<?xml version="1.0" encoding="UTF-8" standalone="no"?><metadata xml:lang="fr">
    <Esri>
        <CreaDate>20171017</CreaDate>
        <CreaTime>10000400</CreaTime>
        <ArcGISFormat>1.0</ArcGISFormat>
        <SyncOnce>FALSE</SyncOnce>
        <DataProperties>
            <itemProps>
                <itemName Sync="TRUE">MesuresSpatiales_PMSSL</itemName>
                <imsContentType Sync="TRUE">002</imsContentType>
                <itemSize Sync="TRUE">0.000</itemSize>
            </itemProps>
            <coordRef>
                <type Sync="TRUE">Projected</type>
                <geogcsn Sync="TRUE">GCS_North_American_1983</geogcsn>
                <csUnits Sync="TRUE">Linear Unit: Meter (1.000000)</csUnits>
                <peXml Sync="TRUE">&lt;ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/2.9.0'&gt;&lt;WKT&gt;PROJCS[&amp;quot;NAD_1983_UTM_Zone_19N&amp;quot;,GEOGCS[&amp;quot;GCS_North_American_1983&amp;quot;,DATUM[&amp;quot;D_North_American_1983&amp;quot;,SPHEROID[&amp;quot;GRS_1980&amp;quot;,6378137.0,298.257222101]],PRIMEM[&amp;quot;Greenwich&amp;quot;,0.0],UNIT[&amp;quot;Degree&amp;quot;,0.0174532925199433]],PROJECTION[&amp;quot;Transverse_Mercator&amp;quot;],PARAMETER[&amp;quot;False_Easting&amp;quot;,500000.0],PARAMETER[&amp;quot;False_Northing&amp;quot;,0.0],PARAMETER[&amp;quot;Central_Meridian&amp;quot;,-69.0],PARAMETER[&amp;quot;Scale_Factor&amp;quot;,0.9996],PARAMETER[&amp;quot;Latitude_Of_Origin&amp;quot;,0.0],UNIT[&amp;quot;Meter&amp;quot;,1.0],AUTHORITY[&amp;quot;EPSG&amp;quot;,26919]]&lt;/WKT&gt;&lt;XOrigin&gt;-5120900&lt;/XOrigin&gt;&lt;YOrigin&gt;-9998100&lt;/YOrigin&gt;&lt;XYScale&gt;450445547.3910538&lt;/XYScale&gt;&lt;ZOrigin&gt;-100000&lt;/ZOrigin&gt;&lt;ZScale&gt;10000&lt;/ZScale&gt;&lt;MOrigin&gt;-100000&lt;/MOrigin&gt;&lt;MScale&gt;10000&lt;/MScale&gt;&lt;XYTolerance&gt;0.001&lt;/XYTolerance&gt;&lt;ZTolerance&gt;0.001&lt;/ZTolerance&gt;&lt;MTolerance&gt;0.001&lt;/MTolerance&gt;&lt;HighPrecision&gt;true&lt;/HighPrecision&gt;&lt;WKID&gt;26919&lt;/WKID&gt;&lt;LatestWKID&gt;26919&lt;/LatestWKID&gt;&lt;/ProjectedCoordinateSystem&gt;</peXml>
                <projcsn Sync="TRUE">NAD_1983_UTM_Zone_19N</projcsn>
            </coordRef>
        </DataProperties>
        <SyncDate>20231129</SyncDate>
        <SyncTime>15232100</SyncTime>
        <ModDate>20231129</ModDate>
        <ModTime>15232100</ModTime>
        <scaleRange>
            <minScale>150000000</minScale>
            <maxScale>5000</maxScale>
        </scaleRange>
        <ArcGISProfile>ItemDescription</ArcGISProfile>
    </Esri>
    <dataIdInfo>
        <envirDesc Sync="FALSE">Esri ArcGIS 12.9.4.32739</envirDesc>
        <dataLang>
            <languageCode Sync="TRUE" value="fra"/>
            <countryCode Sync="TRUE" value="CAN"/>
        </dataLang>
        <idCitation>
            <resTitle Sync="TRUE">MesuresSpatiales_PMSSL</resTitle>
            <presForm>
                <PresFormCd Sync="TRUE" value="005"/>
            </presForm>
        </idCitation>
        <spatRpType>
            <SpatRepTypCd Sync="TRUE" value="001"/>
        </spatRpType>
        <idPurp>Mesures spatiales de protection des mammifères marins implémentées dans le parc marin du Saguenay–Saint-Laurent. Ces mesures comprennent des mesures règlementaires selon le règlement sur les activités en mer dans le parc marin du Saguenay–Saint-Laurent (Parcs Canada). Le Règlement sur les activités en mer dans le parc marin du Saguenay–Saint-Laurent encadre les activités en mer afin de protéger les mammifères marins, dont les espèces en péril comme le béluga et le rorqual bleu. Certaines autres mesures présentes dans ce fichier ne sont pas règlementées selon le Règlement sur les activités en mer dans le parc marin du Saguenay–Saint-Laurent et sont définies comme des mesures volontaires.

