Resultados totales (Incluyendo duplicados): 54
Encontrada(s) 6 página(s)
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285500
Dataset. 2022

LONG-TERM MONITORING OF MACROINVERTEBRATES (ABUNDANCE AND DISTRIBUTION) IN DOÑANA WETLANDS 2004-2019

  • Bravo, Miguel A.
  • Román, Isidro
  • Andreu, Ana C.
  • Arribas, Rosa
  • Márquez-Ferrando, Rocío
  • Díaz-Delgado, Ricardo
  • Bustamante, Javier
Dataset are structured following well-established data formats. Three files are provided. The first file (Don_macroinv_ev_20221222) contains the information of each event (eventID, event date, geographical coordinates, sample effort, etc…); the second file (Don_macroinv_occ_20221222) contains the information of the occurrences of individuals recorded in each station and its taxonomic classification; and the third file (Don_macroinv_mof_20221222) provide information of biometric variable (weithg) of macroinvertebrates samples recorded in each occurrence., The monitoring of the macroinvertebrates community in Doñana wetlands was initiated in 2004 as part of the Monitoring Program of Natural Resources and Processes. The aim was to obtain a temporal and continuous series of data in the abundance and distribution of macroinvertebrates species to analyze the evolution of their numbers and estimates biodiversity values. Data were recorded annually between 2004-2019 by more than 2 members of the monitoring team which performed samplings in different locations twice per year in winter-spring and summer seasons when the study sites are flooded. The macroinvertebrates were sampled at the 139 stations classified according to their location (on either aeolian sands or marshland). Funnel traps were used as a sampling method. Between 5-9 funnel traps were randomly distributed (until 50 cm of depth) in each location, depending of the flooded area and depth. The traps were left for 24 hours and emptied the content into white sorting pans. Individuals were counted and identified until the maximun taxonomic level in the field and realease. During samplings, it was identified 65 families. The most abundances were Notonectidae and Corixidae. Data recorded during the surveys included species identification, number of individuals, sex and life stage (pupa, larvae, juvenile, adult) of the organisms when possible, as well as the time and georreferenced data of the observation. Between 2004-2007 data was registered in Excel file and since 2008 data was recorded in CyberTracker sequence). The protocol used has been supervised by researchers and the data have been validated by the members who performed the sampling., We acknowledge financial support from National Parks Autonomous Agency (OAPN) between 2002-2007; Singular Scientific and Technical Infrastructures from the Spanish Science and Innovation Ministry (ICTS-MICINN); Ministry of Agriculture, Livestock, Fisheries and Sustainable Development from the Regional Government of Andalusia (CAGPDES-JA) since 2007; and Doñana Biological Station from the Spanish National Research Council (EBD-CSIC) since all the study period (2005)., 1. Don_macroinv_ev_20221222: eventID, intitutionCode, datasetName, eventDate, year, month, day, continent, country, stateProvince, location, localityID, locality, sampleSizeUnit, sampleSizeEffort, DynamicPropiertiesEvent, eventRemarks, recordedBy.-- 2. Don_macroinv_occ_20221222: eventID, occurrenceID, basisOfRecord, individualCount, sex, lifeStage, kingdom, phylum, order, family, genus, specificEpithet, scientificName.-- 3. Don_macroinv_mof_20221222: ocurrenceID, measurementID, measurementValue, measurementUnit, measurementType, measurementAccuracy, measurementMethod., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/285500, https://doi.org/10.20350/digitalCSIC/14882
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285500
HANDLE: http://hdl.handle.net/10261/285500, https://doi.org/10.20350/digitalCSIC/14882
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285500
PMID: http://hdl.handle.net/10261/285500, https://doi.org/10.20350/digitalCSIC/14882
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285500
Ver en: http://hdl.handle.net/10261/285500, https://doi.org/10.20350/digitalCSIC/14882
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285500

