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Functional biogeography of Neotropical moist forests: trait-climate relationships and assembly patterns of tree communities
datasetposted on 2022-06-10, 02:46 authored by Bruno Pinho, Marcelo Tabarelli, Cajo ter Braak, S. J. Wright, Victor Arroyo-Rodriguez, Maíra Benchimol, Bettina Engelbrecht, Simon Pierce, Peter Hietz, Bráulio Santos, Carlos Peres, Sandra Müller, Ian Wright, Frans Bongers, Madelon Lohbeck, Ülo Niinemets, Martijn Slot, Steven Jansen, Davi Jamelli, Renato Augusto Ferreira de Lima, Nathan Swenson, Richard Condit, Jos Barlow, Ferry Slik, Manuel Hernández-Ruedas, Gabriel Mendes, Miguel Martinez-Ramos, Nigel C. A. Pitman, Nathan Kraft, Nancy Garwood, Juan Andino, Deborah Faria, Eduardo Chacon, Eduardo Mariano-Neto, Valdecir Junior, Jens Kattge, Felipe Melo
Aim: Here we examine the functional profile of regional tree species pools across the latitudinal distribution of Neotropical moist forests, and test trait-climate relationships among local communities. We expected opportunistic strategies (acquisitive traits, small seeds) to be overrepresented in species pools further from the equator due to long-term instability, but also in terms of abundance in local communities in currently wetter, warmer and more seasonal climates. Location: Neotropics. Time period: Recent. Major taxa studied: Trees. Methods: We obtained abundance data from 471 plots across nine Neotropical regions, including ~100,000 trees of 3,417 species, in addition to six functional traits. We compared occurrence-based trait distributions among regional species pools, and evaluated single trait-climate relationships across local communities using community abundance-weighted means (CWM). Multivariate trait-climate relationships were assessed by a double-constrained correspondence analysis that tests both how CWMs relate to climate and how species distributions, parameterized by niche centroids in climate space, relate to their traits. Results: Regional species pools were undistinguished in functional terms, but opportunistic strategies dominated local communities further from the equator, particularly in the northern hemisphere. Climate explained up to 57% of the variation in CWM traits, with increasing prevalence of lower-statured, light-wooded and softer-leaved species bearing smaller seeds in more seasonal, wetter and warmer climates. Species distribution were significantly but weakly related to functional traits. Main conclusions: Neotropical moist forest regions share similar sets of functional strategies, from which local assembly processes, driven by current climatic conditions, select for species with different functional strategies. We can thus expect functional responses to climate change driven by changes in relative abundances of species already present regionally. Particularly, equatorial forests holding the most conservative traits and large seeds are likely to experience the most severe changes if climate change triggers the proliferation of opportunistic tree species.
MethodsThe data are from 471 forest plots from nine biogeographic regions distributed across the Neotropics, covering the whole latitudinal distribution of Neotropical moist forests. All plots were located in lowland (up to 800 m a.s.l.), old-growth forests within a variable matrix of land uses. The two folders contain data and codes for two specific analyses: (a) [MixedModels_Averaging] test of trait-climate relationships from mixed-effects models followed by model selection and multimodel averaging (see Table 1 in Pinho et al. 2021) (b) [dcCA_VarPart] variation partitioning of two sets of site predictors (climate and geo) on all CWM traits, based on results from double constrained correspondence analysis (dcCA; see Table 2 in Pinho et al. 2021). More on the dc-CA analysis is available at https://doi.org/10.6084/m9.figshare.13259534.v2 Ad (a). The mixed-models are based on the plot-level data, including community abundance-weighted mean (CWM) traits, geographic location and average climate variables (based on monthly average data from 1970 to 2000) for each plot. The climate data were obtained from global maps, such as from WorldClim version 2.0 Ad (b). The variation partitioning using dc-CA is based on spatial clusters (N = 59) of nearby plots, including the abundance per cluster and functional traits of 3,417 tree species. Species traits are averages based on multiple records from multiple data sources. Missing values in the species trait dataset were filled by genus-level or imputed data (see Table S2 in Pinho et al. 2021, for a summary) Information of species abundance by plot (instead of clusters) are partly available from the BIEN database, in addition to private data from the authors that can be requested.
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