Data from: Patterns of modern pollen and plant richness across northern Europe
1. Sedimentary pollen offers excellent opportunities to reconstruct vegetation changes over past millennia. Number of different pollen taxa or pollen richness is used to characterise past plant richness. To improve the interpretation of sedimentary pollen richness, it is essential to understand the...
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Data Archiving and Networked Services (DANS)
2020
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Online Access: | https://doi.org/10.5061/dryad.m4s45t4 |
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fttriple:oai:gotriple.eu:50|dedup_wf_001::149536397ba363ece96e89b9dc8fbd4d 2023-05-15T18:40:40+02:00 Data from: Patterns of modern pollen and plant richness across northern Europe Reitalu, Triin Bjune, Anne E. Blaus, Ansis Giesecke, Thomas Helm, Aveliina Matthias, Isabelle Peglar, Sylvia H. Salonen, J. Sakari Seppa, Heikki Väli, Vivika Birks, H. John B. 2020-01-11 https://doi.org/10.5061/dryad.m4s45t4 undefined unknown Data Archiving and Networked Services (DANS) http://dx.doi.org/10.5061/dryad.m4s45t4 https://dx.doi.org/10.5061/dryad.m4s45t4 lic_creative-commons oai:easy.dans.knaw.nl:easy-dataset:119944 10.5061/dryad.m4s45t4 oai:services.nod.dans.knaw.nl:Products/dans:oai:easy.dans.knaw.nl:easy-dataset:119944 10|re3data_____::84e123776089ce3c7a33db98d9cd15a8 10|openaire____::9e3be59865b2c1c335d32dae2fe7b254 10|re3data_____::94816e6421eeb072e7742ce6a9decc5f 10|eurocrisdris::fe4903425d9040f680d8610d9079ea14 re3data_____::r3d100000044 Life sciences medicine and health care climate Palynological diversity Pollen-plant relationship Landscape Quaternary Palaeoecology and land-use history Holocene diversity anthro-bio envir Dataset https://vocabularies.coar-repositories.org/resource_types/c_ddb1/ 2020 fttriple https://doi.org/10.5061/dryad.m4s45t4 2023-01-22T16:51:58Z 1. Sedimentary pollen offers excellent opportunities to reconstruct vegetation changes over past millennia. Number of different pollen taxa or pollen richness is used to characterise past plant richness. To improve the interpretation of sedimentary pollen richness, it is essential to understand the relationship between pollen and plant richness in contemporary landscapes. This study presents a regional-scale comparison of pollen and plant richness from northern Europe and evaluates the importance of environmental variables on pollen and plant richness. 2. We use a pollen dataset of 511 lake-surface pollen samples ranging through temperate, boreal, and tundra biomes. To characterise plant diversity, we use a dataset formulated from the two largest plant atlases available in Europe. We compare pollen and plant richness estimates in different groups of taxa (wind-pollinated vs non-wind-pollinated, trees and shrubs vs herbs and grasses) and test their relationships with climate and landscape variables. 3. Pollen richness is significantly positively correlated with plant richness (r=0.53). The pollen–plant richness correlation improves (r=0.63) when high pollen-producers are downweighted prior to estimating richness minimising the influence of pollen-production on the pollen richness estimate. This suggests that methods accommodating pollen-production differences in richness estimates deserve further attention and should become more widely used in Quaternary pollen diversity studies. 4. The highest correlations are found between pollen and plant richness of trees and shrubs (r=0.83) and of wind-pollinated taxa (r=0.75) suggesting that these are the best measures of broad-scale plant richness over several thousands of square kilometres. 5. Mean annual temperature is the strongest predictor of both pollen and plant richness. Landscape openness is positively associated with pollen richness but not with plant richness. Pollen-richness values from extremely open and/or cold areas where pollen production is low, should be ... Dataset Tundra Unknown |
institution |
Open Polar |
collection |
Unknown |
op_collection_id |
fttriple |
language |
unknown |
topic |
Life sciences medicine and health care climate Palynological diversity Pollen-plant relationship Landscape Quaternary Palaeoecology and land-use history Holocene diversity anthro-bio envir |
spellingShingle |
