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	<front>
		<journal-meta>
			<journal-id journal-id-type="publisher-id">EG</journal-id>
			<journal-title-group>
				<journal-title>Estudios Geogr&#xe1;ficos</journal-title>
				<abbrev-journal-title abbrev-type="publisher">Estud. geogr.</abbrev-journal-title>
			</journal-title-group>
			<issn publication-format="print">0014-1496</issn>
			<issn publication-format="electronic">1988-8546</issn>
			<issn-l>0014-1496</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">estgeogr.2022108.108</article-id>
			<article-id pub-id-type="doi">10.3989/estgeogr.2022108.108</article-id>
			<article-categories>
				<subj-group subj-group-type="heading">
					<subject>Art&#xed;culos / Articles</subject>
				</subj-group>
			</article-categories>
			<title-group>
				<article-title>Land cover changes in the NW Spanish coastal zone: drivers and impact on ecosystem services</article-title>
				<trans-title-group xml:lang="es">
					<trans-title>Cambios en las coberturas del suelo en la costa NW de Espa&#xf1;a: fuerzas tractoras e impacto en los servicios ecosist&#xe9;micos</trans-title>
				</trans-title-group>
			</title-group>
			<contrib-group>
				<contrib contrib-type="author" corresp="yes">
					<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0781-6574</contrib-id>
					<name>
						<surname>Ovejero Campos</surname>
						<given-names>Aida</given-names>
					</name>
					<email xlink:href="aovejero@vigo.es">aovejero@vigo.es</email>
					<aff id="aff1"><institution>Universidad de Vigo</institution></aff>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-7985-0814</contrib-id>
					<name>
						<surname>Fern&#xe1;ndez</surname>
						<given-names>Emilio</given-names>
					</name>
					<email xlink:href="esuarez@uvigo.es">esuarez@uvigo.es</email>
					<aff id="aff2"><institution>Universidad de Vigo</institution></aff>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-6929-3644</contrib-id>
					<name>
						<surname>M&#xe9;ndez Mart&#xed;nez</surname>
						<given-names>Gonzalo</given-names>
					</name>
					<email xlink:href="mendez@uvigo.es">mendez@uvigo.es</email>
					<aff id="aff3"><institution>Universidad de Vigo</institution></aff>
				</contrib>
			</contrib-group>
			<pub-date pub-type="epub">
				<day>09</day>
				<month>05</month>
				<year>2022</year>
			</pub-date>
			<pub-date pub-type="collection">
				<month>06</month>
				<year>2022</year>
			</pub-date>
			<volume>83</volume>
			<issue>292</issue>
			<elocation-id>e100</elocation-id>
			<history>
				<date date-type="received">
					<day>14</day>
					<month>12</month>
					<year>2020</year>
				</date>
				<date date-type="accepted">
					<day>18</day>
					<month>04</month>
					<year>2022</year>
				</date>
				<date date-type="published online">
					<day>25</day>
					<month>05</month>
					<year>2022</year>
				</date>
			</history>
			<permissions>
				<copyright-statement>&#xa9; 2022 CSIC</copyright-statement>
				<copyright-year>2022</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://asclepio.revistas.csic.es/index.php/asclepio/article/view/XXXX/XXXX"/>
			<abstract>
				<title>Abstract</title>
				<p>The increase in the amount of agricultural, forest and other seminatural and natural land taken by urban and other artificial land development is of worldwide concern. Land take is generally more intense in littoral zones, which in turn are especially vulnerable. In this study, the artificialization patterns of the Galician coast (NW Spain) were assessed using the high-resolution land cover map SIOSE. Land take between 2005 and 2014 was monitored, changes in land cover patterns were analysed and their impact on ecosystem services was assessed. The artificialization rate in the coastal municipalities in that period was 1.07 ha day<sup>-1</sup>, being particularly intense in the first four years, with a value of 2.05 ha day<sup>-1</sup>. Land take mainly occurred at the expense of forest and seminatural classes. Consequently, potential services provided by ecosystems were affected; particularly provisioning services which decreased at a 0.35% annual rate.</p>
				<p>The relationship between artificialization rates and demographic and economic variables were also analysed, resulting in a different significant correlation between population, new buildings and domestic gross disposable income among the studied zones.</p>
			</abstract>
			<trans-abstract xml:lang="es">
				<title>Resumen</title>
				<p>El aumento de la ocupaci&#xf3;n de zonas agr&#xed;colas, forestales y otras zonas seminaturales por asentamientos urbanos u otras superficies artificiales es motivo de preocupaci&#xf3;n mundial. La ocupaci&#xf3;n del suelo es generalmente m&#xe1;s intensa en zonas litorales, las cuales a su vez son especialmente vulnerables. En este estudio se evaluaron los patrones de artificializaci&#xf3;n de la costa gallega (noroeste de Espa&#xf1;a) utilizando el mapa de cobertura de suelo de alta resoluci&#xf3;n SIOSE. Se monitore&#xf3; la ocupaci&#xf3;n del suelo entre 2005 y 2014, se analizaron los cambios en los patrones de ocupaci&#xf3;n del suelo y se evaluaron sus impactos en los servicios ecosist&#xe9;micos. La tasa de artificializaci&#xf3;n en los municipios costeros en ese periodo fue de 1,07 ha d&#xed;a<sup>-1</sup>, siendo particularmente intensa en los cuatro primeros a&#xf1;os con un valor de 2,05 ha d&#xed;a<sup>-1</sup>. La ocupaci&#xf3;n del suelo se produjo principalmente en zonas forestales y seminaturales. En consecuencia, la potencialidad de los servicios ecosist&#xe9;micos se vio afectada, en particular aquellos de aprovisionamiento que disminuyeron con una tasa anual del 0,35%. </p>
				<p>Tambi&#xe9;n se analiz&#xf3; la relaci&#xf3;n entre las tasas de artificializaci&#xf3;n y variables demogr&#xe1;ficas y econ&#xf3;micas, lo que result&#xf3; en correlaciones significativas diferentes entre la poblaci&#xf3;n, las nuevas edificaciones y la renta bruta disponible entre las zonas estudiadas. </p>
			</trans-abstract>
			<kwd-group>
				<kwd>land take</kwd>
				<kwd>SIOSE</kwd>
				<kwd>socioeconomic indicators</kwd>
				<kwd>artificialization rates</kwd>
				<kwd>littoralization</kwd>
				<kwd>land take patterns</kwd>
				<kwd>ecosystem services</kwd>
			</kwd-group>
			<kwd-group xml:lang="es">
				<kwd>ocupaci&#xf3;n del suelo</kwd>
				<kwd>SIOSE</kwd>
				<kwd>indicadores socioecon&#xf3;micos</kwd>
				<kwd>tasas de artificializaci&#xf3;n</kwd>
				<kwd>artificializaci&#xf3;n del litoral</kwd>
				<kwd>patrones de ocupaci&#xf3;n del suelo</kwd>
				<kwd>servicios ecosist&#xe9;micos</kwd>
			</kwd-group>
			<counts>
				<fig-count count="11"/>
				<table-count count="11"/>
				<equation-count count="0"/>
				<ref-count count="62"/>
				<page-count count="20"/>
			</counts>
		</article-meta>
	</front>
	<body>
		<sec id="sec1" sec-type="intro">
			<label>1.</label>
			<title>Introduction</title>
			<p>Land take refers to the transformation of natural and/or agrarian areas to artificial surfaces destined to diverse uses such as residential, industrial, commercial, equipment, transport infrastructures, etc. (<xref ref-type="bibr" rid="B24">European Environment Agency, 2017</xref>; <xref ref-type="bibr" rid="B50">Olazabal and Bellet, 2018</xref>). It is a direct indicator of urbanization processes (<xref ref-type="bibr" rid="B24">European Environment Agency, 2017</xref>; <xref ref-type="bibr" rid="B43">Ministerio de Agricultura y Pesca, Alimentaci&#xf3;n y Medio Ambiente, 2017</xref>) that allows analysing the land cover spatio-temporal dynamics that could result from the socioeconomic and environmental pressures operating in a given territory. Due to its irreversibility, these changes are a potential threat to sustainability and have direct implications on the supply of ecosystem services (<xref ref-type="bibr" rid="B56">Prieto and Ruiz, 2013</xref>). Land take is a process of relevance in all UE countries and one of the major environmental challenges Europe is facing (<xref ref-type="bibr" rid="B22">European Commission, 2011</xref>; <xref ref-type="bibr" rid="B60">Wang, Liu &amp; Peng, 2012</xref>). &#x201c;No net land take by 2050&#x201d; has been fixed as a goal in the UE due to its consequences such as losses in biodiversity, habitat fragmentation, soil sealing, urban sprawl, economic impacts derived from the loss of agricultural land, or impacts on the carbon and water cycles (<xref ref-type="bibr" rid="B18">Decoville and Schneider, 2015</xref>).</p>
			<p>The increase of artificial surfaces has been recorded in Europe through the <xref ref-type="bibr" rid="B16">Corine Land Cover</xref> (CLC) project since 1987. The European Environment Agency (EEA) publishes periodically the results of the indicator &#x201c;urban land take&#x201d; which measures the increase of artificial surfaces occurring at the expense of agricultural, forestry or seminatural covers since year 2000. This indicator shows that artificialization rates in Spain have always been above the European average, although the temporal trends are not totally coincident. Thus, for instance, the annual average value of the &#x201c;urban land take&#x201d; indicator in Europe for the periods 2000-2006 and 2006-2012 was 0.5% and 0.4% respectively, while in Spain they were 2.8% (the third in Europe) and 1.5% (the first in Europe) in the same periods. In fact, 23.5% of the European urbanization took place in Spain in the period 2000-2006, in contrast with 12.2% in France and 9.5% in Germany (<xref ref-type="bibr" rid="B17">Couch, 2016</xref>). These high rates were mainly associated with building activity connected with the dispersed urban model and the large investment in infrastructures (<xref ref-type="bibr" rid="B45">Observatorio de la Sostenibilidad, 2006</xref>). As a consequence, the area covered by urban land classes increased in Spain by 25.4% in the 1990-2000 period, while the population rose up by only 5% (<xref ref-type="bibr" rid="B27">Greenpeace, 2010</xref>). </p>
			<p>This urbanization process was not homogeneous throughout the territory but is generally more intense in the littoral zone (<xref ref-type="bibr" rid="B45">Observatorio de la Sostenibilidad, 2006</xref>), a phenomenon known as &#x201c;littoralization&#x201d; which consists in the concentration of the population, infrastructures, economic activities and settlements in the coastal areas (<xref ref-type="bibr" rid="B5">Barrag&#xe1;n Mu&#xf1;oz, 1994</xref>). A result of this pattern is that approximately 40% of the European population lives in the first 50 kilometers from the coastline and almost 40% of the European gross domestic product is generated in those maritime regions (<xref ref-type="bibr" rid="B23">European Environment Agency, 2013</xref>). The increase in artificial areas in the European 10 km coastal zones was, on average, 12% between 1990 and 2000. This value was even higher in Portugal (34%), Ireland (27%) or the whole Spanish territory (18%) (<xref ref-type="bibr" rid="B35">Jim&#xe9;nez Herrero, Guaita Garc&#xed;a, L&#xf3;pez Hern&#xe1;ndez &amp; Delgado Jim&#xe9;nez, 2009</xref>), where the increase of artificial areas in the 10 km coastal zone between 1990 and 2006 represented about 1/3 of the total area built in the previous centuries. Simultaneously, the population living in Spanish coastal municipalities (which represent 8% of the territory) rose from 24% of the total population in 1960 to 44% in 2010 (<xref ref-type="bibr" rid="B42">Ministerio de Agricultura, Alimentaci&#xf3;n y Medio Ambiente, 2014</xref>). The <italic>Observatorio de la Sostenibilidad</italic> (OSE) studied the urbanization process in the Spanish coastal area from 1987 to 2011 showing rates of 2.2 hectares per day in the first 500 meters from the coastline, with some areas showing a complete urbanization of the available space (<xref ref-type="bibr" rid="B46">Observatorio de la Sostenibilidad, 2016a</xref>). According to the Bank of Spain, the number of new houses built in Spain per 10000 inhabitants during the period 2004-2007 was 9.1, which contrasts with the value of 5.7 reported for Europe. Only in 2007, Spanish coastal municipalities approved the construction of nearly three million new dwellings (<xref ref-type="bibr" rid="B27">Greenpeace, 2010</xref>). </p>
