A mechanistic approach reveals non lineareffects of climate warming on musselsthroughout the Mediterranean sea

Valeria Montalto1,2 & Brian Helmuth3& Paolo M Ruti4 &

Alessandro Dell’Aquila5 & Alessandro Rinaldi1,2 &

Gianluca Sarà1

Received: 18 December 2015 /Accepted: 16 August 2016# Springer Science+Business Media Dordrecht 2016

Abstract There is a dire need to forecast the ecological impacts of global climate change atscales relevant to policy and management. We used three interconnected models (climatic,biophysical and energetics) to estimate changes in growth, reproduction and mortality risk by2050, for three commercially and ecologically important bivalves at 51 sites in the Mediter-ranean Sea. These results predict highly variable responses (both positive and negative) in thetime to reproductive maturity and in the risk of lethality among species and sites that do notconform to simple latitudinal gradients, and which would be undetectable by methods focusedonly on lethal limits and/or range boundaries.

1 Introduction

In an era of rapid environmental change, there is a pressing need to quantitatively predictlikely responses of natural and managed ecosystems at scales relevant to management and

Climatic ChangeDOI 10.1007/s10584-016-1780-4

Electronic supplementary material The online version of this article (doi:10.1007/s10584-016-1780-4)contains supplementary material, which is available to authorized users.

* Valeria Montaltomontaltovaleria@gmail.com

1 Dipartimento di Scienze della Terra e del Mare, Università di Palermo, Viale delle Scienze Ed. 16,90128 Palermo, Italy

2 IAMC-CNR, Via G. da Verrazzano, 17, 91014 Castellammare del Golfo, TP, Italy3 Department of Marine and Environmental Sciences, Northeastern University, Nahant, MA, USA4 World Meteorological Organization, 7 bis, Avenue de la Paix, 2300 Genève, Switzerland5 ENEA, Energy & Environment Modeling Unit, Via Anguillarese 301, 00123 Santa Maria di Galeria,

Rome, Italy

adaptation (Estes et al. 2013; Purves et al. 2013). While considerable efforts have beenmade to forecast the likelihood of elevational and latitudinal changes in species rangeboundaries (e.g. Parmesan et al. 2005; De Frenne et al. 2013), there is increasingawareness that many of the first consequences of environmental change may lie not justin lethality, but also in altered patterns of physiological performance such as growth andreproduction (Philippart et al. 2003; Petes et al. 2008), traits that are involved in theprovision of ecosystem goods and services (Mumby et al. 2011). Notably, such responsesto ongoing environmental change are being observed not just at range boundaries, but alsowell within range limits (Lenoir et al. 2008). This suggests that if we focus only on rangelimits, we may be missing highly significant impacts that are both occurring now andwhich will likely occur in the future (Helmuth et al. 2014). Moreover, it is now evident thatspecies vary substantially in their vulnerability to changing conditions, so that there willlikely be both Bwinners^ and Blosers^ (Somero 2012). Here, we present a novel methodthat combines climate, biophysical and bioenergetics modelling approaches to predict theresponses of three commercially and ecologically important species of bivalves to antic-ipated conditions in the year 2050, at 51 sites in the Mediterranean Sea.

In recent decades, a large body of research has focused on methods for forecasting theimpacts of altered weather patterns on organisms, but the complexity of ecological responsesto climate change has hampered the development of a conceptually unified approach (Post2011; Purves et al. 2013). A central criticism of many correlative approaches is the assumptionof model stationarity (i.e. assumption of constant variance) and space for time substitution,namely that the drivers of ecological patterns observed now are predictive of future responsesunder novel climatic conditions (Murphy et al. 2004). A method that has shown promise fortranslating patterns of climate and weather into both lethal and nonlethal responses is theapplication of process-based (mechanistic) models that are species-specific (Kearney et al.2014). While time consuming, when applied to ecologically keystone (Monaco et al. 2014) orengineering species (Sarà et al. 2013a, b), these methods can theoretically provide criticalinformation at the scales of assemblages and ecosystems (Laughlin 2014), and are capable ofaccounting for variability in responses linked to species traits such as thermal sensitivity.

