DOI: 10.5061/dryad.280gb5n2b
title: Relative tree growth and mortality responses to the 2012 midwestern US drought in the central hardwood ecoregion

description: This dataset contains relative drought-driven tree growth and mortality
 responses derived from the USDA FS Forest Inventory and Analysis dataset
 (Gray et al., 2012) in the North American central hardwood ecoregion (a
 region representing the four US states of Indiana, Illinois, Kentucky, and
 Brandt et al., 2014). Data represents a period of 2000 – 2018 and
 characterizes relative responses to the severe 2012 midwestern drought
 (Mallya et al., 2013) between co-located trees with a diameter at breast
 height greater than 12.7 cm. Analyses were limited to regions of the study
 area that experienced  ‘Severe’ or ‘Extreme’ drought conditions
 from March to October of 2012, as defined by the US drought monitor
 program (Svoboda et al., 2002). Co-located trees were defined as those
 growing within the same discrete 875 km2 hexagonal boundary following a
 tessellation approach by which Forest Inventory and Analysis plots were
 aggregated across 560 uniform hexagons imposed over the study area.
 Relative drought-driven responses were quantified among the following tree
 species: Acer rubrum, Acer saccharum, Carya alba, Carya glabra, Carya
 ovata, Carya texana, Celtis occidentalis, Fagus grandifolia, Juglans
 nigra, Liriodendron tulipifera, Nyssa sylvatica, Pinus echinata, Prunus
 serotina, Quercus alba, Quercus coccinea, Quercus rubra, Quercus stellata,
 Quercus velutina, Sassafras albidum, and Ulmus americana.
description: <strong>Relative growth and relative growth
 sensitivity</strong> To calculate relative growth
 (<em>gr_ij</em>)<em> </em>we first quantified
 species-specific growth in each hexagon as a relative growth rate across
 three successive inventories from 2000 – 2018. The relative growth rate
 equation (<em>RGR_i</em>) was expressed as (Brzostek et al.,
 2014):
 <em>RGR_</em><em>i</em>
 <sub><em> </em></sub>=
 [(<em>BA_i,1</em><sub> </sub>‒
 <em>BA_i,0</em>)/<em>BA_i,0</em>] × 100         
 (Equation 1)    where <em>BA_i,0</em> is
 the species-specific tree basal area at the initial inventory and
 <em>BA_i,1</em> is the species-specific tree basal area at the
 next inventory. Next, the impact of drought on <em>RGR_i</em>
 was characterized as a rate change parameter, <em>ΔRGR_i</em>
 (% growth/year), whereby <em>RGR_i</em> after 2012 was
 subtracted by the <em>RGR_i</em> of the conspecific
 individuals occupying the same hexagon prior to drought disturbance.
 Specifically, <em>ΔRGR_i</em> was quantified as:
 <em>ΔRGR_i = </em>
 <em>RGR_i,post_drought </em> ‒ <em>RGR_i,pre_drought   
  </em>(Equation 2) where
 <em>RGR_i,post_drought</em> is species-specific relative tree
 growth following drought (when <em>BA_i,1</em> was sampled
 during the years 2012−2018; Equation 1) and
 <em>RGR_i,pre_drought</em> is the relative tree growth of the
 same species and locations from two successive inventories during a
 non-droughted period (i.e., when <em>BA_i,1</em> was sampled
 during the years 2000−2011; Equation 1). <em>gr_ij</em> is
 then calculated as the pairwise difference between corrected growth rates
 between species <em>i</em> and <em>j</em>,
 expressed as: <em>gr_ij = </em>
  <em>ΔRGR_i  </em>‒ <em>ΔRGR_j</em>       
  (Equation 3) Relative growth sensitivity (%) was then
 quantified as: <em>Relative growth sensitivity_i
 = </em>[(<em>n_gr_ij&lt;0 </em> ‒
 <em>n_gr_ij&gt;0)/n_tot] </em>× 100     (Equation
 4)    where <em>n_gr_ij&lt;0</em> are
 the number of co-occurring species that experienced lower growth
 reductions and <em>n_gr_ij&gt;0</em> are the number of
 species whose growth was more limited by drought.
 <em>n_gr_ij&lt;0</em> and
 <em>n_gr_ij&gt;0</em> were determined by a one sample
 <em>t</em>-test of the species-specific
 <em>gr_ij</em> comparisons. <em>n_tot</em> is the
 number of species that were able to be compared.
