DOI: 10.5061/dryad.nk98sf7zz
title: iNaturalist data for: Multi-taxon biodiversity responses to the 2019–2020 Australian megafires

description: Conditions conducive to fires are becoming increasingly common and
 widespread under climate change. Recent fire events across the globe have
 occurred over unprecedented scales, affecting a diverse array of species
 and habitats. Understanding biodiversity responses to such fires is
 critical for conservation. Quantifying post-fire recovery is problematic
 across taxa, from insects to plants to vertebrates, especially at large
 geographic scales. Novel datasets can address this challenge. We use
 presence-only citizen science data from iNaturalist, collected before and
 after the 2019-2020 megafires in burnt and unburnt regions of eastern
 Australia, to quantify the effect of post-fire diversity responses, up to
 18 months post-fire. The geographic, temporal, and taxonomic sampling of
 this dataset was large, but sampling effort and species discoverability
 were unevenly spread. We used rarefaction and prediction (iNEXT) with
 which we controlled sampling completeness among treatments, to estimate
 diversity indices (Hill numbers: q=0-2) among nine broad taxon groupings
 and seven habitats, including 3885 species. We estimated an increase in
 species diversity up to 18 months after the 2019–2020 Australian megafires
 in regions which were burnt, compared to before the fires in burnt and
 unburnt regions. Diversity estimates in dry sclerophyll forest matched and
 likely drove this overall increase post-fire, while no taxon groupings
 showed clear increases inconsistent with both control treatments
 post-fire. Compared to unburnt regions, overall diversity across all taxon
 groupings and habitats greatly decreased in areas exposed to extreme fire
 severity. Post-fire life histories are complex and species detectability
 is an important consideration in all post-fire sampling. We demonstrate
 how fire characteristics, distinct taxa, and habitat influence
 biodiversity, as seen in local-scale datasets. Further integration of
 large-scale datasets with small-scale studies will lead to a more robust
 understanding of fire recovery.
description: This dataset represents all publicly available, unobscured
 iNaturalist records used in final analyses for the article "Multi-taxon biodiversity responses to the
 2019-2020 Australian megafires". Only the iNaturalist observations
 IDs are reported here, to avoid potential copyright infringement. To
 replicate the dataset used in the paper (without the obscured observations
 (see methods and appendices for details), use the inat_id column to link
 to a download of records from iNaturalist. Details on how these data were
 collected and processed can be found in the "Methods" section
 and appendices to the article. 
description: # iNaturalist data for: Multi-taxon biodiversity responses to the
 2019–2020 Australian megafires
 [https://doi.org/10.5061/dryad.nk98sf7zz](https://doi.org/10.5061/dryad.nk98sf7zz) ## Description of the data and file structure Data provided to support this article were sourced from iNaturalist (https://www.inaturalist.org/). To ensure records for species which are automatically obscured by the iNaturalist platform were included where possible, these data were downloaded on request through the Atlas of Living Australia (https://www.ala.org.au/) which provided unobscured locations for species automatically obscured on the iNaturalist platform. Information on taxon geoprivacy on the iNaturalist platform can be found here and here. As publication of obscured location records are not permitted, these data have been omitted from the public dataset provided with this paper. However, of the 23568 iNaturalist observations of 3885 species, only 206 observations of 57 species were omitted from the public dataset. To replicate the dataset used in the paper - without the obscured observations as described above - use the "inat\_id" column to link to the "id" column when downloading records from iNaturalist (use the export tool, downloading all records inclusive of the period 1<sup>st</sup> Jan 2017 to 23<sup>rd</sup> July 2021 within NSW and the ACT: https://www.inaturalist.org/observations/export). Details on how these data were collected and processed can be found in the "Methods" section and appendices to the article. **The data provided are in .csv format and include 8 columns described below:** *inat\_id*: an individual identifier for each iNaturalist record. Note the dataset includes duplicates as some records were included in multiple temporal samples. *group*: broad taxonomic grouping referred to in the article to which each observation has been assigned. *vegetation\_grouping*: habitat grouping referred to in the article to which each observation has been assigned. *gridcell\_id*: unique identifier for each 1 km2 grid cell used for sampling (see methods in article). *before\_after\_fire*: binary descriptor of whether observation occurred before or after the 2019-2020 Australian megafires. *burn*: binary descriptor of whether observation occurred in areas which were burnt or unburnt in the 2019-2020 Australian megafires. *sample*: categorical descriptor for temporal and spatial sampling units used in the article, including burnt/unburnt, before/after fires. Numbers represent number of days before the fire-front occurred in the grid cell. *time\_since\_fire\_days*: number of days since fire-front occurred in grid cell.