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The effect of environmental filtering on variation in functional diversity along a tropical elevational gradient
Author(s) -
Ding Yi,
Zang Runguo,
Lu Xinghui,
Huang Jihong,
Xu Yue
Publication year - 2019
Publication title -
journal of vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 115
eISSN - 1654-1103
pISSN - 1100-9233
DOI - 10.1111/jvs.12786
Subject(s) - environmental gradient , abiotic component , gradient analysis , transect , specific leaf area , ecology , species richness , ordination , biology , community structure , ecosystem , botany , photosynthesis , habitat
Abstract Questions Elevational gradients encompass multiple resource or non‐resource stressors, but how these different gradients drive functional structure is not well understood. Abiotic variables and functional traits were sampled along a 1,400 m tropical elevational gradient to answer the following questions: (a) how do the functional diversity and functional structure of tree communities change with environment; (b) how does the different assembly vary along the elevational gradient? Location Tropical forests on Hainan Island, South China. Methods Along an elevational gradient from 180 m to 1,521 m, sixty 0.05‐ha transects were established. We recorded all woody stems ≥5 cm dbh (diameter at breast height) and measured functional traits and soil features in each transect. The patterns of abiotic variables, functional diversity and community‐weighted mean ( CWM ) of functional traits were explored along the elevational gradient by using a regression model. The assembly along the elevational gradient was compared with a null model that shuffled species identities. Results The functional richness ( FR ic), functional dispersion ( FD is) and CWM s of specific leaf area, leaf phosphorus and nitrogen content decreased with increasing elevation, as well as with the first axis of the principal components analysis ( PCA 1) of abiotic variables. The CWM s of leaf dry matter content and maximum height did not show significant change with elevational change, but the CWM of maximum height increased with PCA 1. Both FR ic and FD is became less divergent and more convergent with increasing elevation and with PCA 1, which differed from the predicted outcome under the null model. Conclusions All these observations support that environmental filtering selects species with either acquisitive or conservative strategies at low elevations, but it only selects species with conservative strategies at high elevations. The presence of different stressors, resources (water) and non‐resources (temperature and pH ) leads to distinct community assemblages with different functional structures.