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99 results for “Anguilla anguilla”
Fig. 2 in Metazoan Parasites And Health State Of European Eel, Anguilla Anguilla (Anguilliformes, Anguillidae From Tonga Lake And El Mellah Lagoon In The Northeast Of Algeria
Fig. 2. Distribution of the swimbladder degenerative index (SDI) in eels from the two localities.
Fig. 1 in Metazoan Parasites And Health State Of European Eel, Anguilla Anguilla (Anguilliformes, Anguillidae From Tonga Lake And El Mellah Lagoon In The Northeast Of Algeria
Fig. 1. Northeast of Algeria; stars show localization of sampling sites of eels.
Lack of spatial and temporal genetic structure of Japanese eel (Anguilla japonica) populations
Japanese eel (Anguilla japonica) is an important food source in East Asia whose population has dramatically declined since the 1970s. Despite past analysis with DNA sequencing, microsatellite and isozyme methods, management decisions remain hampered by contradictory findings. For example, it remains unresolved whether Japanese eels are a single panmictic population or whether they harbor significant substructure. Accurate assessment of population genetic substructure, both spatial and temporal, is essential for determining the relevant number of distinct management units appropriate for this species. In the present study, we assayed genetic variation genome-wide using Restriction Site Associated DNA Sequencing (RAD-seq) technology to analyze the population genetic structure of Japanese eels. For analysis of temporal isolation, five "cohort" samples were collected yearly from 2005 to 2009 in the Yangtze River Estuary. For analysis of spatial structure, five "arrival wave" samples were collected in China in 2009, and two arrival wave samples were collected in Japan in 2001. In each cohort of each arrival wave, five individuals were collected for a total of 55 eels sampled. In total, 214,210 loci were identified from these individuals, 106,652 of which satisfied quality checks and were retained for further analysis. There was relatively little population differentiation between arrival waves and cohorts collected either at different locations during the same year (Fst = 0.077) or at the same location collected over subsequent years (Fst = 0.082), and locations displayed no consistent isolation-by-distance.
Fig. 1 in Microhabitat Preference And Relationships B E T W E E N M E Ta Z O A N Pa R A S I T E S O N T H E G I L L A P Pa R At U S O F T H E E U R O P E A N E E L (A N G U I L L A Anguilla) From Freshwaters Of Latvia
Fig. 1. The gill apparatus and sectors of gill arch.
Figure 2 in The diversity and distributions of the beetles (Insecta: Coleoptera) of the northern Leeward Islands, Lesser Antilles (Anguilla, Antigua, Barbuda, Nevis, Saba, St. Barthélemy, St. Eustatius, St. Kitts, and St. Martin-St. Maarten
Figure 2. Principal islands of the northern Leeward Islands.
Reassessing a Holocene extinction: multiple lines of evidence do not support the historical presence and recent extirpation of a protected anole on the island of Anguilla
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Lack of spatial and temporal genetic structure of Japanese eel (Anguilla japonica) populations
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Data from: Is the continental life of the European eel Anguilla anguilla affected by the parasitic invader Anguillicoloides crassus?
Quantifying the fitness cost that parasites impose on wild hosts is a challenging task because the epidemiological history of field-sampled hosts is often unknown. In this study we used an internal marker of the parasite pressure on individual hosts to evaluate the costs of parasitism with respect to host body condition, size increase and reproductive potential of field-collected animals for which we also determined individual age. In our investigated system, the European eel Anguilla anguilla and the parasitic invader Anguillicoloides crassus, high virulence and severe impacts are expected because the host lacks an adaptive immune response. We demonstrated a nonlinear relationship between the severity of damage to the affected organ (i.e. the swimbladder, our internal marker) and parasite abundance and biomass, thus showing that the use of classical epidemiological parameters was not relevant here. Surprisingly, we found that the most severely affected eels (with damaged swimbladder) had greater body length and mass (+11% and +41%, respectively) than unaffected eels of same age. We discuss mechanisms that could explain this finding and other counter-intuitive results in this host–parasite system, and highlight the likely importance of host panmixia in generating great inter-individual variability in growth potential and infection risk. Under that scenario, the most active foragers would not only have the greatest size increase, but also the highest probability of becoming repeatedly infected –via trophic parasite transmission– during their continental life.