Both mechanistic and correlative approaches have been used extensively to forecastelevational and latitudinal range shifts (Buckley et al. 2014), and recent studies havecoupled biophysical (heat-budget) and energetics-based modelling approaches to hindcastsublethal responses to temperature change and to estimate the magnitude of futureresponses (Kearney et al. 2010). But, seldom are such diverse classes of models matchedin scale; most often climatic models are developed with little or no consideration for howthey may be applied to ecological predictions (Helmuth et al. 2014). For example, becauseclimate is, by definition, a long-term average of weather, climate models are often tuned tomore accurately predict multi-decadal averages rather than to account for shorter-termvariability that may be more relevant to organismal responses. As a result, model skill -which represents the measurement of the degree of correspondence between modelpredictions and field observations - can diverge significantly when physical outputs ofclimate models are applied to biological questions without consideration of temporal andspatial scale (Potter et al. 2013; Montalto et al. 2014). This Bdouble conflict of scales^ thuscomplicates the integration of information resulting from climate-change research intodecision-making (Ibanez et al. 2012). There is thus a critical need for a generalizableapproach that can quantitatively predict future physiological responses over large portionsof a species’ range (e.g. Gaston et al. 2009; Kearney and Porter 2009; Pörtner 2010).

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Here, we directly address these challenges by applying a down-scaled climate model (basedon the SRES A1B scenario [IPCC 2007]) to a highly resolved coupled biophysical - bioen-ergetics model, to identify the energy allocation strategies and performance levels of threeecologically important mussel species in the Mediterranean Sea, Brachidontes pharaonis,Mytilaster minimus and Mytilus galloprovincialis. As ecological engineers (sensu Gutierrezet al. 2003) bivalves such as these can drive patterns of biodiversity in coastal ecosystems(Smith et al. 2006), and can significantly increase shoreline stability and uptake of excessnutrients (Jones et al. 1994; Grabowski et al. 2012). M. galloprovincialis is an economicallyvital species in the Mediterranean, but also numbers among the 100 worst invaders in otherparts of the world (Global Invasive Species Dataset- www.issg.org), B. pharaonis is aLessepsian species colonizing several coastal areas across the entire Mediterranean basin(Black List of Marine Invasive Species [Otero et al. 2013]) while M. minimus is a smallbivalve native to the Mediterranean Sea. All three species can be found in intertidal habitats,and thus are affected by changes in both the terrestrial and marine environments. Species alldiffer from one another in their thermal optima, performance breadth and lethal temperatures(Fig. 1; Supplementary Tables 1,2).

We made forecasts of size (length at age 5 yr), and time to first spawning for each speciesfor each 5 year period between 2001 and 2050 at 51 sites, both in the intertidal zone (exposedto air during low tide) and subtidal (fully submersed) zones to explore site-specific changes inthe performance of each species. We also calculated mortality risk by accounting for the totalpredicted amount of time where mussels were exposed to temperatures in excess of their lethallimits based on mortality data collected in the laboratory (see Supplementary Information,Fig. S1). Importantly, we recognize that many factors other than temperature will likely varyamong sites, and that many human impacts at local scales can be difficult if not impossible topredict with any real accuracy. However, as temperature is among the most universal drivers ofan organism's physiology and ecology, our results are intended as a first cut approximation ofhow changing climates will likely be translated into ecological effects for these key species,and to explicitly test the hypothesis that physiologically relevant responses will not follow asimple latitudinal gradient, as is commonly assumed. Moreover, because temperatures cannotrealistically be altered as a local level, societal adaptation to climate change will more likelyinvolve the control of other factors with which temperature interacts, such as nutrient run-off

TOPT

Per

form

ance

Body Temperature

Standard performance curve

Performance breadthFig. 1 Standard thermalPerformance Curve (TPCs) de-scribing organismal metabolic per-formance at varying bodytemperatures. TOPT is the centre(peak) of the curve and dashed linerepresents the range of tempera-tures where organismal perfor-mance is at least 69% of themaximum value. Mediterraneantemperatures range between 8.97± 7.82°C and 16.67 ± 8.25°C oc-curred respectively in Croatia(northern Adriatic sub-basin) andPorto Empedocle (Sicily Channel)

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and food supply (Thomas et al. 2011). Spatially explicit models of direct thermal effects canthus potentially inform adaptation efforts, as well as serving as a way of determining whereclimate change may actually have net positive effects.