 <strong>Relative mortality and relative mortality
 sensitivity</strong> To calculate relative
 mortality (<em>mr_ij</em>), we first quantified
 species-specific mortality in each hexagon as a stem loss rate
 (<em>m_i</em>) across three successive inventories from 2000 –
 2018 using the following equation (Sheil et al., 1995):
 <em>m_i = </em>[1<em> </em>‒
 <em>(N_i,1</em>/<em>N_i,0</em>)^(<em>1/t</em>)] × 100     (Equation 5)        where <em>N_i,0</em> is the species-specific number of live stems at the initial inventory (at year = <em>t_0</em>) and <em>N_i,1</em> is the species-specific number of live stems at the next inventory (at year = <em>t_1</em>). The variable <em>t</em> (years) is the difference in time between inventory periods, and equal to <em>t_1 – t_0</em>.  Next, we evaluated the impact of drought as a change in stem loss rate (<em>Δm_i</em>) (% stem loss/year), where species-specific <em>m_i</em> after 2012 were subtracted by <em>m_i</em> quantified in the same hexagon during previous non-drought periods. The <em>Δm_i</em> equation took the following form:          <em>Δm_i </em>= <em>m_i,post_drought</em> ‒ <em>m_i,pre_drought     </em>(Equation 6) where <em>m_i,post_drought</em> is a species-specific drought-driven stem loss rates (when <em>N_i,1</em> was sampled during the years 2012−2018; Equation 5) and <em>m_i,pre_drought</em> is the stem loss rate for the same species and locations from two successive inventories during a non-droughted period (when <em>N_i,1</em> was sampled during the years 2000−2011; Equation 5). <em>mr_ij</em> is then calculated as the pairwise difference between corrected stem loss rates between species <em>i</em> and <em>j</em>, expressed as: <em>mr_ij = </em> <em>Δm_i </em>‒ <em>Δm_j     </em>(Equation 7)                Relative mortality sensitivity (%) was then quantified as: <em>Relative mortality sensitivity_i </em>=  [(<em>n_mr_ij&gt;0 </em>‒ <em>n_mr_ij&lt;0</em>)/<em>n_tot</em>] × 100     (Equation 8)    where <em>n_mr_ij&gt;0</em> are the number of co-occurring species that experienced lower drought-driven stem loss change and <em>n_mr_ij&lt;0</em> are the number of species that experienced greater drought-driven stem loss change. <em>n_mr_ij&gt;0</em> and <em>n_mr_ij&lt;0</em> were determined by a one sample <em>t</em>-test of the species-specific <em>mr_ij</em> comparisons. <em>n_tot</em> is the number of species that were able to be compared.
description: # **Relative tree growth and mortality responses to the 2012 midwestern US
 drought in the central hardwood ecoregion.** Dataset DOI:
 [10.5061/dryad.280gb5n2b](10.5061/dryad.280gb5n2b) #### **Description of
 the data and file structure** The files here include: (1) the
 georeferenced coordinate centers of each tessellated hexagon imposed
 across the study area (i.e., HexagonCoordinates.csv), (2) relative growth
 responses during drought (*gr_ij*) between individual species within each
 hexagon (i.e., gr_ij.csv), (3) Relative growth sensitivity values, which
 reflect a synthesized species-level characterization of the percentile
 difference of the number of co-located species which experienced
 relatively larger or smaller drought-driven growth declines (i.e.,
 RelativeGrowthSensitivity.csv), (4) relative mortality responses during
 drought (*mr_ij*) between individual species within each hexagon (i.e.,
 mr_ij.csv), (5) Relative mortality sensitivity values, which reflect a
 synthesized species-level characterization of the percentile difference of
 the number of co-located species which experienced relatively greater or
 lower drought-driven stem loss (i.e., RelativeMortalitySensitivity.csv),
 and (6) MATLAB code used to calculate the relative growth sensitivity and
 relative mortality sensitivity values of each species based on *gr_ij* and
 *mr_ij*, respectively (i.e.,  Calculate_RelativeSensitivity.m). Analyses
 were limited to the 20 most abundant canopy dominant tree species within
 the regional Forest Inventory and Analysis dataset, which were accessed
 at:
 [https://research.fs.usda.gov/products/dataandtools/fia-datamart](https://research.fs.usda.gov/products/dataandtools/fia-datamart). #### **Files and variables** #### **File 1: HexagonCoordinates.csv** This file contains the georeferenced coordinates (in decimal degrees) of the tessellated 560 hexagons imposed across the study area. The unique hexagon ID is denoted in column 1, the latitude of the respective hexagon center is denoted in column 2, and the longitude of the respective hexagon center is denoted in column 3. The data file is in a comma separated value format and requires no specialized software. #### **File 2: gr\_ij.csv** This file contains calculated relative drought-driven growth responses (i.e., *gr_ij; *Equation 3) between species *i* and *j* in each hexagon. Species *i* is denoted in column 1, the discrete hexagon ID where the comparison was quantified is denoted