnas.1708984114, 2018.
Chang, D. H. S.: The Tibetan Plateau in relation to the vegetation of China,
Ann. Mo. Bot. Gard., 70, 564–570, https://doi.org/10.2307/2992087, 1983.
Chave, J., Coomes, D., Jansen, S., Lewis, S. L., Swenson, N. G., and Zanne,
A. E.: Towards a worldwide wood economics spectrum, Ecol. Lett., 12,
351–366, https://doi.org/10.1111/j.1461-0248.2009.01285.x, 2009.
Chen, D. L., Xu, B. Q., Yao, T. D., Guo, Z. T., Cui, P., Chen, F. H., Zhang,
R. H., Zhang, X. Z., Zhang, Y. L., Fan, J., Hou, Z. Q., and Zhang, T. H.:
Assessment of past, present and future environmental changes on the Tibetan
Plateau, Chin. Sci. Bull., 60, 3025–3035,
https://doi.org/10.1360/N972014-01370, 2015.
Cheng, Q., Wu, X. Q., Wei, L. F., Hu, X. F., and Ni, J.: 30-year average
monthly/1-km climate variables dataset of China (1951–1980, 1981–2010),
Digital J. Global Change Data Repository [data set],
https://doi.org/10.3974/geodb.2022.06.03.V1, 2022.
Commissione Redactorum Flora Xinjiangensis: Flora Xinjiangensis, 6 volumes, Xinjiang
Science & Technology & Hygiene Publishing House, Ürümqi, 1992–1996.
Cornelissen, J. H. C., Lavorel, S., Garnier, E., Díaz, S., Buchmann,
N., Gurvich, D. E., Reich, P. B., ter Steege, H., Morgan, H. D., van der
Heijden, M. G. A., Pausas, J. G., and Poorter, H.: A handbook of protocols
for standardised and easy measurement of plant functional traits worldwide,
Aust. J. Bot., 51, 335–380, https://doi.org/10.1071/BT02124, 2003.
Díaz, S. and Cabido, M.: Vive la différence: plant functional
diversity matters to ecosystem processes, Trends Ecol. Evol., 16, 646–655,
https://doi.org/10.1016/S0169-5347(01)02283-2, 2001.
Díaz, S., Lavorel, S., McIntyre, S., Falczuk, V., Casanoves, F.,
Milchunas, D. G., Skarpe, C., Rusch, G., Sternberg, M., Noy-Meir, I.,
Landsberg, J., Zhang, W., Clark, H., and Campbell, B. D.: Plant trait
responses to grazing – a global synthesis, Glob. Change Biol., 13,
313–341, https://doi.org/10.1111/j.1365-2486.2006.01288.x, 2007.
Díaz, S., Kattge, J., Cornelissen, J. H. C., Wright, I. J., Lavorel,
S., Dray, S., Reu, B., Kleyer, M., Wirth, C., Prentice, I. C., Garnier, E.,
Bonisch, G., Westoby, M., Poorter, H., Reich, P. B., Moles, A. T., Dickie,
J., Gillison, A. N., Zanne, A. E., Chave, J., Wright, S. J., Sheremet'ev, S.
N., Jactel, H., Baraloto, C., Cerabolini, B., Pierce, S., Shipley, B.,
Kirkup, D., Casanoves, F., Joswig, J. S., Gunther, A., Falczuk, V., Ruger,
N., Mahecha, M. D., and Gorne, L. D.: The global spectrum of plant form and
function, Nature, 529, 167–171, https://doi.org/10.1038/nature16489, 2016.
Ding, W. N., Ree, R. H., Spicer, R. A., and Xing, Y. W.: Ancient orogenic
and monsoon-driven assembly of the world's richest temperate alpine flora,
Science, 369, 578–581, https://doi.org/10.1126/science.abb4484, 2020.
Editorial Committee of the Flora of China: Flora Reipublicae Popularis Sinicae, 80
volumes, Science Press, Beijing, 1959–2004.
Editorial Committee of the Flora of Gansu: Flora of Gansu, Volume 2, Gansu Science and
Technology Press, Lanzhou, ISBN 9787542410075, 2005.
Editorial Committee of the Flora Qinghaiica: Flora Qinghaiica, 4 volumes, Qinghai
People’s Publishing House, Xining, 1996–1999.
