Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world
Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen, foraminifera or chironomids are routinely used in climate model–proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2016-12-01
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| Series: | Climate of the Past |
| Online Access: | http://www.clim-past.net/12/2255/2016/cp-12-2255-2016.pdf |
| _version_ | 1818137447037403136 |
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| author | K. Rehfeld M. Trachsel R. J. Telford T. Laepple |
| author_facet | K. Rehfeld M. Trachsel R. J. Telford T. Laepple |
| author_sort | K. Rehfeld |
| collection | DOAJ |
| description | Reconstructions of summer, winter or annual mean temperatures based on the
species composition of bio-indicators such as pollen, foraminifera or
chironomids are routinely used in climate model–proxy data comparison
studies. Most reconstruction algorithms exploit the joint distribution of
modern spatial climate and species distribution for the development of the
reconstructions. They rely on the space-for-time substitution and the
specific assumption that environmental variables other than those
reconstructed are not important or that their relationship with the
reconstructed variable(s) should be the same in the past as in the modern
spatial calibration dataset.
Here we test the implications of this
“correlative uniformitarianism” assumption on climate reconstructions in an
ideal model world, in which climate and vegetation are known at all times.
The alternate reality is a climate simulation of the last 6000 years with
dynamic vegetation. Transient changes of plant functional types are
considered as surrogate pollen counts and allow us to establish, apply and
evaluate transfer functions in the modeled world. We find that in our model
experiments the transfer function cross validation <i>r</i><sup>2</sup> is of limited use to
identify reconstructible climate variables, as it only relies on the modern
spatial climate–vegetation relationship. However, ordination approaches that
assess the amount of fossil vegetation variance explained by the
reconstructions are promising. We furthermore show that correlations between
climate variables in the modern climate–vegetation relationship are
systematically extended into the reconstructions. Summer temperatures, the
most prominent driving variable for modeled vegetation change in the Northern
Hemisphere, are accurately reconstructed. However, the amplitude of the model
winter and mean annual temperature cooling between the mid-Holocene and
present day is overestimated and similar to the summer trend in magnitude.
This effect
occurs because temporal changes of a dominant climate variable, such as
summer temperatures in the model's Arctic, are imprinted on a less important
variable, leading to reconstructions biased towards the dominant variable's
trends. Our results, although based on a model vegetation that is inevitably
simpler than reality, indicate that reconstructions of multiple climate
variables based on modern spatial bio-indicator datasets should be treated
with caution. Expert knowledge on the ecophysiological drivers of the
proxies, as well as statistical methods that go beyond the cross validation on
modern calibration datasets, are crucial to avoid misinterpretation. |
| first_indexed | 2024-12-11T09:56:26Z |
| format | Article |
| id | doaj.art-e20208a7249041459eb4cc74c262b2ea |
| institution | Directory Open Access Journal |
| issn | 1814-9324 1814-9332 |
| language | English |
| last_indexed | 2024-12-11T09:56:26Z |
| publishDate | 2016-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Climate of the Past |
| spelling | doaj.art-e20208a7249041459eb4cc74c262b2ea2022-12-22T01:12:15ZengCopernicus PublicationsClimate of the Past1814-93241814-93322016-12-0112122255227010.5194/cp-12-2255-2016Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model worldK. Rehfeld0M. Trachsel1R. J. Telford2T. Laepple3Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, 14473 Potsdam, GermanyDepartment of Biology, University of Bergen, Postboks 7803, 5020 Bergen, NorwayDepartment of Biology, University of Bergen, Postboks 7803, 5020 Bergen, NorwayAlfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, 14473 Potsdam, GermanyReconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen, foraminifera or chironomids are routinely used in climate model–proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this “correlative uniformitarianism” assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that in our model experiments the transfer function cross validation <i>r</i><sup>2</sup> is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate–vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We furthermore show that correlations between climate variables in the modern climate–vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable, such as summer temperatures in the model's Arctic, are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution. Expert knowledge on the ecophysiological drivers of the proxies, as well as statistical methods that go beyond the cross validation on modern calibration datasets, are crucial to avoid misinterpretation.http://www.clim-past.net/12/2255/2016/cp-12-2255-2016.pdf |
| spellingShingle | K. Rehfeld M. Trachsel R. J. Telford T. Laepple Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world Climate of the Past |
| title | Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world |
| title_full | Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world |
| title_fullStr | Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world |
| title_full_unstemmed | Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world |
| title_short | Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world |
| title_sort | assessing performance and seasonal bias of pollen based climate reconstructions in a perfect model world |
| url | http://www.clim-past.net/12/2255/2016/cp-12-2255-2016.pdf |
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