			<p>The Galician coast was also affected by the substantial expansion of urbanization, with varying intensity depending on the area, but tending towards scattered settlements (<xref ref-type="bibr" rid="B61">Xunta de Galicia, 2011</xref>). Several areas of the Galician region were subjected to an intense artificialization process in the period 1997-2007, with relatively large urban expansions, whereas in other areas this process was moderate. The physiography of the Galician coast presents significant differences between northern and western areas, being, in general, much more exposed and steep in the north and much sheltered in the west. The major singularities of the Galician coast are the rias, ancient valleys occupied by the sea with average depths in the mouth of about 50-60 meters. They are highly productive zones that concentrate a large part of the Galician population, where different uses coexist, therefore supporting a significant human pressure (<xref ref-type="bibr" rid="B26">Fern&#xe1;ndez, &#xc1;lvarez-Salgado, Beiras, Ovejero &amp; M&#xe9;ndez, 2016</xref>). The rugged coastal morphology of the rias occupies 34.5% of the Spanish peninsular coastline. </p>
			<p>Data on artificial cover for Spain generally derives from the Corine Land Cover project, which is known to have several methodological limitations (<xref ref-type="bibr" rid="B52">Ovejero-Campos, Fern&#xe1;ndez, Ramos, Bento &amp; M&#xe9;ndez-Mart&#xed;nez, 2019</xref>), such as those related to the resolution due to the minimal cartographic unit (<xref ref-type="bibr" rid="B8">Batista e Silva, Lavalle &amp; Koomen, 2013</xref>), the possible underestimation of the artificial coverages (<xref ref-type="bibr" rid="B2">Bach <italic>et al</italic>., 2006</xref>), or the existence of unlikely changes in the assigned land cover (<xref ref-type="bibr" rid="B2">Bach <italic>et al</italic>., 2006</xref>; <xref ref-type="bibr" rid="B6">Barreira Gonz&#xe1;lez, Gonz&#xe1;lez, Casc&#xf3;n &amp; Sendra, 2012</xref>; <xref ref-type="bibr" rid="B13">Catal&#xe1; Mateo, Bosque Sendra &amp; Plata Rocha, 2008</xref>; <xref ref-type="bibr" rid="B39">Mart&#xed;nez-Fern&#xe1;ndez, Ruiz-Benito &amp; Zavala, 2015</xref>; <xref ref-type="bibr" rid="B40">Mart&#xed;nez-Fern&#xe1;ndez, Ruiz-Benito, Bonet &amp; G&#xf3;mez, 2019</xref>; <xref ref-type="bibr" rid="B55">Pontius and Lippitt, 2006</xref>). In this connection, <xref ref-type="bibr" rid="B18">Decoville and Schneider (2015)</xref> monitored land take rates at a very accurate scale, and demonstrated that although the results from CLC seem acceptable at the country level, they lack precision when analysing smaller territories. Consequently, in this study we used data derived from the SIOSE project (reference scale 1:25000), as it represents a substantial improvement in the description and assignation of land cover.</p>
			<p>Land cover and land use changes are closely related to the provision of ecosystem services (<xref ref-type="bibr" rid="B9">Burkhard, Kroll, M&#xfc;ller &amp; Windhorst, 2009</xref>). The analysis and mapping of ecosystem services is presently recognised as a key element of sustainable management, thus drawing the attention of policymakers (<xref ref-type="bibr" rid="B7">Bastian, Haase &amp; Grunewald, 2012</xref>; <xref ref-type="bibr" rid="B9">Burkhard <italic>et al</italic>., 2009</xref>; <xref ref-type="bibr" rid="B37">Kandziora, Burkhard &amp; M&#xfc;ller, 2013</xref>) in this paper we suggest returning to the landscape potential concept developed by landscape ecologists in the 1970s. Emerging from both concepts is the hereinafter discussed EPPS framework - ecosystem (or landscape as they allow estimating the impact of human activity (<xref ref-type="bibr" rid="B28">Hasan, Shi &amp; Zhu, 2020</xref>; <xref ref-type="bibr" rid="B38">Li and Zhou, 2016</xref>; <xref ref-type="bibr" rid="B41">Mendoza-Gonz&#xe1;lez, Mart&#xed;nez, Lithgow, P&#xe9;rez-Maqueo &amp; Simonin, 2012</xref>; <xref ref-type="bibr" rid="B57">Riitters, Wickham, Vogelmann &amp; Jones, 2000</xref>).</p>
			<p>Besides the intrinsic interest of the spatial and temporal analysis of land cover and its effect on the ecosystem services, it is of particular relevance assessing the socioeconomic drivers behind those patterns. This research topic has been addressed in the literature using different approaches based on population (<xref ref-type="bibr" rid="B12">Carr, 2004</xref>; <xref ref-type="bibr" rid="B36">Kamwi, Chirwa, Manda, Graz &amp; K&#xe4;tsch, 2015</xref>; <xref ref-type="bibr" rid="B51">Orenstein and Hamburg, 2010</xref>), births, deaths and migration patterns (<xref ref-type="bibr" rid="B15">Clement and York, 2017</xref>) and household formation (<xref ref-type="bibr" rid="B4">Barbieri, Bilsborrow &amp; Pan, 2005</xref>). </p>
			<fig id="f1">
				<label>Figure 1</label>
				<caption>
					<title>Map of the coastal areas studied in this investigation and their location</title>
					<p>Map of the coastal areas studied in this investigation. (A) Superposition of the two coastal zones considered in this study: in green, the 10 km coastal zone (535054 ha), and in grey, the coastal zone delimited by the Galician coastal municipalities (451401 ha). (B) Coastal divisions adopted in this study by grouping coastal municipalities according to their physiographic similarities.</p>
				</caption>
				<graphic id="gra-1" xlink:href="ESTGEOGR-83-292-e100-gf1.png"/>
			</fig>
			<p>The objectives of our research are: (1) to quantify the artificialization rate of the Galician coast in the last decade, (2) to map and estimate changes in ecosystem services resulting from the artificialization process and (3) to relate magnitudes and patterns of coastal artificialization to socioeconomic indicators <italic>a priori</italic> associated with the artificialization process itself, such as the construction of new dwellings or the generation of wealth (expansion of leisure activities, tourism, creation of industries&#x2026;). </p>
		</sec>
		<sec id="sec2" sec-type="methods">
			<label>2.</label>
			<title>Methods</title>
			<p>We estimated the artificial cover in the Galician coast (located in the NW of Spain) following two approaches. Firstly we analysed the 10 km coastal zone, which allows us to compare the results with those published by the OSE and the EEA. Secondly, we carried out the same procedure but in this case, considering the coastal zone as the area delimited by the coastal municipalities, as they are the territorial units of relevance for socioeconomic data (Instituto Galego de Estat&#xed;stica - IGE) (<xref ref-type="fig" rid="f1">Fig. 1</xref>). Besides, municipalities are the minimum administrative unit with competence in spatial planning in the region.</p>
			<p>The SIOSE project analyses land cover and land use. This work focuses on land cover, ie. physical and biological cover of the earth&#x2019;s surface, including artificial surfaces, agricultural areas, forests, natural and seminatural areas, wetlands and water bodies. The concept of land use characterises the territory according to its functional dimension or its socioeconomic dedication, for example, residential, industrial, commercial, agricultural, forestry, recreational (<xref ref-type="bibr" rid="B34">Instituto Geogr&#xe1;fico Nacional, 2015</xref>; <xref ref-type="bibr" rid="B58">Valc&#xe1;rcel and Casta&#xf1;o, 2012</xref>).</p>
			<p>The SIOSE project does not follow a traditional thematic classification model, but assigns to each polygon one or several land cover classes (simple and composed), using occupation percentages and attributes. Simple classes present homogeneity in 100% of the surface and exceed the minimum surface requirement; they include crops, pastures, forests, scrubs, open spaces with little or no vegetation, wetlands, water bodies, and artificial surfaces. Composed classes are described from several land cover classes, which in turn can be simple or composed and, depending on the combination, are called &#x201c;Association&#x201d; (no-fixed distribution) or &#x201c;Mosaic&#x201d; (geometric distribution). Composed classes could be predefined or not predefined. Among the predefined ones, widely distributed by the study area, the class &#x201c;Residential agricultural settlement&#x201d;, includes fractions of herbaceous and/or woody crops, buildings, and may also contain forests, pastures, scrubs or any artificial classes (for example roads, parking lots or bare pedestrian zones) (<xref ref-type="bibr" rid="B21">Equipo T&#xe9;cnico Nacional SIOSE, 2015</xref>). </p>
			<p>We used available SIOSE databases corresponding to 2005, 2009, 2011 and 2014, covering a 9 years period when the artificialization dynamics were explosive due to the &#x201c;real estate boom&#x201d; which occurred in Spain by that time. Vectorial format municipal boundaries supplied by the <italic>Instituto Geogr&#xe1;fico Nacional</italic> (IGN) were included in the geodatabase. Alphanumeric data related to human pressures, population, and new buildings were obtained from the <italic>Instituto Gallego de Estad&#xed;stica</italic> (IGE) and related to the municipal geographic data. </p>
			<p>The wide availability of artificial covers provided by the SIOSE database, justifies its use in this work. Nevertheless, this database also presents some limitations (<xref ref-type="bibr" rid="B58">Valc&#xe1;rcel and Casta&#xf1;o, 2012</xref>). The exploitation of SIOSE data is laborious and has limitations when representing mixed land covers, frequently present on the Galician coast. Scattered settlements, widespread throughout the Northwest Iberian Peninsula, causes confusion in the SIOSE classification between the discontinuous urban fabric and non-urban classes, reflecting a continuous transfer between both land covers, which may cause slightly altered results (<xref ref-type="bibr" rid="B49">Olazabal and Bellet, 2017</xref>). Another limitation, common to this type of data, is the supposed &#x201c;naturalisation&#x201d; that occurs in some polygons, consisting of unlikely changes from artificial surfaces to agricultural or forest areas. The presence of a high contribution of disseminated settlements makes difficult the identification of classes such as &#x201c;Residential agricultural settlement&#x201d;, as it depends on the time of the year when the photograph is taken. On some occasions, polygons bordering road networks are classified as broad-leaved forest or scrubs as a consequence of the appearance of green masses (<xref ref-type="bibr" rid="B49">Olazabal and Bellet, 2017</xref>). </p>
			<p>This paper sets a hierarchical nomenclature derived from SIOSE, and similar to Corine Land Cover (CLC), which includes five land cover classes: artificial surfaces, agricultural areas, forests or seminatural areas, wetlands and water bodies. A reclassification of the SIOSE codes was performed to maintain the polygons and assign each one to a single class. Firstly, a direct reclassification to simple-classes polygons (<xref ref-type="table" rid="t1">Table 1</xref>) was performed, and secondly, codes of the polygons classified as &#x201c;associations&#x201d; or &#x201c;mosaics&#x201d; were split into simple classes and then reclassified attending to the dominant land cover class (<xref ref-type="table" rid="t2">Table 2</xref>).</p>
