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A multidisciplinary study on the effects of climate change in the northern Adriatic Sea and the Marche region (central Italy)

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A multidisciplinary study on the effects of climate change in the northern Adriatic Sea and the Marche region (central Italy)
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  ORIGINAL ARTICLE A multidisciplinary study on the effects of climate changein the northern Adriatic Sea and the Marche region(central Italy) F. Appiotti  • M. Krz ˇelj  • A. Russo  • M. Ferretti  • M. Bastianini  • F. Marincioni Received: 15 June 2012/Accepted: 23 March 2013   Springer-Verlag Berlin Heidelberg 2013 Abstract  An integrated analysis of recent climate change(including atmosphere, sea and land), and social reaction andadaptation, was conducted in central Italy and the northernportion of the AdriaticSea. The collected environmental dataincluded meteorological, oceanographic, and river gaugesstations, covering the time period 1961–2009. Social dataincluded 800 questionnaires and interviews carried out onselected samples of residents, decision-makers, and emer-gency managers. The trend analysis of air temperature datadetailed an overall increase in all seasons, whereas rainfalldata showed decrease in winter, spring, and summer, andincrease in autumn, influencing river flow changes. Marinedata showed a warming of the water column after the year1990,particularlyrelevantinthecoldseason.Surfacesalinityincreased in spring and summer and strongly decreased inautumnandalsoinwinter(duetothespreadingoverthebasinof the increased autumnal river runoff). These changes,combined with anthropogenic effects, appear to influence thenorthern Adriatic marine environment and ecosystems.Impacts in the coastal areas are also evident inland; the anal-ysis of Aridity index, and potential water deficit, suggestsnegativeimpactsintermsofsoildeteriorationandagriculturalproductivity,particularly inthe areanearthecoastline.Atthesame time, the analysis of social data revealed awarenessamong local residents of these impacts and associated risksconnected to climate change. Yet, this awareness is not cur-rently translated into preventive and protective actions;among the main reasons for this delay is also ineffectiveinformation exchange among citizens, public administrators,and the scientific community. Keywords  Regional climate    Adriatic Sea    Marche   Climate change perception Introduction The Earth’s climate is changing, with unequivocal increa-ses of global average air and ocean temperatures. Despitethe fact that climatic variations are a normal expression of the dynamic nature of planet Earth, the current speed of these changes does not seem to find precedents in theplanet’s recent climate record (IPCC 2007). During thetwentieth century, the climatic patterns have producedsignificant alterations of the hydrogeological cycle onEarth’s surface and increased the intensity and frequencyof extreme weather events related to it. These accelerated F. Appiotti    A. Russo ( & )    F. MarincioniDepartment of Life and Environmental Sciences,Universita` Politecnica delle Marche, Via Brecce Bianche,60131 Ancona, Italye-mail: a.russo@univpm.it Present Address: F. AppiottiDepartment of Design and Planning in Complex Environment,IAUV, Venezia S. Croce 1957, 30135 Venice, ItalyM. KrzˇeljDepartment of Marine Studies, University of Split,Livanjska 5/III, 21000 Split, CroatiaA. RussoISMAR, CNR, Via Gobetti, 101, 40129 Bologna, ItalyM. FerrettiDepartment of Integrated Policies for Security and CivilProtection, Regional Council of Marche, Via Gentileda Fabriano 3, 60125 Ancona, ItalyM. BastianiniISMAR, CNR, Arsenale - Tesa 104, Castello 2737/F,30122 Venice, Italy  1 3 Reg Environ ChangeDOI 10.1007/s10113-013-0451-5  changes have cascade effects with many linkages at globallevel and variegated local impacts. For this reason, it isessential to develop climate investigation analysis takinginto consideration both global