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	<front>
		<journal-meta>
			<journal-id journal-id-type="publisher-id">MC</journal-id>
			<journal-title-group>
				<journal-title>Materiales de Construcci&#xf3;n</journal-title>
				<abbrev-journal-title abbrev-type="publisher">Mater. construcc.</abbrev-journal-title>
			</journal-title-group>
			<issn publication-format="electronic">1988-3226</issn>
			<issn-l>0465-2746</issn-l>
			<publisher>
				<publisher-name>Consejo Superior de Investigaciones Cient&#xed;ficas</publisher-name>
			</publisher>
		</journal-meta>
		<article-meta>
			<article-id pub-id-type="publisher-id">mc.2021.11320</article-id>
			<article-id pub-id-type="doi">10.3989/mc.2021.11320</article-id>
			<article-categories>
				<subj-group subj-group-type="heading">
					<subject>Articles</subject>
				</subj-group>
			</article-categories>
			<title-group>
				<article-title>Species effect on decay resistance of wood exposed to exterior conditions above the ground in Spain</article-title>
				<trans-title-group xml:lang="es">
					<trans-title>Efecto de la especie en la resistencia a la pudrici&#xf3;n de la madera expuesta al exterior fuera del contacto con el suelo en Espa&#xf1;a</trans-title>
				</trans-title-group>
			</title-group>
			<contrib-group>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0194-2617</contrib-id>
					<name>
						<surname>Conde-Garc&#xed;a</surname>
						<given-names>M.</given-names>
					</name>
					<aff id="aff1"><institution>Forest Products Department, Wood Technology Lab. CIFOR-INIA</institution>, (<addr-line>Madrid</addr-line>, <country>Spain</country>)</aff>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-5547-8138</contrib-id>
					<name>
						<surname>Conde-Garc&#xed;a</surname>
						<given-names>M.</given-names>
					</name>
					<aff id="aff2"><institution>Universidad de C&#xf3;rdoba, Escuela T&#xe9;cnica Superior de Ingenieros Agr&#xf3;nomos y Montes</institution>, (<addr-line>C&#xf3;rdoba</addr-line>, <country>Spain</country>)</aff>
				</contrib>
				<contrib contrib-type="author" corresp="yes">
					<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-3597-7618</contrib-id>
					<name>
						<surname>Fern&#xe1;ndez-Golf&#xed;n</surname>
						<given-names>J.I.</given-names>
					</name>
					<email xlink:href="golfin@inia.es">golfin@inia.es</email>
					<aff id="aff3"><institution>Forest Products Department, Wood Technology Lab. CIFOR-INIA</institution>, (<addr-line>Madrid</addr-line>, <country>Spain</country>)</aff>
				</contrib>
			</contrib-group>
			<pub-date pub-type="epub">
				<day>01</day>
				<month>03</month>
				<year>2021</year>
			</pub-date>
			<pub-date pub-type="collection">
				<month>03</month>
				<year>2021</year>
			</pub-date>
			<volume>71</volume>
			<issue>341</issue>
			<elocation-id>e236</elocation-id>
			<history>
				<date date-type="received">
					<day>04</day>
					<month>09</month>
					<year>2020</year>
				</date>
				<date date-type="accepted">
					<day>05</day>
					<month>11</month>
					<year>2020</year>
				</date>
				<date date-type="pub">
					<day>17</day>
					<month>03</month>
					<year>2021</year>
				</date>
			</history>
			<permissions>
				<copyright-statement>&#xa9;2021 CSIC</copyright-statement>
				<copyright-year>2021</copyright-year>
				<license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
					<license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License.</license-p>
				</license>
			</permissions>
			<self-uri xlink:href="http://materconstrucc.revistas.csic.es/index.php/materconstrucc/article/view/XXXX/XXXX"/>
			<abstract>
				<title>ABSTRACT</title>
				<p>The objective of this study is to evaluate the effect of the species on the biological resistance of wood against decay and to propose corrective values of the critical dose. To evaluate the species effect, the evolution of the number of days per year with moisture content exceeding 18&#x25; was assessed in flat sawn 20x100x750 mm<sup>3</sup> test samples of Laricio, Scots and Radiata pines and also of Norway spruce, Eucalypt (<italic>globulus</italic>) and sweet chestnut during the years 2016, 2017 and 2018, exposed at seven locations in Spain with the most representative Spanish climates. A value of 1.0 is proposed for the four conifers, 2.51 for the Eucalypt and 1.84 for the Sweet chestnut. As regards the species effect it was not possible to separate that corresponding to the different wetting/releasing ability of each species and that of their crack susceptibility, both aspects having to be evaluated together as “species factor”. </p>
			</abstract>
			<trans-abstract xml:lang="es">
				<title>RESUMEN</title>
				<p>El objetivo del estudio es evaluar el efecto de la especie en la resistencia de la madera frente a la pudrici&#xf3;n y proponer valores de correcci&#xf3;n de la dosis cr&#xed;tica. Para evaluar el factor especie, se analiz&#xf3; la evoluci&#xf3;n del n&#xfa;mero de d&#xed;as anuales con contenido de humedad superior al 18&#x25; en piezas de madera aserrada de 20x100x750 mm<sup>3</sup> de los pinos Laricio, silvestre y radiata as&#xed; como en Abeto rojo, Eucalipto (<italic>globulus</italic>) y casta&#xf1;o europeo durante los a&#xf1;os 2016, 2017 y 2018, expuestas en siete localidades espa&#xf1;olas elegidas por tener los climas m&#xe1;s representativos. Se propone un valor de 1.0 para las cuatro con&#xed;feras, 2.51 para el eucalipto y 1.84 para el casta&#xf1;o. No fue posible diferenciar entre el efecto debido a la diferente capacidad de sorci&#xf3;n/desorci&#xf3;n de cada madera de aqu&#xe9;l motivado por la diferente propensi&#xf3;n al fendado, teniendo que ser integrados ambos aspectos en un &#xfa;nico “factor especie”.</p>
			</trans-abstract>
			<kwd-group>
				<kwd>Wood</kwd>
				<kwd>Durability</kwd>
				<kwd>Weathering</kwd>
				<kwd>Permeability</kwd>
				<kwd>Detection of cracks</kwd>
			</kwd-group>
			<kwd-group xml:lang="es">
				<kwd>Madera</kwd>
				<kwd>Durabilidad</kwd>
				<kwd>Envejecimiento</kwd>
				<kwd>Permeabilidad</kwd>
				<kwd>Detecci&#xf3;n de fisuras</kwd>
			</kwd-group>
			<funding-group id="fw-01">
				<award-group id="aw1">
					<funding-source>Spanish National RDT Plan through Grant</funding-source>
					<award-id>BIA2013-42434-R</award-id>
				</award-group>
				<award-group id="aw2">
					<funding-source>Operational Group “Wood Sustainable Construction” of the European Association for Innovation in Agricultural Productivity and Sustainability (AEI-AGRI)</funding-source>
				</award-group>
				<funding-statement>This work was carried out in the Wood Technology Laboratories at the CIFOR-INIA and University of Cordoba, and was financially supported under the Spanish National RDT Plan through Grant BIA2013-42434-R and the Operational Group “Wood Sustainable Construction” of the European Association for Innovation in Agricultural Productivity and Sustainability (AEI-AGRI). The authors would like to thank all those who have collaborated in the trials, especially NEIKER in the Basque country, Rafael Sanchez at the University of Cordoba, Eugenio Perea at the Asturias-Llames site and Rafael Capuz at the Valencia sites.</funding-statement>
			</funding-group>
			<counts>
				<fig-count count="2"/>
				<table-count count="8"/>
				<equation-count count="3"/>
				<ref-count count="34"/>
				<page-count count="9"/>
			</counts>
		</article-meta>
	</front>
	<body>
		<sec id="sec1" sec-type="intro">
			<label>1.</label>
			<title>Introduction</title>
			<p>Predicting the performance of building products made from timber and other bio-based building materials has become increasingly important. Performance data are requested by designers, planners, authorities and approval bodies, but are rarely available (<xref ref-type="bibr" rid="B1">1</xref>).</p>
			<p>Service life of timber structures in outdoor conditions is predominantly affected by the climatic conditions in terms of moisture and temperature over time (<xref ref-type="bibr" rid="B2">2</xref>). On-site wood decay is the result of a series of concomitant factors which make up the so-called “<italic>material climate</italic>” (the moisture content and temperature of the wood), which in turn has a direct impact on the service life of the wood products and constructions (<xref ref-type="bibr" rid="B3">3</xref>).</p>
			<p>Different works at European level (<xref ref-type="bibr" rid="B4 B5 B6">4-6</xref>) have proposed new technical guidelines for the design of buildings constructed using timber with respect to durability and service life, based on a parametric system similar to that used in mechanical engineering. These guidelines are based on a limit state described as "onset of decay", defined as a state of fungal attack according to rating 1 in EN 252 (<xref ref-type="bibr" rid="B7">7</xref>), which corresponds to a slight attack which is described in the standard as the situation when perceptible surface changes are apparent, but very limited in their intensity and their position or distribution, with softening of the wood being the most common symptom.</p>
			<p>As stated above, in analogy to mechanical engineering, the design principle used in these technical guides is based on the use of expression (<xref ref-type="disp-formula" rid="e1">Equation [1]</xref>) to evaluate every aspect of the design.</p>
			<disp-formula id="e1">
				<mml:math id="mml-1">
					<mml:mi mathvariant="normal">E</mml:mi>
					<mml:mi mathvariant="normal">x</mml:mi>
					<mml:mi mathvariant="normal">p</mml:mi>
					<mml:mi mathvariant="normal">o</mml:mi>
					<mml:mi mathvariant="normal">s</mml:mi>
					<mml:mi mathvariant="normal">u</mml:mi>
					<mml:mi mathvariant="normal">r</mml:mi>
					<mml:mi mathvariant="normal">e</mml:mi>
					<mml:mi mathvariant="normal"> </mml:mi>
					<mml:mo>&#x2264;</mml:mo>
					<mml:mi mathvariant="normal"> </mml:mi>
					<mml:mi mathvariant="normal">R</mml:mi>
					<mml:mi mathvariant="normal">e</mml:mi>
					<mml:mi mathvariant="normal">s</mml:mi>
					<mml:mi mathvariant="normal">i</mml:mi>
					<mml:mi mathvariant="normal">s</mml:mi>
					<mml:mi mathvariant="normal">t</mml:mi>
					<mml:mi mathvariant="normal">a</mml:mi>
					<mml:mi mathvariant="normal">n</mml:mi>
					<mml:mi mathvariant="normal">c</mml:mi>
					<mml:mi mathvariant="normal">e</mml:mi>
				</mml:math>
				<label>[1]</label>
			</disp-formula>
			<p>In expression [A] the exposure is calculated taking into account the basic exposure doses at each site according to the daily averages for <italic>material climate,</italic> modified in accordance with all the factors influencing this material climate (local exposure conditions, sheltering, distance to ground, design of details and other concomitant factors). Similarly, the design-material resistance is calculated considering a critical dose against biological agents modified by all the factors that affect this basic resistance (wetting and drying ability and crack susceptibility of the species used, protection systems, stability, etc.).</p>
			<p>This approach, considering a basic value, not only for exposure but also for resistance, modified by all the factors affecting the basic values, closely follows the factor method idea according to ISO 15686-1 (<xref ref-type="bibr" rid="B8">8</xref>) and is an engineering approach for evaluating each decision regarding design and species/protection.</p>
