Leaf habit affects the distribution of drought sensitivity but not water transport efficiency in the tropics
Data files
Nov 20, 2023 version files 1.35 MB
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rainfall_niches_15_nin.csv
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README_VargasGetal2022
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README.md
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trait_data.csv
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Tree1084.tre
Abstract
Considering the global intensification of aridity in tropical biomes due to climate change, we need to understand what shapes the distribution of drought sensitivity in tropical plants. We conducted a pantropical data synthesis representing 1117 species to test whether xylem-specific hydraulic conductivity (KS), water potential at leaf turgor loss (ΨTLP), and water potential at 50% loss of KS (ΨP50) varied along climate gradients. The ΨTLP and ΨP50 increased with climatic moisture only for evergreen species, but KS did not. Species with high ΨTLP and ΨP50 values were associated with both dry and wet environments. However, drought-deciduous species showed high ΨTLP and ΨP50 values regardless of water availability whereas evergreen species only in wet environments. All three traits showed a weak phylogenetic signal and a short half-life. These results suggest that environmental controls on trait variance, which in turn is modulated by leaf habit along climatic moisture gradients in the tropics.
README: Leaf habit affects the distribution of drought sensitivity but not water transport efficiency in the tropics
https://doi.org/10.5061/dryad.1ns1rn8x4
This repository contains the data and associated Rstudio project to perform the analyses associated with the study: Vargas G., G., Kunert N., Hammond W.H., Berry Z.C., Werden L.K., Smith-Martin C.M., Wolfe B.T., Toro L., Mondragón-Botero A., Pinto-Ledezma J.N., Schwartz N.B., Uriarte M., Sack L., Anderson-Texeira K.J., & Powers J.S. 2022. Leaf habit affects the distribution of drought sensitivity but not water transport efficiency in the tropics. Ecology Letters, Volume25, Issue12, December 2022, Pages 2637-2650.
Description of the data and file structure
Data files used in the manuscript, and their descriptions:
- rainfall_niches_15_nin.csv: Climatic affiliation data obtained from species occurrence records. Each column is described below.
Column name | Description |
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scrubbed_species_binomial | Species name. |
n | Number of occurrence records. |
mar_med | Median annual rainfall (mm) across the geographical extent of the occurrence records. |
mar_min | Minimum annual rainfall (mm) across the geographical extent of the occurrence records. |
mar_max | Maximum annual rainfall (mm) across the geographical extent of the occurrence records. |
mar_90 | 90th percentile annual rainfall (mm) across the geographical extent of the occurrence records. |
mar_10 | 10th percentile annual rainfall (mm) across the geographical extent of the occurrence records. |
mar_iqr | Interquartile range from the annual rainfall (mm) across the geographical extent of the occurrence records. |
sea_med | Median seasonality index across the geographical extent of the occurrence records. |
sea_max | Maximum seasonality index across the geographical extent of the occurrence records. |
sea_min | Minimum seasonality index across the geographical extent of the occurrence records. |
sea_90 | 90th percentile seasonality index across the geographical extent of the occurrence records. |
sea_10 | 10th percentile seasonality index across the geographical extent of the occurrence records. |
sea_iqr | Interquartile range from seasonality index across the geographical extent of the occurrence records. |
mcw_med | Median maximum climatic water deficit across the geographical extent of the occurrence records. |
mcw_max | Maximum maximum climatic water deficit across the geographical extent of the occurrence records. |
mcw_min | Minimum maximum climatic water deficit across the geographical extent of the occurrence records. |
mcw_90 | 90th percentile maximum climatic water deficit across the geographical extent of the occurrence records. |
mcw_10 | 10th percentile maximum climatic water deficit across the geographical extent of the occurrence records. |
mcw_iqr | Interquartile range from maximum climatic water deficit across the geographical extent of the occurrence records. |
dsl_med | Median dry season length across the geographical extent of the occurrence records. |
dsl_max | Maximum dry season length across the geographical extent of the occurrence records. |
dsl_min | Minimum dry season length across the geographical extent of the occurrence records. |
dsl_90 | 90th percentile dry season length across the geographical extent of the occurrence records. |
dsl_10 | 10th percentile dry season length across the geographical extent of the occurrence records. |
dsl_iqr | Interquartile range from the dry season length across the geographical extent of the occurrence records. |
ai_med | median aridity index across the geographical extent of the occurrence records. |
ai_min | minimum aridity index across the geographical extent of the occurrence records. |
ai_max | maximum aridity index across the geographical extent of the occurrence records. |
ai_90 | 90th percentile aridity index across the geographical extent of the occurrence records. |
ai_10 | 10th percentile aridity index across the geographical extent of the occurrence records. |
ai_igr | Interquartile range from aridity index across the geographical extent of the occurrence records. |
- trait_data.csv: Trait database compiled for the present study. NA values represent empty cells whenever for a given observation information on any given variable (column) was not available.
