Climate change and its effects on sea life will be simulated by oceanographic models, based on the projected scenarios of rise in atmospheric pCO2. The present day Adriatic values of several physical, chemical and biological parameters of seawater quality will be simulated with the 3D transport reaction model OPATM-BFM (Lazzari et al. 2012), initialized with current boundary condition and forcing data. The same model initialized with boundary conditions and forcings from different IPCC (Intergovernmental Panel on Climate Change; IPCC 2014) scenarios will simulate expected changes in seawater quality. Outcomes of current situation and simulated scenarios will be used as reference for the setting up of laboratory experiments on selected species (WP4), as well as descriptors of environmental conditions in habitat suitability models.

Resilience of populations in patchily distributed MBHs is strongly affected by the possibility to receive recruits by the dispersal or advection of organisms from similar habitats (Cowen et al. 2007). If populations on a MBH experience difficulties in self-sustaining due to changes in water quality or to human impacts, they can persist if replenished by immigration from nearby sources of larvae or propagules. In this project, the studies on connectivity will be supported by the use of MITgcm (Massachusetts Institute of Technology general circulation model; Marshall et al. 1997), a 3D, finite-volume circulation model coupled with a Lagrangian advection-diffusion model. Data on oceanographic connectivity will be integrated with data on genetic connectivity (WP3). Initial and open boundary conditions, surface forcing and the discharge rate of the main rivers will be obtained by larger scale ocean models, high resolution meteorological models, available datasets and climatologies (Querin et al. 2013). The model will be coupled with the Larval TRANSport Lagrangian model (LTRANS), which is an off-line particle-tracking model, originally developed to simulate oyster larvae. LTRANS can easily be modified to simulate passive particles and other planktonic organisms and includes routines for reflective boundary conditions, larval behaviour and settlement. Based on benthic assemblage structures (WP2) and genetic connectivity (WP3) data, similarities between MBHs and their mutual dispersal relationships will be investigated. Possible source and sink sites for reefs species, where source sites are of greater importance for preservation, will be identified.

Habitat suitability models (Guisan and Zimmermann 2000) will integrate data on biogenic reef populations in the study area (both those already available in the literature (Curiel et al. 2012; Falace et al. 2015; Ponti et al. 2011) and those collected in this project, WP2), with oceanographic data from accessible databases, model simulating present day biogeochemical seawater characteristics, results of connectivity analysis, and results of laboratory experiments. In particular, the habitat suitability for reef building species in relation to seawater temperature and pH will be studied. A comparison of present day habitat suitability maps with those obtained on simulated future scenarios will make possible to estimate the threats induced by climate changes that MBHs’ assemblages could experience in the near future.

Cowen, R.K., Gawarkiewic, G., Pineda, J., Thorrold, S.R., Werner, F.E., 2007. Population connectivity in marine systems: An overview. Oceanography 20, 14-21.

Curiel, D., Falace, A., Bandelj, V., Kaleb, S., Solidoro, C., Ballesteros, E., 2012. Species composition and spatial variability of macroalgal assemblages on biogenic reefs in the northern Adriatic Sea. Bot. Mar. 55, 625-638. http://dx.doi.org/10.1515/bot-2012-0166

Falace, A., Kaleb, S., Curiel, D., Miotti, C., Galli, G., Querin, S., Ballesteros, E., Solidoro, C., Bandelj, V., 2015. Calcareous bio-concretions in the northern Adriatic Sea: Habitat types, environmental factors that influence habitat distributions, and predictive modeling. PLoS ONE 10, e0140931. http://dx.doi.org/10.1371/journal.pone.0140931

Guisan, A., Zimmermann, N.E., 2000. Predictive habitat distribution models in ecology. Ecol. Model. 135, 147-186. http://dx.doi.org/http://dx.doi.org/10.1016/S0304-3800(00)00354-9

IPCC, 2014. Climate change 2014: Impacts, adaptation, and vulnerability. Contribution of working group ii to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Lazzari, P., Solidoro, C., Ibello, V., Salon, S., Teruzzi, A., Béranger, K., Colella, S., Crise, A., 2012. Seasonal and inter-annual variability of plankton chlorophyll and primary production in the Mediterranean Sea: a modelling approach. Biogeosciences 9, 217-233. http://dx.doi.org/10.5194/bg-9-217-2012

Marshall, J., Adcroft, A., Hill, C., Perelman, L., Heisey, C., 1997. A finite-volume, incompressible Navier Stokes model for studies of the ocean on parallel computers. J. Geophys. Res.-Oceans 102, 5753-5766. http://dx.doi.org/10.1029/96jc02775

Ponti, M., Fava, F., Abbiati, M., 2011. Spatial-temporal variability of epibenthic assemblages on subtidal biogenic reefs in the northern Adriatic Sea. Mar. Biol. 158, 1447-1459. http://dx.doi.org/10.1007/s00227-011-1661-3

Querin, S., Cossarini, G., Solidoro, C., 2013. Simulating the formation and fate of dense water in a midlatitude marginal sea during normal and warm winter conditions. J. Geophys. Res.-Oceans 118, 885-900. http://dx.doi.org/10.1002/jgrc.20092