and local levels. Differentlyfrom global analysis, local climate analysis can moreaccurately represent the complex climate of a small areaand offer new insights into precipitations and temperaturepatterns (Boyles and Raman 2003), and to the specific area-related effects. As a matter of fact, the amount and type of consequences related to the ongoing climate change areclosely dependent on individual ecosystems and differstrongly on spatial scale, in relation to the geographicalsetting of the area considered, and its socioeconomiccondition. In order to define useful and effective strategiesto reduce the risks emerging from climate change and tohelp local communities to adapt to future scenarios, it isvery important to understand, not only how climateparameters are changing, but also how people and decision-makers perceive these changes.This study takes into consideration different aspects of theclimatechangeanalysisintheItaliancoastalregionofMarcheand in the northern part of the Adriatic Sea. In particular, thestudy tries to coherently integrate both physical and socialdata; to define rational and adaptive local strategies.Temperature and precipitations trends over the Italianpeninsula during the last century have been investigated byseveral studies (Cundari and Colombo 1992; Maugeri andNanni1998;Buffonietal.1999;Brunettietal.2000a,b,2004, 2006; Colombo et al. 2007; Toreti and Desiato 2008). These studies demonstrated an increasing maximum and minimumtemperature trend since 1980 with small differences fromNorth to South, and a significant reduction of annual andseasonal precipitations. During the twentieth century, pre-cipitation has decreased by about 5 % in the Northern Italyand by about 15 % in the South (Buffoni et al. 1999). More- over, Brunetti et al. (2006) reveals that the area with the most marked annual precipitation decreasing trend is the central-southern Italy with a reduction of 10 % in the last century.Furthermore, winter is the season characterized by a strongerprecipitation reduction over the whole of Italy and especiallyin its Northern part (Brunetti et al. 2000a). The variations in climate trends are also affecting soilcompartment. Due to its localization and its geomorpho-logic characteristics, the Italian peninsula is stronglyexposed to drought and desertification hazards. Althoughactually not yet significantly involved by these hazards, theMarche region appears, especially in the coastal band, to beone of the Italian areas potentially at risk of drought anddesertification impacts (Costantini et al. 2007). Actually, the risk of desertification is expected to be the highest inareas with projected decreases in precipitation, increases inthe frequency of summer droughts and the incidence of forest fires, and intensive land use (EEA/JRC/WHO 2008).Climate is one of the most important agents in the processof desertification and soil degradation. A fitful climateappears to be the main cause of erosion, landslides, andflooding (Costantini et al. 2007; EE/JRC/WHO 2008). Moreover, the climate can build the limiting factor for plantgrowth because of low rainfall and high temperatures, mak-ing unprofitable agricultural cultivation in the absence of irrigation(Costantinietal.2007).Thetemperatureactsonthe soil either directly or indirectly (evapotranspiration) con-tributing to the process of salinization, aridification, anddegradation of organic matter. Indeed, possible future effectsof climate change on soil productivity and desertification arestrictly dependent on both climatic and agro-meteorologicalparameters (e.g., temperature, precipitation, potential waterdeficit and Aridity index), and soil moisture characteristics(ASSAM 2006). The Aridity index and the potential waterdeficit are indicators that can be calculated by collecting andprocessing meteorological data, such as air temperature,precipitation, and evapotranspiration (Nastos et al. 2011). Coastal areas are among the most threatened by climatechange, because of sea level rise and potential