2 Methods

We estimated changes in growth and reproduction by 2050, for three commercially andecologically important bivalves at 51 sites in the Mediterranean Sea using three interconnectedmodels: climatic, biophysical and bioenergetics. We simulated the climatic conditions andrelated changes of coastal Mediterranean water masses using patterns of atmosphere–oceancirculation on a regional scale. In order to correlate any possible shifts in the composition ofmussel communities directly affected by these changes, we used the regional PROTHEUSsystem (Artale et al. 2010) developed by ENEA (Italy) specifically for the Mediterranean Sea.This model comprises the RegCM3 atmospheric regional model and the MITgcm oceanmodel, coupled through the OASIS3 coupler (Artale et al. 2010; Dell’Aquila et al. 2012).This is achieved by forcing PROTHEUS with data from the global coupled model ECHAM5-MPIOM products as part of the CMIP3 (Coupled Model Intercomparison Project; see Gualdiet al. (2013) for further details). The oceanic component of PROTHEUS model has a spatialresolution of 1/8°x1/8°, which corresponds to a non-uniform resolution of 14 km x (9–12) km,the finer spacing being achieved in the northern part of the domain (Artale et al. 2010), whilethe resolution of 30 km is for the atmospheric component (RegCM3). Forty two unevenlyspaced vertical Z-levels are used, with a resolution varying from 10 m at the surface to 300 min the deeper part of the basin, with an intermediate resolution of about 40–50 m in the layerbetween 200 and 700 m. The performance of the oceanic component of PROTHEUS systemin reproducing the Mediterranean circulation is exhaustively discussed in Sannino et al. (2009)and a comparison of the statistics of climate dynamics and heat waves from the multi modelensemble and observations shows that the ensemble as PROTHEUS is able to capture theactual statistics occurring in Mediterranean regions (Jordà et al. 2012).

We used a coupled biophysical-bioenergetics model (Kearney et al. 2010; Matzelle et al.2015) to estimate organism-level responses of the three species forced by weather. Here,weather data (air and water temperatures, wind speed and direction) simulated by thePROTHEUS system within the period 2001–2050 and previously interpolated on an hourlybasis (Montalto et al. 2014) were used as forcing variables to estimate mussel body temper-atures (Helmuth et al. 2011); no attempt was made to tailor these heat budget models to anydifferences in the morphology of the three species since these differences are subtle, butdifferences in size were included. Estimates of body temperatures across geographic localitieswere calculated using a simple heat budget model developed to calculate temperatures ofmussels (Helmuth 1998) and adjusted in Kearney et al. (2010) and Helmuth et al. (2011). Thebiophysical model used has been extensively validated at other sites, where results suggesterrors on the order of ~2°C in daily average temperature during aerial exposure, despiteexcursions of up to 20°C during hot days (Gilman et al. 2006; Wethey et al. 2011).

Calculated mussel body temperatures were used to drive the species-specific physiologicalresponse based on their bioenergetics (Sarà et al. 2013b; Montalto et al. 2014). A DynamicEnergy Budget model (DEB; Kooijman 2010) was used to estimate hourly temperature- andfood-dependent metabolic energy, and to calculate the remaining energy allocation to mainte-nance, growth and reproduction. All animals gain energy from their surroundings and

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transform it into biomass (e.g. tissues, skeleton etc.) and gametes (e.g. eggs). The DEB modelasserts that this transformation follows rules (k-rule) in which a fixed fraction of energy, k, isallocated to maintenance and growth and the remaining fraction, 1-k, is available for devel-opment and reproduction (van der Meer 2006).

DEB parameters for each species were based on laboratory and field observations and onliterature data (Supplementary Table S3). With the exception of few parameters, such as theparameters kappa or the volume specific maintenance costs of M. galloprovincialis, wetook advantage of the covariation method (Lika et al. 2011a, b) which permits the estima-tion of parameters for several species by simultaneously making use of their relatedness.Specifically, knowledge of the parameters used to describe one species can be used toconstrain the parameters describing another closely-related species for which empiricaldata are lacking (Kearney et al. 2015). We recognize that this method ignores the potentialfor DEB parameters to differ intra-specifically among populations inhabiting differentenvironments and/or originating from different genetic lineages (Seebacher et al. 2012),but we here make a first attempt to explore differences at a species or metapopulation level.Detailed description of the DEB model and relative parameters used are listed in theSupplementary Information.

