花粉产量是定量重建古植被、古气候的必要条件,目前花粉产量包括相对花粉产量和绝对花粉产量。由于较难获得多年连续的花粉沉积数据,学者多倾向于使用相对花粉产量进行古植被定量重建。相对花粉产量是某一花粉类型相对于同一参考种的花...花粉产量是定量重建古植被、古气候的必要条件,目前花粉产量包括相对花粉产量和绝对花粉产量。由于较难获得多年连续的花粉沉积数据,学者多倾向于使用相对花粉产量进行古植被定量重建。相对花粉产量是某一花粉类型相对于同一参考种的花粉产量的比值(参考种通常选取植物群落和花粉组合中出现频率较高的同一花粉类型),可通过ERV(Extended R-value)模型进行估算,但其准确性受植被调查方法和模型假设条件影响较大。本文介绍了估算相对花粉产量所需的植被调查方法和利用花粉产量定量重建植被景观的模型。目前较成熟的模型为景观重建模型(Landscape Reconstruction Algorithm),包括REVEALS模型(Regional Estimates of Vegetation Abundance from Large Sites,适用于面积≥1~5km^2的沉积盆地植被重建)和LOVE模型(Local Vegetation Estimates,适用于面积为0.1~1.0km^2的沉积盆地植被重建)。欧洲及我国不同区域相对花粉产量和REVEALS模型定量重建研究结果均表明,重建后的古植被景观能较好反映当地的古植被组成。展开更多
The quantitative relationship between modern pollen and vegetation provides a critical foundation for reconstructing past vegetation,with relative pollen productivity(RPP)serving as a key calibration parameter.However...The quantitative relationship between modern pollen and vegetation provides a critical foundation for reconstructing past vegetation,with relative pollen productivity(RPP)serving as a key calibration parameter.However,in subtropical evergreen broadleaved forests(SEBFs)in China,RPP studies remain scarce,and the impact of human disturbances on RPP estimates has yet to be adequately assessed,limiting the accuracy of quantitative palaeovegetation reconstructions.This study was conducted in Dinghu Mountain Nature Reserve and its surrounding areas in Zhaoqing,Guangdong Province,and included 31 sampling sites.We performed pollen analysis alongside detailed vegetation surveys and utilized ERV submodel 2 and Prentice’s model to estimate the RPP of 9 common plant taxa in the southern SEBFs.There was a particular focus on evaluating the interference effects of bamboo plantations on the estimation of RPP.The results indicate that bamboo within the family Poaceae contributes minimally to surface soil Poaceae pollen because of its unique flowering characteristics,such as long flowering cycles and monocarpic reproduction.The incorporation of bamboo into the Poaceae vegetation coverage in the analysis led to excessively high RPP values for the other taxa.When bamboo coverage was removed from the Poaceae family,the recalculated RPP values aligned closely with those reported in previous studies.The RPP values,ranked from highest to lowest,were as follows:Castanopsis(12.33±0.03)>Araliaceae(1.60±0.03)>Mallotus(1.53±0.26)>Pinus(1.47±0.03)>Rosaceae(1.07±0.02)>Poaceae(1±0)>Euphorbiaceae(0.44±0.03)>Anacardiaceae(0.26±0.03)>Theaceae(0.15±0).Notably,the RPP values for Mallotus,Araliaceae,Theaceae,and Euphorbiaceae represent the first estimates for China’s subtropical region.Differences between certain RPP estimates and those of previous studies may be attributed to factors such as species composition,vegetation structure,and model selection.The findings of this study highlight that due to the widespread distribution of artificial bamboo forests in China’s subtropical regions,future RPP studies should carefully consider the influence of Poaceae.This consideration is essential for improving the accuracy of the application of fossil pollen for quantitative paleo-vegetation reconstruction in these regions.展开更多
The quantitative reconstruction of land cover changes is a major component of global change studies,and pollen analysis is one of the most robust and reliable proxy indicators of land cover.Relative pollen productivit...The quantitative reconstruction of land cover changes is a major component of global change studies,and pollen analysis is one of the most robust and reliable proxy indicators of land cover.Relative pollen productivity(RPP),via its calibration of pollen-vegetation-land cover relationships,has become an indispensable parameter for reconstructing vegetation dynamics and land cover evolution on geological timescales.This study synthesizes RPP estimates from eight regional studies across the Tibetan Plateau.Our objectives were to systematically analyze the key drivers of spatial heterogeneity of the relevant source areas of pollen(RSAP)and the variability of RPP values among major plant taxa,and to evaluate their efficacy in paleovegetation reconstruction.Key findings include:(1)Sedimentary basin type and size,spatial structure of the vegetation,and number of plant taxa were the main causes of differences in the RSAP.(2)Differences in RPP values of the same plant taxon were controlled mainly by the sedimentary carrier,vegetation landscape,plant species composition and spatial distribution,and pollen morphological diversity and dispersal mode.(3)Application of the MAT-REVEALS(Modern Analogue TechniqueRegional Estimates of VEgetation Abundance from Large Sites)approach at Lake Tangra Yumco successfully reconciled the original pollen percentage and modern vegetation data,confirming that the calibrated RPP values substantially enhanced the reliability of the pollen-based vegetation reconstruction.These outcomes contribute to establishing critical boundary conditions for both paleovegetation modeling and climate simulations on the Tibetan Plateau,and they provide mechanistic insights into alpine ecosystem responses to climatic forcing.展开更多
文摘花粉产量是定量重建古植被、古气候的必要条件,目前花粉产量包括相对花粉产量和绝对花粉产量。由于较难获得多年连续的花粉沉积数据,学者多倾向于使用相对花粉产量进行古植被定量重建。相对花粉产量是某一花粉类型相对于同一参考种的花粉产量的比值(参考种通常选取植物群落和花粉组合中出现频率较高的同一花粉类型),可通过ERV(Extended R-value)模型进行估算,但其准确性受植被调查方法和模型假设条件影响较大。本文介绍了估算相对花粉产量所需的植被调查方法和利用花粉产量定量重建植被景观的模型。目前较成熟的模型为景观重建模型(Landscape Reconstruction Algorithm),包括REVEALS模型(Regional Estimates of Vegetation Abundance from Large Sites,适用于面积≥1~5km^2的沉积盆地植被重建)和LOVE模型(Local Vegetation Estimates,适用于面积为0.1~1.0km^2的沉积盆地植被重建)。欧洲及我国不同区域相对花粉产量和REVEALS模型定量重建研究结果均表明,重建后的古植被景观能较好反映当地的古植被组成。
基金supported by the National Natural Science Foundation of China(Grant Nos.42407595&41630753)the National Key Research and Development Program of China(Grant No.2022YFF0801501).
