<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<article xmlns:ns1="http://www.w3.org/1999/xlink" xmlns:ns2="http://www.w3.org/1998/Math/MathML">
    <front>
        <journal-meta>
            <journal-title-group>
                <journal-title>OENO One</journal-title>
            </journal-title-group>
        </journal-meta>
        <article-meta>
            <title-group>
                <article-title>Coincidence of temperature extremes and phenological events of grapevines</article-title>
            </title-group>
            <aff id="aff1">
                <sup>
                    <italic>1</italic>
                </sup>Institute of Terrestrial Ecosystems, ETH Zurich, Switzerland</aff>
            <aff id="aff2">
                <sup>
                    <italic>2</italic>
                </sup>Institute of Data Analysis and Process Design, Zürich University of Applied Sciences; Winterthur, Switzerland</aff>
            <aff id="aff3">
                <sup>
                    <italic>3</italic>
                </sup>Federal Department of Economic Affairs, Education and Research; Agroscope, Pully, Switzerland</aff>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Templ</surname>
                        <given-names>Barbara</given-names>
                    </name>
                    <xref ref-type="aff" rid="aff1">
                        <sup>
                            <italic>1</italic>
                        </sup>
                    </xref>
                </contrib>
                <contrib contrib-type="author">
                    <name>
                        <surname>Templ</surname>
                        <given-names>Matthias</given-names>
                    </name>
                    <xref ref-type="aff" rid="aff2">
                        <sup>
                            <italic>2</italic>
                        </sup>
                    </xref>
                </contrib>
                <contrib contrib-type="author">
                    <name>
                        <surname>Barbieri</surname>
                        <given-names>Roberto</given-names>
                    </name>
                    <xref ref-type="aff" rid="aff2">
                        <sup>
                            <italic>2</italic>
                        </sup>
                    </xref>
                </contrib>
                <contrib contrib-type="author">
                    <name>
                        <surname>Zufferey</surname>
                        <given-names>MichaelMeier1andVivan</given-names>
                    </name>
                    <xref ref-type="aff" rid="aff3">
                        <sup>
                            <italic>3</italic>
                        </sup>
                    </xref>
                </contrib>
            </contrib-group>
            <author-notes>
                <corresp id="cor1">
                    <sup>
                        <italic>*</italic>
                    </sup>corresponding author: barbara.a.templ@gmail.com</corresp>
            </author-notes>
            <abstract>
                <sec id="Abstract">
                    <title>Abstract</title>
                    <p>A growing number of studies have highlighted the consequences of climate change on agriculture, including the impacts of drought, heat waves and frost. The aim of this study was to assess the influence of temperature extremes on various phenological events of grapevine varieties in Southwest Switzerland (Leytron, Canton of Valais). We aimed to capture the occurrence of extreme events in specific years in various grapevine varieties and at different phenological phases to rank the varieties based on their sensitivity to temperature extremes and thus quantify their robustness. Phenological observations (1978–2018) of six <italic>Vitis vinifera</italic> varieties (Arvine, Chardonnay, Chasselas, Gamay, Pinot noir and Syrah) were subjected to event coincidence analysis. Extreme events were defined as values in the uppermost or lowermost percentiles of the timing of the phenophases and daily temperatures within a 30-day window before the phenophase event occurred. Significantly more extreme temperature and phenological events occurred in Leytron between 2003 and 2017 than in the earlier years, with the years 2007, 2011, 2014 and 2017 being remarkable in terms of the number of extreme coincidence events. Moreover, bud development and flowering experienced significantly more extreme coincidence events than other phenophases; however, the occurrence rate of extreme coincidence events was independent of the phenophase. Based on the total number of extreme events, the varieties did not differ in their responses to temperature extremes. Therefore, event coincidence analysis is an appropriate tool to quantify the occurrence of extreme events. The occurrence of extreme temperature events clearly affected the advancement of the timings of phenological events in various grapevines. However, there were no varietal differences in terms of response to extreme temperatures; thus, additional research is warranted to outline the best adaptation measures.</p>
                    <p>
                        <bold>Keywords: </bold>phenological sensitivity, temperature stress, occurrence, Switzerland, coincidence</p>
                </sec>
            </abstract>
        </article-meta>
    </front>
    <body>
        <sec id="Introduction">
            <title>Introduction</title>
            <p>The negative effects that climate change has on agriculture constitute a challenge, with the risk of extreme events being one of the key aspects of current climate research (<xref ref-type="bibr" rid="ref9">Choudhary, 2015</xref>; <xref ref-type="bibr" rid="ref21">FAO, 2016</xref>; <xref ref-type="bibr" rid="ref34">IPCC, 2012</xref>; <xref ref-type="bibr" rid="ref35">IPCC, 2018</xref>). The impact of climate change on viticulture has been extensively studied (<xref ref-type="bibr" rid="ref4">Bernetti <italic>et al.</italic>, 2012</xref>; <xref ref-type="bibr" rid="ref23">Fraga <italic>et al.</italic>, 2012</xref>; <xref ref-type="bibr" rid="ref54">Mozell and Thach, 2014</xref>; <xref ref-type="bibr" rid="ref76">Yzarra <italic>et al.</italic>, 2015</xref>), with studies specifically targeting viticultural suitability (<xref ref-type="bibr" rid="ref28">Hannah <italic>et al.</italic>, 2013</xref>), grape and wine quality and production (<xref ref-type="bibr" rid="ref15">de Orduña, 2010</xref>), irrigation strategies (<xref ref-type="bibr" rid="ref8">Chaves <italic>et al.</italic>, 2010</xref>), tillage treatments (<xref ref-type="bibr" rid="ref23">Fraga <italic>et al.</italic>, 2012</xref>) and grapevine growth stages in the face of changing climate (<xref ref-type="bibr" rid="ref14">de Cortázar-Atauri <italic>et al.</italic>, 2017</xref>; <xref ref-type="bibr" rid="ref27">Greer, 2013</xref>; <xref ref-type="bibr" rid="ref36">Jones and Davis, 2000</xref>). Wine production regions worldwide have experienced changes in climate structure, resulting in shifts of the timing of phenological events in the grape varieties cultivated, changes in grape chemistry and wine quality, and increases in the incidence of insect-borne diseases and grape-ripening disorders, such as berry shrivel (<xref ref-type="bibr" rid="ref40">Krasnow <italic>et al.</italic>, 2009</xref>; <xref ref-type="bibr" rid="ref73">White <italic>et al.</italic>, 2006</xref>; <xref ref-type="bibr" rid="ref79">Zufferey <italic>et al.</italic>, 2015a</xref>). According to grape producers cold and wet growing seasons, extreme heat conditions, rain during bloom and harvest delays are the most severe climate-related risks (<xref ref-type="bibr" rid="ref2">Belliveau <italic>et al.</italic>, 2006</xref>).</p>
            <p>Scientists have shown that the current climate changes have altered the frequency, intensity, spatial extent, duration and timing of extreme climate events (<xref ref-type="bibr" rid="ref34">IPCC, 2012</xref>; <xref ref-type="bibr" rid="ref35">IPCC, 2018</xref>). An extreme climate event is defined as ‘the occurrence of a value of a climate variable above (or below) a threshold value near the upper (or lower) end of the range of observed values of the variable' (<xref ref-type="bibr" rid="ref34">IPCC, 2012</xref>). There is some evidence that heat waves will occur more frequently (<xref ref-type="bibr" rid="ref48">Meehl and Tebaldi, 2004</xref>) and drought will intensify in the 21st century during some seasons (mainly during summer) and in certain areas across Europe (<xref ref-type="bibr" rid="ref32">Hov <italic>et al.</italic>, 2013</xref>). Extreme events, such as late spring frost (<xref ref-type="bibr" rid="ref42">Leolini <italic>et al.</italic>, 2018</xref>) or extreme temperature and water stress, may significantly affect plant development (<xref ref-type="bibr" rid="ref26">Gray and Brady, 2016</xref>; <xref ref-type="bibr" rid="ref30">Hatfield and Prueger, 2015</xref>).</p>
            <p>In cool regions, such as Switzerland, low temperatures often limit leaf and canopy photosynthesis and sugar production, although growth and sink activity of the fruit decrease to a greater extent than photosynthesis under low temperatures (<xref ref-type="bibr" rid="ref39">Körner, 2003</xref>). Temperature and rainfall conditions are crucial before flowering. Low temperatures (&lt; 15 °C) can lead to poor fruit set due to excess flower abortion. Extreme frost and rainy events during the flowering period can lead to substantial yield losses (<xref ref-type="bibr" rid="ref38">Keller and Koblet, 1995</xref>). Following fruit set (post flowering development), the rate and duration of cell division in the berry pericarp are controlled by the number of seeds in the berry, as well as by climatic conditions. Extreme temperatures (very cold or very warm) may inhibit cell division and expansion. Cell division is mostly under genetic control, whereas cell expansion is predominantly driven by environmental factors (<xref ref-type="bibr" rid="ref37">Keller, 2015</xref>). Extreme heat events combined with water stress sharply decrease cell expansion and yield. Nonetheless, leaf photosynthesis can adapt to the prevailing temperature at a given time during the season, particularly after flowering, and this so-called modulative temperature adaptation (<xref ref-type="bibr" rid="ref41">Larcher, 1995</xref>) may occur within a few days or, sometimes, hours. Possible modifications of substrate concentrations or RuBisCO activity and structural alterations of the bio-membranes may explain differences in adaptability to increasing temperatures across cultivars. For grapevines, local acclimation to the prevailing temperature conditions can mitigate the effects of extreme heat events during the ripening period (<xref ref-type="bibr" rid="ref78">Zufferey <italic>et al.</italic>, 2000</xref>). However, a rise in temperature is often accompanied by an increase in canopy evapotranspiration, ultimately increasing the risk of water stress and physiological disorders, such as embolism events (<italic>e.g.</italic>, disruption of the hydraulic conductivity of the vessels) (<xref ref-type="bibr" rid="ref77">Zufferey <italic>et al.</italic>, 2011</xref>), which may further inhibit plant photosynthesis and growth and reduce productivity (<xref ref-type="bibr" rid="ref12">Dayer <italic>et al.</italic>, 2017</xref>).</p>
            <p>To avoid such consequences and maintain the yield and quality of vineyard harvest, adaptation strategies (<xref ref-type="bibr" rid="ref53">Mosedale <italic>et al.</italic>, 2016</xref>; <xref ref-type="bibr" rid="ref70">van Leeuwen <italic>et al.</italic>, 2019a</xref>) are needed. Without these strategies, extreme heat is expected to have detrimental effects on vine physiology and yield, even though some varieties are more tolerant of extreme temperatures than others (<xref ref-type="bibr" rid="ref63">Santos <italic>et al.</italic>, 2020</xref>).</p>
            <p>In the Swiss Rhone catchment (Valais), permanent crop cultivation (orchards and vineyards) and livestock production are the most important agro-economic activities. Under the predicted climate change scenarios, the adverse effects of extreme heat events on Swiss vineyards are expected to become a threat in the upcoming decades (<xref ref-type="bibr" rid="ref24">Fuhrer <italic>et al.</italic>, 2014</xref>). Although there are some data on the increasing risk of spring frost damage in grapevines due to climate change in the Swiss Rhone (<xref ref-type="bibr" rid="ref49">Meier <italic>et al.</italic>, 2018</xref>), there remains a knowledge gap regarding the risk of extreme temperature events in grapevine plantations in this region.</p>
            <p>To this end, the aim of this study was to address the following questions: (1) can the effects of extreme temperature events on grapevine phenophases be captured? (2) which phenophases are the most sensitive to extreme temperature events? and (3) which grape varieties are the most robust (or least sensitive) under extreme temperatures? The observed patterns may offer novel insights to aid wine producers in decision-making on vineyard management in the face of climate change.</p>
        </sec>
        <sec id="Materials-and-methods">
            <title>Materials and methods</title>
            <sec id="1.-Study-area-and-phenological-data">
                <title>1. Study area and phenological data</title>
                <p>Data from six grapevine varieties (<italic>Vitis vinifera</italic> L. Arvine, Chardonnay, Chasselas, Gamay, Pinot noir and Syrah) cultivated at the experimental vineyard of Agroscope in Leytron (LEY; Canton of Valais, 46°10′ N, 7°12′ E; 485 m a.s.l.; Figure 1) were analysed.</p>
                <p>The Canton of is one of the driest regions of Switzerland, with approximately 550 mm of mean annual precipitation in its central Rhône valley. Almost 30 % of the area of Leytron is used for agricultural purposes. Experts from the Plant Sciences Institute collected phenological observations (1978–2018) at Agroscope in Changins (Figure 1) and observations at the vineyard of Agroscope are still ongoing. The complete list of phenophases is presented in Supplementary Information (Table S1). Phenological observations were obtained from adult vines (30 plants per variety) with identical canopy and soil management. Vines were planted in the Guyot pruning system (vertical shoot position trellis system) at a planting density of 5,500 vines/ha. The experimental site (5 ha) in LEY has very stony soil (gravelly, &gt; 60 % large elements, stones, blocks and gravel) and deep soil (vine root depth, &gt; 2.5 m), with an estimated water-holding capacity of 150 mm. The number of observations varied among years and phenophases (SI, Figure S1). All 36 studied phenophases were defined according to the Biologische Bundesanstalt Bundessortenamt und Chemische Industrie (BBCH) scale (<xref ref-type="bibr" rid="ref6">Bloesch and Viret, 2008</xref>; <xref ref-type="bibr" rid="ref43">Lorenz <italic>et al.</italic>, 1994</xref>; <xref ref-type="bibr" rid="ref50">Meier, 1997</xref>).</p>
                <p/>
                <p>
                    <fig>
                        <label>Table</label>
                        <caption>
                            <title>Figure 1. Map showing the location of the study site and data sources in the Canton of Valais, Switzerland</title>
                            <p>Phenological data were collected from a vineyard located in Leytron (LEY); meteorological data were gathered from LEY, Sion (SIO) and Evionnaz (EVI).</p>
                        </caption>
                        <graphic mimetype="image" ns1:type="simple" ns1:href="image1.jpg"/>
                    </fig>
                </p>
                <fig>
                    <label>Table</label>
                    <caption>
                        <title>Figure 1. Map showing the location of the study site and data sources in the Canton of Valais, Switzerland</title>
                        <p>Phenological data were collected from a vineyard located in Leytron (LEY); meteorological data were gathered from LEY, Sion (SIO) and Evionnaz (EVI).</p>
                    </caption>
                    <graphic mimetype="image" ns1:type="simple" ns1:href="image1.jpg"/>
                </fig>
                <p/>
            </sec>
            <sec id="2.-Meteorological-data">
                <title>2. Meteorological data</title>
                <p>Datasets at the study site in Leytron (LEY) were required in order to determine the coincidence between the occurrence of extreme temperature events and the selected phenological phases of <italic>V. vinifera</italic>, daily minimum, mean and maximum temperature. Temperature at 2 m above ground level (a.g.l.) has been recorded by the Agrometeo Weather Station within the vineyard of interest since 2003 (available at </p>
                <p>
                    <ext-link ext-link-type="url" ns1:href="http://www.agrometeo.ch/de/meteorology/datas">http://www.agrometeo.ch/de/meteorology/datas</ext-link>
                </p>
                <p>) and these data were used in the present analysis. Additional temperature data from MeteoSwiss (</p>
                <p>
                    <ext-link ext-link-type="url" ns1:href="https://gate.meteoswiss.ch/idaweb/">https://gate.meteoswiss.ch/idaweb/</ext-link>
                </p>
                <p>) were also collected from the neighbouring weather stations at Sion (SIO) and Evionnaz (EVI), where daily temperature measurements at 2 m a.g.l. have been obtained since 1976 and 1993 respectively. Finally, the daily minimum, mean and maximum temperature values in LEY were estimated using single- and bivariate linear regression models (</p>
                <p>
                    <inline-formula>
                        <ns2:math>
                            <ns2:mi>L</ns2:mi>
                            <ns2:mi>E</ns2:mi>
                            <ns2:mi>Y</ns2:mi>
                            <ns2:mo>~</ns2:mo>
                            <ns2:mi>S</ns2:mi>
                            <ns2:mi>I</ns2:mi>
                            <ns2:mi>O</ns2:mi>
                        </ns2:math>
                    </inline-formula>
                </p>
                <p> and </p>
                <p>
                    <inline-formula>
                        <ns2:math>
                            <ns2:mi>L</ns2:mi>
                            <ns2:mi>E</ns2:mi>
                            <ns2:mi>Y</ns2:mi>
                            <ns2:mo>~</ns2:mo>
                            <ns2:mi>S</ns2:mi>
                            <ns2:mi>I</ns2:mi>
                            <ns2:mi>O</ns2:mi>
