## 5 Results and Discussion
### Intercomparison of the EFTs Map with a Land Cover and Ecoregion Classification  
To evaluate the final EFTs map and provide a further explanation, the map was compared with a hybrid land cover map derived from the combination of four datasets (CORINE, GLC2000, MODIS and GlobCover) [90] and with the ecoregions map [18]. The correspondence analysis (CA) [91] and the Minnick's coefficient of areal correspondence [92] between the EFTs and the compared maps were used for this purpose.  
Figure 10 depicts the correspondence analysis of the EFTs with a land cover and an ecoregion classification by means of a bi-dimensional plot. On the left, the CA for the land cover solution accounts for 77.3% of the total inertia (62.2% and 15.1% for axes 1 and 2, respectively) that is a measure of variance of dispersion in the data. The degree of closeness of points in the CA is indicative of the relationships between the EFTs and land cover datasets, items similar to each other will tend to be near to each other in the graph.  
Several clear associations are observed, such as EFT.7 with broadleaved forest and EFT. 3 with irrigated croplands, as have also been showed by [36]. Two ecosystem functional types (_i.e._, EFT.1 and EFT.2) were specific of cultivated land cover, illustrating the high functional heterogeneity of this land cover [34] that can exhibit a multiple phenological response to environmental conditions, climate variability, plant communities and topography [13]. Moreover, the function describing the extent of overlap between two classes was analyzed by means of the [PERSON]'s coefficient (_Cm_) as follows:  
\[Cm=\frac{A\cap B}{A\cup B-(A\cap B)} \tag{3}\]  
where \(A\) is the map of EFTs and \(B\) is the land cover or ecoregions map, respectively. _A_\(\cap\)_B_ and _A_\(\cup\)_B_ refer to the intersection and the union of \(A\) and \(B\),respectively.  
Values higher than 0.05 are indicative of a moderate to high spatial association (see Tables B and C--Appendix). In the case of land covers, more than half of them are associated with an EFT, indicating that effectively there are a relationship between land cover and ecosystem function. [PERSON]'s values support CA results and highlight several new associations. Strong values (\(>\)0.10) included the relation between Cultivated areas and EFT.2. EFT.3 showing a strong relationship with Irrigated land cover datasets. [PERSON]'s values also show cases were a single land cover class could exhibit a multiple functional response such as needleleaved with EFT.4 (0.10) and EFT.5 (0.28). In contrast, there are ecosystems (_i.e._, EFT.9) that are related to several land covers simultaneously (_i.e._, Broadleaved (0.12), Mixed (0.10) and Cultivated areas (0.09)). We infer that the EFTs map provides unique information for augment available land cover datasets.  
In the Ecoregions, the first two CA axes explained 84.9% of the variance with the EFTs. This higher value indicates that Ecoregions are more related to EFTs than land covers, as well as demonstrates the consistency of these two maps. Clear associations are shown in the CA as the Northeastern Mediterranean Forest and EFT.3. A single Ecoregion, such as the Cantabrian Mixed Forest, encompassesEFT.7, EFT.8 and EFT.9 with 0.36, 0.26 and 0.37 [PERSON]'s values respectively. Hence, the EFTs map complements this map, by providing an even finer level of resolution. In this case, eight ecoregions contain 12 EFTs in a broader level and 36 EFTs in case more detailed levels were considered. Regarding [PERSON]'s values, higher degrees of overlap among ecoregions and ecosystems are found. Moreover, EFT.11 and EFT.12 that showed a lack of correlation with any land cover, presented a slightly relation with the Pyrenees Conifer ecoregion because these EFTs are mainly located in a specific spatial distribution.