Life sciences medicine and health care climate Palynological diversity Pollen-plant relationship Landscape Quaternary Palaeoecology and land-use history Holocene diversity anthro-bio envir Reitalu, Triin Bjune, Anne E. Blaus, Ansis Giesecke, Thomas Helm, Aveliina Matthias, Isabelle Peglar, Sylvia H. Salonen, J. Sakari Seppa, Heikki Väli, Vivika Birks, H. John B. Data from: Patterns of modern pollen and plant richness across northern Europe |
topic_facet |
Life sciences medicine and health care climate Palynological diversity Pollen-plant relationship Landscape Quaternary Palaeoecology and land-use history Holocene diversity anthro-bio envir |
description |
1. Sedimentary pollen offers excellent opportunities to reconstruct vegetation changes over past millennia. Number of different pollen taxa or pollen richness is used to characterise past plant richness. To improve the interpretation of sedimentary pollen richness, it is essential to understand the relationship between pollen and plant richness in contemporary landscapes. This study presents a regional-scale comparison of pollen and plant richness from northern Europe and evaluates the importance of environmental variables on pollen and plant richness. 2. We use a pollen dataset of 511 lake-surface pollen samples ranging through temperate, boreal, and tundra biomes. To characterise plant diversity, we use a dataset formulated from the two largest plant atlases available in Europe. We compare pollen and plant richness estimates in different groups of taxa (wind-pollinated vs non-wind-pollinated, trees and shrubs vs herbs and grasses) and test their relationships with climate and landscape variables. 3. Pollen richness is significantly positively correlated with plant richness (r=0.53). The pollen–plant richness correlation improves (r=0.63) when high pollen-producers are downweighted prior to estimating richness minimising the influence of pollen-production on the pollen richness estimate. This suggests that methods accommodating pollen-production differences in richness estimates deserve further attention and should become more widely used in Quaternary pollen diversity studies. 4. The highest correlations are found between pollen and plant richness of trees and shrubs (r=0.83) and of wind-pollinated taxa (r=0.75) suggesting that these are the best measures of broad-scale plant richness over several thousands of square kilometres. 5. Mean annual temperature is the strongest predictor of both pollen and plant richness. Landscape openness is positively associated with pollen richness but not with plant richness. Pollen-richness values from extremely open and/or cold areas where pollen production is low, should be ... |
format |
Dataset |
author |
Reitalu, Triin Bjune, Anne E. Blaus, Ansis Giesecke, Thomas Helm, Aveliina Matthias, Isabelle Peglar, Sylvia H. Salonen, J. Sakari Seppa, Heikki Väli, Vivika Birks, H. John B. |
author_facet |
Reitalu, Triin Bjune, Anne E. Blaus, Ansis Giesecke, Thomas Helm, Aveliina Matthias, Isabelle Peglar, Sylvia H. Salonen, J. Sakari Seppa, Heikki Väli, Vivika Birks, H. John B. |
author_sort |
Reitalu, Triin |
title |
Data from: Patterns of modern pollen and plant richness across northern Europe |
title_short |
Data from: Patterns of modern pollen and plant richness across northern Europe |
title_full |
Data from: Patterns of modern pollen and plant richness across northern Europe |
title_fullStr |
Data from: Patterns of modern pollen and plant richness across northern Europe |
title_full_unstemmed |
Data from: Patterns of modern pollen and plant richness across northern Europe |
title_sort |
data from: patterns of modern pollen and plant richness across northern europe |
publisher |
Data Archiving and Networked Services (DANS) |
publishDate |
2020 |
url |
https://doi.org/10.5061/dryad.m4s45t4 |
genre |
Tundra |
genre_facet |
Tundra |
op_source |
oai:easy.dans.knaw.nl:easy-dataset:119944 10.5061/dryad.m4s45t4 oai:services.nod.dans.knaw.nl:Products/dans:oai:easy.dans.knaw.nl:easy-dataset:119944 10|re3data_____::84e123776089ce3c7a33db98d9cd15a8 10|openaire____::9e3be59865b2c1c335d32dae2fe7b254 10|re3data_____::94816e6421eeb072e7742ce6a9decc5f 10|eurocrisdris::fe4903425d9040f680d8610d9079ea14 re3data_____::r3d100000044 |
op_relation |
http://dx.doi.org/10.5061/dryad.m4s45t4 https://dx.doi.org/10.5061/dryad.m4s45t4 |
op_rights |
lic_creative-commons |
op_doi |
https://doi.org/10.5061/dryad.m4s45t4 |
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1766230080925728768 |