Dataset Information

A Review of Relative Pollen Productivity Estimates From Temperate China for Pollen-Based Quantitative Reconstruction of Past Plant Cover.

ABSTRACT: Model-based quantitative reconstruction of past plant cover in Europe has shown great potential for: (i) testing hypotheses related to Holocene vegetation dynamics, biodiversity, and their relationships with climate and land use; (ii) studying long term interactions between climate and land use. Similar model-based quantitative reconstruction of plant cover in China has been restricted due to the lack of standardized datasets of existing estimates of relative pollen productivity (RPP). This study presents the first synthesis of all RPP values available to date for 39 major plant taxa from temperate China and proposes standardized RPP datasets that can be used for model-based quantitative reconstructions of past plant cover using fossil pollen records for the region. We review 11 RPP studies in temperate China based on modern pollen and related vegetation data around the pollen samples. The study areas include meadow, steppe and desert vegetation, various woodland types, and cultural landscapes. We evaluate the strategies of each study in terms of selection of study areas and distribution of study sites; pollen- and vegetation-data collection in field; vegetation-data collection from satellite images and vegetation maps; and data analysis. We compare all available RPP estimates, select values based on precise rules and calculate mean RPP estimates. We propose two standardized RPP datasets for 31 (Alt1) and 29 (Alt2) plant taxa. The ranking of mean RPPs (Alt-2) relative to Poaceae (= 1) for eight major taxa is: Artemisia (21) > Pinus (18.4) > Betula (12.5) > Castanea (11.5) > Elaeagnaceae (8.8) > Juglans (7.5) > Compositae (4.5) > Amaranthaceae/Chenopodiaceae (4). We conclude that although RPPs are comparable between Europe and China for some genera and families, they can differ very significantly, e.g., Artemisia, Compositae, and Amaranthaceae/Chenopodiaceae. For some taxa, we present the first RPP estimates e.g. Castanea, Elaeagnaceae, and Juglans. The proposed standardized RPP datasets are essential for model-based reconstructions of past plant cover using fossil pollen records from temperate China.

SUBMITTER: Li F

PROVIDER: S-EPMC6134201 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Review of Relative Pollen Productivity Estimates From Temperate China for Pollen-Based Quantitative Reconstruction of Past Plant Cover.

Li Furong F Gaillard Marie-José MJ Xu Qinghai Q Bunting Mairi J MJ Li Yuecong Y Li Jie J Mu Huishuang H Lu Jingyao J Zhang Panpan P Zhang Shengrui S Cui Qiaoyu Q Zhang Yahong Y Shen Wei W

Frontiers in plant science 20180905

Model-based quantitative reconstruction of past plant cover in Europe has shown great potential for: (i) testing hypotheses related to Holocene vegetation dynamics, biodiversity, and their relationships with climate and land use; (ii) studying long term interactions between climate and land use. Similar model-based quantitative reconstruction of plant cover in China has been restricted due to the lack of standardized datasets of existing estimates of relative pollen productivity (RPP). This stud ...[more]

PMID: 30233604

Similar Datasets

Project description:Characterization of land cover change in the past is fundamental to understand the evolution and present state of the Earth system, the amount of carbon and nutrient stocks in terrestrial ecosystems, and the role played by land-atmosphere interactions in influencing climate. The estimation of land cover changes using palynology is a mature field, as thousands of sites in Europe have been investigated over the last century. Nonetheless, a quantitative land cover reconstruction at a continental scale has been largely missing. Here, we present a series of maps detailing the evolution of European forest cover during last 12,000 years. Our reconstructions are based on the Modern Analog Technique (MAT): a calibration dataset is built by coupling modern pollen samples with the corresponding satellite-based forest-cover data. Fossil reconstructions are then performed by assigning to every fossil sample the average forest cover of its closest modern analogs. The occurrence of fossil pollen assemblages with no counterparts in modern vegetation represents a known limit of analog-based methods. To lessen the influence of no-analog situations, pollen taxa were converted into plant functional types prior to running the MAT algorithm. We then interpolate site-specific reconstructions for each timeslice using a four-dimensional gridding procedure to create continuous gridded maps at a continental scale. The performance of the MAT is compared against methodologically independent forest-cover reconstructions produced using the REVEALS method. MAT and REVEALS estimates are most of the time in good agreement at a trend level, yet MAT regularly underestimates the occurrence of densely forested situations, requiring the application of a bias correction procedure. The calibrated MAT-based maps draw a coherent picture of the establishment of forests in Europe in the Early Holocene with the greatest forest-cover fractions reconstructed between ?8,500 and 6,000 calibrated years BP. This forest maximum is followed by a general decline in all parts of the continent, likely as a result of anthropogenic deforestation. The continuous spatial and temporal nature of our reconstruction, its continental coverage, and gridded format make it suitable for climate, hydrological, and biogeochemical modeling, among other uses.