			<p>According to Marteinsson (<xref ref-type="bibr" rid="B9">9</xref>), the first to propose the use of the factor method to evaluate wood durability, when applied to wood the “<italic>factor method</italic>” consists of determining a reference value for durability, hazard or “<italic>service life</italic>”, which must then be corrected by applying a series of factors which take into account different concomitant aspects related to both the material itself (species, dimensions, treatments applied, type of material etc.) as well as the “<italic>climate</italic>” in which the material is employed, or other aspects such as design details or hazards associated with the failure of the element in question (<xref ref-type="bibr" rid="B10">10</xref>).</p>
			<p>As regards the calculation of the design-material resistance to onset of decay (onwards <italic>D</italic>
				<sub>
					<italic>RD</italic>
				</sub>) in expression [A], this value is defined by a critical dose (<italic>D</italic>
				<sub>
					<italic>crit</italic>
				</sub>) which is adjusted to account for specific properties of the material in terms of water uptake and release, protection against fungal attack, etc. (<italic>k</italic> factors in expression (<xref ref-type="disp-formula" rid="e2">Equation [2]</xref>)) (<xref ref-type="bibr" rid="B6">6</xref>). As in the calculation of the characteristic value for exposure and given its common presence in the European building sector, Norway spruce (<italic>Picea abies</italic>) was chosen as reference material (<xref ref-type="bibr" rid="B3">3</xref>, <xref ref-type="bibr" rid="B6">6</xref>).</p>
			<disp-formula id="e2">
				<mml:math id="mml-2">
					<mml:msub>
						<mml:mrow>
							<mml:mi>D</mml:mi>
						</mml:mrow>
						<mml:mrow>
							<mml:mi>R</mml:mi>
							<mml:mi>D</mml:mi>
						</mml:mrow>
					</mml:msub>
					<mml:mo>=</mml:mo>
					<mml:msub>
						<mml:mrow>
							<mml:mi>D</mml:mi>
						</mml:mrow>
						<mml:mrow>
							<mml:mi>c</mml:mi>
							<mml:mi>r</mml:mi>
							<mml:mi>i</mml:mi>
							<mml:mi>t</mml:mi>
						</mml:mrow>
					</mml:msub>
					<mml:mi>*</mml:mi>
					<mml:msub>
						<mml:mrow>
							<mml:mi>k</mml:mi>
						</mml:mrow>
						<mml:mrow>
							<mml:mi>w</mml:mi>
							<mml:mi>a</mml:mi>
						</mml:mrow>
					</mml:msub>
					<mml:mi>*</mml:mi>
					<mml:msub>
						<mml:mrow>
							<mml:mi>k</mml:mi>
						</mml:mrow>
						<mml:mrow>
							<mml:mi>i</mml:mi>
							<mml:mi>n</mml:mi>
							<mml:mi>h</mml:mi>
						</mml:mrow>
					</mml:msub>
					<mml:mi>*</mml:mi>
					<mml:msub>
						<mml:mrow>
							<mml:mi>k</mml:mi>
						</mml:mrow>
						<mml:mrow>
							<mml:mi>s</mml:mi>
							<mml:mi>i</mml:mi>
						</mml:mrow>
					</mml:msub>
				</mml:math>
				<label>[2]</label>
			</disp-formula>
			<def-list id="d1">
				<title>Where:</title>
				<def-item>
					<term>
						<italic>D</italic>
						<sub>
							<italic>crit</italic>
						</sub>
					</term>
					<def>
						<p>
							<italic>-</italic> is the critical dose corresponding to decay rating 1 according to EN 252 (<xref ref-type="bibr" rid="B7">7</xref>) </p>
					</def>
				</def-item>
				<def-item>
					<term>
						<italic>k</italic>
						<sub>
							<italic>wa</italic>
						</sub>
					</term>
					<def>
						<p>
							<italic>-</italic> is a factor accounting for the effect of the physical properties of each wood species (e.g. wetting/releasing ability, crack susceptibility), relative to the reference species of Norway spruce</p>
					</def>
				</def-item>
				<def-item>
					<term>
						<italic>k</italic>
						<sub>
							<italic>inh</italic>
						</sub>
					</term>
					<def>
						<p>
							<italic>-</italic> is a factor accounting for the inherent protective properties of the tested materials against decay, relative to the reference of untreated Norway spruce. If no relevant information is available, it is suggested that a value of <italic>k</italic>
							<sub>
								<italic>inh</italic>
							</sub> = 1.0 be applied for well-maintained coated wood (<xref ref-type="bibr" rid="B6">6</xref>).</p>
					</def>
				</def-item>
				<def-item>
					<term>
						<italic>k</italic>
						<sub>
							<italic>si</italic>
						</sub>
					</term>
					<def>
						<p>- are factors accounting for any other material properties that slow down wetting or limit remaining wet, always relative to the reference of untreated Norway spruce</p>
					</def>
				</def-item>
			</def-list>
			<p>In Isaksson <italic>et al</italic>. (<xref ref-type="bibr" rid="B11">11</xref>) <italic>D</italic>
				<sub>
					<italic>crit</italic>
				</sub> was evaluated for Scots pine sapwood and Douglas fir heartwood. It was found that the critical dose corresponding to decay rating 1 according to EN 252 (<xref ref-type="bibr" rid="B7">7</xref>) can be considered more or less independent of the material. Isaksson <italic>et al</italic>. (<xref ref-type="bibr" rid="B6">6</xref>) identified the observed differences between the performance of different species as being due to differences in water uptake/release (wetting ability) (<italic>k</italic>
				<sub>
					<italic>wa</italic>
				</sub>) and protective properties inherent in the material (<italic>k</italic>
				<sub>
					<italic>inh</italic>
				</sub>).</p>
			<p>As far as the wetting ability (<italic>k</italic>
				<sub>
					<italic>wa</italic>
				</sub>) is concerned, Brischke <italic>et al</italic>. (<xref ref-type="bibr" rid="B12">12</xref>) proposed the <italic>k</italic>
				<sub>
					<italic>wa</italic>
				</sub> values presented in the <xref ref-type="table" rid="t1">Table 1</xref>, expressed relative to the performance of untreated Norway spruce (<italic>Picea abies</italic>), which was chosen as the reference material and assigned a <italic>k</italic>
				<sub>
					<italic>wa</italic>
				</sub> value = 1.0.</p>
			<table-wrap id="t1">
				<label>Table 1</label>
				<caption>
					<title>
						<italic>k</italic>
						<sub>
							<italic>wa</italic>
						</sub> values (<xref ref-type="bibr" rid="B12">12</xref>).</title>
				</caption>
				<table>
					<colgroup>
						<col/>
						<col/>
					</colgroup>
					<thead>
						<tr>
							<th align="justify">Wood species</th>
							<th align="center">
								<italic>k</italic>
								<sub>
									<italic>wa</italic>
								</sub>
							</th>
						</tr>
					</thead>
					<tbody>
						<tr>
							<td align="justify">Norway spruce (<italic>Picea abies</italic>) sapwood&amp;heartwood</td>
							<td align="center">1.0</td>
						</tr>
						<tr>
							<td align="justify">Scots pine sapwood (<italic>Pinus sylvestris</italic>)</td>
							<td align="center">0.8</td>
						</tr>
						<tr>
							<td align="justify">Scots pine heartwood (<italic>Pinus sylvestris</italic>)</td>
							<td align="center">1.5</td>
						</tr>
						<tr>
							<td align="justify">European larch heartwood (<italic>Larix decidua</italic>)</td>
							<td align="center">1.5</td>
						</tr>
						<tr>
							<td align="justify">Siberian larch heartwood (<italic>Larix sibirica</italic>)</td>
							<td align="center">1.5</td>
						</tr>
						<tr>
							<td align="justify">Douglas fir heartwood (<italic>Pseudotsuga menziesii</italic>)</td>
							<td align="center">1.5</td>
						</tr>
						<tr>
							<td align="justify">English oak heartwood (<italic>Quercus robur</italic>)</td>
							<td align="center">1.0</td>
						</tr>
						<tr>
							<td align="justify">Black locust heartwood (<italic>Robinia pseudacacia</italic>)</td>
							<td align="center">1.5</td>
						</tr>
						<tr>
							<td align="justify">Western Red Cedar, heartwood (<italic>Thuja plicata</italic>)</td>
							<td align="center">1.5</td>
						</tr>
						<tr>
							<td align="justify">Coated materials</td>
							<td align="center">2.0</td>
						</tr>
						<tr>
							<td align="justify">Preservative-treated wood, modified wood and wood plastic composites (WPC)</td>
							<td align="center">1.0</td>
						</tr>
					</tbody>
				</table>
			</table-wrap>
			<p>It should be noted that a viable set of test methods has not yet been commonly accepted and until this occurs, the abovementioned <italic>k</italic>
				<sub>
					<italic>wa</italic>
				</sub> values must be considered provisional.</p>
			<p>An aspect which should be highlighted given its importance in the performance of timber exposed to the highly variable climatic conditions typical throughout most of Spain, is the effect of cracks on the moisture content of the wood and therefore on its durability. Meyer-Veltrup <italic>et al</italic>. (<xref ref-type="bibr" rid="B13">13</xref>) studied the effect of artificial cracks on MC in Norway spruce but found a minor effect, although the duration of the exposition in the study was very limited (three months), so the results can only be considered preliminary.</p>
			<p>Osawa <italic>et al</italic>. (<xref ref-type="bibr" rid="B14">14</xref>), working on flat grain redwood (<italic>Sequoia sempervirens</italic>) and Japanese cedar (<italic>Cryptomeria japonica</italic>) specimens used the X-ray densitometry method to study the effect of artificial cracks (slits) on moisture content distribution and found that high moisture content was only present at the bottom of the slits (at a depth of 20 mm), this moisture content being over 30&#x25; after 8 h of drying, regardless of the species. These authors concluded that cracks reaching a depth of 20 mm from the surface might increase the risk of decay, at least in the species studied.</p>
			<p>With regard to crack susceptibility, Meyer-Veltrup <italic>et al</italic>. (<xref ref-type="bibr" rid="B13">13</xref>) found high crack susceptibility in Scots pine and Norway spruce. They also concluded that cracks could provide a starting point for rot, which would affect service life, although they found no significant influence on MC.</p>
			<p>Several previous studies have addressed the relationship between moisture content and fungal activity (studies cited in (<xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B16">16</xref>), some of which have pointed to a risk of fungal attack even below the fibre saturation point, reaching the limit value of 16.3&#x25; in <italic>Picea abies</italic> (<xref ref-type="bibr" rid="B15">15</xref>). The risk of moisture leading to wood decay, however, is commonly considered to be above a moisture content of 20 to 30&#x25; (<xref ref-type="bibr" rid="B16 B17 B18">16-18</xref>). Morris and Winandy (<xref ref-type="bibr" rid="B19">19</xref>) considered moisture content of between 20&#x25; and 30&#x25; to be a suspicious grey area and therefore, for safety reasons, proposed a limit value of 20&#x25; to be used in North American light-framed construction. </p>
			<p>Isaksson and Thelandersson (<xref ref-type="bibr" rid="B5">5</xref>), who considered a moisture content threshold level of 25&#x25; to be that at which the decay process becomes active, proposed a measure of the moisture trapping effect of different features (including cracks) counting for the number of days in a year in which the moisture content is above 25&#x25;. This indicator (number of days with a given MC value) was also considered by Meyer-Veltrup and Brischke (<xref ref-type="bibr" rid="B3">3</xref>) as a useful and simple alternative indicator to the more complex and accurate performance models.</p>
