DOI: 10.5061/dryad.bnzs7h4qv
title: Leaf, wood and root traits and demographic rates of temperate tree species

description: The interspecific tradeoff between tree growth potential in resource-rich
 environments and survival in resource-poor ones is a central element of
 species’ distributions and forest diversity. Aboveground traits are
 commonly used to understand demographic strategies of tree species,
 but research on root trait relationships with tree growth, and
 especially survival is largely lacking. We compiled a dataset with growth
 and survival data from more than 370,000 trees of 15 temperate species and
 added species-level data on leaf, wood and stem traits obtained from
 existing datasets. As such, this entry consists of three datasets that
 compiled publicly available data. When using these data, please cite the
 original source (i.e., FIA, TRY, FRED databases as explained in the
 Methods of the main article).
description: # Leaf, wood and root traits and demographic rates of temperate tree
 species Dataset DOI:
 [10.5061/dryad.bnzs7h4qv](https://doi.org/10.5061/dryad.bnzs7h4qv) ##
 Description of the data and file structure Trait and demographic (size,
 survival) data were collected for 15 temperate tree species, from
 published, online data sources accessed on May 2015 (demographic data) and
 January 2021 (trait data). * FIA_dat.csv. This file contains a
 geographical (northeastern United states) and species subset (15 temperate
 tree species) of the original FIA dataset (see Methods), in which only
 relevant columns were retained with information on tree species, plot
 locations, state, tree identity code, census year, DBH and survival
 records. Each row (n = 736,087) represents a single census *measurement*
 of DBH and survival status (i.e., dead or alive) of a given tree, from a
 given species, in a given FIA plot, censused approximately every five
 years between 2000 and 2014 during which each tree was sampled 1 – 4
 times. * FIA_spp_traits.csv. This file contains the species mean trait
 data obtained from existing, online dataset (i.e., TRY; FRED; see Methods
 in main article), the leaf habit and mycorrhizal type of each species, as
 well as species’ mean growth (in favorable environments, i.e., AGR~95~)
 and survival (in unfavorable environments, SURV~25~) rates. Each row (n =
 15) represents a single *species*. * FIA_demo.csv. In this file, we
 cleaned the FIA data, and merged it with the species-level trait datasets.
 We calculated the absolute growth rate (AGR) per tree, and added spatial
 variables in order to pool nearby FIA census plots in a single 50 x 50
 grid cell (see Methods in main article). Each row (n = 735,683) represents
 a single census *measurement* of DBH, AGR and survival status (i.e., dead
 or alive) of a given tree, from a given species, in a given FIA plot and
 50 x 50 km grid cell. This dataset was used for our further statistical
 analyses. ### Files and variables #### File: FIA_spp_traits.csv
 **Description:** Trait values per species obtained from previous datasets
 (TRY, FRED, Chave et al. 2009 – see references in Methods of main
 article), and species-averaged growth and survival (i.e., AGR95, SURV25;
 see below). Each row represents a single species. ##### Variables *
 Species: Species (Latin) name * Leaf_habit: Leaf habit per tree with two
 categories: angio, angiosperm; gymno, gymnosperm. * MF: Mycorrhizal fungal
 association per tree with two categories: AM, arbuscular mycorrhizal; EcM,
 ectomycorrhizal. * RD: Root diameter (mm) * RN: Root nitrogen (mg g-1) *
 RTD: Root tissue density (g cm-3) * SRL: Specific root length (m g-1) *
 LN: Leaf nitrogen (mg g-1) * SLA: Specific leaf area (mm2 mg-1) * WD: Wood
 density (g cm-3) * AGR: Absolute growth rate (cm y-1) * SURV: Survival
 status (0 = dead; 1 = alive) * AGR95: Absolute growth rate of the %
 fastest-growing trees per species (cm y-1) * SURV25: Survival probability
