A mechanistic model of climate change risk: Growth rates and microhabitat specificity for conservation priority woodland epiphytes

Climate change studies need to develop models for species risk that are mechanistic and predictive, with conservation strategies explored through the use of scenarios. This study focused on a diverse group for climate change analysis - lichen epiphytes - to develop a heuristic model for quantifying risk that has two key components. First, it draws on the classic ecological concept - 'das Gesetz der relativen Standortskonstanz' - which explains how the suitable niche space of a species (at a microhabitat-scale) may occur under different local circumstances in contrasting macroclimatic zones. To quantify this pattern, conservation priority cyanolichen and tripartite epiphytes were sampled across a steep climatic gradient, to characterise their different microhabitat preferences in optimal and sub-optimal macroclimates. Second, the model used climatically controlled growth rates as a functional response to climate variability, leading to an increase in generation time for sub-optimal climates. Together, the macroclimate-microhabitat and growth rate data parameterise a mechanistic population model that was used to explore the effect of environmental change scenarios, including: 1. Climate change leading to longer generation times, and 2. A reduction in habitat quality, e.g. through a tree disease scenario such as ash dieback. The advantage of this population approach was its down-scaling to better understand a species' local vulnerability. Accordingly, the study suggested how management at landscape or habitat-scales can be used to offset the negative effects of climate change. Because extinction rates for the epiphyte populations are low, and established individuals are relatively long-lived, there is a time-lag during which conservation can increase the resilience of threatened populations. However, multiple threats, such as climate change and tree disease combined, severely shorten this window of opportunity.