Author(s): Simon Van Wynsberge 1 , Serge Andréfouët 1 , * , Mélanie A. Hamel 1 , Michel Kulbicki 2
Among the existing conservation measures used to mitigate natural and anthropogenic impacts on marine ecosystems, the establishment of reserves are useful both to protect biodiversity and to sustain adjacent resources . However, to be well designed and effective, reserves should be implemented using biological, social, and economic criteria, but this often requires a large amount of very specific data . Considering biodiversity representativeness only, a comprehensive census of overall species richness, rarity, or endemism would be needed . As ecosystem functioning depends more on functional traits than on species themselves , new conservation strategies promote the representation of functional groups, where important functional groups with little or no redundancy should warrant priority conservation effort. Unfortunately, costs of data acquisition, knowledge of species, and time limit taxonomic and functional inventories, which remain scarce. One possible approach to overcome this problem is to use surrogates . The overall diversity of species and functional groups may remain unknown, but can be approximated by estimator surrogates variables that are more easily collected. These can be other taxa -, environmental variables , and habitats . In practice, surrogate-based conservation planning may require two steps. First, the effectiveness of various surrogates to represent the conservation target is evaluated using a reduced but representative data set. Second, if surrogacy is found sufficiently effective and sufficiently robust to sampling, the best surrogate can be used to search for new protected areas with confidence. At this stage, the surrogate is often spatially generalized and gridded at a given resolution by interpolation or modelling, if it is not already a gridded data set (remote sensing image for instance). Here, we focus on the first part of this two-stage process.
Surrogacy is only one of the tool available for conservation planning, which can be based on expert-opinion, customary rules, optimization of conservation costs for a given objectives and so forth . Yet, surrogacy refers to date to a wide body of work . In its simpler and more intuitive form, surrogacy is referring to the identification and use of surrogates data, instead of other data difficult to collect, for instance with statistical measurements of good-fit between the surrogate and the target ("pattern-based surrogate"). In its more achieved form, surrogacy is related to the use of "selection-based surrogates" to design a network of protected areas (a suite of locations of remarkable features) with a selection algorithm . Our study is also related to the later domain.
One way to test if estimator surrogates are efficient for conservation planning consists in measuring to which extent a virtual reserve network established on surrogate data allow a good representation of the target data within the network , , , . Using this approach (i.e. reserve selection algorithms) is interesting since algorithms maximize complementarity between selected sites. For example, prioritizing sites of high species richness only might result in a selection of sites containing similar...