 of the 25% slowest-growing trees per species #### File: FIA_dat.csv
 **Description:** Census data from the FIA program measured per tree, per
 census. Each row represents a single census measurement. Trees measured at
 multiple censuses are thus represented in multiple rows (and can be
 identified by the variable ‘ID’, see below). ##### Variables ·        
 Species: Species (Latin) name ·         PLOT: Unique identifier of the FIA
 plot in which a tree was censused ·         SUBP: Unique identifier of the
 FIA sub-plot in which a tree was censused ·         LAT: Latitude degrees
 of the FIA plot center ·         LON: Longitude degrees of the FIA plot
 center ·         STATE: Unique 2-digit code for the state in which a plot
 was located ·         STATEAB: Abbreviated state name ·         TREE: Tree
 number assigned by FIA ·         ID: Unique identifier of each censused
 tree ·         YEAR: Year in which a tree was censused ·         STATUS:
 Tree survival status at census, with 2 categories: 0, dead; 1, alive
 ·         DBH: Diameter at breast height of tree at census (cm) #### File:
 FIA_tree_demo.csv **Description:** This dataset contains the data from
 FIA_dat.csv, to which new variables were added (listed below) related to
 species traits, demographic rates, spatial grid system. Trees that had
 shrunk more 75% in their DBH between censuses were removed. Each row
 represents a single census measurement. Trees measured at multiple
 censuses are thus represented in multiple rows (and can be identified by
 the variable ‘ID’, see below). ##### Variables * Species: Species (Latin)
 name * Leaf_habit: Leaf habit per tree with two categories: angio,
 angiosperm; gymno, gymnosperm. * MF: Mycorrhizal fungal association per
 tree with two categories: AM, arbuscular mycorrhizal; EcM,
 ectomycorrhizal. * RD: Root diameter (mm) * RN: Root nitrogen (mg g-1) *
 RTD: Root tissue density (g cm-3) * SRL: Specific root length (m g-1) *
 LN: Leaf nitrogen (mg g-1) * SLA: Specific leaf area (mm2 mg-1) * WD: Wood
 density (g cm-3) * PLOT: Unique identifier of the FIA plot in which a tree
 was censused * SUBP: Unique identifier of the FIA sub-plot in which a tree
 was censused * LAT: Latitude degrees of the FIA plot center * LON:
 Longitude degrees of the FIA plot center * STATE: Unique 2-digit code for
 the state in which a plot was located * STATEAB: Abbreviated state name *
 TREE: Tree number assigned by FIA * ID: Unique identifier of each censused
 tree * YEAR: Year in which a tree was censused * STATUS: Tree survival
 status at census (0, dead; 1, alive) * DBH: Diameter at breast height of
 tree at census (cm) * location: unique identified or a spatial grid cell
 to which PLOTs were assigned (see Methods in main article) * long2: X
 coordinate of the grid cell (‘location’) * lat2: Y coordinate of the grid
 cell (‘location’) * grain: grain of grid system (here: 50 x 50 km) *
 PYEAR: Previous census year * PDBH: Tree DBH at previous census (cm) *
 AGR: Absolute growth rate of a tree based on difference in DBH between
 current and previous census (cm y-1) * SURV: Survival status (= STATUS) *
 PDBHQ: 0.75 quantile of PDBH used to filter trees that had shrunk more
 than 75% in DBH between censuses #### File: FIA_sub_fast.csv
 **Description:** Subset of FIA_tree_demo.csv in which only the 5%-fastest
 growing trees per species were selected. We added new variables (listed
 below) that were used to run our Trait-Growth models. Each row represents
 a single census measurement. Trees measured at multiple censuses are thus
 represented in multiple rows (and can be identified by the variable ‘ID’,
 see below). ##### Variables * Species: Species (Latin) name * Leaf_habit:
 Leaf habit per tree with two categories: angio, angiosperm; gymno,
 gymnosperm. * MF: Mycorrhizal fungal association per tree with two
 categories: AM, arbuscular mycorrhizal; EcM, ectomycorrhizal. * RD:
 Species root diameter (mm) * RN: Species root nitrogen concentration (mg