Data from: Genomic footprints of speciation in Atlantic eels (Anguilla anguilla and A. rostrata)
The importance of speciation-with-gene-flow scenarios is increasingly appreciated. However, the specific processes and the resulting genomic footprints of selection are subject to much discussion. We studied the genomics of speciation between the two panmictic, sympatrically spawning sister-species; European (Anguilla anguilla) and American eel (A. rostrata). Divergence is assumed to have initiated more than 3 million years ago, and although low gene flow still occurs strong postzygotic barriers are present. Restriction-site Associated DNA (RAD) sequencing identified 328,300 SNPs for subsequent analysis. However, despite the presence of 3,757 strongly differentiated SNPs (FST > 0.8), sliding window analyses of FST showed no larger genomic regions (i.e. hundreds of thousands to millions of bases) of elevated differentiation. Overall FST was 0.041 and linkage disequilibrium was virtually absent for SNPs separated by more than 1000 bp. We suggest this to reflect a case of genomic hitchhiking, where multiple regions are under directional selection between the species. However, low but biologically significant gene flow and high effective population sizes leading to very low genetic drift preclude accumulation of strong background differentiation. Genes containing candidate SNPs for positive selection showed significant enrichment for gene ontology (GO) terms relating to developmental processes and phosphorylation, which seems consistent with assumptions that differences in larval phase duration and migratory distances underlie speciation. Most SNPs under putative selection were found outside coding regions, lending support to emerging views that non-coding regions may be more functionally important than previously assumed. In total, the results demonstrate the necessity of interpreting genomic footprints of selection in the context of demographic parameters and life-history features of the studied species.
Data from: Population genetics of the American eel (Anguilla rostrata): FST = 0 and NAO effects on demographic fluctuations of a panmictic species
We performed population genetic analyses on the American eel (Anguilla rostrata) with three main objectives. First, we conducted the most comprehensive analysis of neutral genetic population structure to date in order to revisit the null hypothesis of panmixia in this species. Second, we used this data to provide the first estimates of contemporary effective population size (Ne) and to document temporal variation in effective number of breeders (Nb) in American eel. Third, we tested for statistical associations between temporal variation in the North Atlantic Oscillation (NAO) index, the effective number of breeders and two indices of recruit abundance. A total of 2142 eels from 32 sampling locations were genotyped with 18 microsatellite loci. All measures of differentiation were essentially zero, and no evidence for significant spatial or temporal genetic differentiation was found. The panmixia hypothesis should thus be accepted for this species. Nb estimates varied by a factor of 23 among 12 cohorts, from 473 to 10 999. The effective population size Ne was estimated to be around 22 382. This study also showed that genetically based demographic indices, namely Nb and allelic richness (Ar), can be used as surrogates for the abundance of breeders and recruits, which were both shown to be positively influenced by variation during high (positive) NAO phases. Thus, long-term genetic monitoring of American glass eels at several sites along the North American Atlantic coast would represent a powerful and efficient complement to census monitoring to track demographic fluctuations and better understand their causes.
Speciation history of European (Anguilla anguilla) and American eel (A. rostrata), analyzed using genomic data
<p>Speciation in the ocean could differ from terrestrial environments due to fewer barriers to gene flow. Hence, sympatric speciation might be common, with American and European eel being candidates for exemplifying this. They show disjunct continental distributions on both sides of the Atlantic, but spawn in overlapping regions of the Sargasso Sea from where juveniles are advected to North American, European and North African coasts. Hybridization and introgression is known to occur, with hybrids almost exclusively observed in Iceland. Different speciation scenarios have been suggested, involving either vicariance or sympatric ecological speciation. Using RAD sequencing and whole-genome sequencing data from parental species and F1 hybrids, we analyzed speciation history based on the Joint Allele Frequency Spectrum (JAFS) and PSMC (pairwise sequentially Markovian coalescent) plot. JAFS supported a model involving a split without gene flow 150,000 – 160,000 generations ago, followed by secondary contact 87,000 – 92,000 generations ago, with 64% of the genome experiencing restricted gene flow. This supports vicariance rather than sympatric speciation, likely associated with Pleistocene Glaciation cycles and ocean current changes. Whole genome PSMC analysis of F1 hybrids from Iceland suggested divergence 200,000 generations ago and indicated subsequent gene flow rather than strict isolation. Finally, simulations showed that results from both approaches (JAFS and PSMC) were congruent. Hence, there is strong evidence against sympatric speciation in North Atlantic eels. These results reiterate the need for careful consideration of cases of possible sympatric speciation, as even in seemingly barrier-free oceanic environments palaeoceanographic factors may have promoted vicariance and allopatric speciation.</p>
FIGURES 14–16. Stegodexamine anguillae. 14 in Faunal survey and identification key for the trematodes (Platyhelminthes: Digenea) infecting Potamopyrgus antipodarum (Gastropoda: Hydrobiidae) as first intermediate host
FIGURES 14–16. Stegodexamine anguillae. 14, Redia, EtOH-fixed and acetocarmine-stained. Scale bar = 100. 15, Cercaria, live. Scale bar = 100. Numerical scale division = 10. 16, Close-up of live cercaria body to better indicate the four pairs of penetration glands. Scale bar = 100. Numerical scale division = 5.