			<table-wrap id="t1">
				<label>Table 1</label>
				<caption>
					<title>Reclassified land cover classes and their codes</title>
				</caption>
				<table>
					<colgroup>
						<col/>
						<col/>
					</colgroup>
					<thead>
						<tr>
							<th align="center">SIOSE land cover classes</th>
							<th align="center">Reclassified land cover classes</th>
						</tr>
					</thead>
					<tbody>
						<tr>
							<td align="left">Artificial surfaces</td>
							<td align="left">Artificial surfaces (1)</td>
						</tr>
						<tr>
							<td align="left">Crops</td>
							<td align="left">Agricultural areas (2)</td>
						</tr>
						<tr>
							<td align="left">Pastures</td>
							<td align="left" rowspan="4">Forest and seminatural areas (3)</td>
						</tr>
						<tr>
							<td align="left">Forests</td>
						</tr>
						<tr>
							<td align="left">Scrubs</td>
						</tr>
						<tr>
							<td align="left">Open spaces with little or no vegetation</td>
						</tr>
						<tr>
							<td align="left">Wetlands</td>
							<td align="left">Wetlands (4)</td>
						</tr>
						<tr>
							<td align="left">Water bodies</td>
							<td align="left">Water bodies (5)</td>
						</tr>
					</tbody>
				</table>
			</table-wrap>
			<table-wrap id="t2">
				<label>Table 2</label>
				<caption>
					<title>Examples of reclassified siose polygons</title>
				</caption>
				<table>
					<colgroup>
						<col/>
						<col/>
						<col/>
					</colgroup>
					<thead>
						<tr>
							<th align="center">SIOSE code</th>
							<th align="center">Percentages of land cover class</th>
							<th align="center">New code</th>
						</tr>
					</thead>
					<tbody>
						<tr>
							<td align="left">A(60FDPpl_40MTR)</td>
							<td align="center">100% (3)</td>
							<td align="center">3</td>
						</tr>
						<tr>
							<td align="left">A(50SDN_35MTR_10PST_05FDP)</td>
							<td align="center">100% (3)</td>
							<td align="center">3</td>
						</tr>
						<tr>
							<td align="left">I(60CNF_15FDP_10MTR_05PRDsc_05MTRct_05SDNfc)</td>
							<td align="center">95% (3), 5% (2)</td>
							<td align="center">3</td>
						</tr>
						<tr>
							<td align="left">I(80ZEV_15MTRct_05A(90MTR_10FDP))</td>
							<td align="center">80% (1), 20% (3)</td>
							<td align="center">1</td>
						</tr>
						<tr>
							<td align="left">I(80VAP_10EDFnv_10OCT)</td>
							<td align="center">100% (1)</td>
							<td align="center">1</td>
						</tr>
						<tr>
							<td align="left">R(35CHLsc_20EDFva_15PRDsc_10VAP_10LFNsc_05OCT_05MTRpc)</td>
							<td align="center">60% (2), 35% (1), 5% (3)</td>
							<td align="center">2</td>
						</tr>
						<tr>
							<td align="left">R(35EDFva_20PRDsc_15FDC_10VAP_10CHLsc_10CNF)</td>
							<td align="center">45% (1), 30% (2), 25% (3)</td>
							<td align="center">1</td>
						</tr>
					</tbody>
				</table>
			</table-wrap>
			<p>Once the information was generated, total areas were calculated for each land cover class and geoprocessing was performed, integrating land cover information, socioeconomic data, and digital aerial orthophotos derived from the &#x201c;Plan Nacional de Ortofotograf&#xed;a A&#xe9;rea&#x201d; (PNOA). </p>
			<p>In this study, we estimated the potential of the coastal zone to deliver ecosystem services from the ecosystem service potential matrix described in (<xref ref-type="bibr" rid="B11">Burkhard, Kandziora, Hou &amp; M&#xfc;ller, 2014</xref>). As that matrix derived from CLC classes, it was adapted to the land cover classes defined in our study which derived from the SIOSE 3-level classes. The ecosystem service classification used was based on 11 regulation services, 10 provisioning services and 6 cultural services (see supplementary material). The potential of each land cover class to produce the selected ecosystem services was assessed on a scale from 0 (no relevant potential) to 5 (very high relevant potential). Regulation, provisioning and cultural ecosystem services were mapped using the mean value of their components. The evolution of each ecosystem service from 2005 to 2014 was assessed taking into account the area occupied by each land cover class and then estimating annual changing rates.</p>
		</sec>
		<sec id="sec3" sec-type="results|discussion">
			<label>3.</label>
			<title>Results and discussion</title>
			<sec id="sec3.1">
				<title>3.1. Artificial land cover changes and fluxes in the Galician coast</title>
				<p>The land cover distribution observed in the Galician coast in 2014 (last year available) is shown in <xref ref-type="fig" rid="f2">Figure 2</xref>. 65% of the coastal area was dedicated to forest and seminatural areas, occupying a total of 273534 hectares when the coastal municipalities were considered. Agricultural areas accounted for 21% of the coastal area whereas artificial surfaces, located mainly around the coastal cities, represented 12%. Wetlands and water bodies were much less represented. These results were very similar when the 10 km coastal zone or the municipalities&#x2019; coastal strip was considered, suggesting that both methodological approaches could be used indistinctly.</p>
				<fig id="f2">
					<label>Figure 2</label>
					<caption>
						<title>Reclassified land cover classes derived from SIOSE 2014 in the 10 km coastal zone versus the area delimited by the coastal municipalities</title>
						<p>Reclassified land cover classes derived from SIOSE 2014 in the 10 km coastal zone versus the area delimited by the coastal municipalities. Pie charts represent the relative contribution of the land classes to the total area (% of the total surface).</p>
					</caption>
					<graphic id="gra-2" xlink:href="ESTGEOGR-83-292-e100-gf2.png"/>
				</fig>
				<p>
					<xref ref-type="fig" rid="f3">Figure 3A</xref> shows absolute and relative changes in land cover in the area delimited by the Galician coastal municipalities in the period 2005-2014. The largest relative change occurred in the artificial surfaces, which increased by ca. 7.4% in the study period. Agricultural areas decreased by 3% and the other land classes varied less than 1%. However, the most considerable absolute losses were found in the agricultural areas, showing a decrease of 2753 hectares, albeit only represented 3% in relative terms.</p>
				<fig id="f3">
					<label>Figure 3</label>
					<caption>
						<title>A: gross and net land cover&#x2019;s change. B: land cover changes</title>
					</caption>
					<p>A: Absolute and relative change in land cover classes in the coastal municipalities between 2005 and 2014. Relative change is expressed as the % with respect to the total area of the same land cover class in the year 2005 (dark bars) and absolute change is expressed in hectares (soft bars). Changes in wetlands and water bodies are not represented because of their small magnitude. B: Daily land cover changes in the municipalities&#x2019; coastal zone in the 2005-2009, 2009-2011, 2011-2014 and 2005-2014 periods.</p>
					<graphic id="gra-3" xlink:href="ESTGEOGR-83-292-e100-gf3.png"/>
				</fig>
				<p>As expected, the same pattern was observed when the 10 km coastal zone was used, although differences were found in the absolute number of hectares, as the total extent of both areas differed (<xref ref-type="fig" rid="f1">Fig. 1</xref>). <xref ref-type="fig" rid="f3">Figure 3B</xref> shows daily rates of land cover changes in the municipalities of the coastal strip. In general, artificial areas increased and agricultural areas decreased. However, forest and seminatural areas decreased from 2005 to 2009, but increased in the 2009-2014 period. Artificial land cover rose from 47361 ha in 2005 to 50350 ha in 2009, which yields a daily growth rate of ca. 2 ha day<sup>-1</sup> (i.e. /day) in that period, while in the 2009-2011 and 2011-2014 periods these rates were 0.2 and 0.4 ha day<sup>-1</sup>. The estimated rate for the 10 km coastal zone from 2005 to 2009 was 2.5 ha day<sup>-1</sup> due to the large size of some coastal municipalities, which penetrate into the continent where exposition to anthropogenic pressures is less intense. </p>
				<p>When the results obtained in this study (using SIOSE), are compared with the data published by the <xref ref-type="bibr" rid="B47">Observatorio de la Sostenibilidad (2016b)</xref>, derived from CLC, substantial differences were found in both the artificial area and the annual land cover change rate. According to CLC, 36054 hectares were classified as artificial surfaces in the 10 km coastal zone in 2011, which represents 6.8% of the total coastal area, whereas the results obtained in this study show that 11.4% of the 10 km coastal zone was covered by artificial surfaces (60963 ha) in the same year. Previous studies have warned about the underestimation of the artificial area along the Spanish coast due to the scale of CLC data, an error enhanced in areas with a dispersed settlement, for example, the Galician coast (<xref ref-type="bibr" rid="B47">Observatorio de la Sostenibilidad, 2016b</xref>). In addition, the CLC project discards linear data such as roads and rail networks as artificial surfaces, thus reinforcing this underestimation (<xref ref-type="bibr" rid="B50">Olazabal and Bellet, 2018</xref>). These authors also reported the potential effect of the minimum percentage (5%) considered by each SIOSE polygon when digitising large polygons representing disseminated urban settlements, which may result in abnormally high values of urban surfaces. The above-mentioned differences are also reflected in the between-periods variability of annual artificialization rates (<xref ref-type="table" rid="t3">Table 3</xref>).</p>
				<table-wrap id="t3">
					<label>Table 3</label>
					<caption>
						<title>Annual artificialization rates</title>
					</caption>
					<table>
						<colgroup>
							<col/>
							<col/>
							<col/>
							<col/>
							<col/>
						</colgroup>
						<thead>
							<tr>
								<th align="center">Area</th>
								<th align="center">Period</th>
								<th align="center">Artificialization rate (ha/day)</th>
								<th align="center">Annual change (%/year)</th>
								<th align="center">Data</th>
							</tr>
						</thead>
						<tbody>
							<tr>
								<td align="left">Spain 10 km coastal zone</td>
								<td align="center">1987-2011</td>
								<td align="center">15.4</td>
								<td align="center">2.3</td>
								<td align="center">CLC</td>
							</tr>
							<tr>
								<td align="left">Galicia 10 km coastal zone</td>
								<td align="center">1987-2011</td>
								<td align="center">1.1</td>
								<td align="center">1.52</td>
								<td align="center">CLC</td>
							</tr>
							<tr>
								<td align="left">Spain 10 km coastal zone</td>
								<td align="center">2006-2012</td>
								<td align="center">20.6</td>
								<td align="center">1.48</td>
								<td align="center">CLC</td>
							</tr>
							<tr>
								<td align="left">Galicia 10 km coastal zone</td>
								<td align="center">2006-2012</td>
								<td align="center">0.64</td>
								<td align="center">0.67</td>
								<td align="center">CLC</td>
							</tr>
							<tr>
								<td align="left">Galicia 10 km coastal zone</td>
								<td align="center">2005-2011</td>
								<td align="center">1.7</td>
								<td align="center">1.1</td>
								<td align="center">SIOSE</td>
							</tr>
						</tbody>
					</table>
					<table-wrap-foot>
						<fn id="TFN1">
