DOI: 10.5061/dryad.xsj3tx9n7
title: Functional traits and drought strategy predict leaf thermal tolerance

description: Heat stress imposes an important physiological constraint on native plant
 species – one that will only worsen with human-caused climate change.
 Indeed, rising temperatures have already contributed to large-scale plant
 mortality events across the globe. These impacts may be especially severe
 in cities, where the urban heat island effect amplifies climate warming.
 Understanding how plant species will respond physiologically to rising
 temperatures and how these responses differ among plant functional groups
 is critical for predicting future biodiversity scenarios and making
 informed land management decisions. In this study, we evaluated the
 effects of elevated temperatures on a functionally and taxonomically
 diverse group of woody native plant species in a restored urban nature
 preserve in southern California using measurements of chlorophyll
 fluorescence as an indicator of leaf thermotolerance. Our aim was to
 determine if species’ traits and drought strategies could serve as useful
 predictors of thermotolerance. We found that leaf thermotolerance differed
 among species with contrasting drought strategies, and several leaf-level
 functional traits were significant predictors of thermotolerance
 thresholds. Drought deciduous species with high specific leaf area, high
 rates of transpiration, and low water-use efficiency were the most
 susceptible to heat damage, while evergreen species with sclerophyllous
 leaves, high relative water content, and high water-use efficiency
 maintained photosynthetic function at higher temperatures. While these
 native shrubs and trees are physiologically equipped to withstand
 relatively high temperatures in this Mediterranean-type climate, hotter
 conditions imposed by climate change and urbanization may exceed the
 tolerance thresholds of many species. We show that leaf functional traits
 and plant drought strategies may serve as useful indicators of species’
 vulnerabilities to climate change, and this information can be used to
 guide restoration and conservation in a warmer world.
description: In this study, we evaluated the effects of elevated temperatures
 on a functionally and taxonomically diverse group of woody native plant
 species in a restored urban nature preserve in southern California using
 measurements of chlorophyll fluorescence as an indicator of leaf
 thermotolerance. Our aim was to determine if species’ traits and drought
 strategies could serve as useful predictors of thermotolerance.
description: # Functional traits and drought strategy predict leaf thermal tolerance
 [https://doi.org/10.5061/dryad.xsj3tx9n7](https://doi.org/10.5061/dryad.xsj3tx9n7) Data include leaf functional trait values and thermotolerance thresholds for nine native woody plant species from southern California. Aslo included in climate data for the study site. ## Description of the data and file structure Data are included in separate .csv files for (1) climate data for the study site; (2) chlorophyll fluorescence data; and (3) leaf functional trait data. Files, explanation, abbreviations, and units: * **annual\_temps.csv**: annual mean (tmean), minimum (tmin), and maximum (tmax) temperatures (degrees C) for the study site from 1895 to 2022 * **annual\_temp\_anomalies.csv**: annual temperature anomalies (deviation from average temperatures in degrees C) from 1895 to 2022 * **daily\_climate\_data.csv**: daily climate data from 1981 to 2022, including precipitation (ppt; mm) and daily mean (tmean), minimum (tmin), and maximum (tmax) temperatures (degrees C) for the study site * **monthly\_temps.csv**: monthly mean (tmean), minimum (tmin), and maximum (tmax) temperatures (degrees C) for the study site from 1895 to 2022 * **monthly\_averages.csv**: average (30 year normals) monthly climate variables for the study site including precipitation (ppt) and daily mean (tmean), minimum (tmin), and maximum (tmax) temperatures * **FVFM\_data.csv**: chlorophyll fluorescence data (Fv/Fm values) for nine native plant species measured on plants exposed to different heat treatments (Temp; degrees C). Species codes are the first letter of genus and species (full species names are shown in the 'study\_species.csv' file. Drought strategy is also indicated (D = drought deciduous; E = evergreen) * **leaf\_trait\_data.csv**: leaf functional trait values for the nine study species including leaf thickness (Thick; mm), specific leaf area (SLA; leaf area per leaf mass), relative water content (RWC; %), leaf water content (LWC; %) and equivalent water thickness (EWT). Species codes are the first letter of genus and species (full species names are shown in the 'study\_species.csv' file. Drought strategy is also indicated (D = drought deciduous; E = evergreen) * **gas\_exchange\_data.csv**: gas exchange data for each of the nine study species, including photosynthetic rate (Amax), stomatal conductance (gs), transpiration (E), and instantaneous water-use efficiency (WUE). Species codes are the first letter of genus and species (full species names are shown in the 'study\_species.csv' file. Drought strategy is also indicated (D = drought deciduous; E = evergreen) * **study\_species.csv**: scientific names (genus and species) of the nine study species, species codes (used in other files), and drought strategy (D = drought deciduous; E = evergreen) ## Sharing/Access information This is a section for linking to other ways to access the data, and for linking to sources the data is derived from, if any. Links to other publicly accessible locations of the data: * [http://...](http://...) Data was derived from the following sources: * ## Code/Software This is an optional, freeform section for describing any code in your submission and the software used to run it. Describe any scripts, code, or notebooks (e.g., R, Python, Mathematica, MatLab) as well as the software versions (including loaded packages) that you used to run those files. If your repository contains more than one file whose relationship to other scripts is not obvious, provide information about the workflow that you used to run those scripts and notebooks.