                            <ns2:mo>+</ns2:mo>
                            <ns2:mi>E</ns2:mi>
                            <ns2:mi>V</ns2:mi>
                            <ns2:mi>I</ns2:mi>
                        </ns2:math>
                    </inline-formula>
                </p>
                <p>) for 1978–1992 and 1993–2002 respectively. Agrometeorological observations for the years 2003–2018 were used.</p>
                <p>As temperatures at SIO and EVI were highly correlated, observations at the latter station were partialled out from the linear regression (</p>
                <p>
                    <inline-formula>
                        <ns2:math>
                            <ns2:mi>E</ns2:mi>
                            <ns2:mi>V</ns2:mi>
                            <ns2:mi>I</ns2:mi>
                            <ns2:mo>~</ns2:mo>
                            <ns2:mi>S</ns2:mi>
                            <ns2:mi>I</ns2:mi>
                            <ns2:mi>O</ns2:mi>
                        </ns2:math>
                    </inline-formula>
                </p>
                <p>). Finally, the remaining daily residuals were subjected to bivariate linear regression (</p>
                <p>
                    <inline-formula>
                        <ns2:math>
                            <ns2:mi>L</ns2:mi>
                            <ns2:mi>E</ns2:mi>
                            <ns2:mi>Y</ns2:mi>
                            <ns2:mi> </ns2:mi>
                            <ns2:mo>~</ns2:mo>
                            <ns2:mi> </ns2:mi>
                            <ns2:mi>S</ns2:mi>
                            <ns2:mi>I</ns2:mi>
                            <ns2:mi>O</ns2:mi>
                            <ns2:mo>+</ns2:mo>
                            <ns2:mi>r</ns2:mi>
                            <ns2:mi>E</ns2:mi>
                            <ns2:mi>V</ns2:mi>
                            <ns2:mi>I</ns2:mi>
                        </ns2:math>
                    </inline-formula>
                </p>
                <p>, where </p>
                <p>
                    <inline-formula>
                        <ns2:math>
                            <ns2:mi>r</ns2:mi>
                            <ns2:mi>E</ns2:mi>
                            <ns2:mi>V</ns2:mi>
                            <ns2:mi>I</ns2:mi>
                            <ns2:mo>=</ns2:mo>
                            <ns2:mi>E</ns2:mi>
                            <ns2:mi>V</ns2:mi>
                            <ns2:mi>I</ns2:mi>
                            <ns2:mo>-</ns2:mo>
                            <ns2:mover accent="true">
<ns2:mrow>
    <ns2:mi>E</ns2:mi>
    <ns2:mi>V</ns2:mi>
    <ns2:mi>I</ns2:mi>
</ns2:mrow>
<ns2:mo>^</ns2:mo>
                            </ns2:mover>
                        </ns2:math>
                    </inline-formula>
                </p>
                <p>, with </p>
                <p>
                    <inline-formula>
                        <ns2:math>
                            <ns2:mover accent="true">
<ns2:mrow>
    <ns2:mi>E</ns2:mi>
    <ns2:mi>V</ns2:mi>
    <ns2:mi>I</ns2:mi>
</ns2:mrow>
<ns2:mo>^</ns2:mo>
                            </ns2:mover>
                        </ns2:math>
                    </inline-formula>
                </p>
                <p> being the predicted temperature in Evionnaz).</p>
                <p>For temperature estimation, overlapping observations were used from 2003 to 2014. A random sample of 60 % of these overlapping observations was used for calibration of the linear regression models, and the remaining 40 % was used to evaluate temperature estimation based on root mean square error (RMSE) and Nash–Sutcliffe efficiency [NSE; (<xref ref-type="bibr" rid="ref55">Nash and Sutcliffe, 1970</xref>)] index. The RMSE values were between 0.54 and 1.00 °C and the NSE values were between 0.98 and 0.99, indicating a satisfactory temperature reconstruction for LEY (Table 1). The average temperature time series of the whole period (1978–2018) is shown in SI, Figure S2.</p>
                <p>
                    <table-wrap position="float" orientation="portait">
                        <label>Table</label>
                        <caption>
                            <title>Table 1. Root mean square error (RMSE) and Nash–Sutcliffe efficiency (NSE) index for the single and bivariate linear regression models of daily minimum, mean and maximum temperature values in Leytron (LEY).</title>
                        </caption>
                        <alternatives>
                            <table style="table table-bordered table-striped affichage-tableau">
<col width="25%"/>
<col width="25%"/>
<col width="25%"/>
<col width="25%"/>
<col width="25%"/>
<col width="25%"/>
<col width="25%"/>
<col width="25%"/>
<thead>
    <tr>
        <td xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xs="http://www.w3.org/2001/XMLSchema" xsi:type="xs:string">titre du tableau </td>
    </tr>
</thead>
<tr>
    <th>Measure of accuracy</th>
    <th>Variable</th>
    <th>LEY ~ <italic>SIO</italic> (°C)</th>
    <th>LEY ~ <italic>SIO </italic>+ <italic>rEVI</italic> (°C)</th>
</tr>
<tr>
    <th>RMSE</th>
    <th>Daily minimum temperature</th>
    <th>1.0003</th>
    <th>0.08462</th>
</tr>
<tr>
    <th>NSE</th>
    <th>Daily minimum temperature</th>
    <th>0.9809</th>
    <th>0.9864</th>
</tr>
<tr>
    <th>RMSE</th>
    <th>Daily mean temperature</th>
    <th>0.6383</th>
    <th>0.5350</th>
</tr>
<tr>
    <th>NSE</th>
    <th>Daily mean temperature</th>
    <th>0.9938</th>
    <th>0.9956</th>
</tr>
<tr>
    <th>RMSE</th>
    <th>Daily maximum temperature</th>
    <th>0.9117</th>
    <th>0.8100</th>
</tr>
<tr>
    <th>NSE</th>
    <th>Daily maximum temperature</th>
    <th>0.9899</th>
    <th>0.9920</th>
</tr>
                            </table>
                        </alternatives>
                        <table-wrap-foot>
                            <fn>
<p>The corresponding temperatures in Sion (SIO) and Evionnaz (EVI) were used as explanatory variables, with the latter being partialled-out and only the residual (<italic>rEVI</italic>) used.</p>
                            </fn>
                        </table-wrap-foot>
                    </table-wrap>
                </p>
            </sec>
            <sec id="3.-Data-analysis">
                <title>3. Data analysis</title>
                <p>To characterise various phenophases (<xref ref-type="bibr" rid="ref6">Bloesch and Viret, 2008</xref>), phenological trends were calculated for each grape variety (Figure 2). The trend lines and the corresponding confidence interval were estimated based on a generalised additive model (<xref ref-type="bibr" rid="ref29">Hastie and Tibshirani, 1990</xref>) with a smoothing function using thin plate regression splines (<xref ref-type="bibr" rid="ref75">Wood, 2003</xref>). As an example, exploratory analysis for Syrah between temperature and doy of the leaf unfolding phenophase were made (Figure 3).</p>
                <sec id="3.1-Quantifying-the-occurrence-of-extreme-events">
                    <title>3.1 Quantifying the occurrence of extreme events</title>
                    <p>Event coincidence analysis was used (<xref ref-type="bibr" rid="ref16">Donges <italic>et al.</italic>, 2011</xref>; <xref ref-type="bibr" rid="ref17">Donges <italic>et al.</italic>, 2016</xref>) to identify whether the timing of extremely early or late phenological events was in accordance with the periods of extremely low or high daily temperature conditions. To achieve this, first, the occurrence of extreme events was quantified, and then the coincidence between the extreme events captured in the temperature and phenological data was identified (Figure 4C), as described by <xref ref-type="bibr" rid="ref65">Siegmund <italic>et al.</italic> (2016)</xref> with minor modifications (see Supplementary Information for details). We compared the Siegmund method to two other methods (quantile and robust covariance methods) to determine its novelty and assess what type of additional new information it can provide. Of note, mean temperature in this study indicates the arithmetic mean of the mean temperature values in a specific time window before the phenological event occurred (from 33 days before until 3 days before the occurrence of the phenological event).</p>
                    <p>Using the quantile method, the (0.1 and 0.9) quantiles of the mean temperature and the quantile of the phenological data were calculated and extreme values were identified (indicated within the lower right and top left corner of Figure 4A). This approach is an over-simplification of the Siegmund method, because all temperature values are no longer evaluated on a daily basis and are instead summarised within a given time window (Figures 3 and 4).</p>
                    <p>Alternatively, the robust covariance estimation method was applied to identify extreme values. We estimated the bivariate robust covariance (minimum covariance determinant; <xref ref-type="bibr" rid="ref62">Rousseeuw, 1999</xref>) of the mean temperature and day-of-year (doy) values of the phenophase in each year to detect atypical observations (Figure 4B). Outliers in the 0.8 quantiles of the chi-square distribution with 36 degrees of freedom (1978–2018, 36 years), which appear in the lower quarter of the ellipse (the year with mean temperature higher than the median of temperature values of all years, but doy lower than the median doy) indicate early extremes. Meanwhile, observations in the upper left corner of Figure 4B indicate (if any) late extremes.</p>
                </sec>
                <sec id="3.2.-Estimation-of-years-with-high-coincidence-of-extreme-events">
                    <title>3.2. Estimation of years with high coincidence of extreme events</title>
                    <p>An overview of the extreme coincidences in Syrah at each studied year is visualised in Figure 5. Corresponding figures for all other studied varieties are available in Supplementary Information (SI, Figures S3 - S7). One-sided Poisson test was applied to identify the years with significantly more extreme events than others. For this test, the coincident extreme events of all phenological phases were counted for each grapevine variety and each year and then divided by the total number of phenological phases for each grapevine variety within a year. Our null hypothesis was that the rate of extreme events is 0.2 (20 %) and the alternative hypothesis was that this rate is higher than 0.2 (20 %). The rate is based on the definition of quantiles (top and bottom 10 %). Based on the upper confidence interval obtained from the Poisson test, we were able to examine whether the occurrence rate of an extreme event in a year was significantly higher than 0.2 (indicated by black or grey bars in Figure 7). The higher the rate, the more the extreme event at a given phenophase in a given year.</p>
                </sec>
                <sec id="3.3.-Estimation-of-the-occurrence-rate-per-phenophase">
                    <title>3.3. Estimation of the occurrence rate per phenophase</title>
                    <p>Both the number and rate of occurrence of extreme events per phenophase (<xref ref-type="bibr" rid="ref6">Bloesch and Viret, 2008</xref>) were estimated to determine the phenophase that was the most susceptible to temperature extremes (Table 3). The rate of extreme event occurrence was defined as the number of coinciding extreme events per phenophase divided by the total number of coinciding extreme events. The following phenophases were investigated: 0: bud development (BBCH 0-9), 1: leaf development (BBCH 10-16), 5: inflorescence emergence (BBCH 53-59), 6: flowering (BBCH 61-69), 7: fruit development (BBCH 71-79) and 8: ripening of berries (BBCH 81-89). The codes of phenophases follow the BBCH classification (<xref ref-type="bibr" rid="ref6">Bloesch and Viret, 2008</xref>; see SI, Table S1 for more details). Pairwise proportional tests (<xref ref-type="bibr" rid="ref56">Newcombe, 1998</xref>) were applied to test for differences in occurrence of coincidence rates between growth stages. p-values were corrected for multiple testing with method Holm (<xref ref-type="bibr" rid="ref31">Holm, 1979</xref>). Our null hypothesis (H<sub>0</sub>) was that the rate of extreme coincidences is 20 %, and if the rate is higher than this value, H<sub>0</sub> is rejected, indicating significance.</p>
                </sec>
                <sec id="3.4.-Calculation-of-the-sensitivity-of-the-grapevine">
                    <title>3.4. Calculation of the sensitivity of the grapevine</title>
                    <p>For demonstrative purposes, the coincidences of extreme phenological and temperature events of six grapevine varieties in one of the warmest years on record (2017) and in a usual year (1999; with only a few extreme coincidence events per year confirmed by Figure S3-S7) are shown in Figures 6A and 6B respectively. To evaluate the sensitivity of grapevine varieties to extreme temperature events, the total number and rate of occurrence of extreme events were calculated for each variety. The occurrence rate was calculated by factoring in the number of years in which observations were made. Our hypothesis was that the extreme events in a time series, the robust the variety is to extreme temperatures. A value of 0 indicated a very robust variety, meaning that it is robust against extreme heat, as no extreme phenological event coincided with an extreme temperature event in its dataset. Meanwhile, a value of 1 indicated a very sensitive variety. Extreme events of ‘doy only’ (extreme phenological event without coincidence with an extreme temperature event) were not considered in this analysis. To determine differences across varieties based on the occurrence rate, we conducted Poisson exact test for two samples (<xref ref-type="bibr" rid="ref22">Fay, 2010</xref>).</p>
                </sec>
            </sec>
        </sec>
        <sec id="Results">
            <title>Results</title>
            <sec id="1.-Phenological-characteristics">
                <title>1. Phenological characteristics</title>
                <p>This section provides an overview of the phenological trends found in our study (Figure 2), specifically in response to mean temperature (Figure 3). An example is shown in Figure 2, demonstrating that the timing of leaf unfolding (BBCH 10; <xref ref-type="bibr" rid="ref6">Bloesch and Viret, 2008</xref>) has become earlier. We found that almost all studied phenophases showed advancing trends in all varieties within the study period (results not shown). </p>
                <p/>
                <p>
                    <fig>
                        <label>Table</label>
                        <caption>
                            <title>Figure 2. Annual variations (1978–2018) in the timing of the leaf unfolding (BBCH 10; <xref ref-type="bibr" rid="ref6">Bloesch and Viret, 2008</xref>) phenophase in Leytron, Switzerland, for different grapevine varieties. </title>
                            <p>Abbreviations: doy: day of the year.</p>
                        </caption>
                        <graphic mimetype="image" ns1:type="simple" ns1:href="image2.jpg"/>
                    </fig>
                </p>
                <fig>
                    <label>Table</label>
                    <caption>
                        <title>Figure 2. Annual variations (1978–2018) in the timing of the leaf unfolding (BBCH 10; <xref ref-type="bibr" rid="ref6">Bloesch and Viret, 2008</xref>) phenophase in Leytron, Switzerland, for different grapevine varieties. </title>
                        <p>Abbreviations: doy: day of the year.</p>
                    </caption>
                    <graphic mimetype="image" ns1:type="simple" ns1:href="image2.jpg"/>
                </fig>
                <p/>
                <p>We found a relatively strong negative linear correlation (Pearson correlation, r = -0.62) between doy of the phenophase (here leaf unfolding, BBCH 10: <xref ref-type="bibr" rid="ref6">Bloesch and Viret, 2008</xref>) and mean temperature within the given time window (Figure 3A). For instance, in 2017, very early leaf unfolding can be observed, because the average temperature before the event was very high. Interestingly, however, there is no correlation (r = -0.05) between the temperature values within this time window and the leaf unfolding event, indicating that fluctuations in temperature hardly influenced the timing of leaf unfolding (Figure 3B). Similarly, there are strong correlations between mean temperatures and phenological events for other grape varieties (results not shown), thus supporting our speculations.</p>
                <p/>
                <p>
                    <fig>
                        <label>Table</label>
                        <caption>
                            <title>Figure 3. Exploratory analysis for Syrah as an example. </title>
                            <p>Day of the year (doy) of the leaf unfolding phenophase (BBCH 10; <xref ref-type="bibr" rid="ref6">Bloesch and Viret, 2008</xref>) in response to mean temperature (A) and standard deviation of temperature values from 33 days before until 3 days before the event in each year (B). Blue line represents the ordinary least squares (OLS) regression line and the grey shaded areas correspond to the confidence intervals.</p>
                        </caption>
                        <graphic mimetype="image" ns1:type="simple" ns1:href="image3.jpg"/>
                    </fig>
                </p>
                <fig>
                    <label>Table</label>
                    <caption>
                        <title>Figure 3. Exploratory analysis for Syrah as an example. </title>
                        <p>Day of the year (doy) of the leaf unfolding phenophase (BBCH 10; <xref ref-type="bibr" rid="ref6">Bloesch and Viret, 2008</xref>) in response to mean temperature (A) and standard deviation of temperature values from 33 days before until 3 days before the event in each year (B). Blue line represents the ordinary least squares (OLS) regression line and the grey shaded areas correspond to the confidence intervals.</p>
                    </caption>
                    <graphic mimetype="image" ns1:type="simple" ns1:href="image3.jpg"/>
                </fig>
                <p/>
            </sec>
            <sec id="2.-Occurrence-of-extreme-events">
                <title>2. Occurrence of extreme events</title>
                <sec id="2.1.-Occurrence-of-extreme-events-in-specific-years">
                    <title>2.1. Occurrence of extreme events in specific years</title>