							<p>Annual artificialization rates in Spain and Galicia (10 km coastal zone, 1987-2012).</p>
						</fn>
					</table-wrap-foot>
				</table-wrap>
				<p>The artificialization of the 10 km coastal zone in Spain between 1987 and 2011 showed a rate of 15.4 ha day<sup>-1</sup> according to CLC, increasing the artificial surface by 2.3% per year (<xref ref-type="bibr" rid="B47">Observatorio de la Sostenibilidad, 2016b</xref>). Specifically, artificial surfaces in Spain increased by 1.48% per year in the period 2006-2012, the highest rate in the EU, where the average rate was 0.41% year<sup>-1</sup> (i.e. /year) (<xref ref-type="bibr" rid="B20">Direcci&#xf3;n General de Medio Ambiente de la Comisi&#xf3;n Europea, 2017</xref>). The annual growth rate of artificial surface in the Galician coastal zone (10 km) according to CLC between 1987 and 2011, was 1.52%, which meant 1.1 ha day<sup>-1</sup> (<xref ref-type="bibr" rid="B47">Observatorio de la Sostenibilidad, 2016b</xref>). However, the increase in artificial hectares in the Galician coastal zone (10 km) in the period 2006-2012 was 0.64 ha day<sup>-1</sup>, representing an increase of 0.67% per year. When these data are compared with those obtained in this work using SIOSE, and choosing the closest available interval, 2005-2011, the artificial surface increased by 1.1% per year, with an annual rate of 1.7 ha day<sup>-1</sup>. This is consistent with the underestimation of CLC and the overestimation of SIOSE in terms of artificial surfaces previously reported in the literature (<xref ref-type="bibr" rid="B19">Diaz-Pacheco and Guti&#xe9;rrez, 2014</xref>; <xref ref-type="bibr" rid="B47">Observatorio de la Sostenibilidad, 2016b</xref>, <xref ref-type="bibr" rid="B48">2017</xref>; <xref ref-type="bibr" rid="B49">Olazabal and Bellet, 2017</xref>, <xref ref-type="bibr" rid="B50">2018</xref>; <xref ref-type="bibr" rid="B52">Ovejero-Campos <italic>et al</italic>., 2019</xref>). </p>
				<p>The relative contribution of the artificial land cover in the Galician coast in 2014 is represented in <xref ref-type="fig" rid="f4">Figure 4</xref>, and shows the presence of areas intensely artificialized mainly linked to the main coastal cities. The municipalities with the highest percentage of artificialization were A Coru&#xf1;a (64%) and Vigo (51%).</p>
				<fig id="f4">
					<label>Figure 4</label>
					<caption>
						<title>Relative contribution of artificial land cover in each coastal municipality</title>
						<p>Relative contribution (%) of artificial land cover in each coastal municipality in 2014.</p>
					</caption>
					<graphic id="gra-4" xlink:href="ESTGEOGR-83-292-e100-gf4.png"/>
				</fig>
				<p>The distribution of this variable (<xref ref-type="fig" rid="f4">Fig. 4</xref>) agrees with the location of the urban aggregates defined in the regional littoral planning (Plan de Ordenaci&#xf3;n do Litoral de Galicia) which corresponds to areas of concentration of urban growth where favorable topographic conditions facilitate the development of multiple economic activities (<xref ref-type="bibr" rid="B61">Xunta de Galicia, 2011</xref>). It also matches with the metropolitan areas of Vigo-Pontevedra and A Coru&#xf1;a-Ferrol.</p>
				<p>
					<xref ref-type="fig" rid="f5">Figure 5</xref> shows the annual artificialization rate (%) of the Galician coastal municipalities calculated with respect to the municipal area, which represents the amount of natural surfaces (forest and seminatural areas, agricultural zones and land reclamation) has been &#x201c;denatured&#x201d;.</p>
				<fig id="f5">
					<label>Figure 5</label>
					<caption>
						<title>Annual artificialization rates of the galician coastal municipalities</title>
						<p>Annual artificialization rates of the Galician coastal municipalities (according to SIOSE), with respect to the total municipal area.</p>
					</caption>
					<graphic id="gra-5" xlink:href="ESTGEOGR-83-292-e100-gf5.png"/>
				</fig>
				<p>The highest artificialization rates with respect to the total area of the municipalities were found in the 2005-2009 period, in those areas contiguous to the larger coastal cities (<xref ref-type="fig" rid="f5">Fig. 5</xref>). In the following period (2009-2011), clear differences were found between southern municipalities, showing relatively low land artificialization rates, and northern municipalities where this artificialization was practically non-existent. In the most recent period (2011-2014), a south to north artificialization gradient was observed, albeit rates were lower than in the first period (2005-2009).</p>
				<p>To further investigate the patterns of land artificialization in this region, the Galician coast was divided into zones according to the different degrees of artificialization, derived from their physiographic characteristics, geographical location, climate, orientation, demographic burden, or even the economic and social characteristics. As a result, five groups of coastal municipalities were defined: Costa da Morte, Mari&#xf1;as Coru&#xf1;esas, R&#xed;as Altas, R&#xed;as Baixas and Sur de Galicia (<xref ref-type="fig" rid="f1">Fig. 1</xref>). The maximum annual artificialization rates were generally observed in the period 2005-2009, albeit large differences among coastal groups were observed, with Mari&#xf1;as Coru&#xf1;esas almost doubling the artificialization rates of the R&#xed;as Baixas, R&#xed;as Altas and Costa da Morte, and the Sur de Galicia area showing an artificialization rate 5-fold lower than Mari&#xf1;as Coru&#xf1;esas. A similar pattern was observed in the 2011-2014 period. During the 2009-2011 period, land artificialization was only detected in the southern groups (<xref ref-type="fig" rid="f6">Fig. 6</xref>).</p>
				<fig id="f6">
					<label>Figure 6</label>
					<caption>
						<title>Evolution of artificialization rates in the coastal divisions</title>
						<p>Evolution of land artificialization rates in the groups of coastal municipalities identified in the Galician coast. Annual artificialization rate was calculated with respect to the total area of each group.</p>
					</caption>
					<graphic id="gra-6" xlink:href="ESTGEOGR-83-292-e100-gf6.png"/>
				</fig>
				<p>
					<xref ref-type="fig" rid="f7">Figure 7</xref> shows fluxes between land cover classes in the municipalities&#x2019; coastal strip (2005-2014) resulting from the corresponding cross-matrix, as proposed by <xref ref-type="bibr" rid="B54">Pontius, Shusas &amp; McEachern (2004)</xref> and <xref ref-type="bibr" rid="B39">Mart&#xed;nez-Fern&#xe1;ndez <italic>et al</italic>. (2015)</xref>. The total area transformed into the artificial class in this period was 4610 ha. Almost 3000 of them were previously classified as forest or seminatural areas, and around 1600 hectares as agricultural areas. 215 hectares of total land uptake by artificial surfaces correspond with land reclamation.</p>
				<fig id="f7">
					<label>Figure 7</label>
					<caption>
						<title>Land cover fluxes in the municipalities&#x2019; coastal strip</title>
						<p>Land cover fluxes in the municipalities&#x2019; coastal strip between 2005 and 2014. Units: hectares. Data less than 0.01% are not included.</p>
					</caption>
					<graphic id="gra-7" xlink:href="ESTGEOGR-83-292-e100-gf7.png"/>
				</fig>
				<p>Therefore, 61.4% of the new artificial areas derive from forests or seminatural areas, 33.8% from agricultural areas, 4.7% from areas reclaimed from the sea and 0.1% from wetlands and water bodies. </p>
				<p>We further explored fluxes involving land artificialization to analyse and characterise their dynamics, aiming at a better understanding of the processes involved in the generation of artificial land (<xref ref-type="table" rid="t4">Table 4</xref>). It is worth mentioning that artificialization fluxes in the coastal municipalities strip and in the 10 km coastal zone coincide.</p>
				<table-wrap id="t4">
					<label>Table 4</label>
					<caption>
						<title>Land cover annual change rates with respect to the total area of each land cover class in the initial year of each period and with respect to the area of each class</title>
					</caption>
					<table>
						<colgroup>
							<col/>
							<col/>
							<col/>
							<col/>
							<col/>
						</colgroup>
						<thead>
							<tr>
								<th align="center"> </th>
								<th align="center" colspan="4">Land cover annual change with respect to the total area </th>
							</tr>
							<tr>
								<th align="left"> </th>
								<th align="center">05-09</th>
								<th align="center">09-11</th>
								<th align="center">11-14</th>
								<th align="center">05-14</th>
							</tr>
						</thead>
						<tbody>
							<tr>
								<td align="left">Agricultural zones to artificial surfaces</td>
								<td align="center">0.073</td>
								<td align="center">0.008</td>
								<td align="center">0.028</td>
								<td align="center">0.042</td>
							</tr>
							<tr>
								<td align="left">Forest or seminatural areas to artificial surfaces</td>
								<td align="center">0.132</td>
								<td align="center">0.016</td>
								<td align="center">0.071</td>
								<td align="center">0.076</td>
							</tr>
							<tr>
								<td align="left">Land reclamation</td>
								<td align="center">0.009</td>
								<td align="center">0.002</td>
								<td align="center">0.005</td>
								<td align="center">0.006</td>
							</tr>
							<tr>
								<td align="left"> </td>
								<td align="center" colspan="4">
									<bold>Land cover annual change with respect to the area of each class</bold>
								</td>
							</tr>
							<tr>
								<td align="left"> </td>
								<td align="center">
									<bold>05-09</bold>
								</td>
								<td align="center">
									<bold>09-11</bold>
								</td>
								<td align="center">
									<bold>11-14</bold>
								</td>
								<td align="center">
									<bold>05-14</bold>
								</td>
							</tr>
							<tr>
								<td align="left">Agricultural zones to artificial surfaces</td>
								<td align="center">0.338</td>
								<td align="center">0.039</td>
								<td align="center">0.133</td>
								<td align="center">0.193</td>
							</tr>
							<tr>
								<td align="left">Forest or seminatural areas to artificial surfaces</td>
								<td align="center">0.199</td>
								<td align="center">0.025</td>
								<td align="center">0.107</td>
								<td align="center">0.115</td>
							</tr>
							<tr>
								<td align="left">Land reclamation</td>
								<td align="center">-</td>
								<td align="center">-</td>
								<td align="center">-</td>
								<td align="center">-</td>
							</tr>
						</tbody>
					</table>
					<table-wrap-foot>
						<fn id="TFN2">
							<p>Land cover annual change rates (%) with respect to the total area of each land cover class in the initial year of each period, and with respect to the area of each class; agricultural zones changing to artificial surfaces; forests or seminatural areas changing to artificial surfaces, and land reclamation (classified as artificial surfaces). Municipalities&#x2019; coastal strip. (Periods: 2005-2009; 2009-2011; 2011-2014; 2005-2014).</p>
						</fn>
					</table-wrap-foot>
				</table-wrap>