Subspecies and Distribution. M.p.plethodonG.S.Miller,1900—Barbados. M. p. luciae G. S. Miller, 1902 — Lesser Antilles, from Anguilla to Saint Vincent Is. in Phyllostomidae
Subspecies and Distribution. M.p.plethodonG.S.Miller,1900—Barbados. M. p. luciae G. S. Miller, 1902 — Lesser Antilles, from Anguilla to Saint Vincent Is.
Atlas of European Eel Distribution (Anguilla anguilla) in Portugal, Spain and France
<p><strong>DESCRIPTION</strong></p> <p><strong>----------------</strong></p> <p>VERSIONS</p> <p>version1.0.1 fixes problem with functions</p> <p>version1.0.2 added table dbeel_rivers.rn_rivermouth with GEREM basin, distance to Gibraltar and link to CCM.</p> <p>version1.0.3 fixes problem with functions</p> <p>version1.0.4 adds views rn_rna and rn_rne to the database</p> <p> </p> <p>----------------</p> <p>The <a href="https://sudoang.eu/en/">SUDOANG</a> project aims at providing common tools to managers to support eel conservation in the SUDOE area (Spain, France and Portugal). <a href="https://sudoang.eu/fr/visuang/">VISUANG</a> is the SUDOANG Interactive Web Application that host all these tools . The application consists of an eel distribution atlas (GT1), assessments of mortalities caused by turbines and an atlas showing obstacles to migration<br> (GT2), estimates of recruitment and exploitation rate (GT3) and escapement (chosen as a target by the EC for the Eel Management Plans) (GT4). In addition, it includes an interactive map showing sampling results from the pilot basin network produced by GT6.</p> <p>The eel abundance for the eel atlas and escapement has been obtained using the Eel Density Analysis model (EDA, GT4's product). EDA extrapolates the abundance of eel in sampled river segments to other segments taking into account how the abundance, sex and size of the eels change depending on different parameters. Thus, EDA requires two main data sources: those related to the river<br> characteristics and those related to eel abundance and characteristics.</p> <p>However, in both cases, data availability was uneven in the SUDOE area. In addition, this information was dispersed among several managers and in different formats due to different sampling sources: Water Framework Directive (WFD), Community Framework for the Collection, Management and Use of Data in the Fisheries Sector (EUMAP), Eel Management Plans, research groups, scientific<br> papers and technical reports. Therefore, the first step towards having eel abundance estimations including the whole SUDOE area, was to have a joint river and eel database. In this report we will describe the database corresponding to the river’s characteristics in the SUDOE area and the eel abundances and their characteristics.</p> <p>In the case of rivers, two types of information has been collected: </p> <ul> <li><strong>River topology</strong> (RN table): a compilation of data on rivers and their topological and hydrographic characteristics in the three countries.</li> <li><strong>River attributes</strong> (RNA table): contains physical attributes that have fed the SUDOANG models.</li> </ul> <p>The estimation of eel abundance and characteristic (size, biomass, sex-ratio and silver) distribution at different scales (river segment, basin, Eel Management Unit (EMU), and country) in the SUDOE area obtained with the implementation of the EDA2.3 model has been compiled in the <strong>RNE table (eel predictions)</strong>.</p> <p><strong>CURRENT ACTIVE PROJECT</strong></p> <p>The project is currently active here : <a href="https://forgemia.inra.fr/pole-migrateurs/eda">gitlab forgemia</a></p> <p><strong>TECHNICAL DESCRIPTION TO BUILD THE POSTGRES DATABASE</strong></p> <p><strong>1. Build the database in postgres.