Effects of fire frequency and seasonality on the population dynamics of the critically endangered Clanwilliam cedar

The Clanwilliam cedar, (Widdringtonia wallichii, formerly W. cedarbergensis) is a threatened conifer endemic to the fire-adapted fynbos vegetation of the Cederberg mountains, South Africa. Here its population size has drastically declined, and its conservation status subsequently escalated to critically endangered in 2013 by IUCN Red List of Plants. Studies have hypothesised that excessive exploitation for timber products, climate change and unfavourable fire regimes (frequency, intensity and season) have contributed to this species’ decline. This decline led to the overarching aim of the study to gain a better understanding of the effects of fire frequency and seasonality on the life history of Clanwilliam cedar. To characterise fire patterns in the Cederberg Wilderness Area, I used a latent class analysis on fire indices calculated from a fire history database. To explore the effects of fire seasonality on the cedar count numbers I used a negative binomial hurdle model using seasonal fire indices and environmental data. To examine the impact of fire frequency and seasonality on the life-history of the Clanwilliam cedar, I used a stochastic demographic model based on parameter values obtained from the literature. Findings from the latent class model indicated that the main axes of variation in fire frequency were the fire indices representing total fire frequency, summer fires, autumn fires in the last 30 years and fires in the last 30 years. Although these fire indices were able to distinguish relatively well between the three latent classes, it however was difficult to disentangle the relative importance of each fire index due to their strong covariation. This points to a more general pattern, suggesting that it is necessary to examine the entire fire frequency history and the seasonality pattern in order to understand the current state of the population of the Clanwilliam cedar. The linear count model revealed autumn fires as being positively associated, whereas mean annual precipitation and mean annual ...