Lessons from a regional analysis of forest recovery trajectories in West Africa

Abstract

In West Africa, very poorly documented are the recovery trajectories of secondary forests, and even less is known about the origin of the observed variability in recovery rates. To understand the relative importance of local and regional environmental conditions on these trajectories, we inventoried all trees larger than 2.5 cm DBH on 236 plots (0.2 ha), aged from 0 to 45 years plus controls, on eight chronosequences representing the typical regional North-South climatic gradient of West Africa. In a hierarchical Bayesian framework, we modelled recovery trajectories of biodiversity, aboveground biomass and floristic composition and tested the influence of variability in local (plot history, landscape context, remnant trees) and regional (climate and soil) conditions on recovery rates. Our results show that (a) diversity recovers faster than composition and biomass, (b) among the local variables, the number of remnant trees has a positive impact on recovery rates while the duration of agricultural cultivation has a negative impact, and (c) among the regional variables, the high seasonality of precipitation and climate, typical of the dry forests of the northern West African forest zone, leads to faster secondary successions. Our simulation approaches have indicated that poor regional conditions can be counterbalanced by adequate local conditions and vice versa, which argues strongly in favour of a diagnosis that integrates these two aspects in the choice of more or less active technical itineraries for forest restoration.

Keywords

• ecosystem attribute
• Bayesian model
• secondary forest
• secondary succession
• recovery trajectory
• regional gradient