Column name | Description |
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XFT_uniqueID | Xylem functional trait database unique ID. (https://xylemfunctionaltraits.org/). |
old_XFT_uniqueID | Previous compilation of the xylem functional trait database unique ID. |
obs_id | Observation ID in the present database. |
Lat | Latitude coordinates in decimal degrees of each observation. |
Long | Longitude coordinates in decimal degrees of each observation. |
BIOME_NAME | Biome name associated to each observation. |
REALM | Biological realm name associated with each trait observatio. |
ECO_NAME | Ecoregion name associated with each trait observation. |
Country | Country in which each trait observation was collected. |
Location | Location in the country for each trait observation. |
Sampling_season | Whether traits were sampled in the rainy or dry season as reported by the source article. |
Sampling_month | Month in which traits were collected as reported by the original source. |
Ks_method_dif | Hydraulic conductivity method as reported by the original source. CAV (cavitron), FLM (flushed accounting for maximum vessel length), FLM_short (flushed not accounting for maximum vessel length), FLM_short_roots (Flushed not accounting for maximum vessel length in roots, NM (native accounting for maximum vessel length), NM_roots (native accounting for maximum vessel length in roots), NM_short (native conductivity not accounting for maximum vessel length). |
TLP_method | Turgor loss point method as reported by the original source. PVC (pressure-volume curve), OSM (osmometer method). |
P50_method | Xylem vulnerability to embolism method as reported by the original source in the same coding as the xylem functional trait database (https://xylemfunctionaltraits.org/), where: DH (bench dehydration), CE (Centrifuge), CA (Cavitron), AD (air-injection double end), AS (air-injection single end), AE (acoustic emissions), OV (optical vulnerability), Pn (pneumatic method) |
Treatment | Treatment during data collection if any as reported in the original source. |
Family | Taxonomic family. |
Accepted.Family | Accepted family as of June 2022. |
Binomial | Species name as reported by the original source. |
corrected_genus | Accepted species genus as of June 2022. |
corrected_sp | Accepted species epithet as of June 2022. |
Species | Accepted species binomial name as of June 2022. |
sp_code | Six letter species code. |
Accepted_author | Accepted species name authorship as of June 2022. |
plant_organ_ks | Organ in which hydraulic conductivity measurements were done. Where: L (leaves), P (petiole), R (root), S (stems). |
plant_organ_p50 | Organ in which xylem vulnerability measurements were done. Where: L (leaves), P (petiole), R (root), S (stems). |
growth_form | Type of plant growth form. |
Resource_growthform | Reference for growth form if it was not specified in the original source. |
leaf_habit_1 | Leaf habit as reported in the original source. |
leaf_habit | Leaf habit as evergreen , deciduous, or not reported (this study). |
is_drought | If leaf habit reported by the original source is related to water availability in the dry season. Where, Y (yes) and N (no). |
Resource_leafhabit | Reference for leaf habit if it was not specified in the original source. |
Ks | xylem specific hydraulic conductivity (kg m-1 s-1 MPa-1). |
TLP_MPa | Leaf water potential at turgor loss point (MPa). |
P50_MPa | The water potential at which 50 % loss of conductivity or accumulation of embolisms (MPa). |
WD_gcm3 | Wood density (g cm-3). |
SLA_g.1cm2 | Specific leaf area (cm2 g-1). |
short_reference | Original source of the data if any. |
DOI | Digital object identifier of original source if any. |
Contributor | Name of participant who contributed the data. |
evapot | Observation locality mean annual evapotranspiration (mm). |
pet | Observation locality mean annual potential evapotranspiration (mm). |
alpha | Observation locality precipitation alpha. |
MAR | Observation locality mean annual rainfall (mm). |
S | Observation locality seasonality index. |
MCWD | Observation locality maximum climatic water deficit (mm). |
DSL | Observation locality dry season length (months). |
- Tree1084.tre: phylogenetic tree
Alternative access information
The hydraulic trais' data can also be accessed through the xylem functional trait database: https://xylemfunctionaltraits.org/
Code/Software
The compressed folder contains. Compressed file containing the R studio project associated with the analyses in the manuscript with the scripts associated with each statistical procedure in the manuscript:
File name | Description |
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01_data_management.R | Script associated with the preparation of the data for phylogenetic multilevel models (BMLM). |
02_univariate_analyses_all.R | Script to run BMLM for each hydraulic trait as a function of each climatic predictor. |
03_univariate_analyses_stem.R | Script to run BMLM for hydraulic conductivity and xylem vulnerability to embolism as a function of each climatic predictor using data from observations made in stems only. |
04_multivariate_analyses.R | Script to run BMLM for each hydraulic trait as a function of aridity and seasonality, this also includes the code to run each model with observations made on stems only. |
05_phylogenetic_signal.R | Script to obtain the phylogenetic signal from the multivariate BMLMs and the calculation of the phylogenetic half-life with the Ornstein-Uhlenbeck models. |
06_quantile_regression.R | Script to run quantile BMLM for each hydraulic trait as a function of each aridity and seasonality, this also includes the code to run each model with observations made on stems only. |
07_sampling_climatic_biases.R | Script to quantify to what extent climatic predictors obtained from trait sampling locations explain variation in species climatic affiliations. |
08_climate_affinities_leaf_habit.R | Script to test whether species for each leaf habit differ in their climatic affiliations. |