                    <p>In this section, the results of the comparison of various methods applied to identify the coincidence of extreme events in specific years are given. As an example, the results of the analysis of the leaf unfolding data (BBCH 10) for Syrah and mean temperatures within the given time window (section Data analysis) using various methods are summarised.</p>
                    <p>The quantile method (Figure 4A) identified fewer extreme coincidences than the other methods. It captured only 2017 as a year of extremely early coincidence events based on the mean temperature and timing of leaf unfolding; however, it classified 1979 and 1980 as the years of late coincidence events in which cold temperatures delayed leaf unfolding in Syrah.</p>
                    <p>The robust covariance estimation method (Figure 4B) detected only 2011 as an unusual year. In this year, daily mean temperatures before leaf unfolding were high, but leaf unfolding occurred relatively late. Therefore, this method is useful for outlier detection - to assess whether the relationship between temperature and phenological events is unusual - as it is suitable for event coincidence analysis </p>
                    <p>The modified Siegmund method (Figure 4C) identified the most extreme coincidence events (4 early and 4 late extreme coincidences), due to it being more sophisticated and analytical than the other two methods (see Supplementary Information for details).</p>
                    <p/>
                    <p>
                        <fig>
                            <label>Table</label>
                            <caption>
<title>Figure 4. Comparison of results of the three methods [quantile, robust covariance estimation and Siegmund methods (<xref ref-type="bibr" rid="ref65">Siegmund <italic>et al.</italic>, 2016</xref>)] to identify extreme (early or late) events. </title>
<p>As an example, the results of the analysis of the leaf unfolding data for Syrah are shown. Quantile method (Figure 4A): the (0.1 and 0.9) quantiles are indicated in grey lines for the phenological (horizontal dashed lines) and climatological (vertical dashed lines) time series. Extremely early events are located in the lower right-hand corner, whilst extremely late events are located in the top left-hand corner. Robust covariance estimation (Figure 4B): any outlier occurring outside the 0.8 tolerance ellipse is considered an extreme event. Siegmund method (Figure 4C): coincidence between the extreme (early or late) events is captured based on the method described by <xref ref-type="bibr" rid="ref65">Siegmund <italic>et al.</italic> (2016)</xref> with some modifications.</p>
                            </caption>
                            <graphic mimetype="image" ns1:type="simple" ns1:href="image4.jpg"/>
                        </fig>
                    </p>
                    <fig>
                        <label>Table</label>
                        <caption>
                            <title>Figure 4. Comparison of results of the three methods [quantile, robust covariance estimation and Siegmund methods (<xref ref-type="bibr" rid="ref65">Siegmund <italic>et al.</italic>, 2016</xref>)] to identify extreme (early or late) events. </title>
                            <p>As an example, the results of the analysis of the leaf unfolding data for Syrah are shown. Quantile method (Figure 4A): the (0.1 and 0.9) quantiles are indicated in grey lines for the phenological (horizontal dashed lines) and climatological (vertical dashed lines) time series. Extremely early events are located in the lower right-hand corner, whilst extremely late events are located in the top left-hand corner. Robust covariance estimation (Figure 4B): any outlier occurring outside the 0.8 tolerance ellipse is considered an extreme event. Siegmund method (Figure 4C): coincidence between the extreme (early or late) events is captured based on the method described by <xref ref-type="bibr" rid="ref65">Siegmund <italic>et al.</italic> (2016)</xref> with some modifications.</p>
                        </caption>
                        <graphic mimetype="image" ns1:type="simple" ns1:href="image4.jpg"/>
                    </fig>
                    <p/>
                </sec>
                <sec id="2.2.-Occurrence-of-extreme-coincidence-events-per-phenophase">
                    <title>2.2. Occurrence of extreme coincidence events per phenophase</title>
                    <p>In this section, we provide an overview of the occurrence of extreme coincidence events per phenophase in order to identify the stages that are more susceptible to extreme temperatures than others. We identified more extreme coincidence events with the Siegmund method than with the other two methods together. Pairwise proportional tests between the relative occurrence of extremes between growth stages showed significant differences between bud development and inflorescence merge (corrected p-value: 0.049) and bud development and ripening of berries (corrected p-value: 0.023); for example (see also Table 2), 55/171 (relative occurrence of coincidence extremes in bud development growth stage) was significantly larger than 99/ = 478 (related to inflorescence merge), even after p-values correction for multiple testing. The rate of occurrence of extreme coincidence events was almost equal for all the other phenophases in the Siegmund method. The number of extreme coincidence events identified by the quantile method varied across different phenophases; for example, it did not detect ample extreme coincidences at the bud development stage. The robust covariance estimation method revealed a very similar rate of occurrences amongst phenophases; however, it detected almost 50 % fewer coincidence events than the Siegmund method (Table 2).</p>
                    <p>
                        <table-wrap position="float" orientation="portait">
                            <label>Table</label>
                            <caption>
<title>Table 2. Number of extreme coincidence events and rate of occurrence of extreme coincidence events per phenophase [according to the BBCH scale (<xref ref-type="bibr" rid="ref6">Bloesch and Viret, 2008</xref>)], estimated using various methods [quantile, robust covariance estimation and Siegmund methods (<xref ref-type="bibr" rid="ref65">Siegmund <italic>et al.</italic>, 2016</xref>)]. </title>
                            </caption>
                            <alternatives>
<table style="table table-bordered table-striped affichage-tableau">
    <col width="12%"/>
    <col width="12%"/>
    <col width="12%"/>
    <col width="12%"/>
    <col width="12%"/>
    <col width="12%"/>
    <col width="12%"/>
    <col width="12%"/>
    <col width="12%"/>
    <col width="12%"/>
    <col width="12%"/>
    <col width="12%"/>
    <thead>
        <tr>
            <td xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xs="http://www.w3.org/2001/XMLSchema" xsi:type="xs:string">titre du tableau </td>
        </tr>
    </thead>
    <tr>
        <th/>
        <th>Bud <break/>development</th>
        <th>Leaf <break/>development</th>
        <th>Inflorescence <break/>emergence</th>
        <th>Flowering</th>
        <th>Fruit<break/>development</th>
        <th>Ripening <break/>of berries</th>
        <th>Total</th>
    </tr>
    <tr>
        <th>growth stage</th>
        <th>0-9</th>
        <th>10-14</th>
        <th>53-57</th>
        <th>61-69</th>
        <th>71-77</th>
        <th>81-89</th>
        <th>0-89</th>
    </tr>
    <tr>
        <th>count</th>
        <th>171</th>
        <th>503</th>
        <th>478</th>
        <th>550</th>
        <th>393</th>
        <th>629</th>
        <th>2724</th>
    </tr>
    <tr>
        <th>extremes (Siegmund)</th>
        <th>55</th>
        <th>110</th>
        <th>99</th>
        <th>139</th>
        <th>88</th>
        <th>128</th>
        <th>619</th>
    </tr>
    <tr>
        <th>extremes (Quantile)</th>
        <th>8</th>
        <th>34</th>
        <th>11</th>
        <th>32</th>
        <th>15</th>
        <th>50</th>
        <th>150</th>
    </tr>
    <tr>
        <th>extremes (RobCov)</th>
        <th>28</th>
        <th>66</th>
        <th>55</th>
        <th>58</th>
        <th>54</th>
        <th>79</th>
        <th>340</th>
    </tr>
    <tr>
        <th>occurence (Siegmund)</th>
        <th>22.53</th>
        <th>15.32</th>
        <th>14.51</th>
        <th>17.7</th>
        <th>15.69</th>
        <th>14.25</th>
        <th>100</th>
    </tr>
    <tr>
        <th>occurence (Quantile)</th>
        <th>14.94</th>
        <th>21.58</th>
        <th>7.35</th>
        <th>18.57</th>
        <th>12.19</th>
        <th>25.38</th>
        <th>100</th>
    </tr>
    <tr>
        <th>occurence (RobCov)</th>
        <th>21.03</th>
        <th>16.86</th>
        <th>14.78</th>
        <th>13.55</th>
        <th>17.65</th>
        <th>16.13</th>
        <th>100</th>
    </tr>
</table>
                            </alternatives>
                            <table-wrap-foot>
<fn>
    <p/>
</fn>
                            </table-wrap-foot>
                        </table-wrap>
                    </p>
                    <p>The years 2007, 2011, 2014 and 2017 were remarkable (Figure 5) in terms of the number of extreme coincidence events during many phenophases. Figure 5 provides an overview of the extreme coincidences (vertical bar) in Syrah during each studied year. Corresponding figures for all other studied varieties are available in Supplementary Information (Figures S3-S7).</p>
                    <p/>
                    <p>
                        <fig>
                            <label>Table</label>
                            <caption>
<title>Figure 5. Coincidences of extreme phenological and temperature events in Syrah. </title>
<p>The polygon lines indicate the daily mean temperatures of the corresponding years. The coloured areas indicate extreme coincidences [according to Siegmund <italic>et al.</italic>, (2016)] within the time window of the year before the occurrence of the phenological event. The colour of the bars corresponds to the direction of the extreme phenological shift (red bars: earlier doy; blue bars: later doy). The number of bars within the colour-shaded area corresponds to the number of extreme coincidence events. All phenological events considered in the analysis are listed in SI in Table S1.</p>
                            </caption>
                            <graphic mimetype="image" ns1:type="simple" ns1:href="image5.jpg"/>
                        </fig>
                    </p>
                    <fig>
                        <label>Table</label>
                        <caption>
                            <title>Figure 5. Coincidences of extreme phenological and temperature events in Syrah. </title>
                            <p>The polygon lines indicate the daily mean temperatures of the corresponding years. The coloured areas indicate extreme coincidences [according to Siegmund <italic>et al.</italic>, (2016)] within the time window of the year before the occurrence of the phenological event. The colour of the bars corresponds to the direction of the extreme phenological shift (red bars: earlier doy; blue bars: later doy). The number of bars within the colour-shaded area corresponds to the number of extreme coincidence events. All phenological events considered in the analysis are listed in SI in Table S1.</p>
                        </caption>
                        <graphic mimetype="image" ns1:type="simple" ns1:href="image5.jpg"/>
                    </fig>
                    <p/>
                </sec>
                <sec id="2.3.-Occurrence-of-extreme-coincidence-events-per-grapevine-variety">
                    <title>2.3. Occurrence of extreme coincidence events per grapevine variety</title>
                    <p>In 2017, all grapevine varieties exhibited extreme phenological responses to temperatures throughout the year. The most extreme coincidence events appeared from AprilAugust (doy: 95–195), when the phenological events of all varieties were shifted to an earlier doy (red areas in Figure 6A). For comparison, the same Figure was generated for the year 1999 (Figure 6B), which demonstrates the distribution of data of a ‘usual’ year. Only some extreme coincidence events were detected in 1999, when the phenological events of the plants were shifted to a later doy (blue areas in Figure 6B).</p>
                    <p/>
                    <p>
                        <fig>
                            <label>Table</label>
                            <caption>
<title>Figure 6. Example of coincidences of extreme phenological and temperature events of six grapevine varieties in (A) 2017, one of the warmest years on record and in (B) 1999, a usual year.</title>
<p>The coloured areas indicate extreme coincidences (according to <xref ref-type="bibr" rid="ref65">Siegmund <italic>et al.</italic>, 2016</xref>) within the time window of the year before the occurrence of the phenological event. The colour of the bars corresponds to the direction of the extreme phenological shift (red bars: earlier doy; blue bars: later doy). The number of bars within the coloured area corresponds to the number of extreme coincidence events. All phenological events considered in the analysis are listed in Supplementary Information (Table S1).</p>
                            </caption>
                            <graphic mimetype="image" ns1:type="simple" ns1:href="image6.jpg"/>
                        </fig>
                    </p>
                    <fig>
                        <label>Table</label>
                        <caption>
                            <title>Figure 6. Example of coincidences of extreme phenological and temperature events of six grapevine varieties in (A) 2017, one of the warmest years on record and in (B) 1999, a usual year.</title>
                            <p>The coloured areas indicate extreme coincidences (according to <xref ref-type="bibr" rid="ref65">Siegmund <italic>et al.</italic>, 2016</xref>) within the time window of the year before the occurrence of the phenological event. The colour of the bars corresponds to the direction of the extreme phenological shift (red bars: earlier doy; blue bars: later doy). The number of bars within the coloured area corresponds to the number of extreme coincidence events. All phenological events considered in the analysis are listed in Supplementary Information (Table S1).</p>
                        </caption>
                        <graphic mimetype="image" ns1:type="simple" ns1:href="image6.jpg"/>
                    </fig>
                    <p/>
                    <p>No significant differences were observed in terms of the occurrence of extreme coincidence events between the grapevine varieties studied. Based on our results (Table 3, Poisson exact test for two samples), the tested varieties were similarly affected by temperature extremes in the Cantone of Valais, and it is therefore not possible to state whether a specific variety is more robust.</p>
                    <p>
                        <table-wrap position="float" orientation="portait">
                            <label>Table</label>
                            <caption>
<title>Table 3. Occurrence of extreme coincidence events (1978–2018) affecting grapevines in Leytron. </title>
                            </caption>
                            <alternatives>
<table style="table table-bordered table-striped affichage-tableau">
    <col width="14%"/>
    <col width="14%"/>
    <col width="14%"/>
    <col width="14%"/>
    <col width="14%"/>
    <col width="14%"/>
    <col width="14%"/>
    <col width="14%"/>
    <col width="14%"/>
    <col width="14%"/>
    <col width="14%"/>
    <thead>
        <tr>
            <td xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xs="http://www.w3.org/2001/XMLSchema" xsi:type="xs:string">titre du tableau </td>
        </tr>
    </thead>
    <tr>
        <th/>
        <th>Arvine</th>
        <th>Chardonnay</th>
        <th>Chasselas</th>
        <th>Gamay</th>
        <th>Pinot noir</th>
        <th>Syrah</th>
    </tr>
    <tr>
        <th>No. of years</th>
        <th>11</th>
        <th>41</th>
        <th>41</th>
        <th>19</th>
        <th>41</th>
        <th>41</th>
    </tr>
    <tr>
        <th>No. of observations</th>
        <th>171</th>
        <th>573</th>
        <th>554</th>
        <th>315</th>
        <th>567</th>
        <th>544</th>
    </tr>
    <tr>
        <th>No. of extremes (Siegmund)</th>
        <th>54</th>
        <th>125</th>
        <th>125</th>
        <th>81</th>
        <th>115</th>
        <th>119</th>
    </tr>
    <tr>
        <th>No. of extremes (Quantile)</th>
        <th>10</th>
        <th>37</th>
        <th>27</th>
        <th>14</th>
        <th>26</th>
        <th>36</th>
    </tr>
    <tr>
        <th>No. of extremes (RobCov)</th>
        <th>22</th>
        <th>70</th>
        <th>65</th>
        <th>54</th>
        <th>63</th>
        <th>66</th>
    </tr>
    <tr>
        <th>Occurence rate (Siegmund)</th>
        <th>4.91</th>
        <th>3.05</th>
        <th>3.05</th>
        <th>4.26</th>
        <th>2.8</th>
        <th>2.9</th>
    </tr>
    <tr>
        <th>Occurence rate (Quantile)</th>
        <th>0.91</th>
        <th>0.9</th>
        <th>0.66</th>
        <th>0.74</th>
        <th>0.63</th>
        <th>0.88</th>
    </tr>
    <tr>
        <th>Occurence rate (RobCov)</th>
        <th>2</th>
        <th>1.71</th>
        <th>1.59</th>
        <th>2.84</th>
        <th>1.54</th>
        <th>1.61</th>
    </tr>
</table>
                            </alternatives>
                            <table-wrap-foot>
<fn>
    <p>The number of extreme coincidences per year is the rate of occurrence of extreme coincidence events. The higher the sensitivity of a variety, the higher the occurrence rate; conversely, the lower the value, the more robust the variety. The value 0 indicates a very robust variety, meaning that it can withstand extreme heat, as no extreme phenological event coincided with an extreme temperature event in its dataset.</p>
</fn>
                            </table-wrap-foot>
                        </table-wrap>
                    </p>
                    <p>Pairwise proportional tests showed only significant differences between Arvine and Pinot noir, although this result should be treated with caution as only 11 years were observed for Arvine. When only the last 11 years of all wine varieties are analysed, there are (also) no significant differences between the coincidence rates of these two wine varieties (rate Arvine 11/171 <italic>versus</italic> Pinot noir 12/199). The results of the Poisson test show the years when the grapevines experienced a significant rate of extreme coincidences (black bars in Figure 7). Higher rates correspond to more phenophases that coincided with the extreme temperature events in a given year in a given grapevine variety.</p>