Project description:The dataset presented here supports the research paper entitled "A calculator to quantify cover crop effects on soil health and productivity". Soil health (sometimes used synonymously with soil quality) is a concept that describes soil as a living system to sustain plants, animals, and human. Soil physical, chemical, and biological properties, along with their interactions, are required to quantify soil health. The use of cover crops in agricultural rotations may enhance soil health, yet there has been little progress in understanding how external factors such as climate, soil type, and agronomic practices affect soil and cash crop responses. In response, this dataset compiles measurements from 281 studies and provides an analysis of field-measured changes in 38 soil health indicators due to cover crop usage. Environmental and background indicators were also compiled to assess how climatic and management practices affect soil and cash crop responses to cover crops, with specific categories including climate type (tropical, arid, temperate, and continental), soil texture (coarse, medium, and fine), cover crop type (legume, grass, multi-species mixture, and other), and cash crop type (corn, soybean, wheat, vegetable, corn-soybean rotation, corn-soybean-wheat rotation, and other). An unbalanced analysis of variation was used to determine the hierarchy of most to least important factors that affected responsiveness of each soil health indicator. Based on the hierarchy structure, a soil health calculator was then developed to quantify the response of 13 parameters - erosion, runoff, weed suppression, soil aggregate stability, leaching, infiltration, microbial biomass carbon, soil bulk density, soil organic carbon, soil nitrogen, microbial biomass nitrogen, cash crop yield, and saturated hydraulic conductivity - to cover crops. The presented data in the calculator report the mean change in parameter values based on all combinations of climate, soil texture, cover crop type, and cash crop type.

Project description:The diversity-productivity, diversity-invasibility, and diversity-stability hypotheses propose that increasing species diversity should lead, respectively, to increased average biomass productivity, invasion resistance, and stability. We tested these three hypotheses in the context of cover crop mixtures, evaluating the effects of increasing cover crop mixture diversity on aboveground biomass, weed suppression, and biomass stability. Twenty to forty cover crop treatments were replicated three or four times at eleven sites using eighteen species representing three cover crop species each from six pre-defined functional groups: cool-season grasses, cool-season legumes, cool-season brassicas, warm-season grasses, warm-season legumes, and warm-season broadleaves. Each species was seeded as a pure stand, and the most diverse treatment contained all eighteen species. Remaining treatments included treatments representing intermediate levels of cover crop species and functional richness and a no cover crop control. Cover crop seeding dates ranged from late July to late September with both cover crop and weed aboveground biomass being sampled prior to winterkill. Stability was assessed by evaluating the variability in cover crop biomass for each treatment across plots within each site. While increasing cover crop mixture diversity was associated with increased average aboveground biomass, we assert that this was the result of the average biomass of the pure stands being drawn down by low biomass species rather than due to niche complementarity or increased resource use efficiency. At no site did the highest biomass mixture produce more than the highest biomass pure stand. Furthermore, while increases in cover crop mixture diversity were correlated with increases in weed suppression and biomass stability, we argue that this was largely the result of diversity co-varying with aboveground biomass, and that differences in aboveground biomass rather than differences in diversity drove the differences observed in weed suppression and stability.

Dataset Information

A Review of Relative Pollen Productivity Estimates From Temperate China for Pollen-Based Quantitative Reconstruction of Past Plant Cover.

Publications

A Review of Relative Pollen Productivity Estimates From Temperate China for Pollen-Based Quantitative Reconstruction of Past Plant Cover.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets