NDVI -based productivity and heterogeneity as indicators of plant-species richness in boreal landscapes

Decision making in managing biological diversity is critically dependent on adequate information concerning species-richness patterns and a rigorous understanding of species-habitat relationships. Measures of primary productivity derived from satellite images may provide useful cost-effective estimates of species richness and distribution patterns over wide areas. We constructed Generalized Additive models (GAM) to investigate the potential of primary productivity and its heterogeneity based on Normalized Difference Vegetation Index (NDVI) to explain the species richness in 28 separate vascular plant families in boreal forest landscapes, northern Finland. The productivity models explained on average more of the species richness than the heterogeneity models. However, models that performed best were produced by combining productivity and heterogeneity variables into the same models. Species richness responded mainly unimodally or positively to productivity and its heterogeneity. We conclude that measures of productivity and heterogeneity based on remote sensing can provide useful 'first filters' of locations of high diversity in plant families in boreal landscapes.