			<p>As regards the influence of temperature on fungal growth, Zak and Wildman (<xref ref-type="bibr" rid="B20">20</xref>) found that the majority of fungi appear to develop satisfactorily at temperatures of between 5 and 35&#xba;C, while Viitanen (<xref ref-type="bibr" rid="B21">21</xref>) identified a lower limit for fungal development of 0&#xba;C.</p>
			<p>The objective of the present study is to improve our understanding of the factors affecting the biological resistance of timber and therefore the service life of timber elements by characterizing the effect of species under the prevalent climatic conditions in Spain. </p>
			<p>The discernible effect of species on the expected service life of untreated timber is mainly due, apart from aspects related to the natural durability of each species, to certain physical characteristics, such as their susceptibility to cracking, degree of permeability or rate of release in drying, since all of these aspects affect the time of wetness (time during which the wood has a moisture content above the established risk threshold) at the surface in contact with the water and the depth reached by the moisture. </p>
			<p>With respect to the effect of different wetting/releasing ability, wood species that are less permeable to water are expected to perform better than those which are more permeable in uses where wood is exposed to intermittent wetting (<xref ref-type="bibr" rid="B22">22</xref>). Hence, wetting/releasing ability is expected to play a crucial role in the performance of wood exposed to exterior conditions in those localities where rain events are short and scarce and dry periods are long and intense.</p>
		</sec>
		<sec id="sec2" sec-type="materials|methods">
			<label>2.</label>
			<title>Materials and methods</title>
			<p>In the context of the Spanish national project BIA2013-42434-R on the <italic>Evaluation of functional behaviour of wood in outdoor above ground applications,</italic> seven different field testing devices were deployed outdoors in seven different Spanish locations (<xref ref-type="fig" rid="f1">Figure 1</xref>). These locations were chosen to include the effect of the most representative climates in Spain, reflected in their respective Scheffer index values (<xref ref-type="table" rid="t2">Table 2</xref>). </p>
			<p>The Scheffer index (1971) is an index for estimating potential risk of decay in wood due to the effect of wood-degrading fungi. This index incorporates the multiplier effect of temperature (T) above a specific threshold value (2&#xba;C), a lower thermal limit for the growth of wood-rotting fungi, as well as precipitation frequency (the number of days per month, D, with more than 0.25mm precipitation in its initial formulation). The typical formulation in degrees Celsius is (<xref ref-type="disp-formula" rid="e3">Equation [3]</xref>): </p>
			<disp-formula id="e3">
				<mml:math id="mml-3">
					<mml:mrow>
						<mml:mrow>
							<mml:mi>I</mml:mi>
							<mml:mi>S</mml:mi>
							<mml:mo>=</mml:mo>
							<mml:mstyle displaystyle="true">
								<mml:munderover>
									<mml:mo>&#x2211;</mml:mo>
									<mml:mrow>
										<mml:mi>j</mml:mi>
										<mml:mi>a</mml:mi>
										<mml:mi>n</mml:mi>
									</mml:mrow>
									<mml:mrow>
										<mml:mi>d</mml:mi>
										<mml:mi>e</mml:mi>
										<mml:mi>c</mml:mi>
									</mml:mrow>
								</mml:munderover>
								<mml:mrow>
									<mml:mfrac>
										<mml:mrow>
											<mml:mrow>
												<mml:mo>(</mml:mo>
												<mml:mrow>
													<mml:mi>T</mml:mi>
													<mml:mo>&#x2212;</mml:mo>
													<mml:mtext>2</mml:mtext>
												</mml:mrow>
												<mml:mo>)</mml:mo>
											</mml:mrow>
											<mml:mrow>
												<mml:mo>(</mml:mo>
												<mml:mrow>
													<mml:mi>D</mml:mi>
													<mml:mo>&#x2212;</mml:mo>
													<mml:mtext>3</mml:mtext>
												</mml:mrow>
												<mml:mo>)</mml:mo>
											</mml:mrow>
										</mml:mrow>
										<mml:mrow>
											<mml:mtext>16</mml:mtext>
											<mml:mtext>.7</mml:mtext>
										</mml:mrow>
									</mml:mfrac>
								</mml:mrow>
							</mml:mstyle>
						</mml:mrow>
					</mml:mrow>
				</mml:math>
				<label>[3]</label>
			</disp-formula>
			<p>In this expression, a value of 16.7 is considered as the denominator of the equation so that the index value varied throughout the USA between 0 and 100. This value can be redefined within each country or geographic zone so that the IS varies between 0 and 100. Fern&#xe1;ndez-Golfin <italic>et al</italic>. (<xref ref-type="bibr" rid="B10">10</xref>) made use of the original 16.7 value.</p>
			<p>
				<xref ref-type="table" rid="t2">Table 2</xref> shows the Sheffer index values for each locality, calculated according to AEMET climate data for the period 1981-2010, using two calculation methods proposed by Fern&#xe1;ndez-Golfin <italic>et al</italic> (<xref ref-type="bibr" rid="B10">10</xref>), without considering (IS1) and considering (IS2) the effect of condensation. The data in <xref ref-type="table" rid="t2">Table 2</xref> reveal the discernible effects related to the presence of condensation and the reason why certain locations with similar IS1 values were chosen for the deployment of field testing devices.</p>
			<p>
				<xref ref-type="fig" rid="f1">Figure 1</xref> provides a general view of the variability of the Scheffer index (IS1) values obtained in Spain (<xref ref-type="bibr" rid="B10">10</xref>) along with the location of each of the field testing devices.</p>
			<fig id="f1">
				<label>Figure 1</label>
				<caption>
					<title>Test sites (IS1 Scheffer indexes in Spain (<xref ref-type="bibr" rid="B10">10</xref>)).</title>
				</caption>
				<graphic id="gra-1" xlink:href="MC-71-341-e236-gf1.png"/>
			</fig>
			<table-wrap id="t2">
				<label>Table 2</label>
				<caption>
					<title>Sheffer indexes of each site.</title>
				</caption>
				<table>
					<colgroup>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
					</colgroup>
					<thead>
						<tr>
							<th align="justify">Locality (Place)</th>
							<th align="center">IS1</th>
							<th align="center">IS2</th>
							<th align="center">Climate</th>
							<th align="center">Collateral effects</th>
							<th align="center">Installation date</th>
						</tr>
					</thead>
					<tbody>
						<tr>
							<td align="justify">Asturias-Llames (Private)</td>
							<td align="center">81</td>
							<td align="center">126</td>
							<td align="center">Northern-Atlantic coast</td>
							<td align="center">Sea effect</td>
							<td align="center">19/03/2015</td>
						</tr>
						<tr>
							<td align="justify">Vitoria (NEIKER)</td>
							<td align="center">45</td>
							<td align="center">76</td>
							<td align="center">Continental</td>
							<td align="center">Large sources of humidity (lake)</td>
							<td align="center">12/03/2015</td>
						</tr>
						<tr>
							<td align="justify">Palencia (University-ETSIAM)</td>
							<td align="center">23</td>
							<td align="center">74</td>
							<td align="center">Continental</td>
							<td align="center">Cold winters and dry summers</td>
							<td align="center">28/01/2015</td>
						</tr>
						<tr>
							<td align="justify">Madrid (INIA)</td>
							<td align="center">22</td>
							<td align="center">42</td>
							<td align="center">Continental</td>
							<td align="center">Long, hot summer</td>
							<td align="center">27/11/2014</td>
						</tr>
						<tr>
							<td align="justify">Cordoba (University-Rabanales)</td>
							<td align="center">16</td>
							<td align="center">35</td>
							<td align="center">Continental</td>
							<td align="center">Extremely hot summer</td>
							<td align="center">07/04/2015</td>
						</tr>
						<tr>
							<td align="justify">Huelva (University-La R&#xe1;bida)</td>
							<td align="center">26</td>
							<td align="center">62</td>
							<td align="center">Southern-Atlantic coast</td>
							<td align="center">Sea effect</td>
							<td align="center">08/04/2015</td>
						</tr>
						<tr>
							<td align="justify">Valencia (Private)</td>
							<td align="center">26</td>
							<td align="center">62</td>
							<td align="center">Mediterranean coast</td>
							<td align="center">Sea effect</td>
							<td align="center">4/03/2015 (removed 16/09/2015)</td>
						</tr>
					</tbody>
				</table>
			</table-wrap>
			<p>Each field testing device comprised a metal frame (<xref ref-type="fig" rid="f2">Figure 2</xref>) with seven planks of sawn wood measuring 20x100x750 mm<sup>3</sup>, arranged horizontally and with a gap of 20 mm between each. The planks in each field-testing device were from three different pine wood types: Scots (PS), Laricio (PL) and Radiata (PR), as well as from Sweet chestnut (CS), <italic>Eucalyptus globulus</italic> (EU), thermo-treated radiata pine (at 210&#xba;C) and Norway spruce (SP). These species were chosen because of their common presence in construction products in both the Spanish and European markets and because of their particular characteristics regarding wetting/releasing ability and crack susceptibility and the relationship of the latter with moisture and liquid water. The field testing devices were situated outdoors with no protection at all against the sun or rainfall. All devices were arranged in a north-south direction (boards arranged in an east-west direction).</p>
			<fig id="f2">
				<label>Figure 2</label>
				<caption>
					<title>Trial set-up (Madrid).</title>
				</caption>
				<graphic id="gra-2" xlink:href="MC-71-341-e236-gf2.png"/>
			</fig>
			<p>In each trial set-up, the moisture content of each of the seven solid wood pieces were recorded every two hours using a data logging device installed inside a protective box to prevent leaking (<xref ref-type="fig" rid="f2">Figure 2</xref>). Moisture content measurements were made during 3 years (2016, 2017 and 2018).</p>
			<p>All the pieces included in each test device were selected from approximately tangentially sawn wood, placed with the pith facing upwards to avoid the collateral effect produced by excessive checking. </p>
			<p>Stainless steel screws inserted from the lower face up to the centre of the pieces (10 mm) were used as moisture content sensors, the outer 7mm of which were Teflon covered to avoid measuring the surface moisture. To determine the temperature of the wood a Resistance Temperature Detector (RTD) was inserted into one of the pieces (Scots pine) of wood in each trial and recorded at the same time than the moisture content.</p>
			<p>The horizontal arrangement, separation and size of the planks in this approach as well as the measurement of the moisture content on the underside of the central part of the planks were adopted in accordance with the recommendations in Cost Action FP1303 (<xref ref-type="bibr" rid="B23">23</xref>) for the characterization of exterior wood performance at European level with the aim of creating a common database. The device used to measure and record the moisture content of the wood was composed of an eight channel moisture sensor (Type Gigamodule, Scanntronik GmbH) and a datalogger (Type Thermofox, Scanntronik GmbH), which have commonly been employed in other similar studies conducted at European level, albeit under other climatic conditions. Maximum methodological coincidence was sought with other characterization studies at European level under Cost Action FP1303 in order to contribute to a European database and thus be able to compare results. </p>