                    <p/>
                    <p>
                        <fig>
                            <label>Table</label>
                            <caption>
<title>Figure 7. Distribution of the number of extreme phenological events (all 36 BBCH phenophase) in the studied grapevine varieties over the study period (1978–2018) in Leytron. </title>
<p>The height of the bars represents the number of extreme coincidence events. Black bars indicate greater than 20 % rate of extreme events (p = 0.05); grey bars indicate non-significant years. Higher rates correspond to more phenophases that coincided with the extreme temperature events in a given year in a given grapevine variety. Data at the beginning of the study period are missing for Arvine (1978–2007) and Gamay (1978–1999).</p>
                            </caption>
                            <graphic mimetype="image" ns1:type="simple" ns1:href="image7.jpg"/>
                        </fig>
                    </p>
                    <fig>
                        <label>Table</label>
                        <caption>
                            <title>Figure 7. Distribution of the number of extreme phenological events (all 36 BBCH phenophase) in the studied grapevine varieties over the study period (1978–2018) in Leytron. </title>
                            <p>The height of the bars represents the number of extreme coincidence events. Black bars indicate greater than 20 % rate of extreme events (p = 0.05); grey bars indicate non-significant years. Higher rates correspond to more phenophases that coincided with the extreme temperature events in a given year in a given grapevine variety. Data at the beginning of the study period are missing for Arvine (1978–2007) and Gamay (1978–1999).</p>
                        </caption>
                        <graphic mimetype="image" ns1:type="simple" ns1:href="image7.jpg"/>
                    </fig>
                    <p/>
                    <p>Consistent with our expectations, significantly more coincident extreme events (in both phenological and temperature datasets) occurred after 2000 (Figure 7). Similar graphs are available for the quantile and robust covariance estimation methods in Supplementary Information (Figures S8 and S9).</p>
                </sec>
            </sec>
        </sec>
        <sec id="Discussion">
            <title>Discussion</title>
            <p>The results in Figure 2 show that, on average, flowering takes place earlier and earlier. When comparing the respective temperatures of a given year before the flowering event, it is possible to observe an increase in temperature before the flowering event over the years (see, for example, Figure 3); this is obviously negatively correlated with the day of the year in which the phenological events took place; which is not surprising and is consistent with many studies. Climate-induced phenological shifts have been observed across Switzerland (<xref ref-type="bibr" rid="ref5">Bigler and Bugmann, 2018</xref>). Scientists have shown that the current climate changes have led to changes in the frequency, intensity, spatial extent, duration and timing of extreme climate events throughout the world (<xref ref-type="bibr" rid="ref34">IPCC, 2012</xref>; <xref ref-type="bibr" rid="ref35">IPCC, 2018</xref>). Data from Austria, France (<xref ref-type="bibr" rid="ref10">Chuine <italic>et al.</italic>, 2004</xref>; <xref ref-type="bibr" rid="ref20">Duchêne <italic>et al.</italic>, 2010</xref>; <xref ref-type="bibr" rid="ref47">Maurer <italic>et al.</italic>, 2011</xref>), Germany (<xref ref-type="bibr" rid="ref51">Menzel, 2005</xref>) and the Swiss Alps (<xref ref-type="bibr" rid="ref7">Büntgen <italic>et al.</italic>, 2006</xref>) have confirmed that the year 2003 was an unprecedented extreme year (<xref ref-type="bibr" rid="ref25">García-Herrera <italic>et al.</italic>, 2010</xref>). Many parts of Europe experienced record-breaking temperatures during July 2006, exceeding the values recorded in 2003 (<xref ref-type="bibr" rid="ref11">Dankers and Hiederer, 2008</xref>). Furthermore, the winter season of 2006–2007 was estimated to be the warmest in the previous 500 years (<xref ref-type="bibr" rid="ref44">Luterbacher <italic>et al.</italic>, 2007</xref>). These extreme years are also confirmed by meteorolgical data set from Sion (SIO) and Evionnaz (both in Switzerland) that we used for this study. </p>
            <p>Generally, temperature is a key factor affecting plant development (<xref ref-type="bibr" rid="ref72">Went, 1953</xref>). The ultimate impact of temperature stress on yield or reproductive fitness depends on the developmental stage at which the high temperature stress occurs (<xref ref-type="bibr" rid="ref26">Gray and Brady, 2016</xref>; <xref ref-type="bibr" rid="ref30">Hatfield and Prueger, 2015</xref>), as well as on the variety (<xref ref-type="bibr" rid="ref46">Martínez-Lüscher <italic>et al.</italic>, 2016</xref>). Water stress also increases the vine's susceptibility to heat stress and drought during the bloom period is especially detrimental to fruit set, if it coincides with a heat period (<xref ref-type="bibr" rid="ref68">Srinivasan and Mullins, 1981</xref>).  The upper temperature limit for maximum yield formation in grapevines seems to be at 35 °C (<xref ref-type="bibr" rid="ref37">Keller, 2015</xref>). Higher temperatures (&gt; 35 °C) can produce a so-called heat-shock and protein deformation in berries with sunburn symptoms as an expression of oxidative damage from a combination of high light intensity and high temperature (<xref ref-type="bibr" rid="ref33">Iba, 2002</xref>). The acclimation to low temperatures (&lt; 15°C) - known as chilling acclimation - during the season leads to higher leaf photosynthetic rates and water use efficiency at lower temperatures, because of a downward shift in the optimum temperature for photosynthesis (<xref ref-type="bibr" rid="ref78">Zufferey <italic>et al.</italic>, 2000</xref>). Reproductive development is more vulnerable to chilling stress during the pre-flowering stage (<xref ref-type="bibr" rid="ref37">Keller, 2015</xref>), because fruit sink activity is more sensitive to temperature and carbon shortage at this time than shoot sink activity. Previous studies mainly showed correlations between climatic variables (such as temperature) and flowering times, mostly by linear correlation or liner regression (<italic>e.g.</italic>, <xref ref-type="bibr" rid="ref51">Menzel, 2005</xref>) or model non-linear responses to temperature (<italic>e.g.</italic>, <xref ref-type="bibr" rid="ref13">de Cortázar-Atauri <italic>et al.</italic>, 2010</xref>). An exception is the study from <xref ref-type="bibr" rid="ref65">Siegmund <italic>et al.</italic> (2016)</xref>, who first used appropriate techniques to identify periods prior to the growing season, where extreme temperatures events are statistically related to extreme flowering dates. In this study, we carried out an event coincident analysis (modified from <xref ref-type="bibr" rid="ref65">Siegmund <italic>et al.</italic>, 2016</xref>) to identify the way in which extreme temperature events control the timing of grapevine phenophases. Furthermore, we applied two other methods (quantile and robust covariance estimation) to compare the results of the modified Siegmund method and prove its novelty. </p>
            <p>Using the phenological and temperature datasets, we identified the years when extreme events in both datasets coincided with one another. We showed that most of these coincidental events occurred after 2000 (mainly in 2007, 2011, 2014 and 2017; see Figures 4 and 7), which is the warmest decade on record since the beginning of the modern meteorological records (<xref ref-type="bibr" rid="ref74">WMO, 2013</xref>; <xref ref-type="bibr" rid="ref1">Arguez <italic>et al.</italic>, 2020</xref>).</p>
            <p>The analysis and results confirmed that our modified Siegmund method is more sophisticated than the other two methods, bringing added value to the detection of extreme coincidence events, which provides us new knowledge about the extreme events in the studied Swiss vineyard. By using this method, we discovered that bud development and flowering experienced more extreme coincidence events than the other phenophases and that bud development has significantly more extreme coincidence events than inflorescence merge and ripening of berries. In particular, the much larger influence of temperature on bud development compared to other phenophases has also been shown by other studies, even if they focused on other types of wine from other regions (<xref ref-type="bibr" rid="ref45">Malheiro <italic>et al.</italic>, 2013</xref>). Lethal freeze injury to buds is decisive during winter and spring in terms of potential yield. Low temperatures lead to cold acclimation during winter. Nevertheless, warm episodes during the acclimation period induce rapid de-acclimation, causing problems when a freezing event follows a mild winter, for example. Osmotic adjustment in buds, especially the adjustment of osmotically active sugars (sucrose, glucose and fructose), is essential for good acclimation, because it reduces cell dehydration and inhibits the nucleation and growth of ice crystals in bud cells (<xref ref-type="bibr" rid="ref37">Keller, 2015</xref>).  Deficient C- and N-reserves in permanent grapevine organs and a sudden increase in temperature in early spring can lead to early budbreak, increasing the risk of bud freeze and loss of fruit formation (<xref ref-type="bibr" rid="ref80">Zufferey <italic>et al.</italic>, 2015b</xref>).  </p>
            <p>We did not find any significant differences in the sensitivity of the tested varieties based on the occurrence rate of extreme coincidence events. Thus, we could only rank them based on the total number of extreme coincidence events they experienced during 1978–2018. Disregarding the two wine varieties Arvine and Gamay, from which we had less data, Chasselas and Chardonnay experienced the most extreme events (<xref ref-type="bibr" rid="ref61">Robinson <italic>et al.</italic>, 2012</xref>; <xref ref-type="bibr" rid="ref69">Töpfer <italic>et al.</italic>, 2009</xref>); these varieties can therefore be ranked as the most sensitive of the studied ones, which is in line with conclusions drawn by <xref ref-type="bibr" rid="ref61">Robinson <italic>et al.</italic> (2012)</xref> and <xref ref-type="bibr" rid="ref69">Töpfer <italic>et al.</italic> (2009)</xref>. <xref ref-type="bibr" rid="ref78">Zufferey <italic>et al.</italic> (2000)</xref> reported that photosynthetic rate was observed to increase with increasing temperature for Chasselas, compared with other European cultivars such as Riesling. Even when modulative temperature adaptation occurred (<xref ref-type="bibr" rid="ref41">Larcher, 1995</xref>), with increasing water scarcity and extreme temperatures hydraulic failure was observed in the leaf and petiole vessels (xylem tissues) of Chasselas (<xref ref-type="bibr" rid="ref77">Zufferey <italic>et al.</italic>, 2011</xref>). It is also known that for Pinot noir, the climatic niche is narrow, and the average growing-season temperature for this variety is relatively low (<xref ref-type="bibr" rid="ref67">Spring <italic>et al.</italic>, 2010</xref>). Early-ripening varieties such as Chasselas, Pinot noir and Chardonnay could become more widespread globally, if they were to be cultivated in new, more poleward regions (such as Canada, northern Europe and Tasmania; <xref ref-type="bibr" rid="ref52">Morales-Castilla <italic>et al.</italic>, 2020</xref>). </p>
            <p>The time series for Arvine and Gamay were too short, and when all the wine varieties were broken down to this short time, our results were not significant. From literature, it is known that Gamay is grown in cool-climate regions such as Canada and Switzerland (<xref ref-type="bibr" rid="ref61">Robinson <italic>et al.</italic>, 2012</xref>). While the white varieties (Chardonnay, Chasselas and Arvine<bold>)</bold> are poorly suited to the dry conditions (Zufferey <italic>et al.</italic> 2020), the cultivar Arvine is particularly sensitive to temperature increase and water scarcity events, thus influencing its aromatic compounds. When heat-susceptible cultivars, such as Arvine, are grown in warm climates or in hot growing seasons with intense solar radiation, they often develop poor aromatic compounds in berries and have a negative impact on wine quality (<xref ref-type="bibr" rid="ref81">Zufferey <italic>et al.</italic>, 2020</xref>). More data on Gamay and Arvine would be necessary to prove these statements using our methodology. Syrah (and Pinot noir) were the least sensitive of all the wine varieties examined in this study (see Table 3 and Figure 7). Late-ripening varieties, such as Syrah, Grenache and Mourvedre, are projected to become much more widespread in current global winegrowing regions if temperatures rise by 2 °C (<xref ref-type="bibr" rid="ref52">Morales-Castilla <italic>et al.</italic>, 2020</xref>).</p>
            <p>Several attempts have been made to evaluate drought tolerance and to rank grape varieties (<xref ref-type="bibr" rid="ref59">Parker <italic>et al.</italic>, 2011</xref>; <xref ref-type="bibr" rid="ref58">Parker <italic>et al.</italic>, 2013</xref>), in order to help the variety best adapted to climate change. However, these data are not yet available for all . Wine growers could therefore maintain their income by replacing the grapevines they cultivate with other varieties or crops (<xref ref-type="bibr" rid="ref18">Duchêne, 2016</xref>; <xref ref-type="bibr" rid="ref19">Duchêne <italic>et al.</italic>, 2014</xref>).</p>
            <p>Although grapevines have several survival strategies (<italic>e.g.</italic>, deep root systems or efficient stomatal control), viticulture is strongly dependent on climate (<xref ref-type="bibr" rid="ref23">Fraga <italic>et al.</italic>, 2012</xref>). With more extreme events being expected in Europe (<xref ref-type="bibr" rid="ref3">Beniston <italic>et al.</italic>, 2007</xref>; <xref ref-type="bibr" rid="ref32">Hov <italic>et al.</italic>, 2013</xref>; <xref ref-type="bibr" rid="ref34">IPCC, 2012</xref>; <xref ref-type="bibr" rid="ref35">IPCC, 2018</xref>), additional methods will be required in order to adapt to and mitigate climate change (<xref ref-type="bibr" rid="ref66">Soja <italic>et al.</italic>, 2011</xref>; <xref ref-type="bibr" rid="ref70">van Leeuwen <italic>et al.</italic>, 2019a</xref>; <xref ref-type="bibr" rid="ref71">van Leeuwen <italic>et al.</italic>, 2019b</xref>). Adaptation to higher temperatures include changing plant materials and modifying viticultural techniques. <xref ref-type="bibr" rid="ref70">van Leeuwen <italic>et al.</italic> (2019a)</xref> have outlined the best available practices to make vineyards more resilient to drought, including planting drought resistant plant material (rootstocks), modifying the training system, or selecting soils with greater water-holding capacity. </p>
        </sec>
        <sec id="Conclusions">
            <title>Conclusions</title>
            <p>The main purpose of the study was to capture the coincidences of extreme temperature and phenological events of grape varieties in Leytron, Switzerland. The comparison of various methods showed that the methodology of <xref ref-type="bibr" rid="ref65">Siegmund <italic>et al.</italic> (2016)</xref> seems to be the most appropriate for studying extreme coincidences. The results showed that there were much more such events between 2003 and 2017 than in earlier years (1978–2018). Some phenophases (bud burst and flowering) are less robust in response to extreme temperature, but only significance results were obtained between bud development and inflorescence merge and ripening of berries. While we found differences, we did not find any statistically significant evidence of some grape varieties being more robust or sensitive to temperature extremes than other varieties. However, it might be possible to obtain statistically significant results when comparing grapevine varieties using the proposed methodology on larger data sets from other regions. The observed patterns in our study could provide new insights for winemakers to help make decisions about vineyard management in the face of climate change. However, in order to generalise the statements and findings, this research and methodology would need to be applied to other datasets from different grape varieties in other regions.</p>
        </sec>
    </body>
    <back>
        <ref-list>
            <ref id="ref1">
                <label>1</label>
                <mixed-citation>
                    <name>
                        <surname>Arguez</surname>
                        <given-names>A.</given-names>
                    </name>, <name>
                        <surname>Hurley</surname>
                        <given-names>S.</given-names>
                    </name>, <name>
                        <surname>Inamdar</surname>
                        <given-names>A.</given-names>
                    </name>, <name>
                        <surname>Mahoney</surname>
                        <given-names>L.</given-names>
                    </name>, <name>
                        <surname>Sanchez-Lugo</surname>
                        <given-names>A.</given-names>
                    </name>, <name>
                        <surname>Yang</surname>
                        <given-names>L.</given-names>
                    </name>, <year>2020</year>. <article-title>Should we expect each year in the next decade (2019-2028) to be ranked among the top 10 warmest years globally? Bulletin of the American Meteorological Society, E655-E663</article-title>. <source>https://doi.org/10.1175/BAMS-D-19-0215.1</source>.</mixed-citation>
            </ref>
            <ref id="ref2">
                <label>2</label>
                <mixed-citation>
                    <name>
                        <surname>Belliveau</surname>
                        <given-names>S.</given-names>
                    </name>, <name>
                        <surname>Smit</surname>
                        <given-names>B.</given-names>
                    </name>, <name>
                        <surname>Bradshaw</surname>
                        <given-names>B.</given-names>
                    </name>, <year>2006</year>. <article-title>Multiple exposures and dynamic vulnerability: Evidence from the grape industry in the Okanagan Valley, Canada</article-title>. <source>Global Environmental Change, 16(4), 364–378. https://doi.org/10.1016/j.gloenvcha.2006.03.003</source>.</mixed-citation>
