# Spatial and Temporal Dependency of NDVI Satellite Imagery in Predicting Bird Diversity over France
## 4 Discussion
### Best Single-Date NDVI Is Not Synchronous with the Acquisition Time Period of Bird Data  
In most ecological studies, it is usual to make the acquisition date of images consistent with the ground observations in order to avoid misinterpretations [14; 17; 52; 53]. However, as showed by the results of this study, when NDVI is used as proxy to estimate species diversity at fine scale, this common sens rule must be revised since NDVI is time-dependent.  
This observation supports the conclusions of a previous study carried out in a small area of southwestern France [21]. The best NDVI time period to predict bird diversity patterns at the survey level is the one that enable to separate the mixture of crops, open grasslands and ligneous habitats. These components explain bird requirements for breeding and foraging according to functional groups. Depending on the season, differences between habitats are more or less apparent in the NDVI images (Figure 8). Because NDVI in winter has lower values in deciduous forests, this time period leads to underestimate woodland species richness. For other seasons, models performance is equivalent. For farmland species, overestimation appears for time periods where semi-natural habitats are confused with crops because of close values of NDVI. This is the case for winter and summer crops before senescence or harvesting (at the end of june and august, varying by the location). After soil tillage, cultivated areas and other habitats are better discriminated.  
Until now, this time effect has paid little attention in species distribution models based on continuous remotely sensed variables. Several studies evaluated if seasonal bird richness (breeding vs. wintering) was linked to change in productivity during the year [17; 53] but few of them analyzed the optimal matching between the seasonal NDVI and the bird survey although asynchrony was already observed [22; 52]. This is probably due to the macro ecological hypothesis that underpins these studies and which supposes that productivity determines species richness [54]. In our case, _average_ NDVIreflects dominant habitat identity in each plot and this dominance is best displayed in late spring or begin of autumn. This variable was especially relevant for explaining woodland species richness and farmland species richness (Appendix D). Woodland species richness, which is mainly composed of tree-nesting species feeding on invertebrates (e.g., _Certia brachyductyla_, _Erithacus rubecula_, _Sitta europea_) increased constantly with NDVI. Farmland species richness was constant until a NDVI value of 0.7 and then decreased. The lowest values of NDVI correspond to the most open landscapes (Appendix E) that facilitate farmland ground-nesting species avoiding high vegetation structures (e.g., _Alauda arvensis_, _Alectoris rufa_, _Coturnix coturnix_). Intermediate values of NDVI represent heterogeneous landscapes with grasslands and hedgerows that favor farmland species nesting in hedgerows and requiring complementation of habitats (e.g., _Cardelis cannabina_, _Emberiza cirlus_, _Emberiza citrinella_) [6]. Landscape heterogeneity, through _standard deviation_ NDVI, also explained a part of the species richness of the two bird groups but to a lesser extent. Heterogeneity may increase differentiation of ecological niches allowing different species to coexist in a same landscape [14; 55; 56]. However, the effects of heterogeneity are related to the degree of habitat specialization for the species. Highly specialized bird species tend to be negatively affected by landscape heterogeneity [57]. A more refined discrimination between bird species of each community, according to their habitat specialization, may have led to different conclusions [58].  
Figure 8: Seasonal patterns of MODIS NDVI 16-day-composite products in 2010 (250-m spatial resolution) according to the landscape context of bird plot.