Influence of Lidar-derived forest structure and geographic variables on temperate rainforest quality: a case study on Tayvallich, Scotland

Abstract

Temperate rainforests are globally rare biodiversity hotspots containing unique species of lichen and bryophyte species. With the required conditions existing on less than 1% of the Earth’s surface, Scotland has some of the best examples of temperate rainforests globally. However, these woodlands have been fragmented by overgrazing, invasive species, and deforestation. Expansion and regeneration of these forests is therefore essential for achieving national biodiversity targets. Whilst national drivers of biodiversity and favourable tree species have been identified, the aim of this study is to identify site-specific drivers which can directly inform planting and management strategies. This is achieved by exploring how lidar-derived woodland structure and geographical variables influence temperate rainforest quality, focussing on a site in Tayvallich, Scotland. Quality across 64 sites was assessed using two indices: (1) a standardised rainforest assessment methodology, to measure overall woodland condition, and (2) species richness of unique temperate rainforest lichen and bryophytes, a direct measure of ecological response. Using generalised additive models, canopy cover and proximity to water were identified as the most important variables to consider in planting and management strategies. Proximity to a biodiverse species pool was also found to be highly significant, but further research is required to confirm the role of this variable. Based on these findings, recommendations are made for how to best create and enhance biodiversity in these globally rare ecosystems.