</strong></p> <p>All tables are in ESPG:3035 (European LAEA). The format is postgreSQL database. You can download other formats (shapefiles, csv), here <a href="https://azti.sharepoint.com/sites/Proyectos/SUDOANG/Documentos%20compartidos/Forms/AllItems.aspx?id=%2Fsites%2FProyectos%2FSUDOANG%2FDocumentos%20compartidos%2FSUDOANG%20Database&p=true">SUDOANG gt1 database</a>.</p> <p>Initial command</p> <pre><code class="language-bash"># open a shell with command CMD # Move to the place where you have downloaded the file using the following command cd c:/path/to/my/folder # note psql must be accessible, in windows you can add the path to the postgres #bin folder, otherwise you need to add the full path to the postgres bin folder see link to instructions below createdb -U postgres eda2.3 psql -U postgres eda2.3 # this will open a command with # where you can launch the commands in the next box </code></pre> <p>Within the psql command</p> <pre><code class="language-sql"> create extension "postgis"; create extension "dblink"; create extension "ltree"; create extension "tablefunc"; create schema dbeel_rivers; create schema france; create schema spain; create schema portugal; -- type \q to quit the psql shell</code></pre> <p>Now the database is ready to receive the differents dumps. The dump file are large. You might not need the part including unit basins or waterbodies. All the tables except waterbodies and unit basins are described in the Atlas. You might need to understand what is inheritance in a database. <a href="https://www.postgresql.org/docs/12/tutorial-inheritance.html">https://www.postgresql.org/docs/12/tutorial-inheritance.html</a></p> <p><strong>2. RN (riversegments)</strong></p> <p>These layers contain the topology (see Atlas for detail)</p> <ul> <li>dbeel_rivers.rn</li> <li>france.rn</li> <li>spain.rn</li> <li>portugal.rn</li> </ul> <p>Columns (see Atlas)</p> <table> <tbody> <tr> <td>gid</td> </tr> <tr> <td>idsegment</td> </tr> <tr> <td>source</td> </tr> <tr> <td>target</td> </tr> <tr> <td>lengthm</td> </tr> <tr> <td>nextdownidsegment</td> </tr> <tr> <td>path</td> </tr> <tr> <td>isfrontier</td> </tr> <tr> <td>issource</td> </tr> <tr> <td>seaidsegment</td> </tr> <tr> <td>issea</td> </tr> <tr> <td>geom</td> </tr> <tr> <td>isendoreic</td> </tr> <tr> <td>isinternational</td> </tr> <tr> <td>country</td> </tr> </tbody> </table> <p> </p> <p>dbeel_rivers.rn_rivermouth</p> <table> <tbody> <tr> <td>seaidsegment</td> </tr> <tr> <td>geom (polygon)</td> </tr> <tr> <td>gerem_zone_3</td> </tr> <tr> <td>gerem_zone_4 (used in EDA)</td> </tr> <tr> <td>gerem_zone_5</td> </tr> <tr> <td>ccm_wso_id</td> </tr> <tr> <td>country</td> </tr> <tr> <td>emu_name_short</td> </tr> <tr> <td>geom_outlet (point)</td> </tr> <tr> <td>name_basin</td> </tr> <tr> <td>dist_from_gibraltar_km</td> </tr> <tr> <td>name_coast</td> </tr> <tr> <td>basin_name</td> </tr> </tbody> </table> <pre><code class="language-bash"># dbeel_rivers.rn ! mandatory => table at the international level from which # the other table inherit # even if you don't want to use other countries # (In many cases you should ... there are transboundary catchments) download this first. # the rn network must be restored firt ! #table rne and rna refer to it by foreign keys. pg_restore -U postgres -d eda2.3 "dbeel_rivers.rn.backup" #france pg_restore -U postgres -d eda2.3 "france.rn.backup" # spain pg_restore -U postgres -d eda2.3 "spain.rn.backup" # portugal pg_restore -U postgres -d eda2.3 "portugal.rn.backup" # rivermouth and basins, this