Editorial Committee
of Vegetation Map of China, the Chinese Academy of Sciences (ECVMC): Vegetation of
China and its Geographical Pattern – Illustration of the Vegetation Map of the People's
Republic of China (1:1 000 000), Geology Press, Beijing, ISBN 9787116051461, 2007a.
Editorial Committee
of Vegetation Map of China, the Chinese Academy of Sciences (ECVMC): Vegetation Map of the People's Republic of China (1:1 000 000), Geology Press, Beijing,
ISBN 9787116045132, 2007b.
Fang, J. B., Pang, R. L., Guo, L. L., Xie, H. Z., Li, J., Luo, J., Yu, H.,
Liu, Y., and Wu, F. K.: Determination of nitrogen,
phosphorus and potassium in plants, China Agriculture Press, Beijing, NY/T 2017–2011,
2011.
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S.,
Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S.,
Shimada, J., Umland, J., Werner M., Oskin, M., Burbank, D., and Alsdorf, D.:
The shuttle radar topography mission, Rev. Geophys., 45, RG2004,
https://doi.org/10.1029/2005RG000183, 2007.
Gallego-Sala, A. V., Clark, J. M., House, J. I., Orr, H. G., Prentice, I.
C., Smith, P., Farewell, T., and Chapman, S. J.: Bioclimatic envelope model
of climate change impacts on blanket peatland distribution in Great Britain,
Clim. Res., 45, 151–162, https://doi.org/10.3354/cr00911, 2010.
Geng, Y., Wang, L., Jin, D. M., Liu, H. Y., and He, J. S.: Alpine climate
alters the relationships between leaf and root morphological traits but not
chemical traits, Oecologia, 175, 445–455,
https://doi.org/10.1007/s00442-014-2919-5, 2014.
Guerrero-Ramírez, N. R., Mommer, L., Freschet, G. T., Iversen, C. M.,
McCormack, M. L., Kattge, J., Poorter, H., van der Plas, F., Bergmann, J.,
Kuyper, T. W., York, L. M., Bruelheide, H., Laughlin, D. C., Meier, I. C.,
Roumet, C., Semchenko, M., Sweeney, C. J., van Ruijven, J.,
Valverde-Barrantes, O. J., Aubin, I., Catford, J. A., Manning, P., Martin,
A., Milla, R., Minden, V., Pausas, J. G., Smith, S. W., Soudzilovskaia, N.
A., Ammer, C., Butterfield, B., Craine, J., Cornelissen, J. H. C., de Vries,
F. T., Isaac, M. E., Kramer, K., Konig, C., Lamb, E. G., Onipchenko, V. G.,
Penuelas, J., Reich, P. B., Rillig, M. C., Sack, L., Shipley, B., Tedersoo,
L., Valladares, F., van Bodegom, P., Weigelt, P., Wright, J. P., and
Weigelt, A.: Global root traits (GRooT) database, Global Ecol. Biogeogr.,
30, 25–37, https://doi.org/10.1111/geb.13179, 2021.
He, J. S., Wang, Z. H., Wang, X. P., Schmid, B., Zuo, W. Y., Zhou, M.,
Zheng, C. Y., Wang, M. F., and Fang, J. Y.: A test of the generality of leaf
trait relationships on the Tibetan Plateau, New Phytol., 170, 835–848,
https://doi.org/10.1111/j.1469-8137.2006.01704.x, 2006.
He, J. S., Wang, X. P., Schmid, B., Flynn, D. F. B., Li, X. F., Reich, P.
B., and Fang, J. Y.: Taxonomic identity, phylogeny, climate and soil
fertility as driver of leaf traits across Chinese grassland biomes, J. Plant.
Res., 123, 551–561, https://doi.org/10.1007/s10265-009-0294-9, 2010.
He, N. P., Liu, C. C., Piao, S. L., Sack, L., Xu, L., Luo, Y. Q., He, J. S.,
Han, X. G., Zhou, G. S., Zhou, X. H., Lin, Y., Yu, Q., Liu, S. R., Sun, W.,
Niu, S. L., Li, S. G., Zhang, J. H., and Yu, G. R.: Ecosystem traits linking
functional traits to macroecology, Trends Ecol. Evol., 34, 200–210,
https://doi.org/10.1016/j.tree.2018.11.004, 2019.
