The effect of neighbor species’ phylogenetic and trait difference on tree growth in subtropical forests
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Feb 13, 2024 version files 31.98 KB
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data_paper.txt
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README.md
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Abstract
To comprehensively understand ecological dynamics within a forest ecosystem, it is vital to explore how surrounding trees influence the growth of individual trees in a community. Biotic interactions have a significant potential impacts on individual tree growth and their effects can be evaluated through trait and phylogenetic-based approaches. This study investigates the relative importance of biotic interactions on tree growth by examining several metrics and considering three classes of intrinsic growth rates among the focal individuals: slower, intermediate and faster-growing trees. The metrics include hierarchical and absolute trait differences of focal trees to neighbors, neighborhood crowding index, phylogenetic distance, and trait community metrics. Our results indicated that the phylogenetic distance between the focal tree and its neighbors positively impacted the growth of all classes, whereas different traits have distinct effects on slower and faster-growing trees. Specific leaf area (SLA) and leaf area (LA) showed hierarchical importance to tree growth. Trees surrounded by neighbors with higher SLA and LA than themselves grow better, particularly for slower-growing trees. Higher levels of wood density difference between the focal trees and their neighbors positively impacts slower and faster-growing trees, while height difference negatively impacts faster-growing trees. We conclude that the interactions between trees are mediated by their ecological differences, but the performance and responses to surrounding competitors vary along with their growth class within a community. This study has revealed that the tree's intrinsic growth rate mediates the effect of traits and phylogeny of surrounding trees on individual tree growth.
https://doi.org/10.5061/dryad.djh9w0w66
This study aimed to investigate the relative importance of biotic interactions on tree growth by examining several metrics, including hierarchical and absolute trait differences of focal trees to neighbors, neighborhood crowding index, functional community structure, and phylogenetic distance.
Description of the data and file structure
The dataset includes information related to the site and the plot where the tree individuals were collected, as well as their code in the permanent plots. Additionally, the species' individual trees were identified, as well as their growth class and annual growth rate (AGR).
We utilized plant functional traits, which are indicators of plant functional strategies and are expected to be related to individual tree growth and performance. These traits included height (H, m), leaf area (LA, cm²), specific leaf area (SLA, cm².g-1), leaf dry matter content (LDMC, mg.g-1), and wood density (WD, g.cm³).
The neighborhood variables considered in the study were:
a) Neighborhood crowding index (NCI): based on the steam size and spatial distance of neighboring trees within a fixed radius of 5 m;
b) neighborhood hierarchical mean trait difference (LAh, SLAh, LDMCh, WDh, Hh) and neighborhood absolute mean trait difference (LAs, LDMCs, WDs, Hs) : dissimilarity of functional traits between focal trees and their neighbors. These indices are associated with competitive abilities' trait-mediated ranks and niche differentiation, respectively;
c) community weighted mean (CWM; CWM_LA, CWM_SLA, CWM_LDMC, CWM_WD, CWM_H): mean trait values of each community of tree neighbors accounting for species relative abundance in each community;
d) functional diversity (FD): Rao weighted by species relative abundance in each community;
e) mean phylogenetic difference (mean_PD): the mean phylogenetic distance between the focal individual to all neighbor trees within the radius
To assess the effects of neighborhood interactions and community structure on tree growth, we performed quantile regression models (QR) with AGR logarithmic as the response variable and non-correlated neighborhood variables as predictors, using the 'rq' function in the R package quantreg. We ran the QR using the equation log AGR~ mean_PD+ SLAh+ WDs+ LAh+ LDMCh+ LDMCs+ Hs+ NCI+ CWM_LA+ CWM_SLA+ CWM_LDMC+ CWM_H+ FD and using three quantiles in line with our sampling design: the 25th percentile (QR 25%) for focal trees with slower growth, the 50th percentile (QR 50%) for trees with intermediary growth, and the 75th percentile (QR 75%) for focal trees with faster growth. The analysis is described in the script.
Sharing/Access information
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Code/Software
To assess the effects of neighborhood interactions and community structure on tree growth, we performed quantile regression models (QR) with AGR logarithmic as the response variable and non-correlated neighborhood variables as predictor, using the ‘rq’ function in the R package quantreg.
- Klipel, Joice (2024), The effect of neighbor species' phylogenetic and trait difference on tree growth in subtropical forests, , Article, https://doi.org/10.5281/zenodo.10070169
- Klipel, Joice (2024), The effect of neighbor species' phylogenetic and trait difference on tree growth in subtropical forests, , Article, https://doi.org/10.5281/zenodo.10070170
- Klipel, Joice; Bergamin, Rodrigo Scarton; Bordin, Kauane Maiara et al. (2024). The effect of neighbor species' phylogenetic and trait difference on tree growth in subtropical forests. Journal of Vegetation Science. https://doi.org/10.1111/jvs.13296