			<p>The seven testing devices were set up at the locations and dates listed in the <xref ref-type="table" rid="t2">Table 2</xref>.</p>
			<p>The testing device located in Valencia was withdrawn in September 2016 due to a problem with permission for the installation. As the Valencia and Huelva locations have the same Scheffer index values (IS1 and IS2) as well as sea effect (<xref ref-type="table" rid="t2">Table 2</xref>) the Valencia device was not replaced by another and the location was removed from the analysis.</p>
			<p>To obtain high quality data and avoid measurement errors, the functioning of the measurement device (Gigamodule) was continuously monitored by connecting a 10 Mohms calibrated resistance to channel 8 as well as carrying out monthly controls using manual devices (GANN RTU600) for measuring the moisture content of every plank through moisture content sensors similar to those used for the primary measurements. These duplicated sensors were installed on the underside of each plank, at a distance of 50 mm from the primary sensors. Thus, a monthly comparison between primary and secondary measurements was performed, taking into account the acceptance criteria of maximum differences of &#xb1;2&#x25;. All the manual measurements were taken in the absence of active rain events. Fortunately, all the measurements were within the acceptance threshold.</p>
			<p>In order to convert the electrical resistance readings (R) from the measurement devices to values for wood moisture content (MC), mathematical models were used to relate both variables to each other along with temperature. For the laricio, radiata and scots pines, as well as for the sweet chestnut, the thermo-treated radiata pine and the eucalyptus, the models used in this study were taken from previous studies (<xref ref-type="bibr" rid="B24 B25 B26">24-26</xref>). In the case of spruce, the model used was that published by Fors&#xe9;n and Tarvainen (<xref ref-type="bibr" rid="B27">27</xref>). Thus, the models finally used in the present study were the following (adjusted to 20&#xba;C):</p>
			<list list-type="bullet">
				<list-item>
					<p>
						<italic>Eucalyptus globulus</italic>: MC=(LOG10(LOG10(R)+1)-1.20197)/(-0.05422) (R<sup>2</sup>= 99.7&#x25;)</p>
				</list-item>
				<list-item>
					<p>Laricio Pine: MC=(LOG10(LOG10(R)+1)- 1.078018)/(-0.03783) (R<sup>2</sup>= 99.4&#x25;)</p>
				</list-item>
				<list-item>
					<p>Spruce: MC=(LOG10(LOG10(R)+1)-1.014)/(-0.034) (R<sup>2</sup>= 92.2)</p>
				</list-item>
				<list-item>
					<p>Scots pine: MC=(LOG10(LOG10(R)+1)- 1.097831)/(-0.03914) (R<sup>2</sup>= 99.5&#x25;)</p>
				</list-item>
				<list-item>
					<p>Radiata pine: MC=(LOG10(LOG10(R)+1)- 1.105843)/(-0.03964) (R<sup>2</sup>= 99.2&#x25;)</p>
				</list-item>
				<list-item>
					<p>Sweet chestnut: MC=(LOG10(LOG10(R)+1)-1.03248)/(-0.041097) (R<sup>2</sup>= 99.3&#x25;)</p>
				</list-item>
				<list-item>
					<p>Thermo-treated radiata pine: MC=(LOG10(LOG10(R)+1)-1.08884)/(-0.046215) (R<sup>2</sup>= 99.7&#x25;)</p>
				</list-item>
				<list-item>
					<p>Maritime pine: MC=(LOG10(LOG10(R)+1)- 1.093632)/(-0.04067) (R<sup>2</sup>= 99.5&#x25;)</p>
				</list-item>
			</list>
			<p>The moisture content measurements were adjusted to 20&#xba;C according to our own and unpublished model, later included in the Scanntronik Softfox 3.03 software for automatic corrections. </p>
			<p>To estimate species-specific decay potentials and how they are affected by the different climatological characteristics of sites, an index (NMC18) consisting of the number of days with moisture content greater than 18&#x25; was used in this study. </p>
			<p>A critical limit of 18&#x25; in MC was used rather than a value within the interval 20&#x25; to 25&#x25; for the following reasons:</p>
			<list list-type="order">
				<list-item>
					<p>A MC value of 18&#x25; for solid timber represents the threshold of change from service class 2 to class 3 under norm EN 1995-1-1 (Eurocode 5) (<xref ref-type="bibr" rid="B28">28</xref>), also included in the Spanish Technical Building Code (<xref ref-type="bibr" rid="B29">29</xref>). This value of 18&#x25; is the limit based on which the engineer or design professional must calculate and consider requirements for products due to high moisture content. The use of this threshold allows conclusions to be drawn not only with regard to the biological durability, but also to the physical endurance of the timber elements, especially laminated and agglomerated timber products.</p>
				</list-item>
				<list-item>
					<p>At all the locations in Spain, except for certain specific moments, the average temperature over the year (monthly average temperatures between 3&#xba; and 30&#xba;C) is favourable for the development of fungi, since it is well above the lower threshold of activity established by Viitanen (<xref ref-type="bibr" rid="B21">21</xref>). For this reason, it is necessary to consider a more conservative moisture content limit since a greater intensity of fungal attack can be expected.</p>
				</list-item>
				<list-item>
					<p>As highlighted in the introduction, numerous studies have detected the colonization and even attack by fungi decay at moisture content levels below the fibre saturation point, and even at values below 18&#x25;. Johannsson <italic>et al</italic>. (<xref ref-type="bibr" rid="B30">30</xref>) established a relative humidity (RH) of 80&#x25; at ambient temperature, corresponding to an EMC of 18&#x25; in solid wood, above which there is a non-negligible risk of fungi decay development. Similarly, Morris and Winandy (<xref ref-type="bibr" rid="B19">19</xref>) proposed a limit value of 20&#x25;, for safety reasons, to be used in North American light-framed construction. These factors, combined with the favourable thermal conditions in the Iberian Peninsula for the rapid development of fungi decay, it was decided to adopt a conservative risk management strategy, using a MC threshold of 18&#x25;.</p>
				</list-item>
				<list-item>
					<p>The measurement technique used to estimate the moisture content of the wood (electrical resistance), when used in exterior conditions and on material with drying cracks (common in locations with high seasonal MC variation) presents notable uncertainty as the water accumulated in the cracks can lead to unusual high measurements. The intensity of cracking was high at all the locations except for Asturias-Llames, so unreal fluctuations occurred which affected the precision of the MC measurement. These abnormally high values last for short periods of time (4-8 hours) but are sufficient to artificially increase the number of days with MC values above 22 or 25&#x25; and affecting also the maximum MC values. In all the studied localities, a moisture content level above 18&#x25; already points to the presence of rain events and therefore the existence of a non-negligible risk of moisture content compatible with fungal attack.</p>
				</list-item>
			</list>
			<p>Climate data for all sites were available from AEMET (Agencia Estatal de Meteorolog&#xed;a, Spanish Metereological State Agency) weather stations, where measurements of daily precipitation, daily relative humidity (RH) and average daily temperature were recorded.</p>
			<p>All the wood samples from each of the field testing devices were evaluated every six months to detect the presence of decay according to EN 252 (<xref ref-type="bibr" rid="B7">7</xref>) (<xref ref-type="table" rid="t3">Table 3</xref>).</p>
			<table-wrap id="t3">
				<label>Table 3</label>
				<caption>
					<title>Rating system for the assessment of attack caused by microorganisms on test samples.</title>
				</caption>
				<table>
					<colgroup>
						<col/>
						<col/>
						<col/>
					</colgroup>
					<thead>
						<tr>
							<th align="left">Rating </th>
							<th align="left">Classification </th>
							<th align="left">Definition </th>
						</tr>
					</thead>
					<tbody>
						<tr>
							<td align="center">
								<bold>0</bold>
							</td>
							<td align="left">No attack </td>
							<td align="left">No change perceptible by the means at the disposal of the inspector in the field. If only a change of color is observed, It shall be rated 0. </td>
						</tr>
						<tr>
							<td align="center">
								<bold>1</bold>
							</td>
							<td align="left">Slight attack </td>
							<td align="left">Perceptible changes, but very limited in their intensity and their position or distribution: changes, which only reveal themselves externally by superficial degradation, softening of the wood being the most common symptom. </td>
						</tr>
						<tr>
							<td align="center">
								<bold>2</bold>
							</td>
							<td align="left">Moderate attack </td>
							<td align="left">Clear changes: softening of the wood to a depth of at least 2 mm over a surface area covering at least 10 cm<sup>2</sup>, or softening to a depth of at least 5 mm over a surface area less than 1 cm<sup>2</sup>. </td>
						</tr>
						<tr>
							<td align="center">
								<bold>3</bold>
							</td>
							<td align="left">Severe attack </td>
							<td align="left">Severe changes: marked decay in the wood to a depth of at least 3 mm over a wider surface (covering at least 25 cm<sup>2</sup>), or softening to a depth of at least 10 mm over a more limited surface area. </td>
						</tr>
						<tr>
							<td align="center">
								<bold>4</bold>
							</td>
							<td align="left">Failure </td>
							<td align="left">Impact failure of the sample in the field. </td>
						</tr>
					</tbody>
				</table>
			</table-wrap>
			<p>The moisture content of the thermo-treated radiata pine never exceeded the threshold of 18&#x25; at any time or location, hence it was excluded from the analysis. </p>
			<p>The crack evaluation was carried out every six months during outdoor exposure, according to ISO 4628-4 criteria (<xref ref-type="bibr" rid="B31">31</xref>) (<xref ref-type="table" rid="t4">Table 4</xref>). </p>
			<table-wrap id="t4">
				<label>Table 4</label>
				<caption>
					<title>Classification of cracks according to ISO 4628-4.</title>
				</caption>
				<table>
					<colgroup>
						<col/>
						<col/>
						<col/>
					</colgroup>
					<thead>
						<tr>
							<th align="left">Class </th>
							<th align="left">Number of cracks</th>
							<th align="left">Size of cracks</th>
						</tr>
					</thead>
					<tbody>
						<tr>
							<td align="center">
								<bold>0</bold>
							</td>
							<td align="left">No cracks visible </td>
							<td align="left">Not visible under x 10 magnification </td>
						</tr>
						<tr>
							<td align="center">
								<bold>1</bold>
							</td>
							<td align="left">Single cracks, barely visible and only on the surface </td>
							<td align="left">Visible under magnification up to x 10 </td>
						</tr>
						<tr>
							<td align="center">
								<bold>2</bold>
							</td>
							<td align="left">Small cracks, clearly visible on the surface </td>
							<td align="left">Visible with normal corrected vision </td>
						</tr>
						<tr>
							<td align="center">
								<bold>3</bold>
							</td>
							<td align="left">Moderate number of cracks </td>
							<td align="left">Clearly visible with normal corrected vision </td>
						</tr>
						<tr>
							<td align="center">
								<bold>4</bold>
							</td>
							<td align="left">Large number of cracks </td>
