{"title":"中国花粉 R 值的区域特征","authors":"","doi":"10.1007/s11430-022-1191-8","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>Establishing a quantitative relationship between modern pollen and vegetation remains a pivotal but intricate pursuit within the field of Quaternary palynology. The <em>R</em>-value, a well-established and traditional metric characterized by its simplicity and direct applicability, serves to calibrate the nonlinear disparities between surface pollen and modern vegetation. This study entails the construction of a comprehensive pollen R-value dataset for China derived from <em>R</em>-values published between 1987 and 2021. The dataset, compiled after rigorous screening, calibration, and standardization processes, encompasses 898 modern pollen sampling sites and 2115 pollen R-value data entries, encapsulating 152 pollen taxa spanning 65 families and 113 genera. Synthesizing the extracted <em>R</em>-values yielded the following insights: (1) A macrospatial analysis validates previously established knowledge at a site-specific scale. Evidently, pollen <em>R</em>-value variations across China are statistically significant. Approximately two-thirds of pollen taxa exhibit underrepresentation (e.g., Taxodiaceae, <em>Corylus</em>, <em>Nitraria</em>, <em>Tamarix</em>, Cyperaceae, Poaceae, and Fabaceae), while the remaining one-third display overrepresentation (e.g., <em>Pinus</em>, <em>Picea</em>, <em>Betula</em>, <em>Ephedra</em>, Chenopodiaceae, and <em>Artemisia</em>). The degree of underrepresentation surpasses that of over-representation, and the representation patterns of <em>Castanea</em>, <em>Quercus</em>, Polygonaceae, and Asteraceae are contingent upon vegetation types. (2) Pollen <em>R</em>-values follow distinct spatial distribution patterns within China. In the woody vegetation region of eastern China, <em>R</em>-values progressively decline from north to south, correlating with rising temperatures and precipitation. Conversely, in herbaceous vegetation regions of northern and western China, <em>R</em>-values decrease from east to west and from northeast to southwest, corresponding to increased aridity. Nevertheless, pollen <em>R</em>-values manifest variation contingent on pollen taxa, vegetation types, and climatic regions, even differing for the same taxa across varying vegetation types and climatic conditions. This highlights the intricate nature of pollen <em>R</em>-values and their interpretation of pollen-vegetation relationships. (3) Pollen <em>R</em>-values and relative pollen production estimates exhibit resemblances and a modest positive correlation. However, adjudicating between them as representatives of vegetation requires nuanced consideration, as both metrics convey pollen representation within vegetation, demonstrating the multifaceted relationships they share with modern vegetation. Further recommendations suggest that when assessing pollen representation in modern vegetation, fossil pollen content should be weighted using either the median or log-transformed <em>R</em>-value. This approach underscores the necessity of comprehensively accounting for divergences and convergences across various spatial scales and vegetation types, particularly the disparities observed within identical pollen taxa across dissimilar regions.</p>","PeriodicalId":21651,"journal":{"name":"Science China Earth Sciences","volume":"4 1","pages":""},"PeriodicalIF":6.0000,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Regional features of pollen R-values in China\",\"authors\":\"\",\"doi\":\"10.1007/s11430-022-1191-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3>Abstract</h3> <p>Establishing a quantitative relationship between modern pollen and vegetation remains a pivotal but intricate pursuit within the field of Quaternary palynology. The <em>R</em>-value, a well-established and traditional metric characterized by its simplicity and direct applicability, serves to calibrate the nonlinear disparities between surface pollen and modern vegetation. This study entails the construction of a comprehensive pollen R-value dataset for China derived from <em>R</em>-values published between 1987 and 2021. The dataset, compiled after rigorous screening, calibration, and standardization processes, encompasses 898 modern pollen sampling sites and 2115 pollen R-value data entries, encapsulating 152 pollen taxa spanning 65 families and 113 genera. Synthesizing the extracted <em>R</em>-values yielded the following insights: (1) A macrospatial analysis validates previously established knowledge at a site-specific scale. Evidently, pollen <em>R</em>-value variations across China are statistically significant. Approximately two-thirds of pollen taxa exhibit underrepresentation (e.g., Taxodiaceae, <em>Corylus</em>, <em>Nitraria</em>, <em>Tamarix</em>, Cyperaceae, Poaceae, and Fabaceae), while the remaining one-third display overrepresentation (e.g., <em>Pinus</em>, <em>Picea</em>, <em>Betula</em>, <em>Ephedra</em>, Chenopodiaceae, and <em>Artemisia</em>). The degree of underrepresentation surpasses that of over-representation, and the representation patterns of <em>Castanea</em>, <em>Quercus</em>, Polygonaceae, and Asteraceae are contingent upon vegetation types. (2) Pollen <em>R</em>-values follow distinct spatial distribution patterns within China. In the woody vegetation region of eastern China, <em>R</em>-values progressively decline from north to south, correlating with rising temperatures and precipitation. Conversely, in herbaceous vegetation regions of northern and western China, <em>R</em>-values decrease from east to west and from northeast to southwest, corresponding to increased aridity. Nevertheless, pollen <em>R</em>-values