Spatial measures for the protection of marine mammals implemented in the Saguenay–St. Lawrence Marine Park. These measures include regulatory measures according to the Marine Activities in the Saguenay-St. Lawrence Marine Park Regulations (Parks Canada). The Marine Activities in the Saguenay-St. Lawrence Marine Park Regulations govern activities at sea within the Saguenay–St. Lawrence Marine Park in order to protect marine mammals, including species at risk such as the beluga and the blue whale. Certain other measures present in this file are not regulated according to the Regulation respecting activities at sea in the Saguenay–St. Lawrence Marine Park and are defined as voluntary measures.</idPurp>
        <idAbs>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P STYLE="margin:0 0 1 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Ces données donnent la localisation des mesures spatiales de protection des mammifères marins implémentées dans le parc marin du Saguenay–Saint-Laurent. Ces données comprennent aussi des informations quant aux spécificités de l'application de chaque mesure : le secteur d'application, la période d'application, l'année de la mise en vigueur, les types d'embarcations visés par la mesure, le type de mesure et des informations sur le comportement à adopter à l'intérieur du secteur.&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;P STYLE="margin:0 0 1 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;These data provide the location of spatial measures for the protection of marine mammals implemented in the Saguenay–St. Lawrence Marine Park. These data also include information on the specificities of the application of each measure: the sector of application, the period of application, the year of implementation, the types of vessels targeted by the measure, the type of measure and information on the behavior to adopt within the sector.&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN /&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</idAbs>
        <searchKeys>
            <keyword>Mesures spatiales</keyword>
            <keyword>mammifères marins</keyword>
            <keyword>parc marin du Saguenay–Saint-Laurent</keyword>
            <keyword>Spatial measures</keyword>
            <keyword>marine mammals</keyword>
            <keyword>Saguenay–St. Lawrence Marine Park.</keyword>
        </searchKeys>
        <idCredit>Parc marin du Saguenay–Saint-Laurent (Agence Parcs Canada), 2023
Saguenay-St. Lawrence Marine Park (Parks Canada Agency), 2023</idCredit>
        <resConst>
            <Consts>
                <useLimit>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;Règlement sur les activités en mer dans le parc marin du Saguenay — Saint-Laurent&lt;/SPAN&gt;&lt;SPAN&gt;, &lt;/SPAN&gt;&lt;SPAN&gt;DORS/2002-76&lt;/SPAN&gt;&lt;SPAN&gt;, &lt;/SPAN&gt;&lt;SPAN&gt;https://laws-lois.justice.gc.ca/fra/reglements/DORS-2002-76/&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Garde côtière canadienne&lt;/SPAN&gt;&lt;SPAN&gt;. &lt;/SPAN&gt;&lt;SPAN&gt;Avis aux navigateurs 1 à 46. Édition annuelle / Publié par: Système à la navigation, Pêches et Océans Canada&lt;/SPAN&gt;&lt;SPAN&gt;,2023, &lt;/SPAN&gt;&lt;SPAN&gt;https://www.notmar.gc.ca/annuel&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Nadia Ménard, Samuel Turgeon, Manuela Conversano, Cristiane C.A. Martins,&lt;/SPAN&gt;&lt;SPAN&gt; &lt;/SPAN&gt;&lt;SPAN&gt;Sharing the waters: Application of a marine spatial planning approach to conserve and restore the acoustic habitat of endangered beluga whales (Delphinapterus leucas) in and around the Saguenay–St. Lawrence Marine Park,&lt;/SPAN&gt;&lt;SPAN&gt; &lt;/SPAN&gt;&lt;SPAN&gt;Marine Pollution Bulletin,&lt;/SPAN&gt;&lt;SPAN&gt; &lt;/SPAN&gt;&lt;SPAN&gt;Volume 175,&lt;/SPAN&gt;&lt;SPAN&gt; &lt;/SPAN&gt;&lt;SPAN&gt;2022,&lt;/SPAN&gt;&lt;SPAN&gt; &lt;/SPAN&gt;&lt;SPAN&gt;113325,&lt;/SPAN&gt;&lt;SPAN&gt; &lt;/SPAN&gt;&lt;SPAN&gt;ISSN 0025-326X,&lt;/SPAN&gt;&lt;SPAN&gt; &lt;/SPAN&gt;&lt;SPAN&gt;https://doi.org/10.1016/j.marpolbul.2022.113325&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN /&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</useLimit>
