Data from: Can faster growth compensate for increased mortality in subtropical dry forest fragments?
Data files
May 02, 2024 version files 398.94 MB
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Alison_wood_density.csv
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Araucaria_4_12.csv
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Derrier_3_8.csv
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Dwyer_5_16.csv
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Fraser_1_1.csv
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Fraser_1_2.csv
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Fraser_1_3.csv
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GlobalWoodDensityDatabase.csv
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Ilic_et_al_wood_density_phase_1.csv
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Imbil_plot_scale_data.csv
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Julian_wood_density.csv
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Mitchell_7_24.csv
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month_vpd_metadata.txt
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month_vpd.nc
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README.md
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species_heights.csv
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species_names.csv
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Western_2_4.csv
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Yabba_6_20.csv
Abstract
Capturing the effects of fragmentation and ongoing changing climate on the population dynamics of long-lived trees requires long-term datasets, but these are uncommon in rainforests and dry forests outside of the tropics. This study capitalised on nine 0.04-ha permanent plots established in 1982 within corridors of old-growth subtropical dry forest (Araucarian vine forest) retained as fire breaks within forestry plantations in Imbil (southern Queensland, Australia). Tree diameter growth and survival were censused in 1997 and 2021, resulting in two monitoring periods.
The most recent period was associated with an increasing trend in vapour-pressure deficit (VPD). Consistent with this trend, we found that survival was substantially lower across all size classes in the second period. Mortality-induced reductions in stem density were associated with faster growth rates in all but the largest stems in the second period. Growth was also moderately faster in plots near forest edges in the second period. The richness of obligate understory species declined significantly by an average of 1.44 species over the 40-year study period.
Synthesis and applications: Overall, our results are consistent with increasing tree mortality rates reported recently for the Australian wet tropics and suggest widespread and alarming impacts of increasing VPD on rainforest and dry forest community dynamics. To increase forest resilience in a changing climate, we recommend the retention of a buffer of plantation trees adjacent to old growth forest corridors; widening the forest corridors using faster-growing species identified in this study and maintaining connections between scrub breaks and larger tracts of forest for species dispersal.
README: Data from: Can faster growth compensate for increased mortality in subtropical dry forest fragments?
Date created: 2 May 2024
Authors: Vanessa Moscato, William J. F. McDonald, Birte Balle-Hosking, and John M. Dwyer
Instructions to run the "Imbil_R_Project_Final" R Project:
Download all data files outlined below and save them in the "Data" subfolder in "Imbil_R_Project_Final". Then open the R Project in RStudio and run "Imbil_analysis_script.R" to reproduce all analyses, figures, and tables.
Data description
"Imbil_plot_scale_data.csv": Plot-scale data for the nine plots
- plot_name: name of plot in the format of original logging area number, plot number, and logging area name.
- plot: name of plot as used in the R script and manuscript. Values include "ARAUCARIA1", "DERRIER1", "DWYER1", "FRASER1", "FRASER2", "FRASER3", "MITCHELL1", "WESTERN1", "YABBA1".
- latitude: latitude (decimal degrees)
- longitude: longitude (decimal degrees)
- width_of_break_m: width of scrub break where plot was located (measured in m using GIS)
- dist_to_edge_m: smallest distance from the plot to the edge of the scrub break (measured in m using GIS)
- altitude_m: altitude (m above sea level)
- slope_deg: slope of the plot in degrees
- aspect: categorical classification of aspect. Values include "North", "South", "West", "Northeast", "Southeast".
"species_height.csv"
- species_code: species codes used in the R script (revised to include occasional corrected identificaitons during the 2021 survey)
- scientific_name: scientific name (not used)
- potential_height: species maximum heights (m) as per Harden, McDonald and Williams (2006)
Harden, McDonald and Williams, 2006. Rainforest trees and shrubs: A field guide to their identification. Casino, Australia: Gwen Harden Publishing.
"species_names.csv"
- species_code: species codes used in the R script (revised to include occasional corrected identifications during the 2021 survey)
- Lf: life form code. 1 = tree, 2 = liana, 3 = understory fern, grass or herb and 4 = epiphyte
- scientific_name: scientific name including var. and subsp.
- scientific_name_simple: scientific name excluding var. and subsp.
- family: taxonomic family
- notes: clarifying comments about species names
"month_vpd.nc": Network Common Data Form (NC) format file including monthly vapour pressure deficit data. Metadata for this specific file are provided in "month_vpd_metadata.txt"
Michael Hutchinson, Tingbao Xu, Jennifer Kesteven, Ian Marang, Bradley Evans. Monthly vapour pressure deficit for the Australian continent from 1960 to present, on the ANUClimate 0.01 x 0.01 degree grid. Date accessed 15/05/2022, DOI: 10.25914/60a10af667bbe
"Araucaria_4_12.csv", "Derrier_3_8.csv", "Dwyer_5_16.csv", "Fraser_1_1.csv", "Fraser_1_2.csv", "Fraser_1_3.csv", "Mitchell_7_24.csv", "Western_2_4.csv", "Yabba_6_20.csv"
Individual-tree-level data from 1982, 1997 and 2021 in each of the nine plots (one csv file per plot, each with identical column headings). The file names follow the format of logging area name_logging area number_plot number (underscores as separators):
In each file the variable names (column headings) are:
- plot: Plot number (as per original plot setup by Bill McDonald and colleagues) (these are changed in the R script to match those in "Imbil_plot_scale_data.csv")
- subplot: 10 x 10 m subplot within the 20 x 20 m plot (1-4)
- tree_no: Original tree numbers ascribed in 1981 and 1997. New trees in 2021 were ascribed a value of "new".
