Uncertainty in Marine Species Distribution Modelling: Trying to Locate Invasion Hotspots for Pterois miles in the Eastern Mediterranean Sea

Journal of Marine Science and Engineering

Niki Chartosia¹  Stefanos Kalogirou²  Kostas Kougioumoutzis³  Demetris Kletou⁴  Dimitris Poursanidis⁵  Vasileios Minasidis⁶ 

[1] Department of Biological Sciences, University of Cyprus, Nicosia 1678, Cyprus;Laboratory of Applied Hydrobiology, Department of Animal Science, School of Animal Sciences, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece;Laboratory of Botany, Department of Biology, University of Patras, 26504 Patras, Greece;Marine & Environmental Research (MER) Lab, Limassol 4533, Cyprus;TerraSolutions Marine Environment Research, Archimidous 63, Nea Alikarnassos, 71601 Heraklion, Greece;iSea, Environmental Organization for the Preservation of the Aquatic Ecosystems, Kritis 12, 54645 Thessaloniki, Greece;

关键词: Bayesian additive regression trees;    climate-change;    lionfish;    Mediterranean Sea;    uncertainty estimation;   

DOI  :  10.3390/jmse10060729

来源: DOAJ

【 摘 要 】

Biological invasions are considered among the largest threats to native biodiversity. The Mediterranean Sea, connecting the Indo-Pacific and Atlantic oceans, is characterized as a global marine invasion hotspot, due to a multitude of human pathways and vectors such as shipping, aquaculture, tourism, and the opening of the Suez Canal, which have led to the introduction of nearly 700 alien species into the Mediterranean Sea. Among the species introduced, the lionfish Pterois miles could be considered the fastest spreading invasive fish species of the last decade (2012–2022) and has been recorded in all countries of the eastern Mediterranean Sea, reaching as far north as Croatia. Here, we present a Bayesian additive regression tree modelling framework for an updated species distribution modelling invasion map under current and future climate conditions. All climate uncertainty sources have been used, as these are available from the Bio-Oracle, the unique marine predictors database. Important outputs of the current approach are the model’s inadequacy to accurately predict the most recent expansion of species in the Adriatic Sea, and the uncertainty estimation, that are high in areas with confirmed occurrence of individuals, in simulations that can help the decision makers and policy officers understand model limitations and take more informed actions.

【 授权许可】

Unknown