				<p>The largest changes were concentrated again in the period 2005-2009, being the forest and seminatural classes those presenting the more intense annual changes. During that period, 0.13% of the municipalities&#x2019; coastal strip became artificialized at the expense of forests or seminatural areas. The most noticeable change from agricultural areas to artificial surfaces occurred in the same period (0.07% of the total area of the strip per year). When land cover annual changes (%) with respect to the total area of each class were considered, the agricultural class presented the higher rates in all the periods. A total of 1211 agricultural hectares were artificialized between 2005 and 2009, representing a rate 17-fold higher than in the 2009-2011 period and more than 3-fold higher than in the last one (2011-2014). In the forestry class, 2180 hectares classified as forest or seminatural areas in 2005 were transformed into artificial surfaces until 2009, 16-fold higher than in the period 2005-2009 and 2.5 higher than in the last period. </p>
				<p>The high demand for human settlements and the development of economic activities in the coastal zone triggers a high rate of land consumption. In this study, we found the largest changes in the artificial class, which increased by more than 7% in the studied period, at the expenses of forest and seminatural areas. In most cases, the spatial pattern of this artificialization process was associated with disorganised growth detached from traditional urban settlements, resulting in a diffuse transformation of the Galician coast leading to significant territorial and landscape fragmentation. This fragmentation directly affects ecological connectivity, thereby amplifying several environmental problems such as soil sealing, deforestation, water, soil or air pollution, as well as biodiversity losses (<xref ref-type="bibr" rid="B14">Celliers and Ntombela, 2016</xref>; <xref ref-type="bibr" rid="B53">Pasquali and Marucci, 2021</xref>). </p>
			</sec>
			<sec id="sec3.2">
				<label>3.2.</label>
				<title>Impact of artificialization on ecosystem services</title>
				<p>
					<xref ref-type="fig" rid="f8">Figure 8</xref> shows the spatial distribution of land cover and the potential to provide ecosystem services (ES) of the three main categories (regulation, provisioning and cultural). </p>
				<fig id="f8">
					<label>Figure 8</label>
					<caption>
						<title>Spatial distribution of land cover classes and ecosystem services&#x2019; potential in the coastal municipalities</title>
						<p>Spatial distribution of land cover classes and regulating, provisioning and cultural ecosystem services&#x2019; potential (scale from 0 = no potential to 5 = very high relevant potential) in the coastal municipalities in 2014.</p>
					</caption>
					<graphic id="gra-8" xlink:href="ESTGEOGR-83-292-e100-gf8.png"/>
				</fig>
				<fig id="f9">
					<label>Figure 9</label>
					<caption>
						<title>Average values of the different ecosystem services in the study area</title>
						<p>Average values of the different ecosystem services in the study area in 2014. Global climate regulation: GCR; Local climate regulation: LCR; Air quality regulation: AQR; Water flow regulation: WFR; Water purification: WP; Nutrient regulation: NR; Erosion regulation: ER; Natural hazard regulation: NHR; Pollination: P; Pest and disease control: PDC; Regulation of waste: ROW; Crops: CRO; Biomass for energy: BFE; Fodder: FOD, Livestock (domestic): LCR; Fibre: FIB; Timber: TIM; Wood Fuel: WFR; Fish, seafood &amp; edible algae and aquaculture: FSAEA; Wild foods &amp; resources: WAR; Freshwater: FRE; Recreation &amp; tourism: RAT; Landscape aesthetics &amp; inspiration: LAAI; Knowledge systems: KS; Religious &amp; spiritual experience: RASE; Cultural heritage &amp; cultural diversity: CHACD; Natural heritage &amp; natural diversity: NHAND.</p>
					</caption>
					<graphic id="gra-9" xlink:href="ESTGEOGR-83-292-e100-gf9.png"/>
				</fig>
				<p>The lower potential to provide ecosystem services is generally associated with the anthropogenic land cover types (except some cultural ecosystem services), while agricultural and forest or seminatural areas show high potential in the regulation and provisioning ecosystem services. The two divisions characterised by the highest artificialized areas present the lowest values of ES (Mari&#xf1;as Coru&#xf1;esas and R&#xed;as Baixas). </p>
				<p>Local Climate Regulation and Erosion Regulation showed the highest values within the regulation services whereas Wild Foods and Resources and Wood Fuel scored high in provisioning services. Recreation and Tourism, Landscape aesthetics and Inspiration and Knowledge Systems were the most important cultural services. Regulation and provisioning services were largely associated with forest and seminatural areas (the predominant land cover class in the study area, 65%). On the contrary, all the land cover classes contributed to cultural services. </p>
				<p>The potential to deliver ecosystem services showed a temporal declining trend in the study period, showing annual decreasing rates of -0.13% (provisioning services), -0.05% (regulation services) and -0.003% (cultural services). The highest annual loss rates corresponded with two provisioning services, crops (-0.35%) and livestock (-0.32%), and it is related to the decreased by 3% of the agricultural areas. </p>
				<p>Ecosystem services have been presented as a useful tool to assess de parallel evolution between natural and human processes (<xref ref-type="bibr" rid="B9">Burkhard <italic>et al</italic>., 2009</xref>; <xref ref-type="bibr" rid="B28">Hasan <italic>et al</italic>., 2020</xref>). This study revealed that land cover changes produced in the study area had a direct effect on ecosystem services, as previously detected by other authors (<xref ref-type="bibr" rid="B10">Burkhard, Kroll, Nedkov &amp; M&#xfc;ller, 2012</xref>; <xref ref-type="bibr" rid="B28">Hasan <italic>et al</italic>., 2020</xref>; <xref ref-type="bibr" rid="B37">Kandziora <italic>et al</italic>., 2013</xref>; <xref ref-type="bibr" rid="B62">Yirsaw, Wu, Temesgen &amp; Bekele, 2016</xref>). Therefore, it would be desirable to integrate the ecosystem services approach into land use planning as it demonstrated to be a useful tool for environmental sustainable management or (<xref ref-type="bibr" rid="B3">Baral, Keenan, Fox, Stork &amp; Kasel, 2013</xref>; <xref ref-type="bibr" rid="B7">Bastian <italic>et al</italic>., 2012</xref>; <xref ref-type="bibr" rid="B11">Burkhard <italic>et al</italic>., 2014</xref>; <xref ref-type="bibr" rid="B44">M&#xfc;ller and Burkhard, 2007</xref>; <xref ref-type="bibr" rid="B59">Vihervaara, Kumpula, Tanskanen &amp; Burkhard, 2010</xref>).</p>
			</sec>
			<sec id="sec3.3">
				<label>3.3.</label>
				<title>Relationship between artificialization rates and demographic and economic variables</title>
				<p>In <xref ref-type="fig" rid="f10">Figure 10</xref>, the temporal evolution of the population, artificial area and number of new buildings in the coastal municipalities of the Galician coast is shown.</p>
				<fig id="f10">
					<label>Figure 10</label>
					<caption>
						<title>Evolution of the number of inhabitants, hectares classified as artificial surfaces and number of new buildings</title>
						<p>Evolution of the number of inhabitants, the hectares classified as artificial surfaces in the coastal municipalities, and the number of new buildings (2005-2009; 2009-2011; 2011-2014). (&#x201c;Building: permanent construction, fixed on the ground, separate and independent, conceived to be used for residential purposes and/or for the development of an activity&#x201d;).</p>
					</caption>
					<graphic id="gra-10" xlink:href="ESTGEOGR-83-292-e100-gf10.png"/>
				</fig>
				<p>The three variables show a sharp increase from 2005 to 2009, when the registration of new buildings was 6-fold higher than in the rest of the periods studied. Population increased until 2011, then decreased in the last period, although the number of new buildings was similar and, consequently, the artificialized area still increased with respect to the previous period. The number of hectares classified as artificial surfaces per capita raised continuously from 322 m<sup>2</sup> of artificial surface per inhabitant in 2005 to 343 m<sup>2</sup> in 2014.</p>
				<p>Galicia showed a negative demographic growth (-0.06% year<sup>-1</sup>) in the period 2005-2014. However, in the coastal municipalities, the temporal evolution of this variable was positive (+0.10% year<sup>-1</sup>). Spanish population growth in the period 1991-2011 was positive (1.02% year<sup>-1</sup>) and slightly lower (0.87% year<sup>-1</sup>) when the 10 km coastal zone was considered (<xref ref-type="bibr" rid="B47">Observatorio de la Sostenibilidad, 2016b</xref>).</p>
				<p>The domestic gross disposable income was also used in this analysis as it measures the income of the residents of a given territory used for consumption and savings operations. This indicator, therefore, may reflect if the artificialization process carried out in the territory directly reverts to the families&#x2019; economy or, on the contrary, it does not represent an improvement in economic terms for the local populations. </p>
				<p>A correlation analysis was performed among the different variables, including artificialization (artificialized hectares excluding those dedicated to transport networks or industrial development, which represent 55% of the total artificialized area between 2005 and 2014), the variation in the number of inhabitants, the number of new buildings and the changes in the domestic gross disposable income (by municipality in the period 2005-2014). Two municipalities were excluded from the analysis: Ferrol and Arteixo due to their demographic and economic singularities (supplementary material). </p>
				<p>A bivariate Pearson correlation was calculated to assess the relationship between the selected variables in the coastal zone and in each of the geographical divisions. The four variables are significantly correlated when all the coastal municipalities were considered (<xref ref-type="table" rid="t5">Table 5</xref>). The significant correlation between population and land cover/land use changes found in this study is consistent with the results reported in previous investigations focused on the drivers of land use and land cover (<xref ref-type="bibr" rid="B15">Clement and York, 2017</xref>; <xref ref-type="bibr" rid="B36">Kamwi <italic>et al</italic>., 2015</xref>; <xref ref-type="bibr" rid="B51">Oreinstein and Hamburg, 2010</xref>).</p>
				<table-wrap id="t5">
					<label>Table 5</label>
					<caption>
						<title>A: pearson correlation matrix. Variables: artificialization, new buildings, changes in number of inhabitants, changes in domestic gross disposable income along the coastal municipalities&#x2019; zone. B: correlations in the coastal divisions</title>
					</caption>
					<table>
						<colgroup>
							<col/>
							<col/>
							<col/>
							<col/>
							<col/>
						</colgroup>
						<thead>
							<tr>
								<th align="center">A</th>
								<th align="center">Artificialization</th>
								<th align="center">New buildings</th>
								<th align="center">Population </th>
								<th align="center">Domestic gross income</th>
							</tr>
						</thead>
						<tbody>
							<tr>
								<td align="left">Artificialization</td>
								<td align="center">1</td>
								<td align="center">0.611**</td>
								<td align="center">0.460**</td>
								<td align="center">0.540**</td>
							</tr>
							<tr>
								<td align="left">New buildings</td>
								<td align="left"> </td>
								<td align="center">1</td>
								<td align="center">0.706**</td>
								<td align="center">0.641**</td>
							</tr>
							<tr>
								<td align="left">Population </td>
								<td align="left"> </td>
								<td align="left"> </td>
								<td align="center">1</td>
								<td align="center">0.519**</td>
							</tr>
							<tr>
								<td align="left">Domestic gross income</td>
								<td align="left"> </td>
