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
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
Related authors
No articles found.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
A remote-sensing-based dataset to characterize the ecosystem functioning and functional diversity in the Biosphere Reserve of the Sierra Nevada (southeastern Spain)
A global long-term, high-resolution satellite radar backscatter data record (1992–2022+): merging C-band ERS/ASCAT and Ku-band QSCAT
A global database on holdover time of lightning-ignited wildfires
National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the global stocktake
Mammals in the Chornobyl Exclusion Zone's Red Forest: a motion-activated camera trap study
Maps with 1 km resolution reveal increases in above- and belowground forest biomass carbon pools in China over the past 20 years
AnisoVeg: anisotropy and nadir-normalized MODIS multi-angle implementation atmospheric correction (MAIAC) datasets for satellite vegetation studies in South America
Forest structure and individual tree inventories of northeastern Siberia along climatic gradients
Global climate-related predictors at kilometer resolution for the past and future
A daily and 500 m coupled evapotranspiration and gross primary production product across China during 2000–2020
Global land surface 250 m 8 d fraction of absorbed photosynthetically active radiation (FAPAR) product from 2000 to 2021
Fire weather index data under historical and SSP projections in CMIP6 from 1850 to 2100
Rates and timing of chlorophyll-a increases and related environmental variables in global temperate and cold-temperate lakes
Harmonized gap-filled datasets from 20 urban flux tower sites
Holocene spatiotemporal millet agricultural patterns in northern China: a dataset of archaeobotanical macroremains
The biogeography of relative abundance of soil fungi versus bacteria in surface topsoil
Airborne SnowSAR data at X and Ku bands over boreal forest, alpine and tundra snow cover
The Landscape Fire Scars Database: mapping historical burned area and fire severity in Chile
Aridec: an open database of litter mass loss from aridlands worldwide with recommendations on suitable model applications
LegacyPollen 1.0: a taxonomically harmonized global late Quaternary pollen dataset of 2831 records with standardized chronologies
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Nicholas A. Beresford, Sergii Gashchak, Michael D. Wood, and Catherine L. Barnett
Earth Syst. Sci. Data, 15, 911–920, https://doi.org/10.5194/essd-15-911-2023, https://doi.org/10.5194/essd-15-911-2023, 2023
Short summary
Short summary
Camera traps were established in a highly contaminated area of the Chornobyl Exclusion Zone (CEZ) to capture images of mammals. Over 1 year, 14 mammal species were recorded. The number of species observed did not vary with estimated radiation exposure. The data will be of value from the perspectives of effects of radiation on wildlife and also rewilding in this large, abandoned area. They may also have value in future studies investigating impacts of recent Russian military action in the CEZ.
Yongzhe Chen, Xiaoming Feng, Bojie Fu, Haozhi Ma, Constantin M. Zohner, Thomas W. Crowther, Yuanyuan Huang, Xutong Wu, and Fangli Wei
Earth Syst. Sci. Data, 15, 897–910, https://doi.org/10.5194/essd-15-897-2023, https://doi.org/10.5194/essd-15-897-2023, 2023
Short summary
Short summary
This study presented a long-term (2002–2021) above- and belowground biomass dataset for woody vegetation in China at 1 km resolution. It was produced by combining various types of remote sensing observations with adequate plot measurements. Over 2002–2021, China’s woody biomass increased at a high rate, especially in the central and southern parts. This dataset can be applied to evaluate forest carbon sinks across China and the efficiency of ecological restoration programs in China.
Ricardo Dalagnol, Lênio Soares Galvão, Fabien Hubert Wagner, Yhasmin Mendes de Moura, Nathan Gonçalves, Yujie Wang, Alexei Lyapustin, Yan Yang, Sassan Saatchi, and Luiz Eduardo Oliveira Cruz Aragão
Earth Syst. Sci. Data, 15, 345–358, https://doi.org/10.5194/essd-15-345-2023, https://doi.org/10.5194/essd-15-345-2023, 2023
Short summary
Short summary
The AnisoVeg dataset brings 22 years of monthly satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor for South America at 1 km resolution aimed at vegetation applications. It has nadir-normalized data, which is the most traditional approach to correct satellite data but also unique anisotropy data with strong biophysical meaning, explaining 55 % of Amazon forest height. We expect this dataset to help large-scale estimates of vegetation biomass and carbon.
