The influence of fire and silvicultural practices on the landscape-scale genetic structure of an Australian foundation tree species

Brenton von Takach Dukai, Rod Peakall, David B. Lindenmayer, Sam C. Banks

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Abstract

Natural disturbance regimes in forest ecosystems are being rapidly modified by anthropogenic pressures, including silvicultural practices and climate change. Australian forests dominated by mountain ash (Eucalyptus regnans) are critically endangered, with wildfires and clearfell logging predicted to cause ecosystem collapse within the next 50 years. To investigate the influence of disturbance on patterns and extent of genetic diversity in mountain ash, we compare replicated sites with three different disturbance histories (undisturbed, burnt, and logged). We employ genetic analysis at five chloroplast microsatellite loci and 2866 nuclear single-nucleotide polymorphisms (SNPs) to estimate within- and among- population genetic diversity, and assess the extent of fine-scale spatial genetic structure among individuals, for the three disturbance treatments. Consistent with the expectation of extensive pollen dispersal but limited seed dispersal, we detected low levels of genetic differentiation at nuclear SNPs (FST = 0.067), and very high levels of differentiation at cpDNA microsatellites (FST = 0.751). While differences among treatments at nuclear SNPs were small, we found stronger spatial genetic structure in the undisturbed treatment, higher levels of genetic differentiation in the logged treatment and greater partitioning of genetic diversity among logged sites. Analysis of cpDNA revealed significantly higher levels of total and within-site genetic diversity in the logged treatment than the burnt or undisturbed treatments, with haplotypes entering the system via the use of non-local seed in the regeneration process. We suggest that artificial regeneration activities should utilise a greater number of maternal parents, which could be achieved via variable retention harvesting or utilising a regional admixture provenancing approach.

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