Although recent climate models make use of schemes that partition nutrients, plankton,zooplankton and detritus, the high variability of CO2 uptake in the aquatic environmentscan lead to considerable uncertainty about future marine ecosystem dynamics and bio-geochemistry cycling. For this reason we used monthly satellite chlorophyll-a (10 × 10 kmgrid-space) for the period 1998–2007 to estimate food availability within each site(Table S4). A previous study conducted in the region (Sarà et al. 2011), compared differenttypes of CHL-a measures against field data carried out along the Italian coasts (seeSupplementary Information), carried out along the Italian coasts, and showed that CHL-a from satellite imagery consistently mirrored the actual level of CHL-a close to thecoastline (see Supplementary Information Figure S1). We recognize that CHL-a is animperfect metric for calculating total food availability, as mussels also feed on dissolvedand particulate matter (Bracken et al. 2012). However, CHL-a has been successfully usedin other studies as a good relative indicator of food availability (e.g. Dahlhoff 2004; Lesseret al. 2010; Thomas et al. 2011).

Simulations were run both for submerged and for intertidal mussels located at a fixedheight on the shore (mean lower low water [MLLW] +0.35 m; Sarà et al. 2011) at each site.While in the former case, mussel temperature can generally be assumed to equal the temper-ature of the surrounding water (Lima et al. 2011). In contrast, during low tide the interactionbetween solar radiation, wind and air temperature sets the body temperature of mussels(Helmuth et al. 2011). Emersion time was estimated using tide projections for the closest site,acquired on an hourly basis from X-Tide (http://www.wxtide32.com/index.html) throughoutthe available period (i.e. 2001–2037). For the period ranging from 2038 to 2050, the tidesdataset was filled with X-Tide projections starting from the year 2026, which were thenrepeated for the interval period 2026–2037. Wind speed and direction follow projectionsprovided by PROTHEUS while site specific daily radiation per each month was downloadedfrom the EU commission website (http://re.jrc.ec.europa.eu/pvgis/apps4/pvest.php). Lastly,to include the effect of density, we calculated hourly functional responses, ranging between0 and 1, with values corresponding to 0 during emersion hours, when feeding (andassimilation) was assumed to stop (Sarà et al. 2011), while physiological stress responsesleading to higher energetic demands are paid by depleting reserves (see Supplementary info).

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Combining information outputted from the three models (climate, biophysical, energetic)we were then able to produce maps of variation of growth performances and organismal fitnessresulting from projected changes in climatic conditions (up to 2050).

3 Results

In a A1B emission scenario, the climate model simulation projected a substantial warming inthe Mediterranean region with temperature increasing on average about 1.5°C in winter andabout 2°C in summer in the 2021–2050 period compared to the reference period (1961–1990).

While forecasted increases in temperature result in highly variable and size-specific re-sponses as a result of body temperatures they experienced within each location, they did notresult in changes in growth performances, being the largest increases in length predicted on theorder of 1mm or less (see Supplementary Data, Table S5).

In contrast, all three species were predicted to experience significant decreases in the annualtime of first spawning in 5 year old mussels (Fig. 2 a,b; Supplementary Data, Table S5). Thesephenological shifts varied between 19 and 38 days in subtidal (Fig. 2b) and intertidal (Fig. 2a)conditions respectively. The magnitude of the phenological shift varied among species andamong sites, with the greatest advancements (averaged across all sites) observed inM. minimus and the smallest inM. galloprovincialis. Temporal shifts were greater in intertidal(Fig. 2a; Table S5) than in subtidal (Fig. 2b; Table S5) conditions. WhereasM. galloprovincialis showed no trend in phenological shifts with latitude, the phenologicaladvancement in time to first spawning was greatest in B. pharaonis at higher latitudes.M. minimus showed an increase in time to spawning at mid latitudes, and a decrease at lowerlatitudes.