Timon Miesner, Ulrike Herzschuh, Luidmila A. Pestryakova, Mareike Wieczorek, Evgenii S. Zakharov, Alexei I. Kolmogorov, Paraskovya V. Davydova, and Stefan Kruse
Earth Syst. Sci. Data, 14, 5695–5716, https://doi.org/10.5194/essd-14-5695-2022, https://doi.org/10.5194/essd-14-5695-2022, 2022
Short summary
Short summary
We present data which were collected on expeditions to the northeast of the Russian Federation. One table describes the 226 locations we visited during those expeditions, and the other describes 40 289 trees which we recorded at these locations. We found out that important information on the forest cannot be predicted precisely from satellites. Thus, for anyone interested in distant forests, it is important to go to there and take measurements or use data (as presented here).
Philipp Brun, Niklaus E. Zimmermann, Chantal Hari, Loïc Pellissier, and Dirk Nikolaus Karger
Earth Syst. Sci. Data, 14, 5573–5603, https://doi.org/10.5194/essd-14-5573-2022, https://doi.org/10.5194/essd-14-5573-2022, 2022
Short summary
Short summary
Using mechanistic downscaling, we developed CHELSA-BIOCLIM+, a set of 15 biologically relevant, climate-related variables at unprecedented resolution, as a basis for environmental analyses. It includes monthly time series for 38+ years and 30-year averages for three future periods and three emission scenarios. Estimates matched well with station measurements, but few biases existed. The data allow for detailed assessments of climate-change impact on ecosystems and their services to societies.
Shaoyang He, Yongqiang Zhang, Ning Ma, Jing Tian, Dongdong Kong, and Changming Liu
Earth Syst. Sci. Data, 14, 5463–5488, https://doi.org/10.5194/essd-14-5463-2022, https://doi.org/10.5194/essd-14-5463-2022, 2022
Short summary
Short summary
This study developed a daily, 500 m evapotranspiration and gross primary production product (PML-V2(China)) using a locally calibrated water–carbon coupled model, PML-V2, which was well calibrated against observations at 26 flux sites across nine land cover types. PML-V2 (China) performs satisfactorily in the plot- and basin-scale evaluations compared with other mainstream products. It improved intra-annual ET and GPP dynamics, particularly in the cropland ecosystem.
Han Ma, Shunlin Liang, Changhao Xiong, Qian Wang, Aolin Jia, and Bing Li
Earth Syst. Sci. Data, 14, 5333–5347, https://doi.org/10.5194/essd-14-5333-2022, https://doi.org/10.5194/essd-14-5333-2022, 2022
Short summary
Short summary
The fraction of absorbed photosynthetically active radiation (FAPAR) is one of the essential climate variables. This study generated a global land surface FAPAR product with a 250 m resolution based on a deep learning model that takes advantage of the existing FAPAR products and MODIS time series of observation information. Direct validation and intercomparison revealed that our product better meets user requirements and has a greater spatiotemporal continuity than other existing products.
Yann Quilcaille, Fulden Batibeniz, Andreia F. S. Ribeiro, Ryan S. Padrón, and Sonia I. Seneviratne
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-413, https://doi.org/10.5194/essd-2022-413, 2022
Revised manuscript accepted for ESSD
Short summary
Short summary
We present a new database of four annual fire weather indicators over 1850–2100 and over all land area. Our first analysis shows that in a 3 °C warmer world with respect to preindustrial times, the mean fire weather would on average double in duration and intensity. The produced 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 low as possible.
Hannah Adams, Jane Ye, Bhaleka D. Persaud, Stephanie Slowinski, Homa Kheyrollah Pour, and Philippe Van Cappellen
Earth Syst. Sci. Data, 14, 5139–5156, https://doi.org/10.5194/essd-14-5139-2022, https://doi.org/10.5194/essd-14-5139-2022, 2022
Short summary
Short summary
Climate warming and land-use changes are altering the environmental factors that control the algal
productivityin lakes. To predict how environmental factors like nutrient concentrations, ice cover, and water temperature will continue to influence lake productivity in this changing climate, we created a dataset of chlorophyll-a concentrations (a compound found in algae), associated water quality parameters, and solar radiation that can be used to for a wide range of research questions.
Mathew Lipson, Sue Grimmond, Martin Best, Winston T. L. Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, Jonathan Evans, Krzysztof Fortuniak, Bert G. Heusinkveld, Je-Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, Joseph P. McFadden, Oliver Michels, Wlodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, and Helen Claire Ward
Earth Syst. Sci. Data, 14, 5157–5178, https://doi.org/10.5194/essd-14-5157-2022, https://doi.org/10.5194/essd-14-5157-2022, 2022
Short summary
Short summary
We describe a new openly accessible collection of atmospheric observations from 20 cities around the world, capturing 50 site years. The observations capture local meteorology (temperature, humidity, wind, etc.) and the energy fluxes between the land and atmosphere (e.g. radiation and sensible and latent heat fluxes). These observations can be used to improve our understanding of urban climate processes and to test the accuracy of urban climate models.