            </ref>
            <ref id="ref3">
                <label>3</label>
                <mixed-citation>
                    <name>
                        <surname>Beniston</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Stephenson</surname>
                        <given-names>D. B.</given-names>
                    </name>, <name>
                        <surname>Christensen</surname>
                        <given-names>O. B.</given-names>
                    </name>, <name>
                        <surname>Ferro</surname>
                        <given-names>C. A. T.</given-names>
                    </name>, <name>
                        <surname>Frei</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Goyette</surname>
                        <given-names>S.</given-names>
                    </name>, <name>
                        <surname>Halsnaes</surname>
                        <given-names>K.</given-names>
                    </name>, <name>
                        <surname>Holt</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Jylhä</surname>
                        <given-names>K.</given-names>
                    </name>, <name>
                        <surname>Koffi</surname>
                        <given-names>B.</given-names>
                    </name>, <name>
                        <surname>Palutikof</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Schöll</surname>
                        <given-names>R.</given-names>
                    </name>, <name>
                        <surname>Semmler</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Woth</surname>
                        <given-names>K.</given-names>
                    </name>, <year>2007</year>. <article-title>Future extreme events in European climate: An exploration of regional climate model projections</article-title>. <source>Climatic Change, 81(1), 71–95. https://doi.org/10.1007/s10584-006-9226-z</source>.</mixed-citation>
            </ref>
            <ref id="ref4">
                <label>4</label>
                <mixed-citation>
                    <name>
                        <surname>Bernetti</surname>
                        <given-names>I.</given-names>
                    </name>, <name>
                        <surname>Menghini</surname>
                        <given-names>S.</given-names>
                    </name>, <name>
                        <surname>Marinelli</surname>
                        <given-names>N.</given-names>
                    </name>, <name>
                        <surname>Sacchelli</surname>
                        <given-names>S.</given-names>
                    </name>, <name>
                        <surname>Sottini</surname>
                        <given-names>V. A.</given-names>
                    </name>, <year>2012</year>. <article-title>Assessment of climate change impact on viticulture: Economic evaluations and adaptation strategies analysis for the Tuscan wine sector</article-title>. <source>Wine Economics and Policy, 1(1), 73–86. https://doi.org/10.1016/j.wep.2012.11.002</source>.</mixed-citation>
            </ref>
            <ref id="ref5">
                <label>5</label>
                <mixed-citation>
                    <name>
                        <surname>Bigler</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Bugmann</surname>
                        <given-names>H.</given-names>
                    </name>, <year>2018</year>. <article-title>Climate-induced shifts in leaf unfolding and frost risk of European trees and schrubs</article-title>. <source>Scientific Reports, 8, 9865. https://doi.org/10.1038/s41598-018-27893-1</source>.</mixed-citation>
            </ref>
            <ref id="ref6">
                <label>6</label>
                <mixed-citation>
                    <name>
                        <surname>Bloesch</surname>
                        <given-names>B.</given-names>
                    </name>, <name>
                        <surname>Viret</surname>
                        <given-names>O.</given-names>
                    </name>, <year>2008</year>. <article-title>Stades phénologiques repères de la vigne</article-title>. <source>Revue Suisse Viticulture, Arboriculture, Horticulture, 40(6), 1-4.</source>.</mixed-citation>
            </ref>
            <ref id="ref7">
                <label>7</label>
                <mixed-citation>
                    <name>
                        <surname>Büntgen</surname>
                        <given-names>U.</given-names>
                    </name>, <name>
                        <surname>Frank</surname>
                        <given-names>D. C.</given-names>
                    </name>, <name>
                        <surname>Nievergelt</surname>
                        <given-names>D.</given-names>
                    </name>, <name>
                        <surname>Esper</surname>
                        <given-names>J.</given-names>
                    </name>, <year>2006</year>. <article-title>Summer Temperature Variations in the European Alps, a.d</article-title>. <source>755–2004. Journal of Climate, 19(21), 5606–5623. https://doi.org/10.1175/JCLI3917.1</source>.</mixed-citation>
            </ref>
            <ref id="ref8">
                <label>8</label>
                <mixed-citation>
                    <name>
                        <surname>Chaves</surname>
                        <given-names>M. M.</given-names>
                    </name>, <name>
                        <surname>Zarrouk</surname>
                        <given-names>O.</given-names>
                    </name>, <name>
                        <surname>Francisco</surname>
                        <given-names>R.</given-names>
                    </name>, <name>
                        <surname>Costa</surname>
                        <given-names>J. M.</given-names>
                    </name>, <name>
                        <surname>Santos</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Regalado</surname>
                        <given-names>A. P.</given-names>
                    </name>, <name>
                        <surname>Rodrigues</surname>
                        <given-names>M. L.</given-names>
                    </name>, <name>
                        <surname>Lopes</surname>
                        <given-names>C. M.</given-names>
                    </name>, <year>2010</year>. <article-title>Grapevine under deficit irrigation: Hints from physiological and molecular data</article-title>. <source>Annals of Botany, 105(5), 661–676. https://doi.org/10.1093/aob/mcq030</source>.</mixed-citation>
            </ref>
            <ref id="ref9">
                <label>9</label>
                <mixed-citation>
                    <name>
                        <surname>Choudhary</surname>
                        <given-names>V.</given-names>
                    </name>, <year>2015</year>. <article-title>Agricultural risk management in the face of climate change</article-title>. <source>The World Bank, No. AUS5773, 1–60. http://documents.worldbank.org/curated/en/787511468170682886/Agricultural-risk-management-in-the-face-of-climate-change</source>.</mixed-citation>
            </ref>
            <ref id="ref10">
                <label>10</label>
                <mixed-citation>
                    <name>
                        <surname>Chuine</surname>
                        <given-names>I.</given-names>
                    </name>, <name>
                        <surname>Yiou</surname>
                        <given-names>P.</given-names>
                    </name>, <name>
                        <surname>Viovy</surname>
                        <given-names>N.</given-names>
                    </name>, <name>
                        <surname>Seguin</surname>
                        <given-names>B.</given-names>
                    </name>, <name>
                        <surname>Daux</surname>
                        <given-names>V.</given-names>
                    </name>, <name>
                        <surname>Ladurie</surname>
                        <given-names>E. L. R.</given-names>
                    </name>, <year>2004</year>. <article-title>Grape ripening as a past climate indicator</article-title>. <source>Nature, 432(7015), 289–290. https://doi.org/10.1038/432289a</source>.</mixed-citation>
            </ref>
            <ref id="ref11">
                <label>11</label>
                <mixed-citation>
                    <name>
                        <surname>Dankers</surname>
                        <given-names>R.</given-names>
                    </name>, <name>
                        <surname>Hiederer</surname>
                        <given-names>R.</given-names>
                    </name>, <year>2008</year>. <article-title>Extreme Temperatures and Precipitation in Europe: Analysis of a High-Resolution Climate Change Scenario (JRC Scientific and Technical Reports ISSN 1018-5593; p</article-title>. <source>82). https://esdac.jrc.ec.europa.eu/ESDB_Archive/eusoils_docs/other/EUR23291EN.pdf</source>.</mixed-citation>
            </ref>
            <ref id="ref12">
                <label>12</label>
                <mixed-citation>
                    <name>
                        <surname>Dayer</surname>
                        <given-names>S.</given-names>
                    </name>, <name>
                        <surname>Peña</surname>
                        <given-names>J. P.</given-names>
                    </name>, <name>
                        <surname>Gindro</surname>
                        <given-names>K.</given-names>
                    </name>, <name>
                        <surname>Torregrosa</surname>
                        <given-names>L.</given-names>
                    </name>, <name>
                        <surname>Voinesco</surname>
                        <given-names>F.</given-names>
                    </name>, <name>
                        <surname>Martínez</surname>
                        <given-names>L.</given-names>
                    </name>, <name>
                        <surname>Prieto</surname>
                        <given-names>J. A.</given-names>
                    </name>, <name>
                        <surname>Zufferey</surname>
                        <given-names>V.</given-names>
                    </name>, <year>2017</year>. <article-title>Changes in leaf stomatal conductance, petiole hydraulics and vessel morphology in grapevine (Vitis vinifera cv. Chasselas) under different light and irrigation regimes. Functional Plant Biology, 44(7), 679–693. https://doi.org/10.1071/FP16041</article-title>.  .</mixed-citation>
            </ref>
            <ref id="ref13">
                <label>13</label>
                <mixed-citation>
                    <name>
                        <surname>de Cortázar-Atauri</surname>
                        <given-names>I. G.</given-names>
                    </name>, <name>
                        <surname>Chuine</surname>
                        <given-names>I.</given-names>
                    </name>, <name>
                        <surname>Donatelli</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Parker</surname>
                        <given-names>A.</given-names>
                    </name>, <name>
                        <surname>van Leeuwen</surname>
                        <given-names>C.</given-names>
                    </name>, <year>2010</year>. <article-title>A curvilinear process-based phenological model to study impacts of climatic change on grapevine (Vitis vinifera L.)</article-title>. <source>Proceedings of Agro 2010: the 11th ESA Congress, Montpellier, France (Agropolis International Editions: Montpellier), 907–908.</source>.</mixed-citation>
            </ref>
            <ref id="ref14">
                <label>14</label>
                <mixed-citation>
                    <name>
                        <surname>de Cortázar-Atauri</surname>
                        <given-names>I. G.</given-names>
                    </name>, <name>
                        <surname>Duchêne</surname>
                        <given-names>E.</given-names>
                    </name>, <name>
                        <surname>Destrac-Irvine</surname>
                        <given-names>A.</given-names>
                    </name>, <name>
                        <surname>Barbeau</surname>
                        <given-names>G.</given-names>
                    </name>, <name>
                        <surname>de Rességuier</surname>
                        <given-names>L.</given-names>
                    </name>, <name>
                        <surname>Lacombe</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Parker</surname>
                        <given-names>A. K.</given-names>
                    </name>, <name>
                        <surname>Saurin</surname>
                        <given-names>N.</given-names>
                    </name>, <name>
                        <surname>van Leeuwen</surname>
                        <given-names>C.</given-names>
                    </name>, <year>2017</year>. <article-title>Grapevine phenology in France: From past observations to future evolutions in the context of climate change</article-title>. <source>OENO One, 51(2), 115–126. https://doi.org/10.20870/oeno-one.2017.51.2.1622</source>.</mixed-citation>
            </ref>
            <ref id="ref15">
                <label>15</label>
                <mixed-citation>
                    <name>
                        <surname>de Orduña</surname>
                        <given-names>R. M.</given-names>
                    </name>, <year>2010</year>. <article-title>Effects of climate change on grape and wine quality and production</article-title>. <source>Food Research International, 43(7), 1844–1855. https://doi.org/10.1016/j.foodres.2010.05.001</source>.</mixed-citation>
            </ref>
            <ref id="ref16">
                <label>16</label>
                <mixed-citation>
                    <name>
                        <surname>Donges</surname>
                        <given-names>J. F.</given-names>
                    </name>, <name>
                        <surname>Donner</surname>
                        <given-names>R. V.</given-names>
                    </name>, <name>
                        <surname>Trauth</surname>
                        <given-names>M. H.</given-names>
                    </name>, <name>
                        <surname>Marwan</surname>
                        <given-names>N.</given-names>
                    </name>, <name>
                        <surname>Schellnhuber</surname>
                        <given-names>H. -J.</given-names>
                    </name>, <name>
                        <surname>Kurths</surname>
                        <given-names>J.</given-names>
                    </name>, <year>2011</year>. <article-title>Nonlinear detection of paleoclimate-variability transitions possibly related to human evolution</article-title>. <source>Proceedings of the National Academy of Sciences, 108(51), 20422–20427. https://doi.org/10.1073/pnas.1117052108</source>.</mixed-citation>
            </ref>
            <ref id="ref17">
                <label>17</label>
                <mixed-citation>
                    <name>
                        <surname>Donges</surname>
                        <given-names>J. F.</given-names>
                    </name>, <name>
                        <surname>Schleussner</surname>
                        <given-names>C. -F.</given-names>
                    </name>, <name>
                        <surname>Siegmund</surname>
                        <given-names>J. F.</given-names>
                    </name>, <name>
                        <surname>Donner</surname>
                        <given-names>R. V.</given-names>
                    </name>, <year>2016</year>. <article-title>Event coincidence analysis for quantifying statistical interrelationships between event time series</article-title>. <source>The European Physical Journal Special Topics, 225(3), 471–487. https://doi.org/10.1140/epjst/e2015-50233-y</source>.</mixed-citation>
            </ref>
            <ref id="ref18">
                <label>18</label>
                <mixed-citation>
                    <name>
                        <surname>Duchêne</surname>
                        <given-names>E.</given-names>
                    </name>, <year>2016</year>. <article-title>How can grapevine genetics contribute to the adaptation to climate change? OENO One, 50(3)</article-title>. <source>https://doi.org/10.20870/oeno-one.2016.50.3.98</source>.</mixed-citation>
            </ref>
            <ref id="ref19">
                <label>19</label>
                <mixed-citation>
                    <name>
                        <surname>Duchêne</surname>
                        <given-names>E.</given-names>
                    </name>, <name>
                        <surname>Huard</surname>
                        <given-names>F.</given-names>
                    </name>, <name>
                        <surname>Pieri</surname>
                        <given-names>P.</given-names>
                    </name>, <year>2014</year>. <article-title>Grapevine and climate change: What adaptations of plant material and training systems should be anticipate? Journal International Des Sciences de La Vigne et Du Vin, Special Laccave, 61–69.</article-title>.  .</mixed-citation>
            </ref>
            <ref id="ref20">
                <label>20</label>
                <mixed-citation>
                    <name>
                        <surname>Duchêne</surname>
                        <given-names>E.</given-names>
                    </name>, <name>
                        <surname>Huard</surname>
                        <given-names>F.</given-names>
                    </name>, <name>
                        <surname>Dumas</surname>
                        <given-names>V.</given-names>
                    </name>, <name>
                        <surname>Schneider</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Merdinoglu</surname>
                        <given-names>D.</given-names>
                    </name>, <year>2010</year>. <article-title>The challenge of adapting grapevine varieties to climate change</article-title>. <source>Climate Research, 41(3), 193–204. https://doi.org/10.3354/cr00850</source>.</mixed-citation>
            </ref>
            <ref id="ref21">
                <label>21</label>
                <mixed-citation>
                    <name>
                        <surname>FAO</surname>
                        <given-names></given-names>