Water temperatures predicted for 2050 never exceeded the lethal limit of any of the speciesexamined, but in contrast there were marked changes in mortality (i.e. the difference in thetime spent above the estimated species’ thermal tolerance ranges from 2005 and 2050)predicted for some species at some locations under intertidal conditions (i.e. during aerialexposure; Fig. 3). Expected mortality rates of Brachidontes increased significantly (by twofoldover current predicted levels) but at only one site on the northern coast of Africa. In contrast,predicted mortality rates for Mytilaster increased at most sites.

4 Discussion and conclusion

Understanding how species’ functional traits affect their vulnerability to environmental changeis a powerful means of exploring the mechanisms via which global change affects ecosystemprocesses and patterns of distribution and biodiversity (Stuart-Smith et al. 2013). Predictedrates of phenological advancement (averaged across all species) by 2050 of 3.8 (subtidal) - 7.6days (intertidal) per decade were comparable to the responses observed for many taxonomicgroups since ~1950 showing advancements of 2–7 days per decade (Root et al. 2003). Such atrend is notably widespread across the terrestrial, freshwater and marine habitats with ratesdiffering significantly among trophic levels, suggesting also that phenological shifts maydisrupt the stability and functioning of aquatic and terrestrial ecosystems, and the delivery ofkey ecosystem services (Thackeray et al. 2010). These effects may be even more severe in thecase of free spawning organisms such as bivalves, for which the first chance of success is

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mainly dictated by highly unpredictable stochastic events. Indeed it is well known that growth,reproduction, and mortality are the traits that at the individual level are responsible forpopulation growth and that the magnitude of such traits drives the local persistence of anypopulation. As a main consequence if we exclude time-dependent effects of stress on growthperformance which may impair/enhance sensitivity among and within taxonomic group (e.g.acclimation; Kingsolver and Woods 2016), we can mechanistically predict the potentialcontribution of each individual to the growth of its population. Thus it should be possible totrace population changes back to changes in the mass and energy budgets of the individual

Fig. 2 Map reporting differences in days needed to reach the maturation time (i.e. the occurrence of the firstspawning event) between 5-year old mussels modelled within the period 2046–2050 and 2001–2005 andcalculated as : (trait2046–2050 - trait2001–2005/trait2001–2005); a intertidal and b subtidal individuals. Redbar = B. pharaonis, yellow bar =M. galloprovincialis, green bar =M. minimus. The number next to the chartsymbol represents the attribute value for the each bar and corresponds to a Reference Unit (R. U.) of 2 days foreach symbol of that size on the map. Maps were created using ArcGIS® software by ESRI (EnvironmentalSystems Resource Institute, ArcMap 10.1, (www.esri.com)

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organisms that make up the population (Loreau 2006). While the greatest increases in mortalitywere predicted for southern and western Mediterranean sites (Fig 3), geographic patterns inmortality increase did not conform to a simple latitudinal gradient. Similar patterns have beenproposed for other intertidal (Helmuth et al. 2006; Mislan et al. 2011) and terrestrial (Ackerlyet al. 2015) species at different sites and highlight the importance of local environmentalconditions in either mediating or exacerbating large-scale climatic trends. These results arefurther consistent with recent studies showing high interspecific variability in vulnerability totemperature change (Buckley and Kingsolver 2012).

Present results emphasize the importance of considering the impacts of climate change thatmay occur well within species range boundaries, and of considering both lethal and nonlethalimpacts. Our results also highlight the importance of considering not just averages or extremes,but also thermal history (Giomi et al. 2016) and the role of environmental variability in drivingcumulative effects of physiological performance (Kearney et al. 2010). As recently shown byVasseur et al. (2014) estimates of vulnerability to environmental change by temperate andtropical species based on weather patterns can lead to predictions that deviate substantiallyfrom those based on climatic averages, in part because such variability can increase theprobability of exceeding lethal extremes. Additionally, interpretation of the physiologicaleffects of fluctuating environmental temperatures is further complicated by non-linearity inthe way which organismal body temperature can affect its physiology (Dowd et al. 2015), aswell as the effects of thermal history (Kearney et al. 2012; Giomi et al. 2016). Critically, thesecomplex physiological responses are detectable only if one uses an approach that estimatesbody temperature at fine temporal scales using multiple environmental drivers (Wethey 2002;Gilman et al. 2006).