file contains GEREM basins, distance to Gibraltar, the link to CCM id for each basin flowing to the sea. pg_restore -U postgres -d eda2.3 "dbeel_rivers.rn_rivermouth.backup" # with the schema you will probably want to be able to use the functions, but launch this only after # restoring rna in the next step psql -U postgres -d eda2.3 -f "function_dbeel_rivers.sql"</code></pre> <p><strong>3. RNA (Attributes)</strong></p> <p>This corresponds to tables</p> <ul> <li>dbeel_rivers.rna</li> <li>france.rna</li> <li>spain.rna</li> <li>portugal.rna</li> </ul> <p>Columns (See Atlas)</p> <table> <tbody> <tr> <td>idsegment</td> </tr> <tr> <td>altitudem</td> </tr> <tr> <td>distanceseam</td> </tr> <tr> <td>distancesourcem</td> </tr> <tr> <td>cumnbdam</td> </tr> <tr> <td>medianflowm3ps</td> </tr> <tr> <td>surfaceunitbvm2</td> </tr> <tr> <td>surfacebvm2</td> </tr> <tr> <td>strahler</td> </tr> <tr> <td>shreeve</td> </tr> <tr> <td>codesea</td> </tr> <tr> <td>name</td> </tr> <tr> <td>pfafriver</td> </tr> <tr> <td>pfafsegment</td> </tr> <tr> <td>basin</td> </tr> <tr> <td>riverwidthm</td> </tr> <tr> <td>temperature</td> </tr> <tr> <td>temperaturejan</td> </tr> <tr> <td>temperaturejul</td> </tr> <tr> <td>wettedsurfacem2</td> </tr> <tr> <td>wettedsurfaceotherm2</td> </tr> <tr> <td>lengthriverm</td> </tr> <tr> <td>emu</td> </tr> <tr> <td>cumheightdam</td> </tr> <tr> <td>riverwidthmsource</td> </tr> <tr> <td>slope</td> </tr> <tr> <td>dis_m3_pyr_riveratlas</td> </tr> <tr> <td>dis_m3_pmn_riveratlas</td> </tr> <tr> <td>dis_m3_pmx_riveratlas</td> </tr> <tr> <td>drought</td> </tr> <tr> <td>drought_type_calc</td> </tr> </tbody> </table> <p>Code :</p> <pre><code class="language-bash">pg_restore -U postgres -d eda2.3 "dbeel_rivers.rna.backup" pg_restore -U postgres -d eda2.3 "france.rna.backup" pg_restore -U postgres -d eda2.3 "spain.rna.backup" pg_restore -U postgres -d eda2.3 "portugal.rna.backup" </code></pre> <p><strong>4. RNE (eel predictions)</strong></p> <p>These layers contain eel data (see Atlas for detail)</p> <ul> <li>dbeel_rivers.rne</li> <li>france.rne</li> <li>spain.rne</li> <li>portugal.rne</li> </ul> <p>Columns (see Atlas)</p> <table> <tbody> <tr> <td>idsegment</td> </tr> <tr> <td>surfaceunitbvm2</td> </tr> <tr> <td>surfacebvm2</td> </tr> <tr> <td>delta</td> </tr> <tr> <td>gamma</td> </tr> <tr> <td>density</td> </tr> <tr> <td>neel</td> </tr> <tr> <td>beel</td> </tr> <tr> <td>peel150</td> </tr> <tr> <td>peel150300</td> </tr> <tr> <td>peel300450</td> </tr> <tr> <td>peel450600</td> </tr> <tr> <td>peel600750</td> </tr> <tr> <td>peel750</td> </tr> <tr> <td>nsilver</td> </tr> <tr> <td>bsilver</td> </tr> <tr> <td>psilver150300</td> </tr> <tr> <td>psilver300450</td> </tr> <tr> <td>psilver450600</td> </tr> <tr> <td>psilver600750</td> </tr> <tr> <td>psilver750</td> </tr> <tr> <td>psilver</td> </tr> <tr> <td>pmale150300</td> </tr> <tr> <td>pmale300450</td> </tr> <tr> <td>pmale450600</td> </tr> <tr> <td>pfemale300450</td> </tr> <tr> <td>pfemale450600</td> </tr> <tr> <td>pfemale600750</td> </tr> <tr> <td>pfemale750</td> </tr> <tr> <td>pmale</td> </tr> <tr> <td>pfemale</td> </tr> <tr> <td>sex_ratio</td> </tr> <tr> <td>cnfemale300450</td> </tr> <tr> <td>cnfemale450600</td> </tr> <tr> <td>cnfemale600750</td> </tr> <tr> <td>cnfemale750</td> </tr> <tr> <td>cnmale150300</td> </tr> <tr> <td>cnmale300450</td> </tr> <tr> <td>cnmale450600</td> </tr> <tr> <td>cnsilver150300</td> </tr> <tr> <td>cnsilver300450</td> </tr> <tr> <td>cnsilver450600</td> </tr> <tr> <td>cnsilver600750</td> </tr> <tr> <td>cnsilver750</td> </tr> <tr> <td>cnsilver</td> </tr> <tr> <td>delta_tr</td> </tr> <tr> <td>gamma_tr</td> </