modificationsoftheenvironmentalparametersintheshelfareas.Thisaspectis particularly relevant, considering that an important portionof the human population lives in coastal areas. Coastal ero-sion, changes of river discharge, modifications of sea tem-perature, salinity, circulation and nutrient salts content,eutrophication, anoxia, and alien species are some of thefactorswhichmayaffectthecoastalandmarineenvironments.Finally, climate change is a complex phenomenon whichinvolves diversified aspects of life and push citizens andinstitutions to define effective strategies to face with newfuture conditions and emerging risks. People’s predispositionto implement mitigation and adaptation strategies, as well astosupportandurgegovernmentstodothesame,isnotdirectlyrelated to the real level of risks but to the perceived one(O’Connor et al. 1999). Threats and hazards interact withpsychological, social, institutional, and cultural processes inways that may amplify or attenuate the public perception of risk.The channelsofthisamplificationorattenuationprocessare strongly related to the information transfer mechanisms(direct and indirect communication), personal knowledge of cause and consequences of climate change, past experiences,and cultural and environmental beliefs (Kasperson et al.1988). All these aspects, acting on public and personal per-ception of risk, may increase people’s willingness to takeaction to reduce risk and to adapt to new conditions.Theinteractionandexchangeofinformationamongexpertsof disaster prevention, politicians, and citizens play animportant role in disseminating disaster knowledge and shap-ingindividualandcollectiveriskconscience(Grayetal.1999).This manuscript confronts the scientific evidence of climate change, on different environmental domains, withlocal residents, policy makers, and emergency managers’ F. Appiotti et al.  1 3  perceptionoftheemergingclimaterisks.Afterintroducingtheenvironmental context, the following section describes thestudy area. Research methodology and data collection arereported in the third section, whereas trends and changes ana-lyzedintheair,water,soil,andhumansrealmsarediscussedinthe fourth one. The last section presents the results and thediscussions about prevention strategies of future impacts.Study areaThe study area considered in this work includes the Marcheregion in central Italy and the northern part of the AdriaticSea (Fig. 1). The Marche region This is one of the 20 administrative division of Italy, it islocatedaroundlatitude43  Nandlongitude14  E,extendsforatotal surface of 9.385 km 2 and counts 1,565,000 residents.TheregionalclimateisaffectedbythepresenceoftheAdriaticSea to the east and of the Apennines mountains chain to thewest.Thecoastalareathatextendsnorthtosouthfor173 kmisthe mostproductive zoneoftheregion.Fromeasttowest,theregion can be subdivided in three different thermal and geo-morphological bands: coastal, valley/low hill, and high hill/ mountain. Some 69 % of the territory is valley and low hill,prevalently composed of clayey sandstone sediments, and31 % is high hill and mountain with a large part composed of massive limestone. Only a small portion presents coastalmorphologyalongtheAdriaticseaboard.Finally,about30 %of the territory is covered by forests.From a climatic perspective, each of these bands showsdifferenttemperatureandprecipitationtrends,withthemeanannual temperature of 15, 14 and 13   C, respectively (Murriand Fusari 1987). July and August are the months withhighest temperatures, while the lowest ones are generallyrecorded in January. In terms of precipitation, the  coastalband  receivesmeanprecipitationvaluesrangingfrom600to850 mm/year, the  medium – low hill band   between 850 to1,000 mm/year, and the  high hill and mountain band   over Fig. 1  Study area:  a  TheMediterranean basin, with the box  indicating Marche regionand the  dashed box  theinvestigated northern Adriaticarea;  b  the Marche region withthe numbers corresponding tothe location of temperaturestations as reported in Table 1; c  position of the oceanographicstations