Ecological niche modeling, cytogenetics and phylogeography of the genera Geomalacus and Letourneuxia (Gastropoda, Pulmonata) from the Iberian-Moroccan region

First described more that 150 years ago, the systematics of the genera Geomalacus and Letourneuxia (Arionidae, Gastropoda, Pulmonata) is still challenging. The taxonomic classification of arionid species is based on extremely labile characters such as body size or color that depends both on diet and environment, as well as age. Moreover, there is little information on the genetic diversity and population structure of the Iberian slugs that could provide extra clues to disentangle their problematic classification. The present work uses different analytical tools such as habitat suitability (Ecological Niche Modeling - ENM), cytogenetic analysis and phylogeography to establish the geographical distribution and evolutionary history of these pulmonate slugs. The potential distribution of the four Geomalacus species was modeled using ENM, which allowed the identification of new locations for G. malagensis, including a first report in Portugal. Also, it was predicted a much wider distribution for G. malagensis and G. oliveirae than previously known. Classical cytogenetic analyses were assayed with reproductive and a novel use of somatic tissues (mouth and tentacles) returning the number of chromosomes for the four Geomalacus species and L. numidica (n = 31, 2n = 62) and the respective karyotypes. G. malagensis and L. numidica present similar chromosome morphologies and karyotypic formulae, being more similar to each other than the Geomalacus among themselves. We further reconstructed the phylogeny of the genera Geomalacus and Letourneuxia using partial sequences of the mitochondrial cytochrome oxidase subunit I (COI) and the nuclear ribosomal small subunit (18S rRNA), and applied an independent evolutionary rate method, the indicator vectors correlation, to evaluate the existence of cryptic diversity within species. The five nominal species of Geomalacus and Letourneuxia comprise 14 well-supported cryptic lineages. Letourneuxia numidica was retrieved as a sister group of G. malagensis. G. oliveirae is paraphyletic with respect to G. anguiformis. According to our dating estimates, the most recent common ancestor of Geomalacus dates back to the Middle Miocene (end of the Serravallian stage). The major lineage splitting events within Geomalacus occurred during the dry periods of the Zanclean stage (5.3-3.6 million years) and some lineages were confined to more humid mountain areas of the Iberian Peninsula, which lead to a highly geographically structured mitochondrial genetic diversity. The major findings of this are the following: (1) provides updated species distribution maps for the Iberian Geomalacus expanding the known geographic distribution of the concerned species, (2) unravels the cryptic diversity within the genera Geomalacus and Letourneuxia, (3) Geomalacus oliveirae is paraphyletic with G. anguiformis and (4) Letourneuxia numidica is sister group of G. malagensis.

Habitat use and diel vertical migration of bigeye thresher shark: overlap with pelagic longline fishing gear

Pelagic longliners targeting swordfish and tunas in oceanic waters regularly capture sharks as bycatch, including currently protected species as the bigeye thresher, Alopias superciliosus. Fifteen bigeye threshers were tagged with pop-up satellite archival tags (PSATs) in 2012-2014 in the tropical northeast Atlantic, with successful transmissions received from 12 tags for a total of 907 tracking days. Marked diel vertical movements were recorded on all specimens, with most of the daytime spent in deeper colder water (mean depth = 353 m, SD = 73; mean temperature = 10.7 °C, SD = 1.8) and nighttime spent in warmer water closer to the surface (mean depth = 72 m, SD = 54; mean temperature = 21.9 °C, SD = 3.7). The operating depth of the pelagic longline gear was measured with Minilog Temperature and Depth Recorders (TDRs), and the overlap with habitat utilization was calculated. Overlap is taking place mainly during the night and is higher for juveniles. The results presented herein can be used as inputs for Ecological Risk Assessments for bigeye threshers captured in oceanic tuna fisheries, and serve as a basis for efficient management and conservation of this vulnerable shark species.

Using niche modelling of indicator species to predict the distribution of xerophitic shrub dune communities in South-Western Portugal

Inland sand dune systems are amongst the most threatened habitat types of Europe. Affected by severe conditions, these habitats present distinct community compositions, which makes them excellent for studying possible interactions among their integrating species and the environment. We focus on understanding the distribution and cooccurrence of the species from dune plant assemblages as a key step for the adequate protection of these habitats. Using data from an extensive survey we identified the shrub species that could be considered indicators of the different xerophytic scrub dune communities in South West Portugal. Then, we modelled the responses of these species to the environmental conditions using Ecological Niche Factor Analysis. We present some preliminary results elucidating whether using species distribution models of indicator species at a regional scale is a valid approach to predict the distribution of the different types of communities inhabiting these endangered habitats.

Landscape metrics as indicators of coastal morphology and its use in ecological niche modelling of seagrass species

Dependence of some species on landscape structure has been proved in numerous studies. So far, however, little progress has been made in the integration of landscape metrics in the prediction of species associated with coastal features. Specific landscape metrics were tested as predictors of coastal shape using three coastal features of the Iberian Peninsula (beaches, capes and gulfs) at different scales. We used the landscape metrics in combination with environmental variables to model the niche and find suitable habitats for a seagrass species (Cymodocea nodosa) throughout its entire range of distribution. Landscape metrics able to capture variation in the coastline enhanced significantly the accuracy of the models, despite the limitations caused by the scale of the study. We provided the first global model of the factors that can be shaping the environmental niche and distribution of C. nodosa throughout its range. Sea surface temperature and salinity were the most relevant variables. We identified areas that seem unsuitable for C. nodosa as well as those suitable habitats not occupied by the species. We also present some preliminary results of testing historical biogeographical hypotheses derived from distribution predictions under Last Glacial Maximum conditions and genetic diversity data.

Can we use niche models of indicator species to predict the distribution of endangered communities?

European-wide conservation policies are based on the identification of priority habitats. However, research on conservation biogeography often relies on the results and projections of species distribution models to assess species' vulnerability to global change. We assess whether the distribution and structure of threatened communities can be predicted by the suitability of the environmental conditions for their indicator species. We present some preliminary results elucidating if using species distribution models of indicator species at a regional scale is a valid approach to predict these endangered communities. Dune plant assemblages, affected by severe conditions, are excellent models for studying possible interactions among their integrating species and the environment. We use data from an extensive survey of xerophytic inland sand dune scrub communities from Portugal, one of the most threatened habitat types of Europe. We identify indicator shrub species of different types of communities, model their geographical response to the environment, and evaluate whether the output of these niche models are able to predict the distribution of each type of community in a different region.