							<td align="left">Large cracks generally up to 1 mm wide </td>
						</tr>
						<tr>
							<td align="center">
								<bold>5</bold>
							</td>
							<td align="left">Very large number of cracks </td>
							<td align="left">Very large cracks generally more than 1 mm wide </td>
						</tr>
					</tbody>
				</table>
			</table-wrap>
			<p>Regarding the analysis of crack susceptibility for the different wood species, our initial hypothesis was to consider that this susceptibility could be established by means of the use of the Coefficient of anisotropy (relation between tangential and radial shrinkage) and the Absolute anisotropy (difference between the total tangential and radial shrinkage). The values for both coefficients for the different wood species considered in the present study can be read in <xref ref-type="table" rid="t5">Table 5</xref>. These values were obtained according to ISO 4469 (<xref ref-type="bibr" rid="B32">32</xref>) methodology.</p>
			<table-wrap id="t5">
				<label>Table 5</label>
				<caption>
					<title>Physical properties of wood affecting wood-water relationships.</title>
				</caption>
				<table>
					<colgroup>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
					</colgroup>
					<thead>
						<tr>
							<th align="justify">Property</th>
							<th align="center">Standard</th>
							<th align="center">Pine Scots</th>
							<th align="center">Pine Laricio</th>
							<th align="center">Pine Radiata</th>
							<th align="center">Spruce</th>
							<th align="center">Eucalypt</th>
							<th align="center">Chestnut</th>
							<th align="center">Source</th>
						</tr>
					</thead>
					<tbody>
						<tr>
							<td align="left">Coeff of anisotropy</td>
							<td align="center">ISO 4469</td>
							<td align="center">1.8</td>
							<td align="center">1.5</td>
							<td align="center">1.8</td>
							<td align="center">2.2*</td>
							<td align="center">2.3</td>
							<td align="center">2.2</td>
							<td align="center">(<xref ref-type="bibr" rid="B33">33</xref>)</td>
						</tr>
						<tr>
							<td align="left">Absolute anisotropy</td>
							<td align="center">ISO 4469</td>
							<td align="center">3.2</td>
							<td align="center">2.6</td>
							<td align="center">3.3</td>
							<td align="center">3.0</td>
							<td align="center">5.7</td>
							<td align="center">4.3</td>
							<td align="center">* (<xref ref-type="bibr" rid="B34">34</xref>)</td>
						</tr>
					</tbody>
				</table>
			</table-wrap>
		</sec>
		<sec id="sec3" sec-type="results|discussion">
			<label>3.</label>
			<title>Results and discussion</title>
			<p>
				<xref ref-type="table" rid="t6">Table 6</xref> shows an annual summary of the main results per species and location. <xref ref-type="table" rid="t7">Table 7</xref> presents a summary of the values recorded over the three years for each location and wood species.</p>
			<p>The data in <xref ref-type="table" rid="t6">tables 6</xref> and <xref ref-type="table" rid="t7">7</xref> are derived from the daily data (measures taken at 12a.m.) for MC and temperature of the wood, from which monthly averages, an annual value (<xref ref-type="table" rid="t6">Table 6</xref>) and subsequently a value for the whole period, are calculated (<xref ref-type="table" rid="t7">Table 7</xref>).</p>
			<p>The data shown in <xref ref-type="table" rid="t6">Table 6</xref> are the following: </p>
			<list list-type="bullet">
				<list-item>
					<p>“Rt”: Total annual rainfall in mm</p>
				</list-item>
				<list-item>
					<p>“NR”: Total number of rainfall days with precipitation of more than 0.2mm </p>
				</list-item>
				<list-item>
					<p>“NR10”: Total number of rainfall days with precipitation of more than 10 mm</p>
				</list-item>
				<list-item>
					<p>“NR50”: Total number of rainfall days with precipitation of more than 50 mm</p>
				</list-item>
				<list-item>
					<p>“NMC18”: Total number of days with MC above 18&#x25;</p>
				</list-item>
				<list-item>
					<p>“NMC18R”: Percentage of the number of days with MC above 18&#x25; relative to the reference species (SP-Norway spruce), calculated for each location. For SP, NMC18R will always be 1.00</p>
				</list-item>
				<list-item>
					<p>“Aver_NMC18R”: Average value of NMC18R per species for the three years analyzed (2016, 2017, 2018)</p>
				</list-item>
				<list-item>
					<p>“SP”: Wood species (EU-Eucalypt, PL-Laricio Pine, SP-Norway Spruce, PR-radiata Pine, CS-Chestnut)</p>
				</list-item>
			</list>
			<p>
				<xref ref-type="table" rid="t7">Table 7</xref> contains the following data:</p>
			<list list-type="bullet">
				<list-item>
					<p>“IS1”: Scheffer index calculated according to the original expression (<xref ref-type="bibr" rid="B10">10</xref>)</p>
				</list-item>
				<list-item>
					<p>“IS2”: Scheffer index calculated taking into account the effect of condensations (<xref ref-type="bibr" rid="B10">10</xref>)</p>
				</list-item>
				<list-item>
					<p>“&#x3a3;T<sub>med</sub>”: Summation (three years) of the average monthly temperatures</p>
				</list-item>
				<list-item>
					<p>“&#x3a3;NT30”: Summation (three years) of the number of days with temperature above 30&#xba;C</p>
				</list-item>
				<list-item>
					<p>“&#x3a3;NT&lt;10”: Summation (three years) of the number of days with temperature below 10&#xba;C</p>
				</list-item>
				<list-item>
					<p>“&#x3a3;Rt”: Summation (three years) of the annual rainfall</p>
				</list-item>
				<list-item>
					<p>“&#x3a3;NR”: Summation (three years) of the number of days with rainfall of more than 0.2 mm</p>
				</list-item>
				<list-item>
					<p>“&#x3a3;NR10”: Summation (three years) of the number of days with rainfall above 10 mm</p>
				</list-item>
				<list-item>
					<p>“&#x3a3;NR50”: Summation (three years) of the number of days with rainfall above 50 mm</p>
				</list-item>
				<list-item>
					<p>“NR50R”: Percentage of days with rainfall above 50 mm (&#x3a3;NR50) with respect to the total (&#x3a3;NR). This is a measure of the torrential nature of the rainfall.</p>
				</list-item>
			</list>
			<table-wrap id="t6">
				<label>Table 6</label>
				<caption>
					<title>Summary of annual results per species and location.</title>
				</caption>
				<table>
					<colgroup>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
					</colgroup>
					<thead>
						<tr>
							<th align="left">Place</th>
							<th align="center">SP</th>
							<th align="center">Year</th>
							<th align="center">Rt</th>
							<th align="center">NR</th>
							<th align="left">NR10</th>
							<th align="center">NR50</th>
							<th align="center">NMC18</th>
							<th align="center">NMC18R</th>
							<th align="center">Aver_NMC18R</th>
							<th align="center">Place</th>
							<th align="center">SP</th>
							<th align="center">Year</th>
							<th align="center">Rt</th>
							<th align="center">NR</th>
							<th align="left">NR10</th>
							<th align="center">NR50</th>
							<th align="center">NMC18</th>
							<th align="center">NMC18R</th>
							<th align="center">Aver_NMC18R</th>
						</tr>
					</thead>
					<tbody>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2016</td>
							<td align="center"> 979.5</td>
							<td align="center"> 156</td>
							<td align="center"> 105</td>
							<td align="center"> 67</td>
							<td align="center"> 21</td>
							<td align="center"> 0.06</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2016</td>
							<td align="center"> 559.2</td>
							<td align="center"> 61</td>
							<td align="center"> 52</td>
							<td align="center"> 32</td>
							<td align="center"> 18</td>
							<td align="center"> 0.26</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2017</td>
							<td align="center"> 1239.6</td>
							<td align="center"> 174</td>
							<td align="center"> 131</td>
							<td align="center"> 74</td>
							<td align="center"> 20</td>
							<td align="center"> 0.05</td>
							<td align="center"> 0.07</td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2017</td>
							<td align="center"> 513.7</td>
							<td align="center"> 33</td>
							<td align="center"> 30</td>
							<td align="center"> 17</td>
							<td align="center"> 13</td>
							<td align="center"> 0.25</td>
							<td align="center"> 0.27</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2018</td>
							<td align="center"> 1281.3</td>
							<td align="center"> 182</td>
							<td align="center"> 134</td>
							<td align="center"> 76</td>
							<td align="center"> 30</td>
							<td align="center"> 0.08</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2018</td>
							<td align="center"> 588.0</td>
							<td align="center"> 85</td>
							<td align="center"> 61</td>
							<td align="center"> 33</td>
							<td align="center"> 28</td>
							<td align="center"> 0.29</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 313</td>
							<td align="center"> 0.95</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 60</td>
							<td align="center"> 0.88</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 349</td>
							<td align="center"> 0.96</td>
							<td align="center"> 0.96</td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 50</td>
							<td align="center"> 0.94</td>
							<td align="center"> 0.91</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 356</td>
							<td align="center"> 0.98</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 88</td>
							<td align="center"> 0.90</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 330</td>
							<td align="center"> 1.00</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 68</td>
							<td align="center"> 1.00</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 365</td>
							<td align="center"> 1.00</td>
							<td align="center"> 1.00</td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 52</td>
							<td align="center"> 1.00</td>
							<td align="center"> 1.00</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 365</td>
							<td align="center"> 1.00</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 98</td>
							<td align="center"> 1.00</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 324</td>
							<td align="center"> 0.98</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 70</td>
							<td align="center"> 1.03</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 363</td>
							<td align="center"> 0.99</td>
							<td align="center"> 0.99</td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 57</td>
							<td align="center"> 1.08</td>
							<td align="center"> 1.04</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 360</td>
							<td align="center"> 0.99</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 99</td>
							<td align="center"> 1.01</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 319</td>
							<td align="center"> 0.97</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 59</td>
							<td align="center"> 0.87</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 363</td>
							<td align="center"> 1.00</td>
							<td align="center"> 0.98</td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 46</td>
							<td align="center"> 0.87</td>
							<td align="center"> 0.87</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 358</td>
							<td align="center"> 0.98</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 86</td>
							<td align="center"> 0.88</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 169</td>