within the marine studyarea. Location of 4 meteostations is reported; the threeboxes represent marine areasconsidered for time series in thenorthern Adriatic Sea:  Po dotted,  Nord   continuous,  Est  dashedA multidisciplinary study on the effects  1 3  1,000 mm/year. Autumn is the rainy season, with theexception of the third band (high hill and mountains) wherethe rainy season is winter (Grassi and Zepponi 2009).In terms of soil aridity, 15.5 % of regional coastal andlow valley areas are currently considered at risk of desertification (Grassi and Zepponi 2009). Considering thatin 2002 the Marche region was defined an area not vul-nerable to desertification (Grassi and Zepponi 2009), thesizeable increase over the last 10 years of the area at risk of desertification is likely due to the great climate variabilitythat is affecting the Mediterranean basin. The northern Adriatic Sea This is a shallow shelf basin with a maximum depth of about 100 m and is located at the northernmost tip of theMediterranean Sea. It has a limited and confined area andvolume but receives large river runoff capable of influ-encing the deep circulation of the adjacent Ionian Seas, andthe whole of the Eastern Mediterranean Sea. The northernAdriatic is also an important economic resource areahosting huge maritime traffic, fisheries, aquaculture, andoffshore activities (drilling plants for mainly natural gasextraction, and presently also Liquefied Natural Gas—LNG, regasification terminal) as well as tourism. Unques-tionably, coastal erosion, massive mucilaginous aggre-gates, harmful algal blooms, biogeochemical fluxes,modifications due to climate change heavily affect tourismand fishery, two most relevant economic activities of theMarche region.Due to its shallowness and topography conditions (assurrounded by land and mountainous chains, such as theApennines to the West, the Alps to the North, and theDinaric Alps to the east), the northern Adriatic Searesponds faster and more intensely to changes in theboundary conditions (atmosphere and river runoff   in pri-mis ). The Po River, which flows into the Adriatic about100 km northwestward of the coastline of Marche, with its1,500 m 3 s - 1 long-term average runoff is one of the majordriver of the Adriatic environmental dynamics. The Adri-atic sea’s general circulation is cyclonic moving freshwaterinput from the Po, and the other northern Adriatic rivers,southeastward along its western coast, directly influencingthe Marche coastal area (Artegiani et al. 1997). In fact, therivers of Marche have an annual average runoff on theorder of tenths of cubic meters per second and are unable toheavily influence surface seawater salinity (and otherproperties), except for the first few hundred meters aroundthe rivers’ mouth. The Po River is also the largest nutrientpoint source in the northern Adriatic, and its freshwaterspreads significantly influence the water column stratifi-cation and the circulation pattern, contributing to largespatial and temporal variability of eutrophication gradientand primary production in that area (Smodlaka 1986; De-gobbis and Gilmartin 1990; Gilmartin et al. 1990; Raicich 1996; Degobbis et al. 2000; Tedesco et al. 2007a, b; Socal et al. 2008; Cozzi and Giani 2011; Djakovac et al. 2012; Giani et al. 2012). Materials and methods To define the general climatic trends in the Marche region,daily temperature and precipitation data were collected andanalyzed for the 50-year period 1960–2009. The dataset wasobtainedfromtheMarcheRegion’s‘‘CentroFunzionaledellaProtezione Civile’’ (the regional monitoring and forecastingcenterforcivilprotection).Thiscenterisresponsibletocollectand manage the regional meteorological data since 2002.Before that, all the data were collected from the ‘‘ItalianNational Hydrographic and Maritime Office.’’ The data forthis study were gathered from 21 temperature and 61 precip-itation stations distributed over the territory of Marche. Yet,due to the presence of missing values, not all the recordsavailable fromthese stationshavebeenusedfor thestatisticalanalysis performed for this work. According to the recom-mendations of the ‘‘Guide to Climatological Data’’ (WMO2007),themonthly valuesoftemperature werenot calculatedif:(1)10ormoredailymeasuresweremissingor(2)5ormoreconsecutive daily measures were missing. Applying suchcriteria data from only 14 stations of minimum temperature( T  min ) and 15 stations for maximum temperature ( T  max ) wereanalyzed (Fig. 1b; Table 1). Conversely, the precipitation data were selected on the base of general criteria used by theEuropean climate assessment and dataset (ECAD), whichestablishesthat(a)datamustbeavailableforatleast40 years,(b) the total missing data cannot be more than 10 %, (c) themissing data from each year cannot exceed 20 %, and (d) theperiod of missing measures cannot exceed 3 consecutivemonths (Bartholy and Pongracz 2007).From these daily data, annual trends for maximum andminimum temperature ( T  max  and  T  min ), and precipitationover Marche were also analyzed over the period1960–2009. Furthermore, seasonal trend for each stationwas calculated according to the following seasonalbreakdown:Winter: January, February, and March,Spring: April, May, and June,Summer: July, August, and September,Autumn: October, November, and  December. These are not the astronomical time periods used forthese seasons (there is a delay of about 10 days); yet, suchaveraging strategy avoids having few December’s datafalling in the previous year. Also, oceanographic dataanalysis uses the above seasonal breakdown. F. Appiotti et al.  1 3  The time series of rainfall and temperature were ana-lyzed using the Mann–Kendall (MK) statistical test (Mann1945; Kendall 1975). This is a rank-based nonparametric test (Novotny and Stefan 2007), commonly used to assessthe significance of the hydro-meteorological time seriestrends of temperature, precipitation, and streamflow(Westmacott and Burn 1997; Yue et al. 2002). The Mann–Kendall test was carried out using Makesens(Mann–Kendall test for trend and Sen’s slope estimates)and template (Salmi et al. 2002). Four different signifi-cance levels  a  where chosen for this study: 0.1, 0.05, 0.01,and 0.001 to which correspond the levels of confidence of 90, 95, 99, and 99.9 %, respectively. The Z was insteadused to identify a statistically significant trend and Table 1  Results of the Mann–Kendall statistical test applied to the seasonal values of the maximum/minimum air temperature at selectedstationsTime series Winter Spring T  max  T  min  T  max  T  min Test Z Sign Test Z Sign Test Z Sign Test Z SignAncona 3.3 *** 4.9 *** 4.3 *** 4.9 ***Arcevia 2.3 * 4.5 *** 3.2 ** 3.7 ***AscoliPiceno 2.3 * 1.8  ? 2.7 ** 3.7 ***Bargni 3 ** 3.6 *** 3.1 ** 3.4 ***Cingoli 0.8 ns 5.1 *** 2.1 * 4.5 ***Fabriano 0.8 ns 0.3 2.7 ** 2  ? Fano 3.4 *** 5.7 *** 4.3 *** 5.1 ***Jesi 1 ns 2.4 * 0.2 ns 3.2 **Lornano 2.7 ** 3.4 *** 3.8 *** 3.6 ***Mercatello 2.3 * 4.1 *** 2.2 * 3.8 ***Montemonaco 2.9 ** 3 ** 2.6 * 1.6 nsNovafeltria 1.5 ns 3.7 *** 2.8 ** 3 **Pergola 2.8 ** 0.7 ns 1.7  ?  0.9 nsServigliano 3.8 ***  - 4.2    5.4 *** –2   Urbino 1.2 ns 4.2 *** 3 ** 3.5 ***Time series Summer Autumn T  max  T  min  T  max  T  min Test Z Sign Test Z Sign Test Z Sign Test Z SignAncona 4.7 *** 4.2 *** 3 ** 2.7 **Arcevia 4 *** 4.2 *** 3.1 ** 2.9 **AscoliPiceno 3.5 *** 3.1 ** 1.3 ns 1.5 nsBargni 2.8 ** 2.9 ** 1.9  ? 2.3 *Cingoli 1.5 ns 4 ***  - 0.4 ns 3.8 ***Fabriano 2.2 * 2 *  - 1.1 ns 0.3 nsFano 5.5 *** 5.5 *** 4.3 *** 4.8 ***Jesi  - 0.2 ns 2.8 ** 0.5 ns 2.1 *Lornano 4.3 *** 3.9 *** 1.2 ns 2.1 *Mercatello 2 * 4.4 *** 1.1 ns 2 *Montemonaco 2.8 ** 1.6 ns 2.8 ** 1.7  ? Novafeltria 1.2 ns 3.2 ** 1.2 ns 2.4 *Pergola 1.5 ns 1.1 ns 0.4 ns 0.6 nsServigliano 5.8 ***  - 0.6 ns 4.3 ***  - 2.5   Urbino 3.6 *** 3.7 ***  - 0.2 ns 3.1 **Positive trend: ns not significant,  ? P \ 0.1, *  P \ 0.05, **  P \ 0.01, ***  P \ 0.001Negative trend: ns not significant,  V   =  P \ 0.1,    P \ 0.05,    P \ 0.01,    P \ 0.001A multidisciplinary study on the effects  1 3
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