He, N. P., Liu, Y., Liu, C. C., Xu, L., Li, M. X., Zhang, J. H., He, J. S.,
Tang, Z. Y., Han, X. G., Ye, Q., Xiao, C. W., Yu, Q., Liu, S. R., Sun, W.,
Niu, S. L., Li, S. G., Sack, L., and Yu, G. R.: Plant trait networks:
improved resolution of the dimensionality of adaptation, Trends Ecol. Evol.,
35, 908–918, https://doi.org/10.1016/j.tree.2020.06.003, 2020.
Hutchinson, M. F. and Xu, T. B.: ANUSPLIN Version 4.4 User Guide, Fenner School of Environment and Society, the Australian
National University, Canberra, 2013.
Integrated Scientific Expedition to Qinghai-Tibet Plateau, Chinese Academy of Sciences:
Flora Xizangica, 5 volumes, Science Press, Beijing, 1983–1987.
Iversen, C. M., McCormack, M. L., Powell, A. S., Blackwood, C. B., Freschet,
G. T., Kattge, J., Roumet, C., Stover, D. B., Soudzilovskaia, N. A.,
Valverde-Barrantes, O. J., van Bodegom, P. M., and Violle, C.: A global
Fine-Root Ecology Database to address below-ground challenges in plant
ecology, New Phytol., 215, 15–26, https://doi.org/10.1111/nph.14486, 2017.
Jin, Y., Wang, H., Xia, J., Ni, J., Li, K., Hou, Y., Hu, J., Wei, L., Xia,
H., and Zhou, B.: A dataset of leaf traits on the Tibetan Plateau
(2018–2021), National Tibetan Plateau Data Center [data set],
https://doi.org/10.11888/Terre.tpdc.272516, 2022a.
Jin, Y. L., Wang, H. Y., Wei, L. F., Hu, J., Wu, K., Xia, H. J., Xia, J.,
Zhou, B. R., Li, K., and Ni, J.: A plot dataset of plant community of
Qingzang Plateau, Chin. J. Plant Ecol., 46, 846–854, https://doi.org/10.17521/cjpe.2022.0174, 2022b.
Liu, Y. X.: Flora in Desertis Reipublicae Populorum Sinarum, 3 volumes, Science Press,
Beijing, 1985–1992.
Lu, L. M., Mao, L. F., Yang, T., Ye, J. F., Liu, B., Li, H. L., Sun, M.,
Miller, J. T., Mathews, S., Hu, H. H., Niu, Y. T., Peng, D. X., Chen, Y. H.,
Smith, S. A., Chen, M., Xiang, K. L., Le, C. T., Dang, V. C., Lu, A. M.,
Soltis, P. S., Soltis, D. E., Li, J. H., and Chen, Z. D.: Evolutionary
history of the angiosperm flora of China, Nature, 554, 234–238,
https://doi.org/10.1038/nature25485, 2018.
Luo, T. X., Luo, J., and Pan, Y. D.: Leaf traits and associated ecosystem
characteristics across subtropical and timberline forests in the Gongga
Mountains, Eastern Tibetan Plateau, Oecologia, 142, 261–273,
https://doi.org/10.1007/s00442-004-1729-6, 2005.
Ma, Z. Q., Guo, D. L., Xu, X. L., Lu, M. Z., Bardgett, R. D., Eissenstat, D.
M., McCormack, M. L., and Hedin, L. O.: Evolutionary history resolves global
organization of root functional traits, Nature, 555, 94–97,
https://doi.org/10.1038/nature26163, 2018.
Maes, S. L., Perring, M. P., Depauw, L., Bernhardt-Romermann, M., Blondeel,
H., Brumelis, G., Brunet, J., Decocq, G., den Ouden, J., Govaert, S.,
Hardtle, W., Hedl, R., Heinken, T., Heinrichs, S., Hertzog, L., Jaroszewicz,
B., Kirby, K., Kopecky, M., Landuyt, D., Malis, F., Vanneste, T., Wulf, M.,
and Verheyen, K.: Plant functional trait response to environmental drivers
across European temperate forest understorey communities, Plant Biol., 22,
410–424, https://doi.org/10.1111/plb.13082, 2020.
