Browsing by Author "Trigas, Panayiotis"
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- KBAscope: key biodiversity area identification in RPublication . Spiliopoulou, Konstantina; Rigal, François; Plumptre, Andrew J.; Trigas, Panayiotis; Paragamian, Kaloust; Hochkirch, Axel; Lymberakis, Petros; Portolou, Danae; Stoumboudi, Maria; Triantis, KostasKey Biodiversity Areas (KBAs) represent the largest global network of sites critical to the persistence of biodiversity, which have been identified against standardised quantitative criteria. Sites that hold very high biodiversity value or potential are given specific attention on site-based conservation targets of the Kunming-Montreal Global Biodiversity Framework (GBF), and KBAs are already used in indicators for the GBF and the Sustainable Development Goals. However, most of the species that trigger KBA status are birds and to maximise benefits for biodiversity under the actions taken to fulfil the GBF, countries need to update their KBAs to represent important sites across multiple taxa. Here we introduce KBAscope, an R package to identify potential KBAs using multiple taxonomic groups. KBAscope provides flexible, user-friendly functions to edit species data (population, range maps, area of occupancy, area of habitat and localities); apply KBA criteria; and generate outputs to support the delineation and validation of KBAs. The details of the analysis – such as the spatial units tested or the KBA criteria applied – can be decided according to the scope of the analysis. We demonstrate the functionality of KBAscope by using it to identify potential KBAs in Greece based on multiple terrestrial taxonomic groups and four sizes of grid cells (4 km2, 25 km2, 100 km2, 225 km2).
- Topography-driven isolation, speciation and a global increase of endemism with elevationPublication . Steinbauer, Manuel J.; Field, Richard; Grytnes, John-Arvid; Trigas, Panayiotis; Ah-Peng, Claudine; Attorre, Fabio; Birks, H. John B.; Borges, Paulo A. V.; Cardoso, Pedro; Chou, Chang-Hung; De Sanctis, Michele; Sequeira, Miguel M.; Duarte, Maria C.; Elias, Rui B.; Fernández-Palacios, José María; Gabriel, Rosalina; Gereau, Roy E.; Gillespie, Rosemary G.; Greimler, Josef; Harter, David E. V.; Huang, Tsurng-Juhn; Irl, Severin D. H.; Jeanmonod, Daniel; Jentsch, Anke; Jump, Alistair S.; Kueffer, Christoph; Nogué, Sandra; Otto, Rüdiger; Price, Jonathan; Romeiras, Maria M.; Strasberg, Dominique; Stuessy, Tod; Svenning, Jens-Christian; Vetaas, Ole R.; Beierkuhnlein, CarlAIM: Higher-elevation areas on islands and continental mountains tend to be separated by longer distances, predicting higher endemism at higher elevations; our study is the first to test the generality of the predicted pattern. We also compare it empirically with contrasting expectations from hypotheses invoking higher speciation with area, temperature and species richness. Location Thirty-two insular and 18 continental elevational gradients from around the world. Methods We compiled entire floras with elevation-specific occurrence information, and calculated the proportion of native species that are endemic (‘percent endemism’) in 100-m bands, for each of the 50 elevational gradients. Using generalized linear models, we tested the relationships between percent endemism and elevation, isolation, temperature, area and species richness. RESULTS: Percent endemism consistently increased monotonically with elevation, globally. This was independent of richness–elevation relationships, which had varying shapes but decreased with elevation at high elevations. The endemism–elevation relationships were consistent with isolation-related predictions, but inconsistent with hypotheses related to area, richness and temperature. Main conclusions Higher per-species speciation rates caused by increasing isolation with elevation are the most plausible and parsimonious explanation for the globally consistent pattern of higher endemism at higher elevations that we identify. We suggest that topography-driven isolation increases speciation rates in mountainous areas, across all elevations and increasingly towards the equator. If so, it represents a mechanism that may contribute to generating latitudinal diversity gradients in a way that is consistent with both present-day and palaeontological evidence.
- Unravelling the small‐island effect through phylogenetic community ecologyPublication . Matthews, Thomas J.; Rigal, François; Kougioumoutzis, Kostas; Trigas, Panayiotis; Triantis, KonstantinosAIM: The small-island effect (SIE) describes a different relationship between island area and species richness on smaller compared to larger islands. The pattern has recently gained widespread support. However, few studies have attempted to identify the actual mechanisms driving the SIE. Here, we use a phylogenetic community framework to study the SIE, based on the assumption that if the dominant assembly processes differ between small and large islands, patterns of phylogenetic community structure should shift across the area and habitat diversity gradient. LOCATION: The Aegean Archipelago, Greece. TAXON: Plants. METHODS: We used a large dataset of 3,262 vascular plant species distributed across 173 islands, in combination with a species-level phylogeny. The phylogenetic community structure of each island was calculated using a null modelling framework and was quantified using effect sizes (ES); negative values indicating phylogenetic clustering and positive values overdispersion. Habitat diversity, species richness, phylogenetic diversity (PD) and ES values were regressed against log10-transformed area and we tested for a SIE using piecewise regression models. We also assessed differences in taxonomic and phylogenetic composition between small and large islands using a beta diversity framework. RESULTS: We found evidence of a SIE using species richness, PD and phylogenetic community structure (ES values). Small islands displayed low variation in habitat diversity and tended to be more phylogenetically clustered, while large islands shifted from phylogenetic clustering towards phylogenetic overdispersion with increasing area and habitat diversity. In addition, we showed that phylogenetic composition tended to be more similar between small islands than expected. MAIN CONCLUSION: Overall, our results provide an example of a SIE in the analysis of island phylogenetic community structure, and point to a role of habitat diversity in driving the SIE more generally.