tr> <tr> <td>type_fit_delta_tr</td> </tr> <tr> <td>type_fit_gamma_tr</td> </tr> <tr> <td>density_tr</td> </tr> <tr> <td>density_pmax_tr</td> </tr> <tr> <td>neel_pmax_tr</td> </tr> <tr> <td>nsilver_pmax_tr</td> </tr> <tr> <td>density_wd</td> </tr> <tr> <td>neel_wd</td> </tr> <tr> <td>beel_wd</td> </tr> <tr> <td>nsilver_wd</td> </tr> <tr> <td>bsilver_wd</td> </tr> <tr> <td>sector_tr</td> </tr> <tr> <td>year_tr</td> </tr> <tr> <td>is_current_distribution_area</td> </tr> <tr> <td>is_pristine_distribution_area_1985</td> </tr> </tbody> </table> <p>Code for restauration</p> <pre><code class="language-bash">pg_restore -U postgres -d eda2.3 "dbeel_rivers.rne.backup" pg_restore -U postgres -d eda2.3 "france.rne.backup" pg_restore -U postgres -d eda2.3 "spain.rne.backup" pg_restore -U postgres -d eda2.3 "portugal.rne.backup"</code></pre> <p><strong>5. Unit basins</strong></p> <p>Units basins are not described in the Altas. They correspond to the following tables :</p> <ul> <li>dbeel_rivers.basinunit_bu</li> <li>france.basinunit_bu</li> <li>spain.basinunit_bu</li> <li>portugal.basinunit_bu</li> <li>france.basinunitout_buo</li> <li>spain.basinunitout_buo</li> <li>portugal.basinunitout_buo</li> </ul> <p>The unit basins is the simple basin that surrounds a segment. It correspond to the topography unit from which unit segment have been calculated. ESPG 3035. Tables bu_unitbv, and bu_unitbvout inherit from dbeel_rivers.unit_bv. The first table intersects with a segment, the second table does not, it corresponds to basin polygons which do not have a riversegment.</p> <p>Source :</p> <ul> <li>Portugal</li> </ul> <p><a href="https://sniambgeoviewer.apambiente.pt/Geodocs/gml/inspire/HY_PhysicalWaters_DrainageBasinGeoCod.zip">https://sniambgeoviewer.apambiente.pt/Geodocs/gml/inspire/HY_PhysicalWaters_DrainageBasinGeoCod.zip</a><a href="https://sniambgeoviewer.apambiente.pt/Geodocs/gml/inspire/HY_PhysicalWaters_DrainageBasinGeoCod.zip">https://sniambgeoviewer.apambiente.pt/Geodocs/gml/inspire/HY_PhysicalWaters_DrainageBasinGeoCod.zip</a></p> <ul> <li>France</li> </ul> <p>In france unit bv corresponds to the RHT (Pella et al., 2012)</p> <ul> <li>Spain</li> </ul> <p><a href="http://www.mapama.gob.es/ide/metadatos/index.html?srv=metadata.show&uuid=898f0ff8-f06c-4c14-88f7-43ea90e48233">http://www.mapama.gob.es/ide/metadatos/index.html?srv=metadata.show&uuid=898f0ff8-f06c-4c14-88f7-43ea90e48233</a></p> <pre><code class="language-bash">pg_restore -U postgres -d eda2.3 'dbeel_rivers.basinunit_bu.backup' # france pg_restore -U postgres -d eda2.3 "france.basinunit_bu.backup" pg_restore -U postgres -d eda2.3 "france.basinunitout_buo.backup" # spain pg_restore -U postgres -d eda2.3 "spain.basinunit_bu.backup" pg_restore -U postgres -d eda2.3 "spain.basinunit_bu.backup" # portugal pg_restore -U postgres -d eda2.3 "portugal.basinunit_bu.backup" pg_restore -U postgres -d eda2.3 "portugal.basinunitout_buo.backup" </code></pre> <p><strong>6- Waterbodies</strong></p> <p>In these tables we have have kept the structure from the source table in WISE or from the bd_topage.</p> <ul> <li>dbeel_rivers.waterbody_unitbv </li> <li>portugal.waterbody_unitbv</li> <li>france.waterbody_unitbv</li> <li>spain.waterbody_unitbv</li> </ul> <p>In France, corresponds to the hydrographic surface from <a href="https://bdtopage.eaufrance.fr/page/documents-ressources">bd_topage</a>. <br> <br> <a href="https://bdtopage.eaufrance.fr/page/documents-ressources">https://bdtopage.eaufrance.fr/page/documents-ressources</a></p> <p>In spain it corresponds to . <a href="http://www.mapama.gob.es/ide/metadatos/index.html?srv=metadata.show&uuid=b3114bb6-4a0c-4bf2-90e2-240b9de82ad0">Cuencas hidrográficas de los principales ríos definidos en el artículo 3 de la Directiva Marco del Agua (DMA)</a>, in Portugal to <a href="https://sniambgeoviewer.apambiente.pt/Geodocs/gml/inspire/HY_PhysicalWaters_DrainageBasinMAgua.zip">HY_PhysicalWaters_DrainageBasinMAgua</a>.