Using models to predict recovery and assess tree species vulnerability in logged tropical forests: A case study from French Guiana

Abstract

A major challenge for forest managers is to define the optimal cutting cycle to ensure that the resource is sustained in the long term. Matrix models of forest dynamics allow time-projection of diameter-class distributions and thus assessment of the time needed, after logging, to recover a given part of the exploitable stock. They are easy to build and they only require, as input variables, the diameter structure of the population(s) under scope. However, such models are based on a coarse description of tree population dynamics and must be used with caution. In particular, as trees are only described from a diameter threshold (usually 10 cm dbh), recruitment of a new tree cannot be linked with the preceding generation since too much time elapsed between seed dispersal and the installation of a 10-cm recruit. This causes predictions of matrix models to be highly questionable in the long term when ingrowth to larger dbh classes greatly depends on the way recruitment has been modelled. We used a case study from French Guiana to test whether or not a simple matrix model is reliable enough to help forest managers choose between management alternatives. We focused on the major timber species Dicorynia guianensis Amshoff (Caesalpiniaceae) harvested under a selective cutting regime. We compared predictions of D. guianensis stock recovery in the short and long term provided by two models: StoMat, a non-regulated matrix model, and SELVA, a single-tree distance dependent model explicitly simulating the entire species life cycle. Both models were independently calibrated on data from Paracou permanent sample plots. We showed that: (i) the short-term recovery of the exploitable stock predicted by StoMat is reliable for a large range of disturbance conditions; (ii) recruitment implementation in StoMat does not influence projections until the third felling cycle; (iii) for shared initial stand conditions SELVA and StoMat give consistent mid- and long-term predictions: the simple recruitment model used into StoMat could efficiently summarise the regeneration processes of the species under low felling intensity. Our results indicate that the current felling regime used in French Guiana may not be sustainable on a long-term basis. In any case, no more than 60% of the initial stock would be recovered after logging. We conclude that simple models can provide as reliable predictions as more complicated ones. They may be sufficient to assess the recovery of a species’ exploitable stock even in the long term, or at least assess the (un)sustainability of particular harvesting regimes.