 g-1) * RTD: Species root tissue density (g cm-3) * SRL: Species specific
 root length (m g-1) * LN: Species leaf nitrogen concentration (mg g-1) *
 SLA: Species specific leaf area (mm2 mg-1) * WD: Species wood density (g
 cm-3) * PLOT: Unique identifier of the FIA plot in which a tree was
 censused * SUBP: Unique identifier of the FIA sub-plot in which a tree was
 censused * LAT: Latitude degrees of the FIA plot center * LON: Longitude
 degrees of the FIA plot center * STATE: Unique 2-digit code for the state
 in which a plot was located * STATEAB: Abbreviated state name * TREE: Tree
 number assigned by FIA * ID: Unique identifier of each censused tree *
 YEAR: Year in which a tree was censused * STATUS: Tree survival status at
 census (0, dead; 1, alive) * DBH: Diameter at breast height of tree at
 census (cm) * location: unique identified or a spatial grid cell to which
 PLOTs were assigned * long2: X coordinate of the grid cell (‘location’) *
 lat2: Y coordinate of the grid cell (‘location’) * grain: grain of grid
 system * PYEAR: Previous year at which a tree was censuses * PDBH: Tree
 DBH at previous census (cm) * AGR95: Absolute growth rate of a tree
 between current and previous census for only the 5%-fastest growing trees
 per species (cm y-1). * SURV: Survival status (= STATUS) * PDBHQ: 0.75
 quantile of PDBH used to filter trees that had shrunk more than 75% in DBH
 between censuses (cm) * logAGR95: Log-transformed AGR (see above) per
 tree. * logAGR95.sc: Scaled and log-transformed AGR (see above) per tree.
 * logDBH.sc: Scaled and log-transformed DBH (see above) per tree. * RD.sc:
 Scaled species root diameter * RN.sc: Scaled species root nitrogen
 concentration * SRL.sc: Scaled species specific root length * LN.sc:
 Scaled species leaf nitrogen concentration * SLA.sc: Scaled species
 specific leaf area * WD.sc: Scaled species wood density * RTD.sc: Scaled
 species root tissue density 
 
 #### File: FIA_sub_slow.csv **Description:** Subset of FIA_tree_demo.csv
 in which only the 25%-slowest growing trees per species were selected. We
 added new variables (listed below) that were used to run our
 Trait-Survival models. Each row represents a single census measurement.
 Trees measured at multiple censuses are thus represented in multiple rows
 (and can be identified by the variable ‘ID’, see below). ##### Variables *
 Species: Species (Latin) name * Leaf_habit: Leaf habit per tree with two
 categories: angio, angiosperm; gymno, gymnosperm. * MF: Mycorrhizal fungal
 association per tree with two categories: AM, arbuscular mycorrhizal; EcM,
 ectomycorrhizal. * RD: Species root diameter * RN: Species root nitrogen
 concentration * RTD: Species root tissue density * SRL: Species specific
 root length * LN: Species leaf nitrogen concentration * SLA: Species
 specific leaf area * WD: Species wood density * PLOT: Unique identifier of
 the FIA plot in which a tree was censused * SUBP: Unique identifier of the
 FIA sub-plot in which a tree was censused * LAT: Latitude degrees of the
 FIA plot center * LON: Longitude degrees of the FIA plot center * STATE:
 Unique 2-digit code for the state in which a plot was located * STATEAB:
 Abbreviated state name * TREE: Tree number assigned by FIA * ID: Unique
 identifier of each censused tree * census1: Previous census year (= YEAR
 in FIA_tree_demo.csv) * STATUS: Tree survival status at census (0, dead;
 1, alive) * DBH1: Diameter at breast height of tree at previous census
 (i.e. ‘census1’) * location: unique identified or a spatial grid cell to
 which PLOTs were assigned * long2: X coordinate of the grid cell
 (‘location’) * lat2: Y coordinate of the grid cell (‘location’) * grain:
 grain of grid system * PYEAR: Previous year at which a tree was censuses *
 PDBH: Tree DBH at previous census (cm) * AGR: Absolute growth rate of a
 tree (cm y-1) * PDBHQ: 0.75 quantile of PDBH used to filter trees that had
