Native biodiversity collapse in the Eastern Mediterranean
Albano, Paolo G. et al. (2020), Native biodiversity collapse in the Eastern Mediterranean, Dryad, Dataset, https://doi.org/10.5061/dryad.pnvx0k6kk
Global warming causes the poleward shift of the trailing edges of marine ectotherm species distributions. In the semi-enclosed Mediterranean Sea, continental masses and oceanographic barriers do not allow natural connectivity with thermophilic species pools: as trailing edges retreat, a net diversity loss occurs. We quantify this loss on the Israeli shelf, among the warmest areas in the Mediterranean, by comparing current native molluscan richness with the historical one obtained from surficial death assemblages. We recorded only 12% and 5% of historically present native species on shallow subtidal soft and hard substrates, respectively. This is the largest climate-driven regional-scale diversity loss in the oceans documented to date. In contrast, assemblages in the intertidal, more tolerant to climatic extremes, and in the cooler mesophotic zone show ~50% of the historical native richness. Importantly, ~60% of the recorded shallow subtidal native species do not reach reproductive size, making the shallow shelf a demographic sink. We predict that, as climate warms, this native biodiversity collapse will intensify and expand geographically, counteracted only by Indo-Pacific species entering from the Suez Canal. These assemblages, shaped by climate warming and biological invasions, give rise to a ‘novel ecosystem’ whose restoration to historical baselines is not achievable.
The dataset origins from the collection of samples of benthonic living molluscs and empty shells from the Mediterranean Israeli coastline (ESM2). Additionally, the dataset contains the maximum size of a subset of species collected alive (ESM3) and the radiocarbon ages used to quantify death assemblage time-averaging (ESM4). Last, four R scripts to analyse the data are provided. Details on the methods can be found in the published paper.
Austrian Science Fund, Award: P28983-B29