in column 2, and the relative response to species *j* (i.e., one of the other 19 study tree species that species i was compared to) are denoted in columns 3 ‒ 22. *gr_ij* values in hexagons where species *i* and *j* did not coexist in the inventory dataset or did not meet the filtering criteria are denoted as ‘NaN’. The data file is in a comma separated value format and requires no specialized software. #### **File 3: RelativeGrowthSensitivity.csv** This file contains a calculated relative growth sensitivity metric (Equation 4) that is defined at the species-level. Column 1 denotes the species and column 2 denotes the relative growth sensitivity value. Relative growth sensitivity quantifies the percentile difference of the number of species which experienced greater or more reduced relative growth than their neighbors during drought. A positive relative growth sensitivity value indicates growth was more strongly reduced by drought while a negative value indicates greater growth tolerance. The data file is in a comma separated value format and requires no specialized software. #### **File 4: mr\_ij.csv** This file contains calculated relative drought-driven mortality responses (*mr_ij*; Equation 7) between species *i* and *j* in each hexagon. Species *i* is denoted in column 1, the discrete hexagon ID where the comparison was quantified is denoted in column 2, and the relative response to species *j* (i.e., one of the other 19 study tree species that species *i* was compared to) are denoted in columns 3 ‒ 22. *mr_ij* values in hexagons where species *i* and *j* did not coexist in the inventory dataset or did not meet the filtering criteria are denoted as ‘NaN’. The data file is in a comma separated value format and requires no specialized software. #### **File 5: RelativeMortalitySensitivity.csv** This file contains a calculated relative mortality sensitivity metric (Equation 8) that is defined at the species-level. Column 1 denotes the species and column 2 denotes the relative mortality sensitivity value. Relative mortality sensitivity quantifies the percentile difference of the number of species which experienced greater or more reduced stem loss during drought than their neighbors. A positive relative mortality sensitivity value indicates greater mortality than their neighbors during drought while a negative one indicates greater survival. The data file is in a comma separated value format and requires no specialized software. #### **Code/software** **Calculate_RelativeSensitivity.m** is the code used to quantify the species-level relative growth sensitivity and relative mortality sensitivity metrics. gr_ij.csv and mr_ij.csv are the input files and RelativeGrowthSensitivity.csv and RelativeMortalitySensitivity.csv are the output files. The file can be opened and manipulated with various software (i.e., NotePad, NotePad++) but the code is written to be executed in MATLAB version R2023a: [https://www.mathworks.com/products/new_products/release2023a.html](https://www.mathworks.com/products/new_products/release2023a.html). We emphasize that executing this code is not necessary to access the relative drought-driven tree growth and mortality responses quantified in this work as the input and output files are included within this dataset as comma separated value formats and requires no specialized software. #### **Access information** **Data was derived from the following source:** The US Department of Agriculture Forest Service, Forest Inventory and Analysis Database and were accessed at: [https://research.fs.usda.gov/products/dataandtools/fia-datamart](https://research.fs.usda.gov/products/dataandtools/fia-datamart) #### **References** Brandt, L., He, H., Iverson, L., Thompson, F. R., Butler, P., Handler, S., ... & Westin, S. (2014). Central Hardwoods ecosystem vulnerability assessment and synthesis: a report from the Central Hardwoods Climate Change Response Framework project. *Gen. Tech. Rep. NRS-124. Newtown* Brzostek, E. R., Dragoni, D., Schmid, H. P., Rahman, A. F., Sims, D., Wayson, C. A., ... & Phillips, R. P. (2014). Chronic water stress reduces tree growth and the carbon sink of deciduous hardwood forests. Global change biology, 20(8), 2531-2539. Gray, A. N., Brandeis, T. J., Shaw, J. D., McWilliams, W. H., & Miles, P. D. (2012). Forest inventory and analysis database of the United States of America (FIA). Biodiversity and Ecology, 4, 225-231. Mallya, G., Zhao, L., Song, X. C., Niyogi, D., & Govindaraju, R. S. (2013). 2012 Midwest drought in the United States. Journal of Hydrologic Engineering, 18(7), 737-745. Sheil, D., Burslem, D. F., & Alder, D. (1995). The interpretation and misinterpretation of mortality rate measures. Journal of Ecology, 331-333. Svoboda, M., LeComte, D., Hayes, M., Heim, R., Gleason, K., Angel, J., ... & Stephens, S. (2002). The drought monitor. *Bulletin of the American Meteorological Society*, *83*(8), 1181-1190.