Data from: The effectiveness of seed rain in recolonising an ecotonal mesic forest following extreme severity fire

Read full text
Authors: Ruby Paroissien, Ryan Tangney, Catherine A. Offord, Mark K. J. Ooi
Cited by: 0

Abstract

As fire severity and extent increase, recovery of fire-sensitive species in plant communities may rely increasingly on seed rain and dispersal from adjacent unburnt areas. The role dispersal plays in driving recovery trajectories is surprisingly understudied. Additionally, how traits drive dispersal can contextualise compositional differences and indicate recovery trajectories. This paper investigated seed rain in recently burned mesic forest and the role of traits in driving post-fire recovery across a gradient of fire severities. We placed seed traps at two locations in the Blue Mountains, located in south-eastern Australia. We collected and identified all seeds that fell into seed traps each month for a year, three years following fire of differing severities. We compared species diversity of seed collections with extant vegetation and measured the minimum dispersal distance each species likely travelled. We used variable selection to identify how traits impacted dispersal distances. Rainforest species were generally lacking from recently burned sites in both the extant vegetation and the seed rain. Composition of the seed rain indicated dispersal occurred primarily from local sources, with minimum distance travelled largely determined by life form, dispersal type and dispersal height. Differences in species richness and composition between unburnt and sites burnt at differing severities was observed in both the extant vegetation and in the seed rain. Increasing fire severity suggests lengthening recovery times, with recolonisation from unburnt areas minimal and slow. The commonality of local dispersal highlights the importance of surviving individuals for maintaining diversity and replenishing populations.

Fields of Study & Subjects

Fire effects on ecosystems Ecology and Vegetation Dynamics Studies Rangeland and Wildlife Management

Publication details

Journal / source
DRYAD
Publication date
10 February 2026
Language
EN
Document type
Dataset