								<td align="left"> </td>
								<td align="left"> </td>
								<td align="center">1</td>
							</tr>
							<tr>
								<td align="center">
									<bold>B</bold>
								</td>
								<td align="center">
									<bold>N</bold>
								</td>
								<td align="center">
									<bold>Artificialization- New buildings</bold>
								</td>
								<td align="center">
									<bold>Artificialization- Population</bold>
								</td>
								<td align="center">
									<bold>Artificialization- Domestic gross income</bold>
								</td>
							</tr>
							<tr>
								<td align="left">Costa da Morte</td>
								<td align="center">14</td>
								<td align="center">0.817**</td>
								<td align="center">0.587*</td>
								<td align="center">0.726**</td>
							</tr>
							<tr>
								<td align="left">Mari&#xf1;as Coru&#xf1;esas</td>
								<td align="center">13</td>
								<td align="center">0.592*</td>
								<td align="center">0.603*</td>
								<td align="center">0.782**</td>
							</tr>
							<tr>
								<td align="left">R&#xed;as Altas</td>
								<td align="center">13</td>
								<td align="center">0.083</td>
								<td align="center">0.052</td>
								<td align="center">0.310</td>
							</tr>
							<tr>
								<td align="left">R&#xed;as Baixas</td>
								<td align="center">29</td>
								<td align="center">0.782**</td>
								<td align="center">0.432*</td>
								<td align="center">0.435*</td>
							</tr>
						</tbody>
					</table>
					<table-wrap-foot>
						<fn id="TFN3">
							<p>A: Pearson correlation matrix. Variables: artificialization, new buildings, changes in the number of inhabitants, changes in the domestic gross disposable income along the coastal municipalities&#x2019; zone (except Ferrol and Arteixo). B: Correlations in the coastal divisions (Sur de Galicia is ruled out because of the low number of municipalities to perform a statistical analysis).</p>
						</fn>
						<fn id="TFN4">
							<p>** Correlation is significant at the 0.01 level. * Correlation is significant at the 0.05 level.</p>
						</fn>
					</table-wrap-foot>
				</table-wrap>
				<p>Neither of the tested variables showed statistically significant correlations in the R&#xed;as Altas division. This area is characterised by the absence of large urban centers concentrating the population and economic activity and, consequently, transforming the environment. Despite this division showed the second highest averaged rates of artificialization (3.33 ha year<sup>-1</sup>), it is not related to parallel population increases (70% of the municipalities in this division show a demographic decrease between 2005 and 2014), nor to domestic gross income variability. Several processes could account for the observed pattern, such as second home developments, which accounted for a large fraction of the total artificialization process in some municipalities or the dispersed occupation of the territory, mainly with single-family buildings, surrounded by small yards, whose designation in the SIOSE classification represents an overestimation of artificial land cover (<xref ref-type="bibr" rid="B49">Olazabal and Bellet, 2017</xref>). </p>
				<p>Almost half of the artificialization of the Galician coast (41.5%) occurring from 2005 to 2014, derived from non-artificial land covers corresponding to the categories: &#x201c;Residential agricultural settlement&#x201d; (areas with mainly residential use, characterised by a dispersed settlement of buildings, accompanied by arable and/or woody crops), or &#x201c;Discontinuous urban fabric&#x201d;, ie. areas occupied by buildings mainly for housing associated with vegetated areas and bare surfaces, including urban areas that may be consolidated or in the process of consolidation. In both cases they do not represent crowded areas of buildings, so it is unlikely that the number of buildings could account for the whole of the artificialized area. The existence of these scattered settlements is the reason why many polygons appeared as transformations from non-artificial land cover to discontinuous urban fabric land covers, thereby yielding inconsistent results. </p>
				<p>The slopes of the linear regressions between changes in population or new buildings and artificialization rates did not significantly differ depending on the zone (ANCOVA p = 0.852 and p = 0.467, respectively). By contrast, significant differences were found in the slope of the regression lines derived from the relationship between artificialization rates and domestic gross income in the different divisions, although the p-value resulting from the correlation between artificialization and domestic gross income (0.08) is close to the reference value (0.05), it does not seem correct to rule out the existence of significant differences (<xref ref-type="bibr" rid="B1">Amrhein, Greenland &amp; McShane, 2019</xref>) since, as shown in <xref ref-type="fig" rid="f11">Figure 11</xref>, the regression line corresponding to Costa da Morte shows a different pattern from the other divisions.</p>
				<fig id="f11">
					<label>Figure 11</label>
					<caption>
						<title>Linear regressions between artificialized areas, number of new buildings, population and domestic gross income in the coastal divisions</title>
						<p>Linear regressions between artificialized areas, number of new buildings, population and domestic gross income in the coastal divisions. (Only regression lines with significant correlation are represented). Period: 2005-2014.</p>
					</caption>
					<graphic id="gra-11" xlink:href="ESTGEOGR-83-292-e100-gf11.png"/>
				</fig>
				<p>On average, 700 m<sup>2</sup> became artificialized per each new building and 96 m<sup>2</sup> of the territory were transformed into artificial per each new inhabitant when the 2005-2014 period was considered. These values can be compared with the data provided by the European Environment Agency, although this comparison should be made with caution since they referred to the whole country and are divided into two periods (2000-2006 and 2006-2012). According to EEA, 115 m<sup>2</sup> was artificialized in Spain per each new inhabitant in the first period and 29 m<sup>2</sup> new inhabitant<sup>-1</sup> in the second one, while the values for France were 149 and 126 m<sup>2</sup> new inhabitant<sup>-1</sup> and 438 and 426 m<sup>2</sup> new inhabitant<sup>-1</sup> in the case of Portugal. It is worth noting that despite the higher number of artificialized hectares per new inhabitant estimated for Spain or France, the subtle demographic growth of Portugal in this period causes the higher amount of surface assigned to each new inhabitant.</p>
				<p>Sanxenxo, located in the R&#xed;as Baixas division, was the municipality with the highest artificialization rates (12.79 ha), and the city of Vigo showed the largest number of new buildings built, with 104 new buildings year<sup>-1</sup>. Unlike the other divisions, in which population decreased, more than 50% of the municipalities belonging to the R&#xed;as Baixas division increased their population (2005-2014). The highest averaged domestic gross income and population are concentrated in the Mari&#xf1;as Coru&#xf1;esas division, although this division did not show the highest average number of new buildings per year. This observation can be explained by the patterns found in urban areas of A Coru&#xf1;a and Ferrol, characterised by an increase in population and domestic gross income. These municipalities form a supramunicipal area, with one of the most important industrial conglomerates in Spain, where energy, construction, shipyards, clothing and metallurgy industries are concentrated. Both divisions (R&#xed;as Baixas and Mari&#xf1;as Coru&#xf1;esas) present very similar patterns, as shown in <xref ref-type="fig" rid="f11">Figure 11</xref>, and as evidenced by the correlation analyses discussed above. </p>
				<p>The relationships between artificialization and domestic gross income present different patterns in the divisions considered in this study. As noted earlier, Mari&#xf1;as Coru&#xf1;esas and R&#xed;as Baixas present similar results, with 1-2 m<sup>2</sup> of territory required to increase the domestic gross disposable income by one unit (thousand of &#x20ac;). On the contrary, the division Costa da Morte, characterised by decreasing population and domestic gross income values, required 12 m<sup>2</sup> to achieve the same goal. Two municipalities under the influence of the urban area of A Coru&#xf1;a, A Laracha and Carballo, stand out with respect to the others, concentrating the largest increases both in inhabitants and domestic gross income and presenting artificialization rates 2 to 3-fold higher than the average of the division, respectively. In the case of this division, the slopes of the regression lines between artificialization and population or income were positive. Most of the municipalities of this division showed increases in artificialization and new buildings that are not associated with parallel increases in population or income. This division contains 5 of the 6 most extensive municipalities of the Galician coastal zone, with a high percentage of non-coastal territory and with a markedly disseminated settlement, ie. the dominant land cover class is the &#x201c;discontinuous urban fabric&#x201d;, which as mentioned above, may involve an overestimation of the artificial surface resulting from the SIOSE classification. It should also be noted that, unlike the other two divisions, Costa da Morte has not any urban aggregate with the potential for development and growth, thus constraining population growth and economic development of this area.</p>
				<p>The results obtained in this study show that land take occurring in the Galician coastal zone, mainly at the expense of forest and seminatural territories, affected the potential services provided by ecosystems but was not generally related to demographic or domestic economic drivers. </p>
			</sec>
		</sec>
		<sec id="sec4" sec-type="conclusions">
			<label>4.</label>
			<title>Conclusions</title>
			<p>Land use change (especially urbanization) directly affect the food provisioning and regulation services, being an anthropogenic driver which modulates ecosystem functioning and structure. The artificialization process led to the reduction of ecosystem services related to local and global climate regulation. Processes derived from land use changes, such as the increase of impervious surfaces or the artificialization of riverbanks give rise to a lower response capacity of the territory, resulting in territories less resilient to climate change. Riparian ecosystems contribute to ecological adaptation to climate change, particularly facing the observed and expected increases in extreme meterological events, in the magnitude and seasonality of precipitation and run-off, and in atmospheric and water temperature. The increase in impervious surfaces prevents infiltration and increases surface run-off, making the territory vulnerable to extreme meteorological events. In addition, the increase in artificial surfaces also has a direct effect on the territory&#x2019;s ability to mitigate climate change, altering its function of carbon sink. When replacing forests with artificial surfaces, fewer areas contribute to carbon dioxide uptake, so the amount of CO<sub>2</sub> in the atmosphere increases. </p>
			<p>In this context, the location of a substantial part of urban spaces in the coastline exposes them to the impact of extreme coastal events and sea level rise while, at the same time, lead to a loss of environmental quality and value of coastal ecosystems. </p>