            </Consts>
        </resConst>
    </dataIdInfo>
    <mdLang>
        <languageCode Sync="TRUE" value="fra"/>
        <countryCode Sync="TRUE" value="CAN"/>
    </mdLang>
    <mdChar>
        <CharSetCd Sync="TRUE" value="004"/>
    </mdChar>
    <distInfo>
        <distFormat>
            <formatName Sync="TRUE">Shapefile</formatName>
        </distFormat>
        <distTranOps>
            <transSize Sync="TRUE">0.000</transSize>
        </distTranOps>
    </distInfo>
    <mdHrLv>
        <ScopeCd Sync="TRUE" value="005"/>
    </mdHrLv>
    <mdHrLvName Sync="TRUE">dataset</mdHrLvName>
    <refSysInfo>
        <RefSystem>
            <refSysID>
                <identCode Sync="TRUE" code="26919" value="4326"/>
                <idCodeSpace Sync="TRUE">EPSG</idCodeSpace>
                <idVersion Sync="TRUE">6.11(3.0.1)</idVersion>
            </refSysID>
        </RefSystem>
    </refSysInfo>
    <spatRepInfo>
        <VectSpatRep>
            <geometObjs Name="MesuresSpatiales_PMSSL">
                <geoObjTyp>
                    <GeoObjTypCd Sync="TRUE" value="002"/>
                </geoObjTyp>
                <geoObjCnt Sync="TRUE">0</geoObjCnt>
            </geometObjs>
            <topLvl>
                <TopoLevCd Sync="TRUE" value="001"/>
            </topLvl>
        </VectSpatRep>
    </spatRepInfo>
    <spdoinfo>
        <ptvctinf>
            <esriterm Name="MesuresSpatiales_PMSSL">
                <efeatyp Sync="TRUE">Simple</efeatyp>
                <efeageom Sync="TRUE" code="4"/>
                <esritopo Sync="TRUE">FALSE</esritopo>
                <efeacnt Sync="TRUE">0</efeacnt>
                <spindex Sync="TRUE">FALSE</spindex>
                <linrefer Sync="TRUE">FALSE</linrefer>
            </esriterm>
        </ptvctinf>
    </spdoinfo>
    <eainfo>
        <detailed Name="MesuresSpatiales_PMSSL">
            <enttyp>
                <enttypl Sync="TRUE">MesuresSpatiales_PMSSL</enttypl>
                <enttypt Sync="TRUE">Feature Class</enttypt>
                <enttypc Sync="TRUE">0</enttypc>
            </enttyp>
            <attr>
                <attrlabl Sync="TRUE">FID</attrlabl>
                <attalias Sync="TRUE">FID</attalias>
                <attrtype Sync="TRUE">OID</attrtype>
                <attwidth Sync="TRUE">4</attwidth>
                <atprecis Sync="TRUE">0</atprecis>
                <attscale Sync="TRUE">0</attscale>
                <attrdef Sync="TRUE">Internal feature number.</attrdef>
                <attrdefs Sync="TRUE">Esri</attrdefs>
                <attrdomv>
                    <udom Sync="TRUE">Sequential unique whole numbers that are automatically generated.</udom>
                </attrdomv>
            </attr>
            <attr>
                <attrlabl Sync="TRUE">Shape</attrlabl>
                <attalias Sync="TRUE">Shape</attalias>
                <attrtype Sync="TRUE">Geometry</attrtype>
                <attwidth Sync="TRUE">0</attwidth>
                <atprecis Sync="TRUE">0</atprecis>
                <attscale Sync="TRUE">0</attscale>
                <attrdef Sync="TRUE">Feature geometry.</attrdef>
                <attrdefs Sync="TRUE">Esri</attrdefs>
                <attrdomv>
                    <udom Sync="TRUE">Coordinates defining the features.</udom>
                </attrdomv>
            </attr>
            <attr>
                <attrlabl Sync="TRUE">Periode</attrlabl>
                <attalias Sync="TRUE">Periode</attalias>
                <attrtype Sync="TRUE">String</attrtype>
                <attwidth Sync="TRUE">50</attwidth>
                <atprecis Sync="TRUE">0</atprecis>
                <attscale Sync="TRUE">0</attscale>