Mariano, E., Gomes, T. F., Lins, S. R. M., Abdalla- Filho, A. L.,
Soltangheisi, A., Araújo, M. G. S., Almeida, R. F., Augusto, F. G.,
Canisares, L. P., Chaves, S. S. F., Costa, C. F. G., Diniz-Reis, T. R.,
Galera, L. A., Martinez, M. G., Morais, M. C., Perez, E. B., Reis, L. C.,
Simon, C. D., Mardegan, S. F., Domingues, T. F., Miatto, R. C., Oliveira, R.
S., Reis, C. R. G., Nardoto, G. B., Kattge, J., and Martinelli, L. A.:
LT-Brazil: A database of leaf traits across biomes and vegetation types in
Brazil, Global Ecol. Biogeogr., 30, 2136–2146,
https://doi.org/10.1111/geb.13381, 2021.
Meng, T. T., Ni, J., and Harrison, S. P.: Plant morphometric traits and
climate gradients in northern China: a meta-analysis using quadrat and flora
data, Ann. Bot., 104, 1217–1229, https://doi.org/10.1093/aob/mcp230, 2009.
Meng, T.-T., Wang, H., Harrison, S. P., Prentice, I. C., Ni, J., and Wang, G.: Responses of leaf traits to climatic gradients: adaptive variation versus compositional shifts, Biogeosciences, 12, 5339–5352, https://doi.org/10.5194/bg-12-5339-2015, 2015.
Moles, A. T., Ackerly, D. D., Tweddle, J. C., Dickie, J. B., Smith, R.,
Leishman, M. R., Mayfield, M. M., Pitman, A., Wood, J. T., and Westoby, M.:
Global patterns in seed size, Global Ecol. Biogeogr., 16, 109–116,
https://doi.org/10.1111/j.1466-8238.2006.00259.x, 2007.
Moles, A. T., Warton, D. I., Warman, L., Swenson, N. G., Laffan, S. W.,
Zanne, A. E., Pitman, A., Hemmings, F. A., and Leishman, M. R.: Global
patterns in plant height, J. Ecol., 97, 923–932,
https://doi.org/10.1111/j.1365-2745.2009.01526.x, 2009.
Myers-Smith, I. H. Thomas, H. J. D., and Bjorkman, A. D.: Plant traits
inform predictions of tundra responses to global change, New Phytol., 221,
1742–1748, https://doi.org/10.1111/nph.15592, 2019.
Pérez-Harguindeguy, N., Díaz, S., Garnier, E., Lavorel, S.,
Poorter, H., Jaureguiberry, P., Bret-Harte, M. S., Cornwell, W. K., Craine,
J. M., Gurvich, D. E., Urcelay, C., Veneklaas, E. J., Reich, P. B., Poorter,
L., Wright, I. J., Ray, P., Enrico, L., Pausas, J. G., de Vos, A. C.,
Buchmann, N., Funes, G., Quétier, F., Hodgson, J. G., Thompson, K.,
Morgan, H. D., ter Steege, H., van der Heijden, M. G. A., Sack, L., Blonder,
B., Poschlod, P., Vaieretti, M. V., Conti, G., Staver, A. C., Aquino, S.,
and Cornelissen, J. H. C.: New handbook for standardised measurement of
plant functional traits worldwide, Aust. J. Bot., 61, 167–234,
https://doi.org/10.1071/BT12225, 2013.
Piao, S. L., Zhang, X. Z., Wang, T., Liang, E. Y., Wang, S. P., Zhu, J. T.,
and Niu, B.: Responses and feedback of the Tibetan Plateau's alpine
ecosystem to climate change, Chin. Sci. Bull., 64, 2842–2855,
https://doi.org/10.1360/TB-2019-0074, 2019.
Reich, P. B. and Oleksyn, J.: Global patterns of plant leaf N and P in
relation to temperature and latitude, P. Natl. Acad. Sci. USA, 101, 11001–11006,
https://doi.org/10.1073/pnas.0403588101, 2004.
Reichstein, M., Bahn, M., Mahecha, M. D., Kattge, J., and Baldocchi, D. D.:
Linking plant and ecosystem functional biogeography, P. Natl. Acad. Sci. USA, 111, 13697–13702,
https://doi.org/10.1073/pnas.1216065111, 2014.
Roddy, A. B., Martínez-Perez, C., Teixido, A. L., Cornelissen, T. G.,
Olson, M. E., Oliveira, R. S., and Silveira, F. A. O.: Towards the flower
economics spectrum, New Phytol., 229, 665–672,
https://doi.org/10.1111/nph.16823, 2021.
