Data from: Elevational range sizes of woody plants increase with climate variability in the Tropical Andes
Data files
Dec 28, 2023 version files 635.16 KB
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FUN_null.elev.ranges_2023-02-10.R
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README.md
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SM_Dataset1_SiteData.csv
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SM_Dataset2_SpeciesData.csv
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SM_Dataset3_RegionalPhylogeny_PhyloMaker_OptionS1.tre
Abstract
Aim: The climate variability hypothesis proposes that species subjected to wide variation in climatic conditions will evolve wider niches, resulting in larger distributions. We test this hypothesis in tropical plants across a broad elevational gradient; specifically, we use a species-level approach to evaluate whether elevational range sizes are explained by the levels of thermal variability experienced by species.
Location: Central Andes
Time period: Present day
Taxon: Woody plants
Methods: Combining data from 479 forest plots, we determined the elevational distributions of nearly 2300 species along an elevational gradient (~209 – 3800 m). For each species, we calculated the maximum annual variation in temperature experienced across its elevational distribution. We used phylogenetic generalized least square models to evaluate the effect of thermal variability on range size. Our models included additional covariates that might affect range size: body size, local abundance, mean temperature and total precipitation. We also considered interactions between thermal variability and mean temperature or precipitation. To account for geometric constraints, we repeated our analyses with a standardized measure of range size, calculated by comparing observed range sizes with values obtained from a null model.
Results: Our results supported the main prediction of the climate variability hypothesis. Thermal variability had a strong positive effect on the range size, with species exposed to higher thermal variability having broader elevational distributions. Body size and local abundance also had positive, yet weak effects, on elevational range size. Furthermore, there was a strong positive interaction between thermal variability and mean annual temperature.
Main conclusions: Thermal variability had an overriding importance in driving elevational range sizes of woody plants in the Central Andes. Moreover, the relationship between thermal variability and range size might be even stronger in warmer regions, underlining the potential vulnerability of tropical montane floras to the effects of global warming.
README: Elevational range sizes of woody plants increase with climate variability in the Tropical Andes
Description of the data and file structure
Overall description of the four files included:
(1) SM_DataSet1_sitedata.csv = Contains per plot data, including species richness, location and survey date and all climatic variables.
(2) SM_DataSet2_speciesdata.csv = Contains per species data, including taxonomic information, size, local abundance, occupancy and all climatic variables used for analyses.
(3) SM_Dataset3_RegionalPhylogeny_Phylomaker_OptionS1.tre = Contains the phylogenetic tree used in our analyses.
(4) FUN_Null.elev.ranges_2023-02-10.R = R Script with the null model used to account for geometric constraints in the estimation of range size of woody plants.
Detailed description of each dataset:
1) SM_DataSet1_sitedata.csv
COLUMN DETAILS
site.name = Code name of plot |
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data.owner = Leading researcher in field data collection in a specific field trip |
contact.info = email to contact data owner |
plot.type = two categories: PP (large plots), PT (small plots) |
area = area of each plot |
n.of.trees = Number of trees in the plot |
richness = Number of species in the plot |
inventory.date = Date of field survey, format mm/dd/yyyy |
longitude = Longitude in degrees |
latitude = Latitude in degrees |
elevation = mean elevation of the plot, in meters a.s.l. |
mat = Mean annual temperature, extracted from WorldClim 2.1 (at ~1km resolution) |
tap = Total Annual Precipitation, extracted from TRMM 2b31-Based Rainfall Climatology Version 1.0 (at ~1km resolution) |
dtr = Diurnal Temperature range. |
ATR = Annual Temperature Range. |
(2) SM_DataSet2_speciesdata.csv
COLUMN DETAILS
spcode = Codes use for each species/morphospecies |
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family = Taxonomic family |
genus = generic name (generic epithet) |
species = specific name (specific epithet) |
size.mean = Average size of all surveyed members of the same species across elevations |
size.max = Maximum value of size among the surveyed members of the same species across elevations |
elev.range.size = Raw elevational range size, calculated as the maximum elevation - minimum elevation on which the species was detected. Species that were present in only one plot will have a value of 0 in this column. |
elev.min = Minimum elevation where the species was detected. |
elev.midpoint = Mid point of the elevational range of the species. |
elev.weighted.mean = Average value of all elevations where the species was detected, weighted by local abundance. |
elev.max = Maximum elevation where the species was detected. |
mat.max = Maximum of mean annual temperature, across all plots where the species was detected. |
mat.weighted.mean = Average value of mean annual temperature, across all plots where the species was detected, weighted by local abundance. |
tap.max = Maximum value of total annual precipitation, across all plots where the species was detected. |
tap.weighted.mean = Average value of total annual precipitation, across all plots where the species was detected, weighted by local abundance. |
dtr.max = Maximum value of diurnal temperature range, across all plots where the species was detected. |
dtr.weighted.mean = Average value of diurnal temperature range, across all plots where the species was detected, weighted by local abundance. |
ATR.max = Maximum value of annual temperature range, across all plots where the species was detected. |
ATR.weighted.mean = Average value of annual temperature range, across all plots where the species was detected, weighted by local abundance |
abund.max = Maximum value of local abundance, across all plots where the species was detected. |
abund.mean = Average value of local abundance, across all plots where the species was detected. |
occup.n = Number of plots where the species was detected. |
ind.n = Total number of individuals surveyed across plots. |
(3) SM_Dataset3_RegionalPhylogeny_Phylomaker_OptionS1.tre
Type of file = .tre\
Phylogenetic tree including all species used for analyses. The phylogenetic relationships among our species are based on Smith and Brown’s (2018) mega-phylogeny, accessed using the R package V.PhyloMaker (Jin & Qian, 2019). Species that were not found in the base phylogeny were added using taxonomic information at base of the branch of the corresponding genus or family using the “S1” option in V.PhyloMaker.
(4) FUN_Null.elev.ranges_2023-02-10.R
Type of file = R Script
Includes the function to calculate the Standarized Effect Sizes of Elevational Ranges (SES Elevational range) used to control for geometric constraints in our analyses. Use files SM_DataSet1_sitedata.csv as site.data and SM_DataSet2_speciesdata.csv as species data
Methods
Species elevational distributions were determined based on a large network of forest plots distributed along the eastern slopes of the Bolivian Andes. The network consists of 48 1-ha plots (henceforth large plots) and 458 0.1-ha plots (small plots) ranging in elevation from 209 m (Amazon forests) to 4,347 m (tree line). Within plots, all individuals of woody plant species with diameters at breast height (dbh) equal or above 10 cm (for large plots) or 2.5 cm (for small plots) were measured and identified. Each individual tree was assigned a species or morphospecies name (henceforth simply species), and extensive taxonomic work was conducted to ensure that names were applied consistently throughout all plots.