</p> <p> </p> <pre><code class="language-bash">pg_restore -U postgres -d eda2.3 "dbeel_rivers.waterbody_unitbv.backup" pg_restore -U postgres -d eda2.3 "portugal.waterbody_unitbv.backup" pg_restore -U postgres -d eda2.3 "france.waterbody_unitbv.backup" </code></pre> <p> </p> <p><br> 7- functions</p> <p>The functions can be found in dbeel_rivers_functions.sql you can read the examples there and description of the functions, here is a quick example showing the functionalities.</p> <p>dbeel_rivers.get_path provides the path between two idsegments of the same basin :</p> <pre><code class="language-sql">select dbeel_rivers.get_path (113670,114115,'FR') -- FR113618.FR114065.FR114053.FR114042</code></pre> <p>dbeel_rivers.get_distance calculates the distance between two rivers segments (including the distance of the idsegments themselves)</p> <pre><code class="language-sql">select dbeel_rivers.get_distance (113670,114115,'FR'); --12669</code></pre> <p>dbeel_rivers.upstream_segments_rn(TEXT) takes an upstream segment and returns a vector of idsegments attention this function is slower than national counterparts, check in schema spain portugal and france for quicker functions. It is use for instance to calculate all eels coming from the upstream basin.</p> <pre><code class="language-sql">SELECT dbeel_rivers.upstream_segments_rn('FR114042'); /* FR114042 FR114053 FR113982 FR114034 ... */</code></pre> <p>dbeel_rivers.upstream_segments_rn_sti(TEXT) takes an upstream segment and a TABLE with idsegment, target, source, this in more convenient for later use of routing functions (like get path) which require source and target<br> dbeel_rivers.downstream_segments_rn(TEXT) takes a segment and returns the path to the sea.</p> <pre><code class="language-sql">SELECT dbeel_rivers.downstream_segments_rn('SP227795');</code></pre> <p><strong>7- READ MORE </strong></p> <ul> <li>Eel data (Anguilla anguilla) and associated environment variables used to fit the EDA model in the SUDOE area (SUDOANG project) (10.5281/zenodo.7964967) </li> <li>Electrofishing data for eel in Spain and Portugal (SUDOANG project) (10.5281/zenodo.8207785)</li> <li>Cumulated dam impact in France, Spain and Portugal (SUDOANG project) (10.5281/zenodo.7825552)</li> </ul> <p> </p>
Data from: Within-population structure highlighted by differential introgression across semipermeable barriers to gene flow in Anguilla marmorata
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Data from: Is the continental life of the European eel Anguilla anguilla affected by the parasitic invader Anguillicoloides crassus?
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Data from: Population genetics of the American eel (Anguilla rostrata): FST = 0 and NAO effects on demographic fluctuations of a panmictic species
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Data from: Genomic footprints of speciation in Atlantic eels (Anguilla anguilla and A. rostrata)
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Data from: RAD-sequencing highlights polygenic discrimination of habitat ecotypes in the panmictic American eel (Anguilla rostrata)
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Data from: Draft genome of the American eel (Anguilla rostrata)
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