                    </name>, <year>2016</year>. <article-title>Climate Change and Food Security: Risks and Responses</article-title>. <source>Food and Agriculture Organizations of the United Nations. http://www.fao.org/policy-support/resources/resources-details/en/c/427091/</source>.</mixed-citation>
            </ref>
            <ref id="ref22">
                <label>22</label>
                <mixed-citation>
                    <name>
                        <surname>Fay</surname>
                        <given-names>M. P.</given-names>
                    </name>, <year>2010</year>. <article-title>Two-sided exact tests and matching confidence intervals for discrete data</article-title>. <source>R Journal, 2(1), 53-58. https://doi.org/10.32614/RJ-2010-008</source>.</mixed-citation>
            </ref>
            <ref id="ref23">
                <label>23</label>
                <mixed-citation>
                    <name>
                        <surname>Fraga</surname>
                        <given-names>H.</given-names>
                    </name>, <name>
                        <surname>Malheiro</surname>
                        <given-names>A. C.</given-names>
                    </name>, <name>
                        <surname>Moutinho‐Pereira</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Santos</surname>
                        <given-names>J. A.</given-names>
                    </name>, <year>2012</year>. <article-title>An overview of climate change impacts on European viticulture</article-title>. <source>Food and Energy Security, 1(2), 94–110. https://doi.org/10.1002/fes3.14</source>.</mixed-citation>
            </ref>
            <ref id="ref24">
                <label>24</label>
                <mixed-citation>
                    <name>
                        <surname>Fuhrer</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Smith</surname>
                        <given-names>P.</given-names>
                    </name>, <name>
                        <surname>Gobiet</surname>
                        <given-names>A.</given-names>
                    </name>, <year>2014</year>. <article-title>Implications of climate change scenarios for agriculture in alpine regions—A case study in the Swiss Rhone catchment</article-title>. <source>Science of The Total Environment, 493, 1232–1241. https://doi.org/10.1016/j.scitotenv.2013.06.038</source>.</mixed-citation>
            </ref>
            <ref id="ref25">
                <label>25</label>
                <mixed-citation>
                    <name>
                        <surname>García-Herrera</surname>
                        <given-names>R.</given-names>
                    </name>, <name>
                        <surname>Díaz</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Trigo</surname>
                        <given-names>R. M.</given-names>
                    </name>, <name>
                        <surname>Luterbacher</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Fischer</surname>
                        <given-names>E. M.</given-names>
                    </name>, <year>2010</year>. <article-title>A Review of the European Summer Heat Wave of 2003</article-title>. <source>Critical Reviews in Environmental Science and Technology, 40(4), 267–306. https://doi.org/10.1080/10643380802238137</source>.</mixed-citation>
            </ref>
            <ref id="ref26">
                <label>26</label>
                <mixed-citation>
                    <name>
                        <surname>Gray</surname>
                        <given-names>S. B.</given-names>
                    </name>, <name>
                        <surname>Brady</surname>
                        <given-names>S. M.</given-names>
                    </name>, <year>2016</year>. <article-title>Plant developmental responses to climate change</article-title>. <source>Developmental biology, 419 (1), 64-77. https://doi.org/10.1016/j.ydbio.2016.07.023 </source>.</mixed-citation>
            </ref>
            <ref id="ref27">
                <label>27</label>
                <mixed-citation>
                    <name>
                        <surname>Greer</surname>
                        <given-names>D. H.</given-names>
                    </name>, <year>2013</year>. <article-title>The impact of high temperatures on Vitis vinifera cv</article-title>. <source>Semillon grapevine performance and berry ripening. Frontiers in Plant Science, 4. https://doi.org/10.3389/fpls.2013.00491</source>.</mixed-citation>
            </ref>
            <ref id="ref28">
                <label>28</label>
                <mixed-citation>
                    <name>
                        <surname>Hannah</surname>
                        <given-names>L.</given-names>
                    </name>, <name>
                        <surname>Roehrdanz</surname>
                        <given-names>P. R.</given-names>
                    </name>, <name>
                        <surname>Ikegami</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Shepard</surname>
                        <given-names>A. V.</given-names>
                    </name>, <name>
                        <surname>Shaw</surname>
                        <given-names>M. R.</given-names>
                    </name>, <name>
                        <surname>Tabor</surname>
                        <given-names>G.</given-names>
                    </name>, <name>
                        <surname>Zhi</surname>
                        <given-names>L.</given-names>
                    </name>, <name>
                        <surname>Marquet</surname>
                        <given-names>P. A.</given-names>
                    </name>, <name>
                        <surname>Hijmans</surname>
                        <given-names>R. J.</given-names>
                    </name>, <year>2013</year>. <article-title>Climate change, wine, and conservation</article-title>. <source>Proceedings of the National Academy of Sciences, 110(17), 6907-6912. https://doi.org/10.1073/pnas.1210127110</source>.</mixed-citation>
            </ref>
            <ref id="ref29">
                <label>29</label>
                <mixed-citation>
                    <name>
                        <surname>Hastie</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Tibshirani</surname>
                        <given-names>R.</given-names>
                    </name>, <year>1990</year>. <article-title>Generalized Additive Models</article-title>. <source>Chapman and Hall/CRC. ISBN: 978-0412343902</source>.</mixed-citation>
            </ref>
            <ref id="ref30">
                <label>30</label>
                <mixed-citation>
                    <name>
                        <surname>Hatfield</surname>
                        <given-names>J. L.</given-names>
                    </name>, <name>
                        <surname>Prueger</surname>
                        <given-names>J. H.</given-names>
                    </name>, <year>2015</year>. <article-title>Temperature extremes: Effect on plant growth and development</article-title>. <source>Weather and Climate Extremes, 10, 4–10. https://doi.org/10.1016/j.wace.2015.08.001</source>.</mixed-citation>
            </ref>
            <ref id="ref31">
                <label>31</label>
                <mixed-citation>
                    <name>
                        <surname>Holm</surname>
                        <given-names>S.</given-names>
                    </name>, <year>1979</year>. <article-title>A simple sequentially rejective multiple test procedure</article-title>. <source>Scandinavian Journal of Statistics, 6, 65–70. https://doi.org/10.2307/4615733</source>.</mixed-citation>
            </ref>
            <ref id="ref32">
                <label>32</label>
                <mixed-citation>
                    <name>
                        <surname>Hov</surname>
                        <given-names>O.</given-names>
                    </name>, <name>
                        <surname>Cubasch</surname>
                        <given-names>U.</given-names>
                    </name>, <name>
                        <surname>Fischer</surname>
                        <given-names>E.</given-names>
                    </name>, <name>
                        <surname>Höppe</surname>
                        <given-names>P.</given-names>
                    </name>, <name>
                        <surname>Iversen</surname>
                        <given-names>T.</given-names>
                    </name>, <year>2013</year>. <article-title>Extreme Weather Events in Europe: Preparing for climate change adaptation</article-title>. <source>Norvegian Meteorological Institute. https://climate-adapt.eea.europa.eu/metadata/publications/extreme-weather-events-in-europe-preparing-for-climate-change-adaptation</source>.</mixed-citation>
            </ref>
            <ref id="ref33">
                <label>33</label>
                <mixed-citation>
                    <name>
                        <surname>Iba</surname>
                        <given-names>K.</given-names>
                    </name>, <year>2002</year>. <article-title>Acclimative response to temperature stress in higher plants: approaches of gene engineering for temperature tolerance</article-title>. <source>Annual Review of Plant Biology, 53, 225-245. https://doi.org/10.1146/annurev.arplant.53.100201.160729</source>.</mixed-citation>
            </ref>
            <ref id="ref34">
                <label>34</label>
                <mixed-citation>
                    <name>
                        <surname>IPCC</surname>
                        <given-names></given-names>
                    </name>, <year>2012</year>. <article-title>Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation</article-title>. <source>A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change [Field, C.B., Barros, V., Stocker, T.F., Qin, D., Dokken, D.J., Ebi, K.L., Mastrandrea, M.D., Mach, K.J., Plattner, G.-K., Allen, S.K., Tignor, M., &amp; Midgley, P.M. (eds.)] (p. 582). Cambridge University Press.</source>.</mixed-citation>
            </ref>
            <ref id="ref35">
                <label>35</label>
                <mixed-citation>
                    <name>
                        <surname>IPCC</surname>
                        <given-names></given-names>
                    </name>, <year>2018</year>. <article-title>Summary of Policymakers</article-title>. <source>In: Global warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., Zhai, P., Pörtner, H.-O., Roberts, D., Skea, J., Shukla, P.R., Pirani, A., Moufouma-Okia, W., Péan, C., Pidcock, R., Connors, S., Matthews, J.B.R., Chen, Y., Zhou, X., Gomis, M.I., Lonnoy, E., Maycock, T., Tignor, M., &amp; Waterfield, T. (eds.)] (p. 32). World Meteorological Organization.</source>.</mixed-citation>
            </ref>
            <ref id="ref36">
                <label>36</label>
                <mixed-citation>
                    <name>
                        <surname>Jones</surname>
                        <given-names>G. V.</given-names>
                    </name>, <name>
                        <surname>Davis</surname>
                        <given-names>R. E.</given-names>
                    </name>, <year>2000</year>. <article-title>Climate Influences on Grapevine Phenology, Grape Composition, and Wine Production and Quality for Bordeaux, France</article-title>. <source>American Journal of Enology and Viticulture, 51(3), 249–261.</source>.</mixed-citation>
            </ref>
            <ref id="ref37">
                <label>37</label>
                <mixed-citation>
                    <name>
                        <surname>Keller</surname>
                        <given-names>M.</given-names>
                    </name>, <year>2015</year>. <article-title>Science of Grapevines: Anatomy and Physiology</article-title>. <source>Second Edition, Elsevier Inc., San Diego, CA, USA, 509 pp. ISBN: 9780124199873</source>.</mixed-citation>
            </ref>
            <ref id="ref38">
                <label>38</label>
                <mixed-citation>
                    <name>
                        <surname>Keller</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Koblet</surname>
                        <given-names>W.</given-names>
                    </name>, <year>1995</year>. <article-title>Stress-induced development of inflorescence necrosis and bunch stem necrosis in Vitis vinifera L</article-title>. <source>in response to environmental and nutritional effects. Vitis, 34, 145-150. https://doi.org/10.5073/vitis.1995.34.145-150</source>.</mixed-citation>
            </ref>
            <ref id="ref39">
                <label>39</label>
                <mixed-citation>
                    <name>
                        <surname>Körner</surname>
                        <given-names>C.</given-names>
                    </name>, <year>2003</year>. <article-title>Carbon limitation in trees</article-title>. <source>Journal of Ecology, 91, 4-17.  https://doi.org/10.1046/j.1365-2745.2003.00742.x</source>.</mixed-citation>
            </ref>
            <ref id="ref40">
                <label>40</label>
                <mixed-citation>
                    <name>
                        <surname>Krasnow</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Weis</surname>
                        <given-names>N.</given-names>
                    </name>, <name>
                        <surname>Smith</surname>
                        <given-names>R. J.</given-names>
                    </name>, <name>
                        <surname>Benz</surname>
                        <given-names>M. J.</given-names>
                    </name>, <name>
                        <surname>Matthews</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Shackel</surname>
                        <given-names>K.</given-names>
                    </name>, <year>2009</year>. <article-title>Inception, progression, and compositional consequences of a Berry Shrivel Disorder</article-title>. <source>American Journal of Enology and Viticulture, 60(1), 24–34.</source>.</mixed-citation>
            </ref>
            <ref id="ref41">
                <label>41</label>
                <mixed-citation>
                    <name>
                        <surname>Larcher</surname>
                        <given-names>W.</given-names>
                    </name>, <year>1995</year>. <article-title>Physiological plant ecology</article-title>. <source>Third Edition. Springer Edition, Berlin, 506 pp. ISBN: 978-3-540-4316-7</source>.</mixed-citation>
            </ref>
            <ref id="ref42">
                <label>42</label>
                <mixed-citation>
                    <name>
                        <surname>Leolini</surname>
                        <given-names>L.</given-names>
                    </name>, <name>
                        <surname>Moriondo</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Fila</surname>
                        <given-names>G.</given-names>
                    </name>, <name>
                        <surname>Costafreda-Aumedes</surname>
                        <given-names>S.</given-names>
                    </name>, <name>
                        <surname>Ferrise</surname>
                        <given-names>R.</given-names>
                    </name>, <name>
                        <surname>Bindi</surname>
                        <given-names>M.</given-names>
                    </name>, <year>2018</year>. <article-title>Late spring frost impacts the future grapevine distribution in Europe</article-title>. <source>Field Crops Research, 222, 197–208. https://doi.org/10.1016/j.fcr.2017.11.018</source>.</mixed-citation>
            </ref>
            <ref id="ref43">
                <label>43</label>
                <mixed-citation>
                    <name>
                        <surname>Lorenz</surname>
                        <given-names>D. H.</given-names>
                    </name>, <name>
                        <surname>Eichhorn</surname>
                        <given-names>K. W.</given-names>
                    </name>, <name>
                        <surname>Bleiholder</surname>
                        <given-names>H.</given-names>
                    </name>, <name>
                        <surname>Klose</surname>
                        <given-names>R.</given-names>
                    </name>, <name>
                        <surname>Meier</surname>
                        <given-names>U.</given-names>
                    </name>, <name>
                        <surname>Weber</surname>
                        <given-names>E.</given-names>
                    </name>, <year>1994</year>. <article-title>Phänologische Entwicklungsstadien der Weinrebe (Vitis vinifera L. ssp</article-title>. <source>Vinifera). Vitic. Enol. Sci., 49, 66–70.</source>.</mixed-citation>
            </ref>
            <ref id="ref44">
                <label>44</label>
                <mixed-citation>
                    <name>
                        <surname>Luterbacher</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Liniger</surname>
                        <given-names>M. A.</given-names>
                    </name>, <name>
                        <surname>Menzel</surname>
                        <given-names>A.</given-names>
                    </name>, <name>
                        <surname>Estrella</surname>
                        <given-names>N.</given-names>
                    </name>, <name>
                        <surname>Della‐Marta</surname>
                        <given-names>P. M.</given-names>
                    </name>, <name>
                        <surname>Pfister</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Rutishauser</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Xoplaki</surname>
                        <given-names>E.</given-names>
                    </name>, <year>2007</year>. <article-title>Exceptional European warmth of autumn 2006 and winter 2007: Historical context, the underlying dynamics, and its phenological impacts</article-title>. <source>Geophysical Research Letters, 34(12), L12704. https://doi.org/10.1029/2007GL029951</source>.</mixed-citation>
            </ref>
            <ref id="ref45">
                <label>45</label>
                <mixed-citation>
                    <name>
                        <surname>Malheiro</surname>
                        <given-names>A. C.</given-names>
                    </name>, <name>
                        <surname>Campos</surname>
                        <given-names>R.</given-names>
                    </name>, <name>
                        <surname>Fraga</surname>
                        <given-names>H.</given-names>
                    </name>, <name>