manifest variation contingent on pollen taxa, vegetation types, and climatic regions, even differing for the same taxa across varying vegetation types and climatic conditions. This highlights the intricate nature of pollen <em>R</em>-values and their interpretation of pollen-vegetation relationships. (3) Pollen <em>R</em>-values and relative pollen production estimates exhibit resemblances and a modest positive correlation. However, adjudicating between them as representatives of vegetation requires nuanced consideration, as both metrics convey pollen representation within vegetation, demonstrating the multifaceted relationships they share with modern vegetation. Further recommendations suggest that when assessing pollen representation in modern vegetation, fossil pollen content should be weighted using either the median or log-transformed <em>R</em>-value. This approach underscores the necessity of comprehensively accounting for divergences and convergences across various spatial scales and vegetation types, particularly the disparities observed within identical pollen taxa across dissimilar regions.</p>\",\"PeriodicalId\":21651,\"journal\":{\"name\":\"Science China Earth Sciences\",\"volume\":\"4 1\",\"pages\":\"\"},\"PeriodicalIF\":6.0000,\"publicationDate\":\"2023-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science China Earth Sciences\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1007/s11430-022-1191-8\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science China Earth Sciences","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s11430-022-1191-8","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
摘要
摘要 建立现代花粉与植被之间的定量关系仍然是第四纪古生物学领域的一项关键而又复杂的工作。R值是一个成熟的传统指标,其特点是简单、直接适用,可用于校准地表花粉与现代植被之间的非线性差异。本研究通过 1987 年至 2021 年间发表的 R 值,为中国建立了一个全面的花粉 R 值数据集。该数据集经过严格的筛选、校准和标准化流程编制而成,包含 898 个现代花粉采样点和 2115 个花粉 R 值数据条目,涵盖 152 个花粉类群,涵盖 65 科 113 属。综合提取的 R 值得出以下结论:(1) 宏观空间分析在特定地点尺度上验证了先前建立的知识。显然,中国各地的花粉 R 值差异在统计学上是显著的。约三分之二的花粉类群表现出代表性不足(如杉木科、榛属、稔属、柽柳属、香蒲科、禾本科和豆科),而其余三分之一的类群则表现出代表性过高(如松属、杉属、桦属、麻黄属、藜属和蒿属)。代表性不足的程度超过了代表性过剩的程度,蓖麻科、柞树科、蓼科和菊科的代表性模式取决于植被类型。(2)花粉 R 值在中国境内有明显的空间分布格局。在中国东部木本植被区,R 值由北向南逐渐下降,这与气温和降水量的上升有关。相反,在中国北部和西部的草本植被区,R 值从东到西和从东北到西南逐渐降低,这与干旱加剧有关。尽管如此,花粉 R 值仍因花粉类群、植被类型和气候区域的不同而存在差异,甚至同一类群在不同植被类型和气候条件下也存在差异。这凸显了花粉 R 值及其对花粉植被关系解释的复杂性。(3) 花粉 R 值与相对花粉产量估计值有相似之处,并呈适度的正相关。然而,将它们作为植被的代表进行判定需要细微的考虑,因为这两个指标都表达了植被中的花粉代表性,显示了它们与现代植被的多方面关系。进一步的建议表明,在评估现代植被中的花粉代表性时,应使用中位数或对数变换的 R 值对化石花粉含量进行加权。这种方法强调了全面考虑不同空间尺度和植被类型中的差异和趋同的必要性,尤其是在不同地区的相同花粉类群中观察到的差异。
Establishing a quantitative relationship between modern pollen and vegetation remains a pivotal but intricate pursuit within the field of Quaternary palynology. The R-value, a well-established and traditional metric characterized by its simplicity and direct applicability, serves to calibrate the nonlinear disparities between surface pollen and modern vegetation. This study entails the construction of a comprehensive pollen R-value dataset for China derived from R-values published between 1987 and 2021. The dataset, compiled after rigorous screening, calibration, and standardization processes, encompasses 898 modern pollen sampling sites and 2115 pollen R-value data entries, encapsulating 152 pollen taxa spanning 65 families and 113 genera. Synthesizing the extracted R-values yielded the following insights: (1) A macrospatial analysis validates previously established knowledge at a site-specific scale. Evidently, pollen R-value variations across China are statistically significant. Approximately two-thirds of pollen taxa exhibit underrepresentation (e.g., Taxodiaceae, Corylus, Nitraria, Tamarix, Cyperaceae, Poaceae, and Fabaceae), while the remaining one-third display overrepresentation (e.g., Pinus, Picea, Betula, Ephedra, Chenopodiaceae, and Artemisia). The degree of underrepresentation surpasses that of over-representation, and the representation patterns of Castanea, Quercus, Polygonaceae, and Asteraceae are contingent upon vegetation types. (2) Pollen R-values follow distinct spatial distribution patterns within China. In the woody vegetation region of eastern China, R-values progressively decline from north to south, correlating with rising temperatures and precipitation. Conversely, in herbaceous vegetation regions of northern and western China, R-values decrease from east to west and from northeast to southwest, corresponding to increased aridity. Nevertheless, pollen R-values manifest variation contingent on pollen taxa, vegetation types, and climatic regions, even differing for the same taxa across varying vegetation types and climatic conditions. This highlights the intricate nature of pollen R-values and their interpretation of pollen-vegetation relationships. (3) Pollen R-values and relative pollen production estimates exhibit resemblances and a modest positive correlation. However, adjudicating between them as representatives of vegetation requires nuanced consideration, as both metrics convey pollen representation within vegetation, demonstrating the multifaceted relationships they share with modern vegetation. Further recommendations suggest that when assessing pollen representation in modern vegetation, fossil pollen content should be weighted using either the median or log-transformed R-value. This approach underscores the necessity of comprehensively accounting for divergences and convergences across various spatial scales and vegetation types, particularly the disparities observed within identical pollen taxa across dissimilar regions.
期刊介绍:
Science China Earth Sciences, an academic journal cosponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China, and published by Science China Press, is committed to publishing high-quality, original results in both basic and applied research.