The choice of considering temperature variability may be especially important whenpredicting species’ susceptibility to climate change and particularly for species whose optimumtemperature is within only a few degrees of lethal temperature (e.g. Brown and Griffin 2005;Estay et al. 2014). This analysis further serves to highlight potential trade-offs between

Fig. 3 Estimates of mortality risk expressed as: hr out of boundaries in the last 5y period (2046–2050) - hr out ofboundaries in the first 5y period (2001–2005) hr out of boundaries in the first 5y period (2001–2005) by eachspecies; red bar = B. pharaonis, yellow bar =M. galloprovincialis, green bar =M. minimus. Reference Unit(R.U.) corresponds to 1,695 hours. Maps were created using ArcGIS® software by Esri (Environmental SystemsResource Institute, ArcMap 10.1, (www.esri.com)

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increased thermal performance, and the increased potential to exceed thermal lethal limitsduring rare but extreme events. Such trade-offs can be complex, but they show that consid-eration of a species’ thermal performance curve (Fig. 1) can be highly informative. As anexample, following adaptive thermoregulation theory, the small Mytilaster behaves as athermal specialist probably as an adaptation to living under restricted intertidal conditions(i.e. upper zones) where limited food resources and food accessibility may result in selectionfor lower body temperatures to minimize metabolic costs (Brown and Griffin 2005). Indeed aslisted in Table S2 although M. minimus showed a better performance than the Lessepsianspecie at cooler temperatures (which also determined slightly wider range of thermal toler-ance), it showed higher performance peaks in oxygen consumption (75.45 μmol h−1 estimatedat 26.5°C) and a steeper slope which resulted in narrower performance breadth (i.e. 2.71degrees ranging between 25.4 and 27.5°C). Thus, even small increases in temperatures canhave a significant impact on physiological performance (Fig. 1). The relatively small differ-ence between optimal and lethal temperatures in this species, however, also increases its risk ofmortality during extreme events. In contrast, the other two species showed a generalist thermalbehavior where the broader width of their thermal niches combined with shallower slope andlower performance peaks (M. galloprovincialis = 15.99 μmol h−1; B. pharaonis = 12.75 μmolh−1; Table S2) are likely to mirror their invasiveness features, allowing them to colonize newhabitats as well as to survive during transient periods of negative energy balance (sensuWoodin et al. 2013).

The forecasting approach developed here does carry with it considerable levels of uncer-tainty, mostly due to the potentially overwhelming effects of local environmental conditions,especially those resulting from human activity. For example, forecasts of mortality can beaffected by the low predictability in the occurrence of aerial exposure when lethal temperaturesare most likely to occur, especially in the Mediterranean where tidal amplitude is relativelysmall and aerial exposure can be affected by wave splash or the presence of low pressuresystems. Other physiological stressors or factors that induce additional energetic demands suchas increasing tolerance to dislodgment from waves (sensu Carrington et al. 2015), the effects ofsalinity (Braby and Somero 2002) and of lowered pH (e.g. Kroeker et al. 2013), changes in therisk of predation (Pincebourde et al. 2012) or changes in food supply driven by localconditions (sensu Kroeker et al. 2016). Our results are therefore best viewed as an "all otherfactors remaining equal" approach. However, as long as it is considered that every species canshow highly variable response times within taxonomic group (sensu Kingsolver and Woods2016), given the overwhelming importance of temperature in driving survival and physiolog-ical response, they do provide a critical first cut estimation of how these key species will likelyrespond to changes in their thermal environments. Moreover, by matching the scales ofenvironmental drivers and physiological responses, the approach outlined here provides aninitial framework in which these and other factors can later be included, and potentiallyexploited by resource managers (Seebacher and Franklin 2012). For example, the methodsoutlined here provide a means to examine relative vulnerability to changes in food availabilityand to identify populations that are most (and least) likely to experience mortality in theabsence of intervention due to thermal effects, which would subsequently lead to ecologicaltipping points (Selkoe et al. 2015).