文摘The quantitative relationship between modern pollen and vegetation provides a critical foundation for reconstructing past vegetation,with relative pollen productivity(RPP)serving as a key calibration parameter.However,in subtropical evergreen broadleaved forests(SEBFs)in China,RPP studies remain scarce,and the impact of human disturbances on RPP estimates has yet to be adequately assessed,limiting the accuracy of quantitative palaeovegetation reconstructions.This study was conducted in Dinghu Mountain Nature Reserve and its surrounding areas in Zhaoqing,Guangdong Province,and included 31 sampling sites.We performed pollen analysis alongside detailed vegetation surveys and utilized ERV submodel 2 and Prentice’s model to estimate the RPP of 9 common plant taxa in the southern SEBFs.There was a particular focus on evaluating the interference effects of bamboo plantations on the estimation of RPP.The results indicate that bamboo within the family Poaceae contributes minimally to surface soil Poaceae pollen because of its unique flowering characteristics,such as long flowering cycles and monocarpic reproduction.The incorporation of bamboo into the Poaceae vegetation coverage in the analysis led to excessively high RPP values for the other taxa.When bamboo coverage was removed from the Poaceae family,the recalculated RPP values aligned closely with those reported in previous studies.The RPP values,ranked from highest to lowest,were as follows:Castanopsis(12.33±0.03)>Araliaceae(1.60±0.03)>Mallotus(1.53±0.26)>Pinus(1.47±0.03)>Rosaceae(1.07±0.02)>Poaceae(1±0)>Euphorbiaceae(0.44±0.03)>Anacardiaceae(0.26±0.03)>Theaceae(0.15±0).Notably,the RPP values for Mallotus,Araliaceae,Theaceae,and Euphorbiaceae represent the first estimates for China’s subtropical region.Differences between certain RPP estimates and those of previous studies may be attributed to factors such as species composition,vegetation structure,and model selection.The findings of this study highlight that due to the widespread distribution of artificial bamboo forests in China’s subtropical regions,future RPP studies should carefully consider the influence of Poaceae.This consideration is essential for improving the accuracy of the application of fossil pollen for quantitative paleo-vegetation reconstruction in these regions.
基金supported by the Excellent Research Group Program for Tibetan Plateau Earth System(Grant No.42588201)the National Natural Science Foundation of China(Grant Nos.42325204&41630753)。
文摘The quantitative reconstruction of land cover changes is a major component of global change studies,and pollen analysis is one of the most robust and reliable proxy indicators of land cover.Relative pollen productivity(RPP),via its calibration of pollen-vegetation-land cover relationships,has become an indispensable parameter for reconstructing vegetation dynamics and land cover evolution on geological timescales.This study synthesizes RPP estimates from eight regional studies across the Tibetan Plateau.Our objectives were to systematically analyze the key drivers of spatial heterogeneity of the relevant source areas of pollen(RSAP)and the variability of RPP values among major plant taxa,and to evaluate their efficacy in paleovegetation reconstruction.Key findings include:(1)Sedimentary basin type and size,spatial structure of the vegetation,and number of plant taxa were the main causes of differences in the RSAP.(2)Differences in RPP values of the same plant taxon were controlled mainly by the sedimentary carrier,vegetation landscape,plant species composition and spatial distribution,and pollen morphological diversity and dispersal mode.(3)Application of the MAT-REVEALS(Modern Analogue TechniqueRegional Estimates of VEgetation Abundance from Large Sites)approach at Lake Tangra Yumco successfully reconciled the original pollen percentage and modern vegetation data,confirming that the calibrated RPP values substantially enhanced the reliability of the pollen-based vegetation reconstruction.These outcomes contribute to establishing critical boundary conditions for both paleovegetation modeling and climate simulations on the Tibetan Plateau,and they provide mechanistic insights into alpine ecosystem responses to climatic forcing.
