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, and Ulrike Herzschuh
EGUsphere, https://doi.org/10.5194/egusphere-2024-1862, https://doi.org/10.5194/egusphere-2024-1862, 2024
This preprint is open for discussion and under review for Climate of the Past (CP).
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We present a 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 areas and Tibetan Plateau during the Last Glacial Maximum and early deglaciation, as well as in North Africa and the Mediterranean regions during the Holocene.
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
TCSIF: a temporally consistent global Global Ozone Monitoring Experiment-2A (GOME-2A) solar-induced chlorophyll fluorescence dataset with the correction of sensor degradation
National forest carbon harvesting and allocation dataset for the period 2003 to 2018
Spatial mapping of key plant functional traits in terrestrial ecosystems across China
HiQ-LAI: a high-quality reprocessed MODIS leaf area index dataset with better spatiotemporal consistency from 2000 to 2022
EUPollMap: the European atlas of contemporary pollen distribution maps derived from an integrated Kriging interpolation approach
Reference maps of soil phosphorus for the pan-Amazon region
Mapping 24 woody plant species phenology and ground forest phenology over China from 1951 to 2020
Sensor-independent LAI/FPAR CDR: reconstructing a global sensor-independent climate data record of MODIS and VIIRS LAI/FPAR from 2000 to 2022
Investigating limnological processes and modern sedimentation at Lake Żabińskie, northeast Poland: a decade-long multi-variable dataset, 2012–2021
Spatiotemporally consistent global dataset of the GIMMS leaf area index (GIMMS LAI4g) from 1982 to 2020
Spatiotemporally consistent global dataset of the GIMMS Normalized Difference Vegetation Index (PKU GIMMS NDVI) from 1982 to 2022
A synthesized field survey database of vegetation and active layer properties for the Alaskan tundra (1972–2020)
CLIM4OMICS: a geospatially comprehensive climate and multi-OMICS database for maize phenotype predictability in the United States and Canada
Quantifying exchangeable base cations in permafrost: a reserve of nutrients about to thaw
Routine monitoring of western Lake Erie to track water quality changes associated with cyanobacterial harmful algal blooms
The Portuguese Large Wildfire Spread database (PT-FireSprd)
Thirty-meter map of young forest age in China
GRiMeDB: the Global River Methane Database of concentrations and fluxes
A gridded dataset of a leaf-age-dependent leaf area index seasonality product over tropical and subtropical evergreen broadleaved forests
Fire weather index data under historical and shared socioeconomic pathway projections in the 6th phase of the Coupled Model Intercomparison Project from 1850 to 2100
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
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
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.
Xiaoran Zhu, Dong Chen, Maruko Kogure, Elizabeth Hoy, Logan Berner, Amy Breen, Abhishek Chatterjee, Scott Davidson, Gerald Frost, Teresa Hollingsworth, Go Iwahana, Randi Jandt, Anja Kade, Tatiana Loboda, Matt Macander, Michelle Mack, Charles Miller, Eric Miller, Susan Natali, Martha Raynolds, Adrian Rocha, Shiro Tsuyuzaki, Craig Tweedie, Donald Walker, Mathew Williams, Xin Xu, Yingtong Zhang, Nancy French, and Scott Goetz
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-222, https://doi.org/10.5194/essd-2023-222, 2023
Revised manuscript accepted for ESSD
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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 study compared to other terrestrial biomes. To support synthesis research and inform future studies, we created the Synthesized Alaskan Tundra Field Dataset (SATFiD), which pulls together field datasets and includes vegetation, active layer, and fire-related properties.
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.
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
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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
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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
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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
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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
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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
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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
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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.
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
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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
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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
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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
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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
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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
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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
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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
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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.
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...
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