Dataset Information

Spatial patterns of vegetation carbon sinks and sources dataset in Central Asia.

ABSTRACT: This dataset includes land use/cover change data with a spatial resolution of 300 m, net ecosystem productivity data based on the monthly grid data of the temperature and precipitation series data from the Climatic Research Unit, terrestrial net primary production data from MOD17 of the Central Asia that underlies the article entitled "Spatial patterns of vegetation carbon sinks and sources under water constraint in Central Asia". We explain the details of the dataset, the data harmonization procedures, and the spatial coverage. We also provide the validation result of NPP data from MOD17. We unified the spatiotemporal resolution of these data from different sources, based on re-sampling (nearest neighbor interpolation) and re-classification techniques, and combined the data from the different source datasets to form comprehensive records.

SUBMITTER: Li Z

PROVIDER: S-EPMC7452710 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Spatial patterns of vegetation carbon sinks and sources dataset in Central Asia.

Li Zhi Z Chen Yaning Y Zhang Qifei Q Li Yang Y

Data in brief 20200820

This dataset includes land use/cover change data with a spatial resolution of 300 m, net ecosystem productivity data based on the monthly grid data of the temperature and precipitation series data from the Climatic Research Unit, terrestrial net primary production data from MOD17 of the Central Asia that underlies the article entitled "Spatial patterns of vegetation carbon sinks and sources under water constraint in Central Asia". We explain the details of the dataset, the data harmonization pro ...[more]

PMID: 32904354

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Project description:The Tianshan Mountains, located in arid Central Asia, have a humid climate and are biodiversity hotspots. Here, we aimed to clarify whether the pattern of species diversity and the phylogenetic structure of plant communities is affected by environmental variables and glacial refugia. In this study, plant community assemblies of 17 research sites with a total of 35 sample plots were investigated at the grassland/woodland boundaries on the Tianshan Mountains. Community phylogeny of these plant communities was constructed based on two plant DNA barcode regions. The indices of phylogenetic diversity and phylogenetic community structure were calculated for these sample plots. We first estimated the correlation coefficients between species richness (SR) and environmental variables as well as the presence of glacial refugia. We then mapped the significant values of indices of community phylogeny (PD, RPD, NRI, and NTI) to investigate the correlation between community phylogeny and environmental structure or macrozones in the study area. The results showed that a significantly higher value of SR was obtained for the refugial groups than for the colonizing groups (P < 0.05); presence of refugia and environmental variables were highly correlated to the pattern of variation in SR. Indices of community phylogeny were not significantly different between refugial and colonizing regions. Comparison with the humid western part showed that plant communities in the arid eastern part of the Tianshan Mountains tended to display more significant phylogenetic overdispersion. The variation tendency of the PhyloSor index showed that the increase in macro-geographical and environmental distance did not influence obvious phylogenetic dissimilarities between different sample plots. In conclusion, glacial refugia and environmental factors profoundly influenced the pattern of SR, but community phylogenetic structure was not affected by glacial refugia among different plant communities on the Tianshan Mountains. This pattern of community phylogenetic structure could have resulted from shared ancestry and species pool among these sample plots.

Dataset Information

Spatial patterns of vegetation carbon sinks and sources dataset in Central Asia.

Publications

Spatial patterns of vegetation carbon sinks and sources dataset in Central Asia.

Similar Datasets

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