These results also provide some insights into how a coastal species may respond toenvironmental change over large sections of its geographic range. Recent studies haveemphasized that populations can display "frayed edges" at the ends of a species distribution,and that the low genetic diversity in these populations can make them susceptible to additional

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environmental change (Pearson et al. 2009). If, as our results suggest, areas of high physio-logical stress exist not just at range edges but also well within range boundaries, postsettlement selection could conceivably operate at a local level to produce genotypes that arephysiologically resistant, and which could serve as a genetic source at metapopulation scales.Conversely, if reproductive isolation occurs, then the mosaic pattern in environmental driversand subsequent physiological response could enhance the probability that local adaptationcould occur. Our results also suggest the possibility of ‘phenological mitigation’ (sensu Bennetet al. 2015) where phenological advancement of reproduction compensates for increasingtemperatures; this has the effect of reducing thermal stress in the post –settlement phases whichhave been demonstrated to play a more important role in the regulation of bivalve populationsthan larval availability or quality (Philippart et al. 2003). Asynchrony in the timing ofreproduction could furthermore have positive feedbacks on the overall stability of metapop-ulations and metacommunities, i.e. the mismatch hypothesis (Dekker and Beukema 2014) and/or Portfolio effects (Bernhardt and Leslie 2013).

In recent years policy discussions aimed at reducing the emission of greenhouse gasesand subsequent warming have shifted to include discussions of adaptation. With therecognition that some impacts of global climate change are inevitable is the furtheracknowledgement of the importance of stressors that occur at local levels (Selkoe et al.2015). Solutions to stressors imposed by global climate change thus increasingly includepolicies designed to minimize the impacts of these more localized drivers (e.g. fishing,pollution, eutrophication) but their enhancement requires that we develop tools forpredicting how multiple stressors play out at these local levels. Furthermore, a key elementof climate adaptation research is to understand the potential role played by biologicalcomplexity and diversity in determining the resistance and resilience of ecosystems toenvironmental pressures. To do so requires that we move from past generalizations such aspoleward range migrations and towards more spatially explicit modeling over a speciesentire range, and that we consider impacts not at the species level, but at the level ofpopulations and the individuals they comprise (Helmuth et al. 2014).

In conclusion, these results strongly suggest that these three structuring species (sensuGutierrez et al. 2003) of coastal mussels will likely experience phenological shifts in thetiming to reproductive maturity, and in intertidal zones, thermal stress cause changes in therisk of mortality. However these consequences are highly species- and site-specific inways that do not always conform to simple latitudinal gradients, and in some cases revealpotential benefits for Mediterranean Sea ecosystems. This study provides one of the firstattempts to estimate spatially explicit changes in growth, fecundity and survival of marineinvertebrates on large spatial scales in the Mediterranean using principles of eco-mechanics (Carrington et al. 2015), providing a generalized method for forecasting thevulnerability of marine taxa, which to date are still poorly studied (Pacifici et al. 2015). Italso represents one of the first attempts to match the scales of outputs of climate modelsand inputs of biophysical and bioenergetics models. While we recognize that given highuncertainty in downscaled climate model predictions the modelled results here should notbe applied without considerable caution, they do provide a window into what levels ofspatial variability we might expect in species responses to climate change in comingdecades, and the importance of considering local-scale impacts. Especially when appliedusing shorter-range climate projections, these coupled models may provide new avenuesfor predicting responses at scales that are relevant to management and conservation in thecontext of global climate change (Petes et al. 2014).

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Acknowledgments PRIN TETRIS 2010 grant n. 2010PBMAXP_003 (G. Sarà), funded by the Italian Ministerof Research and University supported this study. B.H. was supported by a grant from NASA (NNX11AP77). Wethank Erika M.D. Porporato for her help with GIS and all collaborators and students from the EEB lab at UNIPAfor their efforts during the experimental phase.

Compliance with ethical standards

Authorship VM conceived the idea, performed modelling work, analysed output data and led the writing; GS& BH conceived the idea, developed biophysical models and contributed to writing; PR & AD provided climatedata; AR performed modelling work. All authors gave final approval for publication.

Competing interests The authors declare no competing interests.

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