- e_w: Stem mapping coordinate (east-west)
- n_s: Stem mapping coordinate (north-south)
- species_code: Species code based on 1981 and 1997 data
- species_code_1: Revised species codes including occasional corrected identifications during the 2021 survey
- dbh_82: Stem diameter at breast height (DBH; cm) when originally mapped in 1982
- dbh_97: Stem DBH (cm) in 1997
- alive_82_97: Binary variable indicating species that survived from 1982 to 1997 (1) and those that did not (0)
- dbh_21_1: DBH (cm) of single-stemmed individuals in 2021, or DBH of the first measured stem in multi-stemmed individuals in 2021
- dbh_21_2: DBH (cm) of the second measured stem in multi-stemmed individuals in 2021
- dbh_21_3: DBH (cm) of the third measured stem in multi-stemmed individuals in 2021
- dbh_21_4: DBH (cm) of the fourth measured stem in multi-stemmed individuals in 2021
- dbh_21_5: DBH (cm) of the fifth measured stem in multi-stemmed individuals in 2021
- alive_97_21: Binary variable indicating species that survived from 1997 to 2021 (1) and those that did not (0)
- notes_97: Notes regarding the individual in 1997
- notes_21: Notes regarding the individual in 2021
"Alison_wood_density.csv": wood density measurements taken by Alison Brown (reported in Brown et al. 2022)
- abbrev: eight letter species code used by Brown (first four letters of genus and first four letters of species)
- individual_id: individual replicate number per species
- fresh_vol: fresh volume of wood sample determined by water displacement (g)
- dry_mass: dry mass of wood sample (g)
- drying_temp: temperature (deg C) that samples were dried under (used for correction of WD estimates as per Brown et al. 2022)
Brown, A., D. W. Butler, J. Radford-Smith, and J. M. Dwyer. 2022. Changes in trait covariance along an orographic moisture gradient reveal the relative importance of light- and moisture-driven trade-offs in subtropical rainforest communities. New Phytologist 236:839-851.
"Julian_wood_density.csv": wood density measurements taken by Julian Radford-Smith (reported in Radford-Smith et al. 2024)
- abbrev: eight letter species code used by Brown (first four letters of genus and first four letters of species)
- individual: individual replicate number per species
- fresh_vol: fresh volume of wood sample determined by water displacement (g)
- dry_mass: dry mass of wood sample (g)
- drying_temp: temperature (deg C) that samples were dried under (used for correction of WD estimates as per Brown et al. 2022)
Radford-Smith, J., Cathcart-van Weeren, E., Lai, H.R. & Dwyer, J.M. (2023) An ecophysiological basis for the assembly of Australian rainforest tree communities. PREPRINT.[https://www.researchsquare.com/article/rs-3833899/v1]
"GlobalWoodDensityDatabase.csv": A wood density database (Zanne et al., 2009) used for one species (Micromelum minutum).
- number: Wood density sample number (1:16468)
- family: Family
- species: Binomial species name
- wd: Wood density (oven dry mass/fresh volume; g/cm^3)
- region: Region where the sample was collected. Values include "Africa (extratropical)", "Africa (tropical)", "Australia", "Australia/PNG (tropical)", "Central America (tropical)", "China", "Europe", "India", "Madagascar", "Mexico", "NorthAmerica", "Oceania", "South America (extratropical)", "South America (tropical)", "South-East Asia", "South-East Asia (tropical)"
- ref_num: Number of the reference that the wood density estimate was extratected from (1:205)
Zanne, A.E., Lopez-Gonzalez, G., Coomes, D.A., Ilic, J., Jansen, S., Lewis, S.L., Miller, R.B., Swenson, N.G., Wiemann, M.C. & Chave, J. (2009) Global wood density database. Dryad Identifier: http://datadryad.org/handle/10255/dryad.235.
"Ilic_et_al_wood_density_phase_1.csv": A wood density database (extracted from Ilic et al., 2000) used for one species (Dissiliaria baloghioides).
- ** **abbrev: eight letter species code (first four letters of genus and first four letters of species)
- current.taxon: Binomial species name
- basic_density: Wood density in g/cm3
This file was compiled in 2008 by John Kanowski (formerly Griffith University, now Australian Wildlife Conservancy) from data published by:
Ilic, J., Boland, D., McDonald, M., Downes, D. & Blakemore, P. (2000) Woody density phase 1 - State of knowledge. Australian Greenhouse Office, Canberra.
Methods
No data processing was undertaken other than the tidying and wrangling undertaken in the R scripts.