Keyang He, Houyuan Lu, Jianping Zhang, and Can Wang
Earth Syst. Sci. Data, 14, 4777–4791, https://doi.org/10.5194/essd-14-4777-2022, https://doi.org/10.5194/essd-14-4777-2022, 2022
Short summary
Short summary
Here we presented the first quantitative spatiotemporal cropping patterns spanning the Neolithic and Bronze ages in northern China. Temporally, millet agriculture underwent a dramatic transition from low-yield broomcorn to high-yield foxtail millet around 6000 cal. a BP under the influence of climate and population. Spatially, millet agriculture spread westward and northward from the mid-lower Yellow River (MLY) to the agro-pastoral ecotone (APE) around 6000 cal. a BP and diversified afterwards.
Kailiang Yu, Johan van den Hoogen, Zhiqiang Wang, Colin Averill, Devin Routh, Gabriel Reuben Smith, Rebecca E. Drenovsky, Kate M. Scow, Fei Mo, Mark P. Waldrop, Yuanhe Yang, Weize Tang, Franciska T. De Vries, Richard D. Bardgett, Peter Manning, Felipe Bastida, Sara G. Baer, Elizabeth M. Bach, Carlos García, Qingkui Wang, Linna Ma, Baodong Chen, Xianjing He, Sven Teurlincx, Amber Heijboer, James A. Bradley, and Thomas W. Crowther
Earth Syst. Sci. Data, 14, 4339–4350, https://doi.org/10.5194/essd-14-4339-2022, https://doi.org/10.5194/essd-14-4339-2022, 2022
Short summary
Short summary
We used a global-scale dataset for the surface topsoil (>3000 distinct observations of abundance of soil fungi versus bacteria) to generate the first quantitative map of soil fungal proportion across terrestrial ecosystems. We reveal striking latitudinal trends. Fungi dominated in regions with low mean annual temperature (MAT) and net primary productivity (NPP) and bacteria dominated in regions with high MAT and NPP.
Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehviläinen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, and Michael Kern
Earth Syst. Sci. Data, 14, 3915–3945, https://doi.org/10.5194/essd-14-3915-2022, https://doi.org/10.5194/essd-14-3915-2022, 2022
Short summary
Short summary
The manuscript describes airborne, dual-polarised X and Ku band synthetic aperture radar (SAR) data collected over several campaigns over snow-covered terrain in Finland, Austria and Canada. Colocated snow and meteorological observations are also presented. The data are meant for science users interested in investigating X/Ku band radar signatures from natural environments in winter conditions.
Alejandro Miranda, Rayén Mentler, Ítalo Moletto-Lobos, Gabriela Alfaro, Leonardo Aliaga, Dana Balbontín, Maximiliano Barraza, Susanne Baumbach, Patricio Calderón, Fernando Cárdenas, Iván Castillo, Gonzalo Contreras, Felipe de la Barra, Mauricio Galleguillos, Mauro E. González, Carlos Hormazábal, Antonio Lara, Ian Mancilla, Francisca Muñoz, Cristian Oyarce, Francisca Pantoja, Rocío Ramírez, and Vicente Urrutia
Earth Syst. Sci. Data, 14, 3599–3613, https://doi.org/10.5194/essd-14-3599-2022, https://doi.org/10.5194/essd-14-3599-2022, 2022
Short summary
Short summary
Achieving a local understanding of fire regimes requires high-resolution, systematic and dynamic data. High-quality information can help to transform evidence into decision-making. Taking advantage of big-data and remote sensing technics we developed a flexible workflow to reconstruct burned area and fire severity data for more than 8000 individual fires in Chile. The framework developed for the database can be applied anywhere in the world with minimal adaptation.
Agustín Sarquis, Ignacio Andrés Siebenhart, Amy Theresa Austin, and Carlos A. Sierra
Earth Syst. Sci. Data, 14, 3471–3488, https://doi.org/10.5194/essd-14-3471-2022, https://doi.org/10.5194/essd-14-3471-2022, 2022
Short summary
Short summary
Plant litter breakdown in aridlands is driven by processes different from those in more humid ecosystems. A better understanding of these processes will allow us to make better predictions of future carbon cycling. We have compiled aridec, a database of plant litter decomposition studies in aridlands and tested some modeling applications for potential users. Aridec is open for use and collaboration, and we hope it will help answer newer and more important questions as the database develops.
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
Short summary
Short summary
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.
Cited articles
Angiosperm Phylogeny Group: An update of the Angiosperm Phylogeny Group
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...
Special issue