			<p>The significant loss of forests and seminatural areas observed in our study was related to a loss of regulation services and a decrease in the provision of ecosystem services. Soil sealing irreversibly affects highly productive agricultural areas since it causes loss of productive capacity and, ultimately the decline of the primary sector, traditionally very important in the Galician economy. The progressive contraction of agricultural, livestock and forestry activities is parallel to the decrease in the absolute and relative importance of the population employed in the sector. In the 2009-2014 period, the population employed in the &#x201c;Agriculture, livestock, hunting and forestry&#x201d; represented 6.2% in mid-2009 and decreased to 4.9% in 2014 (IGE-INE, Economically Active Population Survey, data consulted 03-22-2022).</p>
			<p>The results obtained in this study indicated that despite the decrease in population of the Galician coastal zone in the last period of this study, the number of artificialized hectares and the construction of new buildings increased. </p>
			<p>The observed changes in the land cover patterns in Galicia, and their effect on ecosystem services and impact on the regional economy, warn of the need to reverse this trend of land occupation. This reversing process should be based on solid territorial planning that integrates the dimensions of urban and rural development, considering energy, housing, infrastructures, economic development and human well-being. In this regard, two relevant planning instruments were established in Galicia in 2011, aiming at the sustainable development of the territory: the &#x201c;Directrices de Ordenaci&#xf3;n del Territorio&#x201d; and the &#x201c;Plan de Ordenaci&#xf3;n Litoral&#x201d;. Although both territorial planning instruments were already operative during the second period analysed in this study, the results of our investigation suggest that they have not been capable of reversing the artificialization trend of the Galician territory. The regional scale of these planning instruments and the diversity of processes and conditions taking place in the littoral strip, makes difficult establishing and implementing territorial indicators leading to the limitation of coastal artificialization. However, the definition of land consumption or land artificialization ratios at the municipal planning scale, or even at more detailed scales, can help promoting compactness and rational use of the territory. In this sense, the definition of one or several strips from the coastline, where anthropization, or some of its components, such as urbanization, could not exceed predetermined values, such as the municipal average, might be an action leading to a more rational territorial management of the coastal areas.</p>
			<p>Our results suggest that modification of the existing planning instruments fostering a sustainable articulation of the territory and improving resilience is needed. The assessment of changes in the ecosystem services provided by the territory introduces a new relevant element to be considered in the evaluation of its use-value and highlights the role of the territory at the service of human well-being.</p>
		</sec>
	</body>
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					<source>Plan de ordenaci&#xf3;n do litoral de Galicia</source>
					<ext-link ext-link-type="uri" xlink:href="http://www.xunta.es/litoral/">http://www.xunta.es/litoral/</ext-link>
				</mixed-citation>
			</ref>
			<ref id="B62">
				<mixed-citation publication-type="journal">
					<person-group person-group-type="author">
						<string-name>
							<surname>Yirsaw</surname>
							<given-names>E.</given-names>
						</string-name>
						<string-name>
							<surname>Wu</surname>
							<given-names>W.</given-names>
						</string-name>
						<string-name>
							<surname>Temesgen</surname>
							<given-names>H.</given-names>
						</string-name>
						<string-name>
							<surname>Bekele</surname>
							<given-names>B.</given-names>
						</string-name>
					</person-group>
					<year>2016</year>
					<article-title>Effect of temporal land use / land cover changes on ecosystem services value in coastal area of China: the case of Su-Xi-Chang region</article-title>
					<source>Applied ecology and environmental research</source>
					<volume>14</volume>
					<fpage>409</fpage>
					<lpage>422</lpage>
					<pub-id pub-id-type="doi">10.15666/aeer/1403_409422</pub-id>
				</mixed-citation>
			</ref>
		</ref-list>
		<app-group>
			<app id="app1">
				<title>Supplementary material</title>
				<supplementary-material id="suppl1" mimetype="application" mime-subtype="pdf" xlink:href="https://doi.org/10.3989/estgeogr.2022108.108">
					<table-wrap id="t6">
						<label>I</label>
						<caption>
							<title>Land cover accounts for the 10 km coastal zone. Units: hectares and percentage</title>
						</caption>
						<table>
							<colgroup>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
							</colgroup>
							<thead>
								<tr>
									<th align="center">Land cover class</th>
									<th align="center">2005</th>
									<th align="center">%</th>
									<th align="center">2009</th>
									<th align="center">%</th>
									<th align="center">2011</th>
									<th align="center">%</th>
									<th align="center">2014</th>
									<th align="center">%</th>
								</tr>
							</thead>
							<tbody>
								<tr>
									<td align="left">Artificial surfaces</td>
									<td align="center">57236.55</td>
									<td align="center">10.70</td>
									<td align="center">60798.86</td>
									<td align="center">11.36</td>
									<td align="center">60962.80</td>
									<td align="center">11.39</td>
									<td align="center">61493.95</td>
									<td align="center">11.49</td>
								</tr>
								<tr>
									<td align="left">Agriculture areas</td>
									<td align="center">114150.83</td>
									<td align="center">21.34</td>
									<td align="center">112376.24</td>
									<td align="center">21.01</td>
									<td align="center">112210.41</td>
									<td align="center">20.97</td>
									<td align="center">110565.14</td>
									<td align="center">20.66</td>
								</tr>
								<tr>
									<td align="left">Forest and seminatural areas</td>
									<td align="center">354670.69</td>
									<td align="center">66.31</td>
									<td align="center">353038.98</td>
									<td align="center">65.99</td>
									<td align="center">353041.87</td>
									<td align="center">65.99</td>
									<td align="center">354190.09</td>
									<td align="center">66.20</td>
								</tr>
								<tr>
									<td align="left">Wetlands</td>
									<td align="center">3258.59</td>
									<td align="center">0.61</td>
									<td align="center">3261.53</td>
									<td align="center">0.61</td>
									<td align="center">3267.97</td>
									<td align="center">0.61</td>
									<td align="center">3281.30</td>
									<td align="center">0.61</td>
								</tr>
								<tr>
									<td align="left">Water bodies</td>
									<td align="center">5515.54</td>
									<td align="center">1.03</td>
									<td align="center">5512.10</td>
									<td align="center">1.03</td>
									<td align="center">5513.17</td>
									<td align="center">1.03</td>
									<td align="center">5525.69</td>
									<td align="center">1.03</td>
								</tr>
							</tbody>
						</table>
					</table-wrap>
					<table-wrap id="t7">
						<label>II</label>
						<caption>
							<title>Land cover accounts in the municipalities&#x2019; coastal zone. Units: hectares and percentage</title>
						</caption>
						<table>
							<colgroup>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
							</colgroup>
							<thead>
								<tr>
									<th align="center">Land cover class</th>
									<th align="center">2005</th>
									<th align="center">%</th>
									<th align="center">2009</th>
									<th align="center">%</th>
									<th align="center">2011</th>
									<th align="center">%</th>
									<th align="center">2014</th>
									<th align="center">%</th>
								</tr>
							</thead>
							<tbody>
								<tr>
									<td align="left">
										<bold>Artificial surfaces</bold>
									</td>
									<td align="center">47360.93</td>
									<td align="center">11.32</td>
									<td align="center">50350.24</td>
									<td align="center">12.03</td>
									<td align="center">50473.89</td>
									<td align="center">12.06</td>
									<td align="center">50865.13</td>
									<td align="center">12.15</td>
								</tr>
								<tr>
									<td align="left">
										<bold>Agriculture areas</bold>
									</td>
									<td align="center">89617.45</td>
									<td align="center">21.42</td>
									<td align="center">88188.86</td>
									<td align="center">21.07</td>
									<td align="center">88025.96</td>
									<td align="center">21.03</td>
									<td align="center">86864.14</td>
									<td align="center">20.75</td>
								</tr>
								<tr>
									<td align="left">
										<bold>Forest and seminatural areas</bold>
									</td>
									<td align="center">274083.74</td>
									<td align="center">65.51</td>
									<td align="center">272678.80</td>
									<td align="center">65.15</td>
									<td align="center">272719.05</td>
									<td align="center">65.16</td>
									<td align="center">273534.09</td>
									<td align="center">65.34</td>
								</tr>
								<tr>
									<td align="left">
										<bold>Wetlands</bold>
									</td>
									<td align="center">3048.35</td>
									<td align="center">0.73</td>
									<td align="center">3051.43</td>
									<td align="center">0.73</td>
									<td align="center">3057.87</td>
									<td align="center">0.73</td>
									<td align="center">3071.20</td>
									<td align="center">0.73</td>
								</tr>
								<tr>
									<td align="left">
										<bold>Water bodies</bold>
									</td>
									<td align="center">4266.32</td>
									<td align="center">1.02</td>
									<td align="center">4262.96</td>
									<td align="center">1.02</td>
									<td align="center">4264.03</td>
									<td align="center">1.02</td>
									<td align="center">4266.18</td>
									<td align="center">1.02</td>
								</tr>
							</tbody>
						</table>
					</table-wrap>
					<table-wrap id="t8">
						<label>III</label>
						<caption>
							<title>Population in 2005, 2009, 2011 and 2014 (SIOSE&#x2019;s dates) and number of new buildings in the periods in between (2005-2009, 2009-2011, 2011-2014) in the Galician coastal divisions</title>
						</caption>
						<table>
							<colgroup>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
							</colgroup>
							<thead>
								<tr>
									<th align="center"> </th>
									<th align="center">Population 2005</th>
									<th align="center">Population 2009</th>
									<th align="center">Population 2011</th>
									<th align="center">Population 2014</th>
									<th align="center">New buildings 2005-2009</th>
									<th align="center">New buildings 2009-2011</th>
									<th align="center">New buildings 2011-2014</th>
								</tr>
							</thead>
							<tbody>
								<tr>
									<td align="left">Costa da Morte</td>
									<td align="center">135592</td>
									<td align="center">136010</td>
									<td align="center">136307</td>
									<td align="center">133400</td>
									<td align="center">1498</td>
									<td align="center">274</td>
									<td align="center">288</td>
								</tr>
								<tr>
									<td align="left">Mari&#xf1;as Coru&#xf1;esas</td>
									<td align="center">456344</td>
