In the context of current global change, having high quality data on species occurrence is key not only for ecological understanding, but also for urgent issues such as determining the degree of threat to species and designing conservation and management strategies.

A first objective of the NextDive project is to improve and complete data from several available Iberian atlases (10 km resolution): flora, tetrapod and butterfly atlases, being the latter of special relevance given its relative incompletedness. Each atlas will be treated as a network of connections (presences) of species and cells, which will allow the use a powerful graph theory technique based on stochastic block modeling (SBM), widely used to calculate probabilities of connections and non-connections in all types of networks, but only recently used in ecology and never for this purpose.

This analysis will allow us to identify possible undetected and spurious presences that we will then check through: 1) field sampling (mainly with butterflies); 2) further searches in electronic repositories and literature; and 3) the collaboration of experts from the different groups studied.

A second objective is to generate reliable predictions of the potential effects of climate change on species and communities using optimized and updated ecological models. To this end, we will implement several innovations: 1) include new covariates (e.g., information on species interactions based on co-occurrence patterns); 2) new protocols to delimit regional species groups (e.g., using biogeographic regions); 3) include information on ecological niches (e.g., information on ecological niches of species and communities); 4) include information on species interactions based on co-occurrence patterns, using biogeographic regions); 3) including information on species ecological niches beyond the region under study (e.g., incorporating European-scale data on species distribution and environmental conditions); and 4) optimizing the modeling process itself (e.g., adopting multiscale approaches through hierarchical analyses).

We will also implement different validation tests of the results: 1) advanced statistics based on cross-validation; 2) modeling based on virtual species distribution data; and 3) comparison of model predictions with the presences found in new sampling and data searches (see above). This would be the first time that this last type of validation has been performed using full regional biotas.

Finally, a third objective is to use the previous results to predict possible effects of climate change through a vulnerability analysis and studies of current and future representativeness of species and diversity in Iberian protected areas.

In order to contribute to the development of future research, conservation and restoration initiatives, both the new data and predictions, and the modeling protocols (R packages) generated in the project, will be accessible through the SABINA research group website.

The project will be developed by a multidisciplinary team of nine researchers with expertise in botany, zoology, forestry, statistics, and spatial and predictive ecology.

NextDive (PID2021-124187NB-I00) is funded by the Spanish Ministry of Science and Innovation (Agencia Estatal de Investigación) and by “FEDER A way to do Europe”.