 shrunk more than 75% in DBH between censuses * RD.sc: Scaled species root
 diameter * RN.sc: Scaled species root nitrogen concentration * SRL.sc:
 Scaled species specific root length * LN.sc: Scaled species leaf nitrogen
 concentration * SLA.sc: Scaled species specific leaf area * WD.sc: Scaled
 species wood density * RTD.sc: Scaled species root tissue density *
 census2: Current census year * DBH2: DBH (see above) at ‘census2’ * surv:
 Survival status at current census (‘census2’) * time: Number of years
 between censuses (‘census1’ and ‘census2’) * d.DBH: Difference between
 current and previous DBH (‘DBH1’ and ‘DBH2’) * d.surv: Difference in
 survival status * logDBH1.sc: Scaled and log-transformed ‘DBH1’ *
 logDBH2.sc: Scaled and log-transformed ‘DBH2’ * DBH1.sc: Scaled ‘DBH1’ ##
 Code/software **Open software used:** Data were cleaned, calculated and
 analysed ysing R Statistical Software (R Core Team. (2024). R: A Language
 and Environment for Statistical Computing; version 4.4.2). The Directed
 Acyclic Diagram (DAG) was constructed in *DAGitty* open software (Textor
 *et al.* 2016). **Pcakages used:** tidyverse, brms, tidybayes, loo, Hmisc,
 ggridges, ggplot2, gridExtra, modelr, rstan, ggpubr, dplyr, dagitty,
 lavaan, data.table, lubridate, sf, rFIA, rnaturalearth, rnaturalearthdata
 **Workflow:** * FIA_dat.csv is the original but cleaned data from the FIA
 program, obtained at: XXX * FIA_tree_demo.csv is a cleaned subset of
 FIA_dat.csv with added calculated variables, incorporates
 FIA_spp_traits.csv for each individual tree measurement. *
 FIA_spp_traits.csv contains trait data from aforementioned existing
 datasets, and (demographic) variables calculated from FIA_tree_demo.csv,
 i.e., AGR and SURV averaged per species. * FIA_sub_fast.csv and
 FIA_sub_slow.csv are subsets of FIA_tree_demo.csv with the 95%
 fastest-growing trees per species, and the 25% slowest-growing trees per
 species, respectively, and additional variables for running our
 statistical models. **Code**: *Weemstra_et_al_RCode.R* includes code for:
 * Data cleaning, calculations, subsetting and merging of species- and
 individual level trait and demographic datasets. * Defining functions *
 Testing DAG-data consistency * Running statistical tests, i.e.: * pairwise
 and multivariate correlations * linear regression models * t tests *
 Bayesian demographic models - Produce the figures in the main article. ##
 Access information Other publicly accessible locations of the data: * N/A
 Data was derived from the following sources: * Tree demographic data (DBH,
 survival) from the USDA Forest Inventory and Analysis (FIA) program: U.S.
 Department of Agriculture. Forest Service, “Forest Inventory Analysis”,
 [https://research.fs.usda.gov/programs/fia](https://research.fs.usda.gov/programs/fia) Leaf trait data from the TRY Plant Trait Database: [https://www.try-db.org/TryWeb/Home.php](https://www.try-db.org/TryWeb/Home.php). Kattge J, Bönisch G, Díaz S, et al. TRY plant trait database – enhanced coverage and open access. Glob Change Biol. 2020; 26: 119–188. [https://doi.org/10.1111/gcb.14904](https://doi.org/10.1111/gcb.14904)  * Root trait data from the Fine-root Ecological Database (FRED): [https://roots.ornl.gov/](https://roots.ornl.gov/). Iversen CM, et al. 2021. Fine-Root Ecology Database (FRED): A Global Collection of Root Trait Data with Coincident Site, Vegetation, Edaphic, and Climatic Data, Version 3. Oak Ridge National Laboratory, TES SFA, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A. Access on-line at: [https://doi.org/10.25581/ornlsfa.014/1459186](https://doi.org/10.25581/ornlsfa.014/1459186). * Wood trait data from: Chave, J., Coomes, D., Jansen, S., Lewis, S.L., Swenson, N.G. & Zanne, A.E. (2009). Towards a worldwide wood economics spectrum. *Ecology Letters*, 12, 351–366. [https://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2009.01285.x](https://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2009.01285.x)