                        <surname>Eiras-Dias</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Silvestre</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Santos</surname>
                        <given-names>J. A.</given-names>
                    </name>, <year>2013</year>. <article-title>Winegrape phenology and temperature relationships in the Lisbon wine region, Portugal</article-title>. <source>OENO One, 47(4), 287–299. https://doi.org/10.20870/oeno-one.2013.47.4.1558</source>.</mixed-citation>
            </ref>
            <ref id="ref46">
                <label>46</label>
                <mixed-citation>
                    <name>
                        <surname>Martínez-Lüscher</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Kizildeniz</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Vučetić</surname>
                        <given-names>V.</given-names>
                    </name>, <name>
                        <surname>Dai</surname>
                        <given-names>Z.</given-names>
                    </name>, <name>
                        <surname>Luedeling</surname>
                        <given-names>E.</given-names>
                    </name>, <name>
                        <surname>van Leeuwen</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Gomès</surname>
                        <given-names>E.</given-names>
                    </name>, <name>
                        <surname>Pascual</surname>
                        <given-names>I.</given-names>
                    </name>, <name>
                        <surname>Irigoyen</surname>
                        <given-names>J. J.</given-names>
                    </name>, <name>
                        <surname>Morales</surname>
                        <given-names>F.</given-names>
                    </name>, <name>
                        <surname>Delrot</surname>
                        <given-names>S.</given-names>
                    </name>, <year>2016</year>. <article-title>Sensitivity of grape phenology to water availability, temperature, and CO2 concentration</article-title>. <source>Frontiers in Environmental Science, 4, 1-48. https://doi.org/10.3389/fenvs.2016.00048</source>.</mixed-citation>
            </ref>
            <ref id="ref47">
                <label>47</label>
                <mixed-citation>
                    <name>
                        <surname>Maurer</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Hammerl</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Koch</surname>
                        <given-names>E.</given-names>
                    </name>, <name>
                        <surname>Hammerl</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Pokorny</surname>
                        <given-names>E.</given-names>
                    </name>, <year>2011</year>. <article-title>Extreme grape harvest data from Austria, Switzerland, and France from A.D</article-title>. <source>1523 to 2007 compared to corresponding instrumental/reconstructed temperature data and various documentary sources. Theoretical and Applied Climatology, 106(1), 55–68. https://doi.org/10.1007/s00704-011-0410-3</source>.</mixed-citation>
            </ref>
            <ref id="ref48">
                <label>48</label>
                <mixed-citation>
                    <name>
                        <surname>Meehl</surname>
                        <given-names>G. A.</given-names>
                    </name>, <name>
                        <surname>Tebaldi</surname>
                        <given-names>C.</given-names>
                    </name>, <year>2004</year>. <article-title>More intense, more frequent, and longer lasting heat waves in the 21st century</article-title>. <source>Science, 305(5686), 994–997. https://doi.org/10.1126/science.1098704</source>.</mixed-citation>
            </ref>
            <ref id="ref49">
                <label>49</label>
                <mixed-citation>
                    <name>
                        <surname>Meier</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Fuhrer</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Holzkämper</surname>
                        <given-names>A.</given-names>
                    </name>, <year>2018</year>. <article-title>Changing the risk of spring frost damage in grapevines due to climate change? A case study of the Swiss Rhone Valley</article-title>. <source>International Journal of Biometeorology, 62(6), 991–1002. https://doi.org/10.1007/s00484-018-1501-y</source>.</mixed-citation>
            </ref>
            <ref id="ref50">
                <label>50</label>
                <mixed-citation>
                    <name>
                        <surname>Meier</surname>
                        <given-names>U.</given-names>
                    </name>, <year>1997</year>. <article-title>Growth stages of mono- and dicotyledonous plants: BBCH monograph - Entwicklungsstadien Mono- und Dikotyler Pflanzen</article-title>. <source>Blackwell-Wiss.-Verlag. ISBN: 978-3-95547-071-5</source>.</mixed-citation>
            </ref>
            <ref id="ref51">
                <label>51</label>
                <mixed-citation>
                    <name>
                        <surname>Menzel</surname>
                        <given-names>A.</given-names>
                    </name>, <year>2005</year>. <article-title>A 500-year pheno-climatological view of the 2003 heatwave in Europe assessed by grape harvest dates</article-title>. <source>Meteorologische Zeitschrift, 14(1), 75–77. https://doi.org/10.1127/0941-2948/2005/0014-0075</source>.</mixed-citation>
            </ref>
            <ref id="ref52">
                <label>52</label>
                <mixed-citation>
                    <name>
                        <surname>Morales-Castilla</surname>
                        <given-names>I.</given-names>
                    </name>, <name>
                        <surname>de Cortázar-Atauri</surname>
                        <given-names>I. G.</given-names>
                    </name>, <name>
                        <surname>Cook</surname>
                        <given-names>B. I.</given-names>
                    </name>, <name>
                        <surname>Lacombe</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Parker</surname>
                        <given-names>A.</given-names>
                    </name>, <name>
                        <surname>van Leeuwen</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Nicholas</surname>
                        <given-names>K. A.</given-names>
                    </name>, <name>
                        <surname>Wolkovich</surname>
                        <given-names>E. M.</given-names>
                    </name>, <year>2020</year>. <article-title>Diversity buffers winegrowing regions from climate change losses</article-title>. <source>Proceedings of the National Academy of Sciences, 117(6), 286-2869. https://doi.org/10.1073/pnas.1906731117</source>.</mixed-citation>
            </ref>
            <ref id="ref53">
                <label>53</label>
                <mixed-citation>
                    <name>
                        <surname>Mosedale</surname>
                        <given-names>J. R.</given-names>
                    </name>, <name>
                        <surname>Abernethy</surname>
                        <given-names>K. E.</given-names>
                    </name>, <name>
                        <surname>Smart</surname>
                        <given-names>R. E.</given-names>
                    </name>, <name>
                        <surname>Wilson</surname>
                        <given-names>R. J.</given-names>
                    </name>, <name>
                        <surname>Maclean</surname>
                        <given-names>I. M. D.</given-names>
                    </name>, <year>2016</year>. <article-title>Climate change impacts and adaptive strategies: Lessons from the grapevine</article-title>. <source>Global Change Biology, 22(11), 3814–3828. https://doi.org/10.1111/gcb.13406</source>.</mixed-citation>
            </ref>
            <ref id="ref54">
                <label>54</label>
                <mixed-citation>
                    <name>
                        <surname>Mozell</surname>
                        <given-names>M. R.</given-names>
                    </name>, <name>
                        <surname>Thach</surname>
                        <given-names>L.</given-names>
                    </name>, <year>2014</year>. <article-title>Impact of climate change on the global wine industry: Challenges and solutions</article-title>. <source>Wine Economics and Policy, 3(2), 81–89. https://doi.org/10.1016/j.wep.2014.08.001</source>.</mixed-citation>
            </ref>
            <ref id="ref55">
                <label>55</label>
                <mixed-citation>
                    <name>
                        <surname>Nash</surname>
                        <given-names>J. E.</given-names>
                    </name>, <name>
                        <surname>Sutcliffe</surname>
                        <given-names>J. V.</given-names>
                    </name>, <year>1970</year>. <article-title>River flow forecasting through conceptual models part I - A discussion of principles</article-title>. <source>Journal of Hydrology, 10(3), 282–290. https://doi.org/10.1016/0022-1694(70)90255-6</source>.</mixed-citation>
            </ref>
            <ref id="ref56">
                <label>56</label>
                <mixed-citation>
                    <name>
                        <surname>Newcombe</surname>
                        <given-names>R. G.</given-names>
                    </name>, <year>1998</year>. <article-title>Two-Sided Confidence Intervals for the Single Proportion: Comparison of Seven Methods</article-title>. <source>Statistics in Medicine, 17, 857–872. https://doi.org/10.1002/(SICI)1097-0258(19980430)17:8&lt;857::AID-SIM777&gt;3.0.CO;2-E.</source>.</mixed-citation>
            </ref>
            <ref id="ref57">
                <label>57</label>
                <mixed-citation>
                    <name>
                        <surname>Olesen</surname>
                        <given-names>J. E.</given-names>
                    </name>, <name>
                        <surname>Trnka</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Kersebaum</surname>
                        <given-names>K. C.</given-names>
                    </name>, <name>
                        <surname>Skjelvåg</surname>
                        <given-names>A. O.</given-names>
                    </name>, <name>
                        <surname>Seguin</surname>
                        <given-names>B.</given-names>
                    </name>, <name>
                        <surname>Peltonen-Sainio</surname>
                        <given-names>P.</given-names>
                    </name>, <name>
                        <surname>Rossi</surname>
                        <given-names>F.</given-names>
                    </name>, <name>
                        <surname>Kozyra</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Micale</surname>
                        <given-names>F.</given-names>
                    </name>, <year>2011</year>. <article-title>Impacts and adaptation of European crop production systems to climate change</article-title>. <source>European Journal of Agronomy, 34(2), 96–112. https://doi.org/10.1016/j.eja.2010.11.003</source>.</mixed-citation>
            </ref>
            <ref id="ref58">
                <label>58</label>
                <mixed-citation>
                    <name>
                        <surname>Parker</surname>
                        <given-names>A. K.</given-names>
                    </name>, <name>
                        <surname>de Cortázar-Atauri</surname>
                        <given-names>I. G.</given-names>
                    </name>, <name>
                        <surname>Chuine</surname>
                        <given-names>I.</given-names>
                    </name>, <name>
                        <surname>Barbeau</surname>
                        <given-names>G.</given-names>
                    </name>, <name>
                        <surname>Bois</surname>
                        <given-names>B.</given-names>
                    </name>, <name>
                        <surname>Boursiquot</surname>
                        <given-names>J.-M.</given-names>
                    </name>, <name>
                        <surname>Cahurel</surname>
                        <given-names>J.-Y.</given-names>
                    </name>, <name>
                        <surname>Claverie</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Dufourcq</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Gény</surname>
                        <given-names>L.</given-names>
                    </name>, <name>
                        <surname>Guimberteau</surname>
                        <given-names>G.</given-names>
                    </name>, <name>
                        <surname>Hofmann</surname>
                        <given-names>R. W.</given-names>
                    </name>, <name>
                        <surname>Jacquet</surname>
                        <given-names>O.</given-names>
                    </name>, <name>
                        <surname>Lacombe</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Monamy</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Ojeda</surname>
                        <given-names>H.</given-names>
                    </name>, <name>
                        <surname>Panigai</surname>
                        <given-names>L.</given-names>
                    </name>, <name>
                        <surname>Payan</surname>
                        <given-names>J.-C.</given-names>
                    </name>, <name>
                        <surname>Lovelle</surname>
                        <given-names>B. R.</given-names>
                    </name>, <name>
                        <surname>van Leeuwen</surname>
                        <given-names>C.</given-names>
                    </name>, <year>2013</year>. <article-title>Classification of varieties for their timing of flowering and veraison using a modeling approach: A case study for the grapevine species Vitis vinifera L</article-title>. <source>Agricultural and Forest Meteorology, 180, 249–264. https://doi.org/10.1016/j.agrformet.2013.06.005</source>.</mixed-citation>
            </ref>
            <ref id="ref59">
                <label>59</label>
                <mixed-citation>
                    <name>
                        <surname>Parker</surname>
                        <given-names>A. K.</given-names>
                    </name>, <name>
                        <surname>de Cortázar‐Atauri</surname>
                        <given-names>I. G.</given-names>
                    </name>, <name>
                        <surname>van Leeuwen</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Chuine</surname>
                        <given-names>I.</given-names>
                    </name>, <year>2011</year>. <article-title>General phenological model to characterise the timing of flowering and veraison of Vitis vinifera L</article-title>. <source>Australian Journal of Grape and Wine Research, 17(2), 206–216. https://doi.org/10.1111/j.1755-0238.2011.00140.x</source>.</mixed-citation>
            </ref>
            <ref id="ref60">
                <label>60</label>
                <mixed-citation>
                    <name>
                        <surname>R Core Team</surname>
                        <given-names></given-names>
                    </name>, <year>2019</year>. <article-title>R: A language and environment for statistical computing</article-title>. <source>R Foundation for Statistical Computing. https://www.R-project.org/</source>.</mixed-citation>
            </ref>
            <ref id="ref61">
                <label>61</label>
                <mixed-citation>
                    <name>
                        <surname>Robinson</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Harding</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Vouillamoz</surname>
                        <given-names>J.</given-names>
                    </name>, <year>2012</year>. <article-title>Wine grapes: A complete guide to 1,368 vine varieties, including their origins and flavours (Slp edition)</article-title>. <source>Ecco. ISBN: 9780062206367</source>.</mixed-citation>
            </ref>
            <ref id="ref62">
                <label>62</label>
                <mixed-citation>
                    <name>
                        <surname>Rousseeuw</surname>
                        <given-names>P. J.</given-names>
                    </name>, <year>1999</year>. <article-title>A Fast Algorithm for the Minimum Covariance Determinant Estimator, American Statistical Association, and the American Society for Quality</article-title>. <source>Technometrics, 41(3), 212-223. https://doi.org/10.1080/00401706.1999.10485670</source>.</mixed-citation>
            </ref>
            <ref id="ref63">
                <label>63</label>
                <mixed-citation>
                    <name>
                        <surname>Santos</surname>
                        <given-names>J. A.</given-names>
                    </name>, <name>
                        <surname>Fraga</surname>
                        <given-names>H.</given-names>
                    </name>, <name>
                        <surname>Malheiro</surname>
                        <given-names>A. C.</given-names>
                    </name>, <name>
                        <surname>Moutinho-Pereira</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Dinis</surname>
                        <given-names>L-T.</given-names>
                    </name>, <name>
                        <surname>Correia</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Moriondo</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Leolini</surname>
                        <given-names>L.</given-names>
                    </name>, <name>
                        <surname>Dibari</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Costafreda-Aumedes</surname>
                        <given-names>S.</given-names>
                    </name>, <name>
                        <surname>Kartschall</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Menz</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Molitor</surname>
                        <given-names>D.</given-names>
                    </name>, <name>
                        <surname>Junk</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Beyer</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Schultz</surname>
                        <given-names>H.R.</given-names>
