Other formats:
BibTeX
LaTeX
RIS
@article{1796130,
author = {Mastrogianni, Anna and Chytrý, Milan and Kallimanis, Athanasios S. and Tsiripidis, Ioannis},
article_location = {Amsterdam},
article_number = {November},
doi = {http://dx.doi.org/10.1016/j.ecolind.2021.108229},
keywords = {Balkan Peninsula; Forest vegetation; Functional diversity; Functional identity; Functional structure; Greece; Plant traits},
language = {eng},
issn = {1470-160X},
journal = {Ecological indicators},
title = {Plant trait filtering is stronger in the herb layer than in the tree layer in Greek mountain forests},
url = {https://doi.org/10.1016/j.ecolind.2021.108229},
volume = {131},
year = {2021}
}
TY - JOUR
ID - 1796130
AU - Mastrogianni, Anna - Chytrý, Milan - Kallimanis, Athanasios S. - Tsiripidis, Ioannis
PY - 2021
TI - Plant trait filtering is stronger in the herb layer than in the tree layer in Greek mountain forests
JF - Ecological indicators
VL - 131
IS - November
SP - "108229"
EP - "108229"
PB - Elsevier
SN - 1470160X
KW - Balkan Peninsula
KW - Forest vegetation
KW - Functional diversity
KW - Functional identity
KW - Functional structure
KW - Greece
KW - Plant traits
UR - https://doi.org/10.1016/j.ecolind.2021.108229
N2 - We studied the differentiation among plant communities of deciduous broadleaved and mountain coniferous forests in terms of functional diversity and identity at a regional scale (northern and central Greece). We asked if patterns of functional differentiation among communities are consistent between the overstorey and understorey layers and if they can be influenced by deep past environmental conditions. Functional Richness (FRic) and Functional Dispersion (FDis), as well as their standardized effect sizes, were employed to assess the multivariate functional diversity of the community types. In contrast, single-trait Community Weighted Means (CWMs) were used as surrogates of functional identity. The aforementioned indices were calculated for three datasets, namely all the vascular plant taxa found in individual vegetation plots (total community), all phanerophyte (tree and shrub) taxa (overstorey) and all non-phanerophyte vascular plant taxa (understorey). We found that community types and especially four broad forest types (beech, ravine, pine and oak forests) are well differentiated in terms of functional composition (identity), as indicated by Non-Metric Multidimensional Scaling (NMDS). After conducting an NMDS for the three datasets, functional identity based on the total floristic composition was found to be the best discriminator of the studied communities. However, contrasting patterns were found for some specific traits or their categories between overstorey and understorey layers. The patterns of functional diversity of the community types (based on multivariate indices), revealed by calculating the standardized effect sizes of FRic and FDis based on the richness null model, did not differ substantially from random expectations for most of the studied community types when the dataset of all the vascular plant taxa was analyzed. However, the patterns revealed for the overstorey layer differed from those for the understorey layer. For the latter layer, the clustered structure was revealed in many community types based on the ses.FDis metric. Indications of deep past influence on the functional composition were found for certain community types (i.e. ravine forests) based on single-trait metrics, but no indication of such influence was found based on multivariate indices. Our findings highlight the complementarity and the additive explanatory value of the simultaneous use of single- and multi-trait approaches and their application to different layers in forests.
ER -
MASTROGIANNI, Anna, Milan CHYTRÝ, Athanasios S. KALLIMANIS and Ioannis TSIRIPIDIS. Plant trait filtering is stronger in the herb layer than in the tree layer in Greek mountain forests. \textit{Ecological indicators}. Amsterdam: Elsevier, 2021, vol.~131, November, p.~''108229'', 12 pp. ISSN~1470-160X. Available from: https://dx.doi.org/10.1016/j.ecolind.2021.108229.
|