							<td align="center"> 0.51</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 32</td>
							<td align="center"> 0.47</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 201</td>
							<td align="center"> 0.55</td>
							<td align="center"> 0.54</td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 22</td>
							<td align="center"> 0.42</td>
							<td align="center"> 0.44</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Llames</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 208</td>
							<td align="center"> 0.57</td>
							<td align="center"> </td>
							<td align="center">
								<bold>Huelva</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 43</td>
							<td align="center"> 0.44</td>
							<td align="center"> </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Place</bold>
							</td>
							<td align="center">
								<bold>SP</bold>
							</td>
							<td align="center">
								<bold>Year</bold>
							</td>
							<td align="center">
								<bold>Rt</bold>
							</td>
							<td align="center">
								<bold>NR</bold>
							</td>
							<td align="left">
								<bold>NR10</bold>
							</td>
							<td align="center">
								<bold>NR50</bold>
							</td>
							<td align="center">
								<bold>NMC18</bold>
							</td>
							<td align="center">
								<bold>NMC18R</bold>
							</td>
							<td align="center">
								<bold>Aver_NMC18R</bold>
							</td>
							<td align="center">
								<bold>Place</bold>
							</td>
							<td align="center">
								<bold>SP</bold>
							</td>
							<td align="center">
								<bold>Year</bold>
							</td>
							<td align="center">
								<bold>Rt</bold>
							</td>
							<td align="center">
								<bold>NR</bold>
							</td>
							<td align="left">
								<bold>NR10</bold>
							</td>
							<td align="center">
								<bold>NR50</bold>
							</td>
							<td align="center">
								<bold>NMC18</bold>
							</td>
							<td align="center">
								<bold>NMC18R</bold>
							</td>
							<td align="center">
								<bold>Aver_NMC18R</bold>
							</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2016</td>
							<td align="center"> 683.1</td>
							<td align="center"> 162</td>
							<td align="center"> 110</td>
							<td align="center"> 39</td>
							<td align="center"> 33</td>
							<td align="center"> 0.18</td>
							<td align="center"> </td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2016</td>
							<td align="center"> 597.4</td>
							<td align="center"> 73</td>
							<td align="center"> 61</td>
							<td align="center"> 37</td>
							<td align="center"> 24</td>
							<td align="center"> 0.35</td>
							<td align="center"> </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2017</td>
							<td align="center"> 613.9</td>
							<td align="center"> 130</td>
							<td align="center"> 90</td>
							<td align="center"> 40</td>
							<td align="center"> 35</td>
							<td align="center"> 0.19</td>
							<td align="center"> 0.19</td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2017</td>
							<td align="center"> 339.3</td>
							<td align="center"> 48</td>
							<td align="center"> 40</td>
							<td align="center"> 22</td>
							<td align="center"> 15</td>
							<td align="center"> 0.39</td>
							<td align="center"> 0.40</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2018</td>
							<td align="center"> 693.6</td>
							<td align="center"> 167</td>
							<td align="center"> 120</td>
							<td align="center"> 50</td>
							<td align="center"> 49</td>
							<td align="center"> 0.21</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2018</td>
							<td align="center"> 619.7</td>
							<td align="center"> 92</td>
							<td align="center"> 67</td>
							<td align="center"> 36</td>
							<td align="center"> 38</td>
							<td align="center"> 0.45</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 185</td>
							<td align="center"> 0.98</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 61</td>
							<td align="center"> 0.88</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 180</td>
							<td align="center"> 0.96</td>
							<td align="center"> 0.98</td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 33</td>
							<td align="center"> 0.87</td>
							<td align="center"> 0.91</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 230</td>
							<td align="center"> 0.98</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 83</td>
							<td align="center"> 0.99</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 188</td>
							<td align="center"> 1.00</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 69</td>
							<td align="center"> 1.00</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 187</td>
							<td align="center"> 0.80</td>
							<td align="center"> 1.00</td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 38</td>
							<td align="center"> 1.00</td>
							<td align="center"> 1.00</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 235</td>
							<td align="center"> 1.00</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 84</td>
							<td align="center"> 1.00</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 191</td>
							<td align="center"> 1.02</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 74</td>
							<td align="center"> 1.07</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 191</td>
							<td align="center"> 1.02</td>
							<td align="center"> 1.02</td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 42</td>
							<td align="center"> 1.11</td>
							<td align="center"> 1.09</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 243</td>
							<td align="center"> 1.03</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 91</td>
							<td align="center"> 1.08</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 186</td>
							<td align="center"> 0.99</td>
							<td align="center"> </td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2016</td>
							<td align="center"> 597.4</td>
							<td align="center"> 73</td>
							<td align="center"> 61</td>
							<td align="center"> 37</td>
							<td align="center"> 52</td>
							<td align="center"> 0.75</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 181</td>
							<td align="center"> 0.97</td>
							<td align="center"> 0.99</td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2017</td>
							<td align="center"> 339.3</td>
							<td align="center"> 48</td>
							<td align="center"> 40</td>
							<td align="center"> 22</td>
							<td align="center"> 32</td>
							<td align="center"> 0.84</td>
							<td align="center"> 0.81</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 239</td>
							<td align="center"> 1.02</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2018</td>
							<td align="center"> 619.7</td>
							<td align="center"> 92</td>
							<td align="center"> 67</td>
							<td align="center"> 36</td>
							<td align="center"> 70</td>
							<td align="center"> 0.83</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 100</td>
							<td align="center"> 0.53</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2016</td>
							<td align="center"> 597.4</td>
							<td align="center"> 73</td>
							<td align="center"> 61</td>
							<td align="center"> 37</td>
							<td align="center"> 22</td>
							<td align="center"> 0.32</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 95</td>
							<td align="center"> 0.51</td>
							<td align="center"> 0.51</td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2017</td>
							<td align="center"> 339.3</td>
							<td align="center"> 48</td>
							<td align="center"> 40</td>
							<td align="center"> 22</td>
							<td align="center"> 11</td>
							<td align="center"> 0.29</td>
							<td align="center"> 0.32</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Vitoria</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 115</td>
							<td align="center"> 0.49</td>
							<td align="center"> </td>
							<td align="center">
								<bold>Cordoba</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2018</td>
							<td align="center"> 619.7</td>
							<td align="center"> 92</td>
							<td align="center"> 67</td>
							<td align="center"> 36</td>
							<td align="center"> 30</td>
							<td align="center"> 0.36</td>
							<td align="center"> </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Place</bold>
							</td>
							<td align="center">
								<bold>SP</bold>
							</td>
							<td align="center">
								<bold>Year</bold>
							</td>
							<td align="center">
								<bold>Rt</bold>
							</td>
							<td align="center">
								<bold>NR</bold>
							</td>
							<td align="left">
								<bold>NR10</bold>
							</td>
							<td align="center">
								<bold>NR50</bold>
							</td>
							<td align="center">
								<bold>NMC18</bold>
							</td>
							<td align="center">
								<bold>NMC18R</bold>
							</td>
							<td align="center">
								<bold>Aver_NMC18R</bold>
							</td>
							<td align="center">
								<bold>Place</bold>
							</td>
							<td align="center">
								<bold>SP</bold>
							</td>
							<td align="center">
								<bold>Year</bold>
							</td>
							<td align="center">
								<bold>Rt</bold>
							</td>
							<td align="center">
								<bold>NR</bold>
							</td>
							<td align="left">
								<bold>NR10</bold>
							</td>
							<td align="center">
								<bold>NR50</bold>
							</td>
							<td align="center">
								<bold>NMC18</bold>
							</td>
							<td align="center">
								<bold>NMC18R</bold>
							</td>
							<td align="center">
								<bold>Aver_NMC18R</bold>
							</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2016</td>
							<td align="center"> 353.8</td>
							<td align="center"> 95</td>
							<td align="center"> 63</td>
							<td align="center"> 22</td>
							<td align="center"> 47</td>
							<td align="center"> 0.27</td>
							<td align="center"> </td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2016</td>
							<td align="center"> 453.5</td>
							<td align="center"> 92</td>
							<td align="center"> 67</td>
							<td align="center"> 34</td>
							<td align="center"> 45</td>
							<td align="center"> 0.36</td>
							<td align="center"> </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2017</td>
							<td align="center"> 187.7</td>
							<td align="center"> 60</td>
							<td align="center"> 40</td>
							<td align="center"> 14</td>
							<td align="center"> 25</td>
							<td align="center"> 0.30</td>
							<td align="center"> 0.29</td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2017</td>
							<td align="center"> 283.8</td>
							<td align="center"> 58</td>
							<td align="center"> 36</td>
							<td align="center"> 14</td>
							<td align="center"> 10</td>
							<td align="center"> 0.37</td>
							<td align="center"> 0.37</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2018</td>
							<td align="center"> 531.4</td>
							<td align="center"> 120</td>
							<td align="center"> 89</td>
							<td align="center"> 36</td>
							<td align="center"> 58</td>
							<td align="center"> 0.30</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> EU</td>
							<td align="center"> 2018</td>
							<td align="center"> 522.3</td>
							<td align="center"> 103</td>
							<td align="center"> 75</td>
							<td align="center"> 32</td>
