Header

UZH-Logo

Maintenance Infos

Traditional plant functional groups explain variation in economic but not size‐related traits across the tundra biome


Thomas, H J D; Myers‐Smith, I H; Bjorkman, A D; et al; Prevéy, J S; Rixen, C; Schaepman-Strub, G (2019). Traditional plant functional groups explain variation in economic but not size‐related traits across the tundra biome. Global Ecology and Biogeography, 28:78-95.

Abstract

Aim:
Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits.
Location: Tundra biome.
Time period: Data collected between 1964 and 2016.
Major taxa studied: 295 tundra vascular plant species.
Methods:
We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species‐level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species‐level traits.

Results:
Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species‐level trait expression.

Main conclusions:
Traditional functional groups only coarsely represent variation in well‐measured traits within tundra plant communities, and better explain resource economic traits than size‐related traits. We recommend caution when using functional group approaches to predict tundra vegetation change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insights for ecological prediction and modelling.

Abstract

Aim:
Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits.
Location: Tundra biome.
Time period: Data collected between 1964 and 2016.
Major taxa studied: 295 tundra vascular plant species.
Methods:
We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species‐level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species‐level traits.

Results:
Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species‐level trait expression.

Main conclusions:
Traditional functional groups only coarsely represent variation in well‐measured traits within tundra plant communities, and better explain resource economic traits than size‐related traits. We recommend caution when using functional group approaches to predict tundra vegetation change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insights for ecological prediction and modelling.

Statistics

Citations

Dimensions.ai Metrics
4 citations in Web of Science®
5 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

6 downloads since deposited on 31 Jan 2020
6 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
08 Research Priority Programs > Global Change and Biodiversity
Dewey Decimal Classification:570 Life sciences; biology
590 Animals (Zoology)
Scopus Subject Areas:Physical Sciences > Global and Planetary Change
Life Sciences > Ecology, Evolution, Behavior and Systematics
Physical Sciences > Ecology
Uncontrolled Keywords:Ecology, Global and Planetary Change, Ecology, Evolution, Behavior and Systematics
Language:English
Date:2019
Deposited On:31 Jan 2020 13:50
Last Modified:12 Sep 2020 11:13
Publisher:Wiley-Blackwell Publishing, Inc.
ISSN:1466-822X
OA Status:Hybrid
Publisher DOI:https://doi.org/10.1111/geb.12783

Download

Hybrid Open Access

Download PDF  'Traditional plant functional groups explain variation in economic but not size‐related traits across the tundra biome'.
Preview
Content: Published Version
Filetype: PDF
Size: 6MB
View at publisher
Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)