									<td align="center">463551</td>
									<td align="center">464328</td>
									<td align="center">460928</td>
									<td align="center">2910</td>
									<td align="center">481</td>
									<td align="center">465</td>
								</tr>
								<tr>
									<td align="left">R&#xed;as Altas</td>
									<td align="center">87973</td>
									<td align="center">88846</td>
									<td align="center">88022</td>
									<td align="center">85720</td>
									<td align="center">1240</td>
									<td align="center">111</td>
									<td align="center">138</td>
								</tr>
								<tr>
									<td align="left">R&#xed;as Baixas</td>
									<td align="center">769402</td>
									<td align="center">784138</td>
									<td align="center">787339</td>
									<td align="center">781676</td>
									<td align="center">5923</td>
									<td align="center">1117</td>
									<td align="center">1129</td>
								</tr>
								<tr>
									<td align="left">Sur de Galicia</td>
									<td align="center">19430</td>
									<td align="center">20222</td>
									<td align="center">20276</td>
									<td align="center">19811</td>
									<td align="center">442</td>
									<td align="center">57</td>
									<td align="center">74</td>
								</tr>
								<tr>
									<td align="left">Total</td>
									<td align="center">1468741</td>
									<td align="center">1492767</td>
									<td align="center">1496272</td>
									<td align="center">1481535</td>
									<td align="center">12013</td>
									<td align="center">2040</td>
									<td align="center">2094</td>
								</tr>
							</tbody>
						</table>
					</table-wrap>
					<table-wrap id="t9">
						<label>IV</label>
						<caption>
							<title>Matrix for the assessment of the different land cover class and its capacity to provide ecosystem services (adapted from Burkhard&#x2019;s matrix)</title>
						</caption>
						<table>
							<colgroup>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
							</colgroup>
							<thead>
								<tr>
									<th align="left"> </th>
									<th align="left">Regulating services</th>
									<th align="left">Global climate regulation</th>
									<th align="left">Local climate regulation</th>
									<th align="left">Air quality regulation</th>
									<th align="left">Water flow regulation</th>
									<th align="left">Water purification</th>
									<th align="left">Nutrient regulation</th>
									<th align="left">Erosion regulation</th>
									<th align="left">Natural hazard regulation</th>
									<th align="left">Pollination</th>
									<th align="left">Pest and disease control</th>
									<th align="left">Regulation of waste</th>
								</tr>
							</thead>
							<tbody>
								<tr>
									<td align="left">
										<bold>Artificial surfaces</bold>
									</td>
									<td align="left"> </td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">2</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">1</td>
									<td align="center">0</td>
								</tr>
								<tr>
									<td align="left">Agricultural areas</td>
									<td align="left"> </td>
									<td align="center">1</td>
									<td align="center">2</td>
									<td align="center">1</td>
									<td align="center">1</td>
									<td align="center">0</td>
									<td align="center">1</td>
									<td align="center">1</td>
									<td align="center">1</td>
									<td align="center">2</td>
									<td align="center">3</td>
									<td align="center">2</td>
								</tr>
								<tr>
									<td align="left">Forest and seminatural areas</td>
									<td align="left"> </td>
									<td align="center">5</td>
									<td align="center">5</td>
									<td align="center">5</td>
									<td align="center">3</td>
									<td align="center">5</td>
									<td align="center">5</td>
									<td align="center">5</td>
									<td align="center">4</td>
									<td align="center">4</td>
									<td align="center">4</td>
									<td align="center">4</td>
								</tr>
								<tr>
									<td align="left">Wetlands</td>
									<td align="left"> </td>
									<td align="center">1</td>
									<td align="center">1</td>
									<td align="center">0</td>
									<td align="center">2</td>
									<td align="center">1</td>
									<td align="center">3</td>
									<td align="center">1</td>
									<td align="center">4</td>
									<td align="center">1</td>
									<td align="center">2</td>
									<td align="center">2</td>
								</tr>
								<tr>
									<td align="left">Water bodies</td>
									<td align="left"> </td>
									<td align="center">1</td>
									<td align="center">1</td>
									<td align="center">0</td>
									<td align="center">3</td>
									<td align="center">3</td>
									<td align="center">3</td>
									<td align="center">0</td>
									<td align="center">3</td>
									<td align="center">0</td>
									<td align="center">3</td>
									<td align="center">5</td>
								</tr>
							</tbody>
						</table>
					</table-wrap>
					<table-wrap id="t10">
						<table>
							<colgroup>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
							</colgroup>
							<thead>
								<tr>
									<th align="left"> </th>
									<th align="left">Provisioning services</th>
									<th align="left">Crops </th>
									<th align="left">Biomass for energy </th>
									<th align="left">Fodder </th>
									<th align="left">Livestock (domestic) </th>
									<th align="left">Fibre </th>
									<th align="left">Timber </th>
									<th align="left">Wood Fuel </th>
									<th align="left">Fish, seafood &amp; edible algae and aquaculture</th>
									<th align="left">Wild foods &amp; resources </th>
									<th align="left">Freshwater </th>
								</tr>
							</thead>
							<tbody>
								<tr>
									<td align="left">
										<bold>Artificial surfaces</bold>
									</td>
									<td align="left"> </td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
								</tr>
								<tr>
									<td align="left">Agricultural areas</td>
									<td align="left"> </td>
									<td align="center">4</td>
									<td align="center">2</td>
									<td align="center">2</td>
									<td align="center">1</td>
									<td align="center">3</td>
									<td align="center">0</td>
									<td align="center">1</td>
									<td align="center">0</td>
									<td align="center">1</td>
									<td align="center">0</td>
								</tr>
								<tr>
									<td align="left">Forest and seminatural areas</td>
									<td align="left"> </td>
									<td align="center">0</td>
									<td align="center">1</td>
									<td align="center">1</td>
									<td align="center">0</td>
									<td align="center">1</td>
									<td align="center">5</td>
									<td align="center">5</td>
									<td align="center">0</td>
									<td align="center">5</td>
									<td align="center">0</td>
								</tr>
								<tr>
									<td align="left">Wetlands</td>
									<td align="left"> </td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">3</td>
									<td align="center">2</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">1</td>
									<td align="center">0</td>
								</tr>
								<tr>
									<td align="left">Water bodies</td>
									<td align="left"> </td>
									<td align="center">0</td>
									<td align="center">2</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">0</td>
									<td align="center">4</td>
									<td align="center">4</td>
									<td align="center">2</td>
								</tr>
							</tbody>
						</table>
					</table-wrap>
					<table-wrap id="t11">
						<table>
							<colgroup>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
							</colgroup>
							<thead>
								<tr>
									<th align="left"> </th>
									<th align="left">Cultural services </th>
									<th align="left">Recreation &amp; tourism </th>
									<th align="left">Landscape aesthetics &amp; inspiration </th>
									<th align="left">Knowledge systems </th>
									<th align="left">Religious &amp; spiritual experience </th>
									<th align="left">Cultural heritage &amp; cultural diversity</th>
									<th align="left">Natural heritage &amp; natural diversity</th>
								</tr>
							</thead>
							<tbody>
								<tr>
									<td align="left">Artificial surfaces</td>
									<td align="left"> </td>
									<td align="center">3</td>
									<td align="center">2</td>
									<td align="center">2</td>
									<td align="center">2</td>
									<td align="center">2</td>
									<td align="center">0</td>
								</tr>
								<tr>
									<td align="left">Agricultural areas</td>
									<td align="left"> </td>
									<td align="center">2</td>
									<td align="center">2</td>
									<td align="center">2</td>
									<td align="center">0</td>
									<td align="center">3</td>
									<td align="center">0</td>
								</tr>
								<tr>
									<td align="left">Forest and seminatural areas</td>
									<td align="left"> </td>
									<td align="center">5</td>
									<td align="center">5</td>
									<td align="center">5</td>
									<td align="center">3</td>
									<td align="center">4</td>
									<td align="center">4</td>
								</tr>
								<tr>
									<td align="left">Wetlands</td>
									<td align="left"> </td>
									<td align="center">2</td>
									<td align="center">2</td>
									<td align="center">3</td>
									<td align="center">0</td>
									<td align="center">2</td>
									<td align="center">2</td>
								</tr>
								<tr>
									<td align="left">Water bodies</td>
									<td align="left"> </td>
									<td align="center">3</td>
									<td align="center">4</td>
									<td align="center">4</td>
									<td align="center">1</td>
									<td align="center">2</td>
									<td align="center">3</td>
								</tr>
							</tbody>
						</table>
						<table-wrap-foot>
							<fn id="TFN5">
								<p>0=no relevant potential; 1=low relevant potential; 2=relevant potential; 3=medium relevant potential; 4=high relevant potential; 5=very high relevant potential.</p>
							</fn>
						</table-wrap-foot>
					</table-wrap>
					<p>V. Municipalities excluded from the regression analysis</p>
					<p>The municipality of Ferrol, presents a population decrease of 751 inhabitants year<sup>-1</sup> and an increase in the artificialization rate of 13.92 ha year<sup>-1</sup> between 2005 and 2014. It is an industrial municipality, which depends almost exclusively on the naval sector, therefore with a low productive flexibility. The lack of employment has caused a continuous and steeped demographic decrease, which is accompanied by population aging. In the case of Arteixo, three main events clearly distorted land use and demographic patterns in this municipality. Firstly the outer port of A Coru&#xf1;a (one of the largest in Spain) was built in that period, implying a high artificialization rate of 61 ha year<sup>-1</sup>. Secondly, there is a disproportionate increase in population (509 inhabitants year<sup>-1</sup>) and thirdly, a high increase in the domestic gross income was also observed (13000 thousand euros year<sup>-1</sup>). Among the causes, it is worth highlighting the industrial complex of Sab&#xf3;n (which houses a relatively large number of companies with a high number of employees), its proximity to A Coru&#xf1;a (that makes Arteixo an alternative as a residence) and, finally, the presence of a powerful business group, Inditex (which positions it as one of the Galician municipalities with the highest per capita income). </p>
				</supplementary-material>
			</app>
		</app-group>
	</back>
</article>