Species intraspecific variation drives tropical forest drought resistance
Data files
Aug 10, 2026 version files 112.79 KB
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BayesianModels.R
56.07 KB
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PueroRicoHydraulicTraitData.csv
38.24 KB
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README.md
3.24 KB
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SiteLevelLinearModels.R
12.94 KB
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SpeciesLevelMixedModels.R
2.30 KB
Abstract
Severe droughts are increasingly driving tree mortality, yet predicting forest resilience remains limited by lack of understanding of within-species variation in drought resistance. Although hydraulic traits such as embolism resistance are central to drought survival, studies conducted primarily in temperate regions have reported little intraspecific variation, implying evolutionary constraints in tree species’ adaptive potential. Here, we test this assumption using an unprecedented dataset comprising eleven hydraulic traits for 290 trees representing 18 species collected along Puerto Rico’s fourfold rainfall gradient (1,000 to 4,000 mm/yr). We find that substantial intraspecific variation, together with species turnover, drives coordinated shifts in drought resistance across the gradient. Most species exhibit significantly more embolism resistance and wider stomatal safety margins in drier forests, demonstrating a previously unrecognized level of phenotypic flexibility in tropical trees and an overlooked mechanism for adaptation to increasingly dry conditions. Species lacking such trait variability may be highly vulnerable under a future drier climate. Incorporating both inter- and intraspecific trait variation into predictive models will advance our ability to forecast forest resilience to intensifying droughts.
Dataset DOI: 10.5061/dryad.r4xgxd2vb
Description of the data and file structure
We measured leaf and stem pressure-volume curves using the bench dry method and leaf and stem embolism vulnerability curves using the optical vulnerability technique.
Files and variables
File: PueroRicoHydraulicTraitData.csv
Description: Hydraulic trait data
Variables
- Site: Sites where the measurements were conducted.
- Prism MAP (mm): from Parameter-elevation Regressions on Independent Slopes Model (PRISM Climate Group, Oregon State University, https://prism.oregonstate.edu, accessed 25 April 2023).
- Geology: primary soil types are derived from limestone and volcanic parent materials
- Code: measured tree species code
- Genus: genus of measured tree
- Species: measured tree species
- Family: measured tree families
- Phenology: leaf phenology (evergreen or drought deciduous)
- LeafSWC (gg-1): leaf saturated water content
- LeafTLP (Mpa): leaf turgor loss point
- LeafCFT (MPa-1): leaf capacitance at full turgor
- LeafCTLP (MPa-1): leaf capacitance at turgor loss point
- P50 leaf(Mpa): water potential at which 50% of the cumulative embolism had occurred in leaves
- P50 stem (Mpa): water potential at which 50% of the cumulative embolism had occurred in stems
- SMP50 leaf (Mpa): leaf stomatal safety margins calculated as LeafTLP - P50 leaf
- SMP50 stem (Mpa): stem stomatal safety margins calculated as LeafTLP - P50 stem
- StemSWC (gg-1): stem saturated water content
- StemCFT (MPa-1): stem capacitance at full turgor
- StemCTLP (MPa-1): stem capacitance at turgor loss point
NA: not available
File: BayesianModels.R
Description: R code for Bayesian hierarchical models (one for each hydraulic trait) using the brms package
File: SiteLevelLinearModels.R
Description: R code for the site-level linear models
File: SpeciesLevelMixedModels.R
Description: R code for the species-level mixed models
Code/software
R statistical software (Version R 4.4.2)
Used packages:
llme41
lmerTest2
brms3
insight4
References:
- Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software 67, 1 - 48 (2015). https://doi.org/10.18637/jss.v067.i01
- Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest Package: Tests in Linear Mixed Effects Models. Journal of Statistical Software 82, 1 - 26 (2017). https://doi.org/10.18637/jss.v082.i13
- Bürkner, P.-C. brms: An R Package for Bayesian Multilevel Models Using Stan. Journal of Statistical Software 80, 1 - 28 (2017). https://doi.org/10.18637/jss.v080.i01
- Lüdecke, D., Waggoner, P. & Makowski, D. insight: A Unified Interface to Access Information from Model Objects in R. Journal of Open Source Software 4, 1412 (2019). https://doi.org/10.21105/joss.01412
