Conserving the functional and phylogenetic trees of life of European tetrapods

Protected areas (PAs) are pivotal tools for biodiversity conservation on the Earth. Europe has had an extensive protection system since Natura 2000 areas were created in parallel with traditional parks and reserves. However, the extent to which this system covers not only taxonomic diversity but also other biodiversity facets, such as evolutionary history and functional diversity, has never been evaluated. Using high-resolution distribution data of all European tetrapods together with dated molecular phylogenies and detailed trait information, we first tested whether the existing European protection system effectively covers all species and in particular, those with the highest evolutionary or functional distinctiveness. We then tested the ability of PAs to protect the entire tetrapod phylogenetic and functional trees of life by mapping species' target achievements along the internal branches of these two trees. We found that the current system is adequately representative in terms of the evolutionary history of amphibians while it fails for the rest. However, the most functionally distinct species were better represented than they would be under random conservation efforts. These results imply better protection of the tetrapod functional tree of life, which could help to ensure long-term functioning of the ecosystem, potentially at the expense of conserving evolutionary history.


Functional trait database.
To make sure all analyses were comparable throughout the four groups, we selected similar or equivalent traits for the four groups. For instance, body mass was used for both birds and mammals while body length was used for amphibians and squamates.
We summarised below the different classes used for each group and for each traits and their meaning. We also added the list of publications where the data where gathered. For birds, most data were extracted from Pearman et al. [1].

Figure S2 Target definition for the four groups.
For each group, we extracted the species for which species range size belonged to the top 10 and 90% quantiles. For those species, the target was fixed to 100% and to 10%. In order words, a target of 100% was set for the 10% rarest species of each group, and the target of 10% was set for the 10% most common species.
For the remaining species, a regression was fitted between the coordinates (10,100) and (90,10) to define their respective targets. Species target achievement was then measured at the ratio between the percentage of range actually covered by the PA system and the target. in three classes, namely low, medium and high, when species' target achievement was lower than 25%, between 25 and 75% and higher than 75%, respectively.

Amphibians Birds
Mammals Squamates  Figure S10 Relationship between species' targets and species ranges in function of the criteria used. The "quantile" approach is the one used in the main text ( Figure S1). The second one used IUCN categories. We used the criteria B1 based on species range to define critically endangered species, species with less than 100km 2 range and vulnerable for species with less than 10,000km 2 . We arbitrarily set that critically endangered species should be protected at 100% and vulnerable at 50%. We then used a regression along these two points to set species targets for all species. Although the ICUN approach is not group-specific the species targets are pretty similar to the ones defined through the quantile approach. Only birds and mammals do differ meaning that our Quantile approach is more severe than the IUCN one (i.e. the quantile approach asks for larger targets meaning high species' target achievement are more difficult to reach).  Table S1. P-value of the OLS regression lines of figure 2 and 3 and the associated r-squares of the regressions.  Table S2. Representation of the land cover types in Europe and their representation in the European protected area network. A pixel has a resolution of 300m. Only the total number of pixels of each land cover type is represented (No of pixels), as well as the number of pixels that fall within a protected area (No of pixels within PAs) and the associated percentage of protection (% in PA)