Shi, W. Q., Wang, G. A., and Han, W. X.: Altitudinal variation in leaf
nitrogen concentration on the eastern slope of Mount Gongga on the Tibetan
Plateau, China, Plos One, 7, e44628,
https://doi.org/10.1371/journal.pone.0044628, 2012.
Sloan, S., Jenkins, C. N., Joppa, L. N., Gaveau, D. L. A., and Laurance, W.
F.: Remaining natural vegetation in the global biodiversity hotspots, Biol.
Conserv., 177, 12–24, https://doi.org/10.1016/j.biocon.2014.05.027, 2014.
Taseski, G. M., Beloe, C. J., Gallagher, R. V., Chan, J. Y., Dalrymple, R.
L., and Cornwell, W. K.: A global-growth form database for 143,616 vascular
plant species, Ecology, 100, e02614, https://doi.org/10.1002/ecy.2614, 2019.
Tavşanoğlu, Ç., and Pausas, J. G.: A functional trait database
for Mediterranean Basin plants, Sci. Data, 5, 180135,
https://doi.org/10.1038/sdata.2018.135, 2018.
van Bodegom, P. M., Douma, J. C., and Verheijen, L. M.: A fully traits-based
approach to modeling global vegetation distribution, P. Natl. Acad. Sci. USA, 111, 13733–13738,
https://doi.org/10.1073/pnas.1304551110, 2014.
Vandvik, V., Halbritter, A. H., Yang, Y., He, H., Zhang, L., Brummer, A. B.,
Klanderud, K., Maitner, B. S., Michaletz, S. T., Sun, X. Y., Telford, R. J.,
Wang, G. X., Althuizen, I. H. J., Henn, J. J., Garcia, W. F. E., Gya, R.,
Jaroszynska, F., Joyce, B. L., Lehman, R., Moerland, M. S., Nesheim-Hauge,
E., Nordås, L. H., Peng, A., Ponsac, C., Seltzer, L., Steyn, C.,
Sullivan, M. K., Tjendra, J., Xiao, Y., Zhao, X. X., and Enquist, B. J.:
Plant traits and vegetation data from climate warming experiments along an
1100 m elevation gradient in Gongga Mountains, China, Sci. Data, 7, 189,
https://doi.org/10.1038/s41597-020-0529-0, 2020.
Violle, C., Navas, M. L., Vile, D., Kazakou, E., Fortunel, C., Hummel, I.,
and Garnier, E.: Let the concept of trait be functional!, Oikos, 116,
882–892, https://doi.org/10.1111/j.0030-1299.2007.15559.x, 2007.
Wang, C. S., Lyu, W. W., Jiang, L. L., Wang, S. P., Wang, Q., Meng, F. D.,
and Zhang, L. R.: Changes in leaf vein traits among vein types of alpine
grassland plants on the Tibetan Plateau, J. Mt. Sci., 17, 2161–2169,
https://doi.org/10.1007/s11629-020-6069-4, 2020.
Wang, H., Prentice, I. C., Keenan, T. F., Davis, T. W., Wright, I. J.,
Cornwell, W. K., Evans, B. J., and Peng, C. H.: Towards a universal model
for carbon dioxide uptake by plants, Nat. Plants, 3, 734–741,
https://doi.org/10.1038/s41477-017-0006-8, 2017.
Wang, H., Harrison, S. P., Prentice, I. C., Yang, Y. Z., Bai, F., Togashi,
H. F., Wang, M., Zhou, S. X., and Ni, J.: The China Plant Trait Database:
toward a comprehensive regional compilation of functional traits for land
plants, Ecology, 99, p. 500, https://doi.org/10.1002/ecy.2091, 2018.
Wang, H., Wang, R. X., Harrison, S. P., and Prentice, I. C.: Leaf
morphological traits as adaptations to multiple climate gradients, J. Ecol.,
110, 1344–1355, https://doi.org/10.1111/1365-2745.13873, 2022.
Wang, Q. and Hong, D. Y.: Understanding the plant diversity on the roof of
the world, The Innovation, 3, 100215,
https://doi.org/10.1016/j.xinn.2022.100215, 2022.
