Résumé
Species distribution within plant communities results from both the
influence of deterministic processes, related to environmental conditions,
and neutral processes related to dispersal limitation and stochastic
events, the relative importance of each factor depending on the
observation scale. Assessing the relative contribution of environment
necessitates controlling for spatial dependences among data points. Recent
methods, combining multiple regression and Moran's eigenvectors maps
(MEM), have been proved successful in disentangling the influence of pure
spatial processes related to dispersal limitation, pure environmental
variables (not spatially structured) and spatially structured
environmental properties. However, the latter influence is usually not
testable when using advanced spatial models like MEM. To overcome this
issue, we propose an original approach, based on torus-translations and
Moran spectral randomizations, to test the fraction of species abundance
variation that is jointly explained by space and seven soil variables,
using three environmental and tree species abundance data sets (consisting
of 120, 52 and 34 plots of 0·2 ha each, located along 101-, 66- and
35-km-long transect-like inventories, respectively) collected in tropical
moist forests in southern Cameroon. The overall abundance of species
represented by ≥30 individuals, and 27% of these species taken
individually, were significantly explained by fine-scale (<5 km)
and/or broad-scale (5–100 km) spatially structured variations in soil
nutrient concentrations (essentially the concentration of available Mn, Mg
and Ca) along the 120-plots area. The number of significant tests
considerably decreased when investigating the two smaller data sets, which
mostly resulted from low statistical power rather than weaker floristic
and/or edaphic variation captured among plots. Synthesis. Our results
provide evidence that tree species turnovers are partly controlled by
spatially structured concentrations in soil nutrients at scales ranging
from few hundreds of metres to c. 100 km, a poorly documented subject in
Central African forests. We also highlight the usefulness of our testing
procedure to correctly interpret the space-soil fraction of variation
partitioning analyses (which always accounted here for the most important
part of the soil contribution), as this fraction was sometimes relatively
high (R2 values up to c. 0·3) but nearly or not significant.