Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 667

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Using plant functional traits to understand the landscape distribution of multiple ecosystem services

Lavorel, Sandra, Grigulis, Karl, Lamarque, Pénélope, Colace, Marie‐Pascale, Garden, Denys, Girel, Jacky, Pellet, Gilles, Douzet, Rolland·2011·Journal of Ecology

Abstract

Summary: 1. Spatially explicit understanding of the delivery of multiple ecosystem services (ES) from global to local scales is currently limited. New studies analysing the simultaneous provision of multiple services at landscape scale should aid the understanding of multiple ES delivery and trade‐offs to support policy, management and land planning. 2. Here, we propose a new approach for the analysis, mapping and understanding of multiple ES delivery in landscapes. Spatially explicit single ES models based on plant traits and abiotic characteristics are combined to identify ‘hot’ and ‘cold’ spots of multiple ES delivery, and the land use and biotic determinants of such distributions. We demonstrate the value of this trait‐based approach as compared to a pure land‐use approach for a pastoral landscape from the central French Alps, and highlight how it improves understanding of ecological constraints to, and opportunities for, the delivery of multiple services. 3. Vegetative height and leaf traits such as leaf dry matter content were response traits strongly influenced by land use and abiotic environment, with follow‐on effects on several ecosystem properties, and could therefore be used as functional markers of ES. 4. Patterns of association among ES were related to the dominant traits underlying different ecosystem properties. The functional decoupling between height and leaf traits provided alternative pathways for high agronomic value, as well as determining hot and cold spots of ES. Traditional land uses such as organic fertilization and mowing or altitude summer grazing were also linked with ES hot spots, because functional characteristics supporting fodder production and quality are compatible with species and functional diversity. 5. Synthesis . Analyses of ES using plant functional variation across landscapes are a powerful approach to understanding the fundamental ecological mechanisms underlying ES provision, and trade‐offs or synergies among services. Sustainable management of species and functionally diverse grassland could simultaneously aim at conserving biodiversity and locally important ES by taking advantage of correlations and trade‐offs among different plant functional traits.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1111/j.1365-2745.2010.01753.x

Cites

9 of 9 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 9 references

Cited by

See all 667

Metadata

Authors
Lavorel, S., Grigulis, K., Lamarque, P., Colace, M., Garden, D., Girel, J., Pellet, G., & Douzet, R.
Venue
Journal of Ecology
Publisher
Wiley
Published
2010-11-22
Volume
99
Issue
1
Pages
135-147
ISSN
  • 0022-0477 (ISSN-L)
  • 1365-2745
OpenAlex
W1531492839
Cited by
667
References
9
FWCI
27.15
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Using plant functional traits to understand the landscape distribution of multiple ecosystem services. https://app.cochat.ai/papers/10.1111/j.1365-2745.2010.01753.x
The paper
Lavorel, S., Grigulis, K., Lamarque, P., Colace, M., Garden, D., Girel, J., Pellet, G., & Douzet, R. (2011). Using plant functional traits to understand the landscape distribution of multiple ecosystem services. Journal of Ecology. https://doi.org/10.1111/j.1365-2745.2010.01753.x

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.