the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Pollen-based reconstruction of spatially-explicit vegetation cover over the Tibetan Plateau since the last deglaciation
Abstract. Spatiotemporally contiguous paleo-vegetation reconstructions are essential for studying climate-vegetation interactions, providing critical data for paleoclimate modeling, and refining past land cover in Earth System Models (ESMs) and scenarios of anthropogenic land-cover changes (ALCCs). Here, we present the first spatiotemporally contiguous paleo-vegetation cover dataset for the Tibetan Plateau, spanning from the last deglaciation (16 ka) to the preindustrial era. This dataset was achieved using two sets of random forest (RF) models: one focused on temporal reconstructions (RF-temporal) and the other on spatial reconstructions (RF-spatial). RF-temporal reconstructs temporal trends from 61 fossil pollen records across the Tibetan Plateau, while RF-spatial interpolates site-based cover, producing a dataset with a spatial resolution of 0.5° × 0.5° and a temporal resolution of 400 years. The dataset provides estimates of vegetation cover, along with standard errors, for three vegetation types (vegetation, woody plant, and herbaceous plant). To illustrate, we present the temporal trends and spatial distribution of vegetation cover for these vegetation types, comparing them with the vegetation cover used in ESMs. We further discuss the dataset’s reliability and applications, along with the discrepancies between our reconstructed results and those used in ESMs, highlighting possible reasons for these differences.
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Status: open (until 28 May 2025)
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RC1: 'Comment on essd-2024-555', Anonymous Referee #1, 10 Apr 2025
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General comments
The manuscript presented a spatiotemporally contiguous palaeovegetation cover dataset of the Tibetan Plateau since the 16ka BP, generated by the temporal and temporal random forest (RF) models using modern pollen and fossil pollen records. This is the first mapping of past vegetation on the Tibetan Plateau which should be benefit to the palae-community. I believe that the methods used in this study is feasible and the results are robust. However, given the complexity of the vegetation of the TP, this study only reconstructed two types of vegetation, woody and herb vegetation, plus the total vegetation, which were too coarse for further use. The pollen records can be transformed to multiple vegetation types on the plateau, at least for example, broadleaved forest, coniferous forest, shrubland and tundra or various alpine vegetation (alpine meadow, steppe and desert). The reviewer suggests that the authors should reconsider the classification of vegetation types as fine as possible.Specific comments
Line 106-108, we used the MODIS Land Cover Type Product (MCD12Q1), which provides an annual Plant Functional Type (PFT) classification (DiMiceli et al., 2022). Trees were classified as "woody", while shrubs and grasses were grouped as "herbaceous." Why not keep the tree, shrub and grass PFTs? These three PFTs should be the appropriate vegetation types of the Tibetan Plateau. Otherwise, trees and shrubs should be classified as "woody", while grasses were grouped as "herbaceous."Line 117-118, for the palaeovegetation models, we standardized all forest vegetation types in the models as woody and all grass and shrub vegetation types as herbaceous. This is not acceptable too.
How to select the past vegetation type from a fossil pollen record at 400-year interval?
For the RF-temporal models, why have only pollen and topographic factors been used? Why not add climate data? But for the RF-spatial models, all the data f climate and topography were applied.
Line 298, zhang 2024 to Zhang 2024.
Citation: https://doi.org/10.5194/essd-2024-555-RC1
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