							<td align="center"> 41</td>
							<td align="center"> 0.39</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 149</td>
							<td align="center"> 0.87</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 115</td>
							<td align="center"> 0.91</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 70</td>
							<td align="center"> 0.83</td>
							<td align="center"> 0.85</td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 25</td>
							<td align="center"> 0.93</td>
							<td align="center"> 0.91</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 168</td>
							<td align="center"> 0.86</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> PL</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 96</td>
							<td align="center"> 0.91</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 172</td>
							<td align="center"> 1.00</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 126</td>
							<td align="center"> 1.00</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 84</td>
							<td align="center"> 1.00</td>
							<td align="center"> 1.00</td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 27</td>
							<td align="center"> 1.00</td>
							<td align="center"> 1.00</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 196</td>
							<td align="center"> 1.00</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> SP</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 106</td>
							<td align="center"> 1.00</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 166</td>
							<td align="center"> 0.97</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 135</td>
							<td align="center"> 1.07</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 78</td>
							<td align="center"> 0.93</td>
							<td align="center"> 0.95</td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 29</td>
							<td align="center"> 1.07</td>
							<td align="center"> 1.07</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 190</td>
							<td align="center"> 0.97</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> PS</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 113</td>
							<td align="center"> 1.07</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 146</td>
							<td align="center"> 0.85</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 110</td>
							<td align="center"> 0.87</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 66</td>
							<td align="center"> 0.79</td>
							<td align="center"> 0.82</td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 24</td>
							<td align="center"> 0.89</td>
							<td align="center"> 0.89</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 162</td>
							<td align="center"> 0.83</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> PR</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 95</td>
							<td align="center"> 0.90</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 55</td>
							<td align="center"> 0.32</td>
							<td align="center">  </td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2016</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 42</td>
							<td align="center"> 0.33</td>
							<td align="center">  </td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 25</td>
							<td align="center"> 0.30</td>
							<td align="center"> 0.32</td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2017</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 10</td>
							<td align="center"> 0.37</td>
							<td align="center"> 0.37</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Palencia</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 70</td>
							<td align="center"> 0.36</td>
							<td align="center"> </td>
							<td align="center">
								<bold>Madrid</bold>
							</td>
							<td align="center"> CS</td>
							<td align="center"> 2018</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> 42</td>
							<td align="center"> 0.40</td>
							<td align="center">  </td>
						</tr>
					</tbody>
				</table>
			</table-wrap>
			<table-wrap id="t7">
				<label>Table 7</label>
				<caption>
					<title>Summary of the three years of climatic records measured for each location and species.</title>
				</caption>
				<table>
					<colgroup>
						<col/>
						<col span="6"/>
					</colgroup>
					<thead>
						<tr>
							<th align="left" rowspan="2">Species</th>
							<th align="center" colspan="6">LOCATIONS (average NMC18R)</th>
						</tr>
						<tr>
							<th align="center">Llames</th>
							<th align="center">Vitoria</th>
							<th align="center">Palencia</th>
							<th align="center">Madrid</th>
							<th align="center">Cordoba</th>
							<th align="center">Huelva</th>
						</tr>
					</thead>
					<tbody>
						<tr>
							<td align="left">
								<bold>PL</bold>
							</td>
							<td align="center"> 0.96</td>
							<td align="center"> 0.98</td>
							<td align="center"> 0.85</td>
							<td align="center"> 0.91</td>
							<td align="center"> 0.91</td>
							<td align="center"> 0.91</td>
						</tr>
						<tr>
							<td align="left">
								<bold>PR</bold>
							</td>
							<td align="center"> 0.98</td>
							<td align="center"> 0.99</td>
							<td align="center"> 0.82</td>
							<td align="center"> 0.89</td>
							<td align="center"> 0.81</td>
							<td align="center"> 0.87</td>
						</tr>
						<tr>
							<td align="left">
								<bold>PS</bold>
							</td>
							<td align="center"> 1.02</td>
							<td align="center"> 1.02</td>
							<td align="center"> 0.95</td>
							<td align="center"> 1.07</td>
							<td align="center"> 1.09</td>
							<td align="center"> 1.04</td>
						</tr>
						<tr>
							<td align="left">
								<bold>SP</bold>
							</td>
							<td align="center"> 1.00</td>
							<td align="center"> 1.00</td>
							<td align="center"> 1.00</td>
							<td align="center"> 1.00</td>
							<td align="center"> 1.00</td>
							<td align="center"> 1.00</td>
						</tr>
						<tr>
							<td align="left">
								<bold>EU</bold>
							</td>
							<td align="center"> 0.07</td>
							<td align="center"> 0.19</td>
							<td align="center"> 0.29</td>
							<td align="center"> 0.37</td>
							<td align="center"> 0.40</td>
							<td align="center"> 0.27</td>
						</tr>
						<tr>
							<td align="left">
								<bold>CS</bold>
							</td>
							<td align="center"> 0.54</td>
							<td align="center"> 0.51</td>
							<td align="center"> 0.32</td>
							<td align="center"> 0.37</td>
							<td align="center"> 0.32</td>
							<td align="center"> 0.44</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Species</bold>
							</td>
							<td align="center" colspan="6">
								<bold>LOCATIONS (&#x3a3;NMC18)</bold>
							</td>
						</tr>
						<tr>
							<td align="left">
								<bold>SP</bold>
							</td>
							<td align="center"> 1060</td>
							<td align="center"> 610</td>
							<td align="center"> 452</td>
							<td align="center"> 259</td>
							<td align="center"> 191</td>
							<td align="center"> 218</td>
						</tr>
						<tr>
							<td align="left">
								<bold>Clima (3 years)</bold>
							</td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
							<td align="center"> </td>
						</tr>
						<tr>
							<td align="left">
								<bold>IS1</bold>
							</td>
							<td align="center"> 42</td>
							<td align="center"> 24</td>
							<td align="center"> 10</td>
							<td align="center"> 10</td>
							<td align="center"> 14</td>
							<td align="center"> 14</td>
						</tr>
						<tr>
							<td align="left">
								<bold>&#x3a3;T</bold>
								<sub>med</sub>
							</td>
							<td align="center"> 528,2</td>
							<td align="center"> 437,9</td>
							<td align="center"> 424,2</td>
							<td align="center"> 547,9</td>
							<td align="center"> 649,3</td>
							<td align="center"> 517.6</td>
						</tr>
						<tr>
							<td align="left">
								<bold>&#x3a3;NT30</bold>
							</td>
							<td align="center"> 0</td>
							<td align="center"> 1</td>
							<td align="center"> 1</td>
							<td align="center"> 17</td>
							<td align="center"> 81</td>
							<td align="center"> 13</td>
						</tr>
						<tr>
							<td align="left">
								<bold>&#x3a3;NT&lt;10</bold>
							</td>
							<td align="center"> 148</td>
							<td align="center"> 451</td>
							<td align="center"> 507</td>
							<td align="center"> 392</td>
							<td align="center"> 174</td>
							<td align="center"> 57</td>
						</tr>
						<tr>
							<td align="left">
								<bold>&#x3a3;Rt</bold>
							</td>
							<td align="center"> 3500.4</td>
							<td align="center"> 1990.6</td>
							<td align="center"> 1072.9</td>
							<td align="center"> 1259.6</td>
							<td align="center"> 1557.9</td>
							<td align="center"> 1661.0</td>
						</tr>
						<tr>
							<td align="left">
								<bold>&#x3a3;NR</bold>
							</td>
							<td align="center"> 512</td>
							<td align="center"> 459</td>
							<td align="center"> 275</td>
							<td align="center"> 253</td>
							<td align="center"> 213</td>
							<td align="center"> 179</td>
						</tr>
						<tr>
							<td align="left">
								<bold>&#x3a3;NR10</bold>
							</td>
							<td align="center"> 370</td>
							<td align="center"> 320</td>
							<td align="center"> 192</td>
							<td align="center"> 178</td>
							<td align="center"> 168</td>
							<td align="center"> 143</td>
						</tr>
						<tr>
							<td align="left">
								<bold>&#x3a3;NR50</bold>
							</td>
							<td align="center"> 217</td>
							<td align="center"> 129</td>
							<td align="center"> 72</td>
							<td align="center"> 80</td>
							<td align="center"> 95</td>
							<td align="center"> 82</td>
						</tr>
						<tr>
							<td align="left">
								<bold>&#x3a3;NR70</bold>
							</td>
							<td align="center"> 174</td>
							<td align="center"> 84</td>
							<td align="center"> 53</td>
							<td align="center"> 59</td>
							<td align="center"> 71</td>
							<td align="center"> 71</td>
						</tr>
						<tr>
							<td align="left">
								<bold>NR50R (&#x25;)</bold>
							</td>
							<td align="center"> 42</td>
							<td align="center"> 28</td>
							<td align="center"> 26</td>
							<td align="center"> 32</td>
							<td align="center"> 45</td>
							<td align="center"> 46</td>
						</tr>
					</tbody>
				</table>
			</table-wrap>
			<p>If the Sheffer index average values (IS1) calculated using the climatic records taken at each site over the three years (2016, 2017 and 2018) are compared with the historic data in <xref ref-type="table" rid="t2">Table 2</xref> for the same sites, it can be observed that the climate over the considered three year period was drier than the historical series, which resulted in a notable reduction in the Sheffer index value and therefore in the risk of decay at all the locations. This fact alone explains the absence of decay in any of the wood samples at any of the locations, except for the Radiata pine at the Asturias-Llames site at the end of 2018, despite the presence of moderate to large levels of cracking at all the sites except Asturias-Llames. </p>
			<p>Due to the generalized absence of decay at the different locations it is impossible to develop a predictive model addressing the relationship between the number of days with moisture content above 18&#x25; (NMC18) and the onset of decay according to wood species and location. Hence, this study only evaluates the relative risk of decay by considering the number of days with humidity content above (NMC18 in <xref ref-type="table" rid="t6">Table 6</xref>) as risk indicator and comparing the NMC18 values for each species with respect to the average values for Norway spruce (SP) at each location.</p>