                    </name>, <year>2020</year>. <article-title>A reivew of potential climate change impacts and adaptation options for European viticulture</article-title>. <source>Applied Sciences, 10, 3092, https://</source>, <pub-id pub-id-type="doi">https://doi.org/10.3390/app10093092 </pub-id>.</mixed-citation>
            </ref>
            <ref id="ref64">
                <label>64</label>
                <mixed-citation>
                    <name>
                        <surname>Siegmund</surname>
                        <given-names>J. F.</given-names>
                    </name>, <name>
                        <surname>Siegmund</surname>
                        <given-names>N.</given-names>
                    </name>, <name>
                        <surname>Donner</surname>
                        <given-names>RV.</given-names>
                    </name>, <year>2017</year>. <article-title>CoinCalc-A new R package for quantifying the simultaneities of event series</article-title>. <source>Computers &amp; Geosciences, 98, 64–72. https://doi.org/10.1016/j.cageo.2016.10.004</source>.</mixed-citation>
            </ref>
            <ref id="ref65">
                <label>65</label>
                <mixed-citation>
                    <name>
                        <surname>Siegmund</surname>
                        <given-names>J. F.</given-names>
                    </name>, <name>
                        <surname>Wiedermann</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Donges</surname>
                        <given-names>J. F.</given-names>
                    </name>, <name>
                        <surname>Donner</surname>
                        <given-names>R. R.</given-names>
                    </name>, <year>2016</year>. <article-title>Impact of temperature and precipitation extremes on the flowering dates of four German wildlife shrub species</article-title>. <source>Biogeosciences, 13(19), 5541–5555. https://doi.org/10.5194/bg-13-5541-2016</source>.</mixed-citation>
            </ref>
            <ref id="ref66">
                <label>66</label>
                <mixed-citation>
                    <name>
                        <surname>Soja</surname>
                        <given-names>G.</given-names>
                    </name>, <name>
                        <surname>Zehetner</surname>
                        <given-names>F.</given-names>
                    </name>, <name>
                        <surname>Rampazzo-Todorovic</surname>
                        <given-names>G.</given-names>
                    </name>, <name>
                        <surname>Schildberger</surname>
                        <given-names>B.</given-names>
                    </name>, <name>
                        <surname>Hackl</surname>
                        <given-names>K.</given-names>
                    </name>, <name>
                        <surname>Hofmann</surname>
                        <given-names>R.</given-names>
                    </name>, <name>
                        <surname>Burger</surname>
                        <given-names>E.</given-names>
                    </name>, <name>
                        <surname>Omann</surname>
                        <given-names>I.</given-names>
                    </name>, <year>2011</year>. <article-title>Wine production under climate change conditions: Mitigation and adaptation options from the vineyard to the sales booth</article-title>. <source>Reviewed Proceedings of the 9th European IFSA Symposium. 9th European IFSA Symposium, Vienna, Austria.</source>.</mixed-citation>
            </ref>
            <ref id="ref67">
                <label>67</label>
                <mixed-citation>
                    <name>
                        <surname>Spring</surname>
                        <given-names>J. -L.</given-names>
                    </name>, <name>
                        <surname>Zufferey</surname>
                        <given-names>V.</given-names>
                    </name>, <name>
                        <surname>Verdenal</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Viret</surname>
                        <given-names>O.</given-names>
                    </name>, <year>2010</year>. <article-title>Alimentation en eau et comportement du Pinot noir : bilan d'un essai dans le vignoble de Chamoson (Valais)</article-title>. <source>Revue suisse Viticulture, Arboriculture, Horticulture, 42(4), 258-266.</source>.</mixed-citation>
            </ref>
            <ref id="ref68">
                <label>68</label>
                <mixed-citation>
                    <name>
                        <surname>Srinivasan</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Mullins</surname>
                        <given-names>M.G.</given-names>
                    </name>, <year>1981</year>. <article-title>Physiology of flowering in the grapevine: a review</article-title>. <source>American Journal of Enology and Viticulture, 32(1), 47-63.</source>.</mixed-citation>
            </ref>
            <ref id="ref69">
                <label>69</label>
                <mixed-citation>
                    <name>
                        <surname>Töpfer</surname>
                        <given-names>R.</given-names>
                    </name>, <name>
                        <surname>Sudharma</surname>
                        <given-names>K. N.</given-names>
                    </name>, <name>
                        <surname>Kecke</surname>
                        <given-names>S.</given-names>
                    </name>, <name>
                        <surname>Marx</surname>
                        <given-names>G.</given-names>
                    </name>, <name>
                        <surname>Eibach</surname>
                        <given-names>R.</given-names>
                    </name>, <name>
                        <surname>Maghradze</surname>
                        <given-names>D.</given-names>
                    </name>, <name>
                        <surname>Maul</surname>
                        <given-names>E.</given-names>
                    </name>, <year>2009</year>. <article-title>Vitis International Variety Catalogue (VIVC): New design and more information</article-title>. <source>Bulletin OIV, 82, 42–56.</source>.</mixed-citation>
            </ref>
            <ref id="ref70">
                <label>70</label>
                <mixed-citation>
                    <name>
                        <surname>van Leeuwen</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Destrac-Irvine</surname>
                        <given-names>A.</given-names>
                    </name>, <name>
                        <surname>Dubernet</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Duchêne</surname>
                        <given-names>E.</given-names>
                    </name>, <name>
                        <surname>Gowdy</surname>
                        <given-names>M.</given-names>
                    </name>, <name>
                        <surname>Marguerit</surname>
                        <given-names>E.</given-names>
                    </name>, <name>
                        <surname>Pieri</surname>
                        <given-names>P.</given-names>
                    </name>, <name>
                        <surname>Parker</surname>
                        <given-names>A.</given-names>
                    </name>, <name>
                        <surname>de Rességuier</surname>
                        <given-names>L.</given-names>
                    </name>, <name>
                        <surname>Ollat</surname>
                        <given-names>N.</given-names>
                    </name>, <year>2019a</year>. <article-title>An Update on the Impact of Climate Change in Viticulture and Potential Adaptations</article-title>. <source>Agronomy, 9(9), 514. https://doi.org/10.3390/agronomy9090514</source>.</mixed-citation>
            </ref>
            <ref id="ref71">
                <label>71</label>
                <mixed-citation>
                    <name>
                        <surname>van Leeuwen</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Roby</surname>
                        <given-names>J.-P.</given-names>
                    </name>, <name>
                        <surname>Ollat</surname>
                        <given-names>N.</given-names>
                    </name>, <year>2019b</year>. <article-title>Viticulture in a changing climate: Solutions exist</article-title>. <source>IVES Technical Reviews, Vine &amp; Wine. https://doi.org/10.20870/IVES-TR.2019.2530</source>.</mixed-citation>
            </ref>
            <ref id="ref72">
                <label>72</label>
                <mixed-citation>
                    <name>
                        <surname>Went</surname>
                        <given-names>F. W.</given-names>
                    </name>, <year>1953</year>. <article-title>Effect of temperature on plant growth</article-title>. <source>Annual Review of Plant Physiology, 4(1), 347–362. https://doi.org/10.1146/annurev.pp.04.060153.002023</source>.</mixed-citation>
            </ref>
            <ref id="ref73">
                <label>73</label>
                <mixed-citation>
                    <name>
                        <surname>White</surname>
                        <given-names>M. A.</given-names>
                    </name>, <name>
                        <surname>Diffenbaugh</surname>
                        <given-names>N. S.</given-names>
                    </name>, <name>
                        <surname>Jones</surname>
                        <given-names>G. V.</given-names>
                    </name>, <name>
                        <surname>Pal</surname>
                        <given-names>J. S.</given-names>
                    </name>, <name>
                        <surname>Giorgi</surname>
                        <given-names>F.</given-names>
                    </name>, <year>2006</year>. <article-title>Extreme heat reduces and shifts United States premium wine production in the 21st century</article-title>. <source>Proceedings of the National Academy of Sciences, 103(30), 11217–11222. https://doi.org/10.1073/pnas.0603230103</source>.</mixed-citation>
            </ref>
            <ref id="ref74">
                <label>74</label>
                <mixed-citation>
                    <name>
                        <surname>WMO</surname>
                        <given-names></given-names>
                    </name>, <year>2013</year>. <article-title>Global Climate 2001-2010: A decade of climate extremes: Summary Report</article-title>. <source>World Meteorological Organization. https://reliefweb.int/report/world/global-climate-2001-2010-decade-climate-extremes-summary-report</source>.</mixed-citation>
            </ref>
            <ref id="ref75">
                <label>75</label>
                <mixed-citation>
                    <name>
                        <surname>Wood</surname>
                        <given-names>S. N.</given-names>
                    </name>, <year>2003</year>. <article-title>Thin plate regression splines</article-title>. <source>Journal of the Royal Statistical Society Series B, 65(1), 95-114. https://doi.org/10.1111/1467-9868.00374</source>.</mixed-citation>
            </ref>
            <ref id="ref76">
                <label>76</label>
                <mixed-citation>
                    <name>
                        <surname>Yzarra</surname>
                        <given-names>W.</given-names>
                    </name>, <name>
                        <surname>Sanabria</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Cáceres</surname>
                        <given-names>H.</given-names>
                    </name>, <name>
                        <surname>Solis</surname>
                        <given-names>O.</given-names>
                    </name>, <name>
                        <surname>Lhomme</surname>
                        <given-names>J.-P.</given-names>
                    </name>, <year>2015</year>. <article-title>Impact of climate change on some grapevine varieties grown in Peru on Pisco production</article-title>. <source>OENO One, 49(2), 103–112. https://doi.org/10.20870/oeno-one.2015.49.2.90</source>.</mixed-citation>
            </ref>
            <ref id="ref77">
                <label>77</label>
                <mixed-citation>
                    <name>
                        <surname>Zufferey</surname>
                        <given-names>V.</given-names>
                    </name>, <name>
                        <surname>Cochard</surname>
                        <given-names>H.</given-names>
                    </name>, <name>
                        <surname>Ameglio</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Spring</surname>
                        <given-names>J. -L.</given-names>
                    </name>, <name>
                        <surname>Viret</surname>
                        <given-names>J.</given-names>
                    </name>, <year>2011</year>. <article-title>Diurnal cycles of embolism formation and repair in petioles of grapevine (Vitis vinifera cv</article-title>. <source>Chasselas). Journal of Experimental Botany, 62(11), 3885–3894. https://doi.org/10.1093/jxb/err081 </source>.</mixed-citation>
            </ref>
            <ref id="ref78">
                <label>78</label>
                <mixed-citation>
                    <name>
                        <surname>Zufferey</surname>
                        <given-names>V.</given-names>
                    </name>, <name>
                        <surname>Murisier</surname>
                        <given-names>F.</given-names>
                    </name>, <name>
                        <surname>Schultz</surname>
                        <given-names>H. R.</given-names>
                    </name>, <year>2000</year>. <article-title>A model analysis of the photosynthetic response of V</article-title>. <source>vinifera L. cvs. Riesling and Chasselas leaves in the field: I. Interaction of age, light, and temperature. Vitis, 39(1), 19-26. https://doi.org/10.5073/vitis.2000.39.19-26</source>.</mixed-citation>
            </ref>
            <ref id="ref79">
                <label>79</label>
                <mixed-citation>
                    <name>
                        <surname>Zufferey</surname>
                        <given-names>V.</given-names>
                    </name>, <name>
                        <surname>Spring</surname>
                        <given-names>J. -L.</given-names>
                    </name>, <name>
                        <surname>Voinesco</surname>
                        <given-names>F.</given-names>
                    </name>, <name>
                        <surname>Viret</surname>
                        <given-names>O.</given-names>
                    </name>, <name>
                        <surname>Gindro</surname>
                        <given-names>K.</given-names>
                    </name>, <year>2015a</year>. <article-title>Physiological and histological approaches to study berry shrivel in grapes</article-title>. <source>OENO One, 49(2), 113-125. https://doi.org/10.20870/oeno-one.2015.49.2.89</source>.</mixed-citation>
            </ref>
            <ref id="ref80">
                <label>80</label>
                <mixed-citation>
                    <name>
                        <surname>Zufferey</surname>
                        <given-names>V.</given-names>
                    </name>, <name>
                        <surname>Murisier</surname>
                        <given-names>F.</given-names>
                    </name>, <name>
                        <surname>Vivin</surname>
                        <given-names>P.</given-names>
                    </name>, <name>
                        <surname>Belcher</surname>
                        <given-names>S.</given-names>
                    </name>, <name>
                        <surname>Lorenzini</surname>
                        <given-names>F.</given-names>
                    </name>, <name>
                        <surname>Spring</surname>
                        <given-names>J.-L.</given-names>
                    </name>, <name>
                        <surname>Viret</surname>
                        <given-names>O.</given-names>
                    </name>, <year>2015b</year>. <article-title>Nitrogen and carbohydrate reserves in the grapevine Vitis vinifera L</article-title>. <source>cv. Chasselas: the influence of the leaf to fruit ratio. Vitis, 54, 183-188. https://doi.org/10.5073/vitis.2015.54.183-188</source>.</mixed-citation>
            </ref>
            <ref id="ref81">
                <label>81</label>
                <mixed-citation>
                    <name>
                        <surname>Zufferey</surname>
                        <given-names>V.</given-names>
                    </name>, <name>
                        <surname>Verdenal</surname>
                        <given-names>T.</given-names>
                    </name>, <name>
                        <surname>Lorenzini</surname>
                        <given-names>F.</given-names>
                    </name>, <name>
                        <surname>Dienes-Nagy</surname>
                        <given-names>A.</given-names>
                    </name>, <name>
                        <surname>Belcher</surname>
                        <given-names>S.</given-names>
                    </name>, <name>
                        <surname>Koestel</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>M. Blackford</surname>
                        <given-names>G.</given-names>
                    </name>, <name>
                        <surname>Bourdin</surname>
                        <given-names>R. J.</given-names>
                    </name>, <name>
                        <surname>Spangenberg</surname>
                        <given-names>J.</given-names>
                    </name>, <name>
                        <surname>Viret</surname>
                        <given-names>O.</given-names>
                    </name>, <name>
                        <surname>Carlen</surname>
                        <given-names>C.</given-names>
                    </name>, <name>
                        <surname>Spring</surname>
                        <given-names>J. L.</given-names>
                    </name>, <year>2020</year>. <article-title>The influence of plant water status on gas exchange, berry composition, and quality of Arvine wines in Switzerland</article-title>. <source>OENO One, 54(3), 553-568. https://doi.org/10.20870/oeno-one.2020.54.3.3106</source>.</mixed-citation>
            </ref>
        </ref-list>
    </back>
</article>