            </attr>
            <attr>
                <attrlabl Sync="TRUE">Name</attrlabl>
                <attalias Sync="TRUE">Name</attalias>
                <attrtype Sync="TRUE">String</attrtype>
                <attwidth Sync="TRUE">254</attwidth>
                <atprecis Sync="TRUE">0</atprecis>
                <attscale Sync="TRUE">0</attscale>
            </attr>
            <attr>
                <attrlabl Sync="TRUE">Depuis_Sin</attrlabl>
                <attalias Sync="TRUE">Depuis_Sin</attalias>
                <attrtype Sync="TRUE">Integer</attrtype>
                <attwidth Sync="TRUE">10</attwidth>
                <atprecis Sync="TRUE">10</atprecis>
                <attscale Sync="TRUE">0</attscale>
            </attr>
            <attr>
                <attrlabl Sync="TRUE">Nom</attrlabl>
                <attalias Sync="TRUE">Nom</attalias>
                <attrtype Sync="TRUE">String</attrtype>
                <attwidth Sync="TRUE">50</attwidth>
                <atprecis Sync="TRUE">0</atprecis>
                <attscale Sync="TRUE">0</attscale>
            </attr>
            <attr>
                <attrlabl Sync="TRUE">Secteur_Ar</attrlabl>
                <attalias Sync="TRUE">Secteur_Ar</attalias>
                <attrtype Sync="TRUE">String</attrtype>
                <attwidth Sync="TRUE">100</attwidth>
                <atprecis Sync="TRUE">0</atprecis>
                <attscale Sync="TRUE">0</attscale>
            </attr>
            <attr>
                <attrlabl Sync="TRUE">Informatio</attrlabl>
                <attalias Sync="TRUE">Informatio</attalias>
                <attrtype Sync="TRUE">String</attrtype>
                <attwidth Sync="TRUE">250</attwidth>
                <atprecis Sync="TRUE">0</atprecis>
                <attscale Sync="TRUE">0</attscale>
            </attr>
            <attr>
                <attrlabl Sync="TRUE">Applicatio</attrlabl>
                <attalias Sync="TRUE">Applicatio</attalias>
                <attrtype Sync="TRUE">String</attrtype>
                <attwidth Sync="TRUE">254</attwidth>
                <atprecis Sync="TRUE">0</atprecis>
                <attscale Sync="TRUE">0</attscale>
            </attr>
            <attr>
                <attrlabl Sync="TRUE">Type_Mesur</attrlabl>
                <attalias Sync="TRUE">Type_Mesur</attalias>
                <attrtype Sync="TRUE">String</attrtype>
                <attwidth Sync="TRUE">254</attwidth>
                <atprecis Sync="TRUE">0</atprecis>
                <attscale Sync="TRUE">0</attscale>
            </attr>
            <attr>
                <attrlabl Sync="TRUE">Shape_Leng</attrlabl>
                <attalias Sync="TRUE">Shape_Leng</attalias>
                <attrtype Sync="TRUE">Double</attrtype>
                <attwidth Sync="TRUE">19</attwidth>
                <atprecis Sync="TRUE">0</atprecis>
                <attscale Sync="TRUE">0</attscale>
            </attr>
            <attr>
                <attrlabl Sync="TRUE">Shape_Area</attrlabl>
                <attalias Sync="TRUE">Shape_Area</attalias>
                <attrtype Sync="TRUE">Double</attrtype>
                <attwidth Sync="TRUE">19</attwidth>
                <atprecis Sync="TRUE">0</atprecis>
                <attscale Sync="TRUE">0</attscale>
                <attrdef Sync="TRUE">Area of feature in internal units squared.</attrdef>
                <attrdefs Sync="TRUE">Esri</attrdefs>
                <attrdomv>
                    <udom Sync="TRUE">Positive real numbers that are automatically generated.</udom>
                </attrdomv>
            </attr>
        </detailed>
    </eainfo>
    <mdDateSt Sync="TRUE">20231129</mdDateSt>
    <Binary>
        <Thumbnail>
            <Data EsriPropertyType="PictureX">iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO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</Data>
        </Thumbnail>
    </Binary>
</metadata>