DOI: 10.5061/dryad.9ghx3ffqq
title: Data from: Extreme fire severity interacts with seed traits to moderate post-fire species assemblages

description: Premise: Climate change is pushing fire regimes to new extremes, with
 unprecedented large-scale severe fires observed globally. Persistent
 soil-stored seed banks are a key mechanism for plant species recovery
 after fires, but extreme fire severity may generate soil temperatures
 beyond thresholds seeds are adapted to. Seeds are protected from lethal
 temperatures through soil burial, with temperatures decreasing with
 increasing depth. However, smaller seeds, due to their lower mass and
 corresponding energy stores, are restricted to emerging from shallower
 depths compared to larger-seeded counterparts. We examined recruitment
 patterns across a landscape-scale gradient of fire severity, to determine
 whether seed mass and dormancy class mediate shifts in community
 assemblages. Methods: We surveyed 25 sites in wet sclerophyll forests in
 south-eastern Australia impacted by the 2019-2020 Black Summer Fires,
 burnt at either moderate, high, or extreme severity. We calculated
 abundance and density of seedlings from 27 common native shrub species.
 Key results: Extreme severity fires caused significant declines in
 seedling recruitment. Recruitment patterns differed between dormancy
 class, with steeper declines in seedling emergence for species with
 physiologically dormant (PD) compared to physically dormant (PY) seeds at
 extreme fire severity. Relative emergence proportions differed between
 fire severity and seed size groups for both PY and PD species.
 Conclusions: Large-scale extreme severity fires favour larger-seeded
 species, shifting community composition. Future recurrent extreme fire
 events could therefore place smaller-seeded species at risk. Seed mass,
 dormancy type and other novel seed traits should be considered when
 exploring post-fire responses, to better predict impacts on plant species.
description: # Fire severity, interacting with seed traits drives post-fire recruitment
 following Black Summer Fires
 [https://doi.org/10.5061/dryad.9ghx3ffqq](https://doi.org/10.5061/dryad.9ghx3ffqq) R script and raw data were used to analyse the dynamics between seed mass, burn severity, and seed dormancy in plant species found in south-eastern Australia. ## File List and Descriptions: **alldata_AJB_3.0.csv** - contains raw data used for analysis. * Community = ecological community, UB is Upland Basalt, and STIF is Sydney Turpentine-Ironbark forest. * Site Number = site number for sites surveyed * BurnSeverity = burn severity * ScientificName = scientific name of study species * SeedSize = seed size in mg * DormancyType = dormancy type, physically dormant (PY), and physiologically dormant (PD) * Recruits = number of seedlings observed Missing data: N/A **density_data_AJB_2.0.csv** - contains raw data used for analysis. * Community = ecological community, UB is Upland Basalt, and STIF is Sydney Turpentine-Ironbark forest. * Site Number = site number for sites surveyed * BurnSeverity = burn severity * ScientificName = scientific name of study species * SeedSize = seed size in mg * SeedSize2 = seed size category * DormancyType = dormancy type, physically dormant (PY), and physiologically dormant (PD) * Recruits = number of seedlings observed * Density = density of seedlings Missing data: N/A **proportionalbinomialglmAJB.csv** - contains data used to analyse relative emergence proportions between fire severity and seed size. Proportions were calculated from raw data in "alldata_AJB_3.0.csv" * Dormancy = dormancy type, physically dormant (PY), and physiologically dormant (PD) * BurnSeverity = burn severity * SeedSize = seed size category * Full = proportions of seedlings for each category calculated from raw data **density_redo_Figure_2.rmd** - R script used to analyse the relationship between categorical variables burn severity, dormancy type and seed size, and the dependent variable seedling density. **Figure_3.rmd** - R script used to analyse the relationship between the proportion of total emergence recorded at each burn severity and each seed size category at each burn severity. **Figure_4.rmd** - R script used to analyse the relationship between seedling recruitment and seed mass as a continuous variable.