Wei, L. F., Hu, X. F., Cheng, Q., Wu, X. Q., and Ni, J.: A dataset of
spatial distribution of bioclimatic variables inChina at 1 km resolution,
China Sci. Data [data set], https://doi.org/10.11922/11-6035.csd.2022.0003.zh, 2022.
Weigelt, P., König, C., and Kreft, H.: GIFT – A Global Inventory of
Floras and Traits for macroecology and biogeography, J. Biogeogr., 47,
16–43, https://doi.org/10.1111/jbi.13623, 2019.
Wright, I. J., Reich, P. B., Westoby, M., Ackerly, D. D., Baruch, Z.,
Bongers, F., Cavender-Bares, J., Chapin, T., Cornelissen, J. H. C., Diemer,
M., Flexas, J., Garnier, E., Groom, P. K., Gulias, J., Hikosaka, K., Lamont,
B. B., Lee, T., Lee, W., Lusk, C., Midgley, J. J., Navas, M. L., Niinemets,
Ü., Oleksyn, J., Osada, N., Poorter, H., Poot, P., Prior, L., Pyankov,
V. I., Roumet, C., Thomas, S. C., Tjoelker, M. G., Veneklaas, E. J., and
Villar, R.: The worldwide leaf economics spectrum, Nature, 428, 821–827,
https://doi.org/10.1038/nature02403, 2004.
Wu, D. X.: Protocols for Standard Biological Observation and Measurement in Terrestrial
Ecosystems, China Environmental Science Press, Beijing, ISBN 9787511141071, 2007.
Wullschleger, S. D., Epstein, H. E., Box, E. O., Euskirchen, E. S., Goswami,
S., Iversen, C. M., Kattge, J., Norby, R. J., van Bodegom, P. M., and Xu, X.
F.: Plant functional types in Earth system models: past experiences and
future directions for application of dynamic vegetation models in
high-latitude ecosystems, Ann. Bot., 114, 1–16,
https://doi.org/10.1093/aob/mcu077, 2014.
Xu, H. Y., Wang, H., Prentice, I. C., Harrison, S. P., Wang, G. X., and Sun,
X. Y.: Predictability of leaf traits with climate and elevation: a case
study in Gongga Mountain, China, Tree Physiol., 41, 13360–1352,
https://doi.org/10.1093/treephys/tpab003, 2021.
Xu, T. B. and Hutchinson, M. F.: New developments and applications in the
ANUCLIM spatial climatic and bioclimatic modelling package, Environ. Modell.
Softw., 40, 267–279, https://doi.org/10.1016/j.envsoft.2012.10.003, 2013.
Yan, Y. J., Yang, X., and Tang, Z. Y.: Patterns of species diversity and
phylogenetic structure of vascular plants on the Qinghai-Tibetan Plateau,
Ecol. Evol., 3, 4584–4595, https://doi.org/10.1002/ece3.847, 2013.
Yao, T. D., Thompson, L., Yang, W., Yu, W. S., Gao, Y., Guo, X. J., Yang, X.
X., Duan, K. Q., Zhao, H. B., Xu, B. Q., Pu, J. C., Lu, A. X., Xiang, Y.,
Kattel, D. B., and Joswiak, D.: Different glacier status with atmospheric
circulations in Tibetan Plateau and surroundings, Nat. Clim. Change, 2,
663–667, https://doi.org/10.1038/nclimate1580, 2012.
Zhang, X. Z., Yang, Y. P., Piao, S. L., Bao, W. K., Wang, S. P., Wang, G.
X., Sun, H., Luo, T. X., Zhang, Y. J., Shi, P. L., Liang, E. Y., Shen, M.
G., Wang, J. S., Gao, Q. Z., Zhang, Y. L., and Ouyang, H.: Ecological change
on the Tibetan Plateau, Chin. Sci. Bull., 60, 3048–3056,
https://doi.org/10.1360/N972014-01339, 2015.
Short summary
The TiP-Leaf dataset was compiled from direct field measurements and included 11 leaf traits from 468 species of 1692 individuals, covering a great proportion of species and vegetation types on the highest plateau in the world. This work is the first plant trait dataset that represents all of the alpine vegetation on the TP, which is not only an update of the Chinese plant trait database, but also a great contribution to the global trait database.
The TiP-Leaf dataset was compiled from direct field measurements and included 11 leaf traits...
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