			<p>Norway spruce was chosen as the basis for comparison because this species is commonly used in studies evaluating <italic>D</italic>
				<sub>
					<italic>crit</italic>
				</sub>, the critical dose for decay resistance (<xref ref-type="bibr" rid="B3">3</xref>, <xref ref-type="bibr" rid="B6">6</xref>), and <italic>k</italic>
				<sub>
					<italic>wa</italic>
				</sub> indexes (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B12">12</xref>).</p>
			<p>With the exception of coastal areas (Asturias-Llames and to a lesser extent Huelva) or those affected by nearby sources of moisture (Vitoria, with big lakes closed to the device), the degree of cracking in all the wood samples can be classified as moderate to large, although with differences among species. </p>
			<p>Focusing on the evaluation according to aspect, among the conifer species, especially at the sites with intense continental climates (Palencia, Madrid, C&#xf3;rdoba), the Scots pine is that which shows the highest level of cracking (level 4 in <xref ref-type="table" rid="t4">Table 4</xref>) at the end of the three year period, followed by Radiata pine (level 3) and Laricio pine (also level 3 but with less cracks than Radiata pine). Norway spruce presents an intermediate level of cracking (level 3), similar to that of Laricio pine. This conclusion agrees with the conclusion of Meyer-Veltrup <italic>et al</italic>. (<xref ref-type="bibr" rid="B13">13</xref>) regarding the high susceptibility of cracking of Scots Pine but does not confirm the initial hypothesis we had on the direct effect of the Coefficient of anisotropy and the Absolute anisotropy (<xref ref-type="table" rid="t5">Table 5</xref>) on the cracking behaviour. This difference in behaviour in the samples evaluated with respect to the expected theoretical behaviour suggests that in practice the susceptibility to cracking also depends on other factors such as the microstructure, chemical composition or permeability.</p>
			<p>A notable difference can be observed in the performance of the hardwoods, being its cracking intensity much lower than that of the conifer species, despite having higher Coefficient of anisotropy and Absolute anisotropy values. Eucalyptus presents a large amount of short, shallow cracks (level 2), while the Sweet chestnut has very few cracks, although longer and deeper (level 1). This difference in the observed level of cracking between hardwoods and conifer species may be due to the notably stronger transversal microstructure and lower permeability of the hardwood species under study, which is evidenced by the lower NMC18 values at all the locations meaning that extreme variations in MC are much less frequent.</p>
			<p>Since straight fibre pieces were selected in all cases, none of them presented twists.</p>
			<p>As regards the relative values, with respect to Norway spruce, for the total number of days with a moisture content above 18&#x25; (NMC18R), as presented in the upper part of <xref ref-type="table" rid="t7">Table 7</xref>, the following aspects can be observed:</p>
			<list list-type="order">
				<list-item>
					<p>In the case of the softwoods (PS, PL, PR, SP):</p>
					<list list-type="alpha-lower">
						<list-item>
							<p>In general, the values for the three pine species (PL, PS, PR) reflect similar performance, since the relative index values are close to one, with the exception of PR in Cordoba.</p>
						</list-item>
						<list-item>
							<p>As expected, the most permeable woods; Laricio pine (PL) and especially Radiata pine (PR), seem to present lower NMC18R values in those locations where the sum of the monthly average temperatures is warmer (higher &#x3a3;T<sub>med</sub> values) and where there are more high-temperature events, represented by higher &#x3a3;NT30 values (Madrid, Cordoba and Huelva). In these locations, the torrential risk index represented by the NR50R value is also higher. This effect can be explained by the short duration of the rain events (2 days on average) and long duration of the dry periods also with the greater drying ability of PL and PR drives to reduced values of MC for more days during the year (see NMC18 values for these species per year in <xref ref-type="table" rid="t6">Table 6</xref>). At the Huelva site these values are less appreciable than in Cordoba and Madrid due to the sea proximity effect in Huelva, which leads to higher annual average relative humidity and therefore slower drying rate and smaller number of cracks (due to lower annual variations in MC values).</p>
						</list-item>
					</list>

				</list-item>
				<list-item>
					<p>In the case of the hardwoods (EU and CS):</p>
					<list list-type="alpha-lower">
						<list-item>
							<p>The reduced wetting ability of eucalyptus leads to lower NMC18 values at all sites, this effect being much more evident at the sites with highest rainfall (Asturias-Llames and Vitoria). The more rapid drying of chestnut in comparison to eucalyptus leads to lower NMC18 values in chestnut at those sites with fewer rain events (Palencia, Madrid, Cordoba and Huelva). </p>
						</list-item>
						<list-item>
							<p>The slower drying rate of eucalyptus also results in less cracking compared to chestnut, not only due to smaller differences between maximum and minimum MC but also to lower drying stress values. </p>
						</list-item>
					</list>

				</list-item>
			</list>
			<p>It is not possible to determine the effect of cracking in wood exposed to outdoor conditions only by analysing the absolute and relative NMC18 values obtained (<xref ref-type="table" rid="t6">Tables 6</xref> and <xref ref-type="table" rid="t7">7</xref>) at the different sites, nor is it possible to confirm the affirmation of Meyer-Veltrup <italic>et al</italic>. (<xref ref-type="bibr" rid="B13">13</xref>) with respect to the limited influence of cracking in the MC of exterior wood. Therefore, the different performance observed among species can only be attributed to the joint contribution of their different wetting/releasing ability along with their susceptibility to cracking. Hence, the NM18R values presented in <xref ref-type="table" rid="t6">Tables 6</xref> and <xref ref-type="table" rid="t7">7</xref> can be used to obtain the species factor (<italic>k</italic>
				<sub>
					<italic>wa</italic>
				</sub>) value for the studied species.</p>
			<p>The <italic>k</italic>
				<sub>
					<italic>wa</italic>
				</sub> values proposed in this study for the considered species will be the inverse of the maximum NMC18R values for each species, taking into consideration the six sites analyzed as a whole. These proposed values are shown in <xref ref-type="table" rid="t8">Table 8</xref>.</p>
			<table-wrap id="t8">
				<label>Table 8</label>
				<caption>
					<title>
						<italic>k</italic>
						<sub>
							<italic>wa</italic>
						</sub> values.</title>
				</caption>
				<table>
					<colgroup>
						<col/>
						<col/>
					</colgroup>
					<thead>
						<tr>
							<th align="left">Species</th>
							<th align="center">
								<italic>k<sub>wa</sub>
								</italic>
							</th>
						</tr>
					</thead>
					<tbody>
						<tr>
							<td align="left">
								<bold>PL</bold>
							</td>
							<td align="center">
								<bold>1,03</bold>
							</td>
						</tr>
						<tr>
							<td align="left">
								<bold>PR</bold>
							</td>
							<td align="center">
								<bold>1,01</bold>
							</td>
						</tr>
						<tr>
							<td align="left">
								<bold>PS</bold>
							</td>
							<td align="center">
								<bold>0,92</bold>
							</td>
						</tr>
						<tr>
							<td align="left">
								<bold>SP</bold>
							</td>
							<td align="center">
								<bold>1,00</bold>
							</td>
						</tr>
						<tr>
							<td align="left">
								<bold>EU</bold>
							</td>
							<td align="center">
								<bold>2,51</bold>
							</td>
						</tr>
						<tr>
							<td align="left">
								<bold>CS</bold>
							</td>
							<td align="center">
								<bold>1,84</bold>
							</td>
						</tr>
					</tbody>
				</table>
			</table-wrap>
			<p>In accordance with the data in <xref ref-type="table" rid="t7">Table 7</xref> it would appear logical to use, for simplicity, a common value of 1.0 for all the conifers analyzed, 2.51 for the eucalyptus and 1.84 for the chestnut.</p>
		</sec>
		<sec id="sec4" sec-type="conclusions">
			<label>4.</label>
			<title>Conclusions</title>
			<p>The wood species factor can have a decisive influence on the decay resistance of wood exposed to outdoor condition because it affects the number of days per year in which the wood has high moisture content values. This is confirmed by the data obtained for the hardwood species, eucalyptus and chestnut, considered in this study. However, it has not been confirmed in the case of wood from the conifer species studied, since their performance can be described as being very similar from one to the other as well as to the reference species of Norway spruce.</p>
			<p>The observed difference in the performance of the wood from the different conifer species at the studied locations may be due to their differing wetting/releasing ability and to a lesser degree to their susceptibility to cracking. The intensity of the effect of each of these variables could not be verified since the effects of each are intertwined, although the data obtained seems to point to a limited effect of cracks, mainly associated with the generation of short, intense and non-real increases in the average moisture content. All of the locations, with the exception of those with the wettest climates (Asturias-Llames, Vitoria and to a lesser extent, Huelva) show very similar crack presence levels, so the differences in performance of the wood from the different species at these locations can only be due to the differences in wetting/releasing ability.</p>
			<p>Based on the above information, it can be deduced that the “physical” effect of the species factor on the resistance to fungi decay must be taken into account as a whole, which, according to (<xref ref-type="bibr" rid="B3">3</xref>, <xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B11">11</xref>) is the so-called species factor.</p>
			<p>Based on the results, it is proposed that a value of 1.0 be employed as “species factor” for the four studied conifers, 2.51 for the Eucalyptus and 1.84 for the Sweet chestnut.</p>
		</sec>
	</body>
	<back>
		<ack>
			<title>Acknowledgements</title>
			<p>This work was carried out in the Wood Technology Laboratories at the CIFOR-INIA and University of Cordoba, and was financially supported under the Spanish National RDT Plan through Grant BIA2013-42434-R and the Operational Group “Wood Sustainable Construction” of the European Association for Innovation in Agricultural Productivity and Sustainability (AEI-AGRI). The authors would like to thank all those who have collaborated in the trials, especially NEIKER in the Basque country, Rafael Sanchez at the University of Cordoba, Eugenio Perea at the Asturias-Llames site and Rafael Capuz at the Valencia sites.</p>
		</ack>
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