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285505
Dataset. 2022

LONG-TERM MONITORING OF FISH (ABUNDANCE AND DISTRIBUTION) IN DOÑANA WETLANDS 2004-2019

  • Bravo, Miguel A.
  • Román, Isidro
  • Andreu, Ana C.
  • Arribas, Rosa
  • Márquez-Ferrando, Rocío
  • Díaz-Delgado, Ricardo
  • Bustamante, Javier
Dataset are structured following well-established data formats. Three files are provided. The first file (Don_fish_ev_20221222) contains the information of each event (eventID, event date, geographical coordinates, sample effort, etc…); the second file (Don_fish_occ_20221222) contains the information of the occurrences of fish species recorded in each station, taxonomic classification; and the third file (Don_fish_mof_20221222) provide information of the biometric variable (weight) of fish sample in each occurrence., The monitoring of the fish community in Doñana wetlands was initiated in 2004 as part of the Monitoring Program of Natural Resources and Processes. The aim was to obtain a temporal and continuous series of data in the abundance and distribution of fish species to analyze the evolution of their numbers and estimates biodiversity values. Data were recorded annually between 2004-2019 by more than 2 members of the monitoring team which performed samplings in different locations twice per year in winter-spring and summer seasons when the study sites are flooded. The fishes were sampled at the 139 stations classified according to their location (on either aeolian sands or marshland). Funnel traps were used as a sampling method. Between 5-9 funnel traps were randomly distributed (until 50 cm of depth) in each location, depending of the flooded area and depth. The traps were left for 24 hours and emptied the content into white sorting pans. Individuals were counted and identified until the maximun taxonomic level in the field and realease. During samplings, it was identified 15 families. The most abundances were Poecilidae and Cyprinidae. Data recorded during the surveys included species identification, number of individuals, sex and life stage (pupa, larvae, inmature, mature) of the organisms when possible, as well as the time and georreferenced data of the observation. Between 2004-2007 data was registered in Excel file and since 2008 data was recorded in CyberTracker sequence). The protocol used has been supervised by researchers and the data have been validated by the members who performed the sampling., We acknowledge financial support from National Parks Autonomous Agency (OAPN) between 2002-2007; Singular Scientific and Technical Infrastructures from the Spanish Science and Innovation Ministry (ICTS-MICINN); Ministry of Agriculture, Livestock, Fisheries and Sustainable Development from the Regional Government of Andalusia (CAGPDES-JA) since 2007; and Doñana Biological Station from the Spanish National Research Council (EBD-CSIC) since all the study period (2005)., 1. Don_fish_ev_20221222: eventID, intitutionCode, institutionID, datasetName, eventDate, year, month, day, country, stateProvince, location, localityID, locality, decimalLatitude, decimalLongitude, habitat, sampleSizeUnit, sampleSizeEffort, DynamicPropiertiesEvent, eventRemarks, recordeBy.-- 2. Don_fish_occ_20221222: eventID, occurrenceID, individualCount, sex, lifeStage, kingdom, phylum, order, family, genus, specificEpithet, scientificName.-- 3. Don_fish_mof_20221222: OccurrenceID, measurementID, measurementType, measurementValue, measurementUnit, measurementMethod., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/285505, https://doi.org/10.20350/digitalCSIC/14883
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285505
HANDLE: http://hdl.handle.net/10261/285505, https://doi.org/10.20350/digitalCSIC/14883
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285505
PMID: http://hdl.handle.net/10261/285505, https://doi.org/10.20350/digitalCSIC/14883
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285505
Ver en: http://hdl.handle.net/10261/285505, https://doi.org/10.20350/digitalCSIC/14883
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285505

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285756
Dataset. 2019

WATER TURBIDITY MASKS DOÑANA 1984/2019

  • Díaz-Delgado, Ricardo
  • Afán, Isabel
  • Aragonés, David
  • García, Diego
  • Bustamante, Javier
Time Series water turbidity derived from Landsat TM, ETM+ & OLI in the Path 202 Row 34 (Doñana). Also, the product and its metadata are freely available to consult or downloaded in the LAST-EBD Cartography Server: http://mercurio.ebd.csic.es/imgs/ Teh methodology is described in the paper: Empirical models to estimate water turbidity from reflectance data from TM or ETM+ Landsat sensors in shallow wetlands such as Doñana marshes. See the reference: Bustamante, J. et al. 2009. Predictive models of turbidity and water depth in the Doñana marshes using Landsat TM and ETM+ images. Journal of Environmental Management. 90:2219-2225.https://doi.org/10.1016/j.jenvman.2007.08.021, European Commission: ECOPOTENTIAL - ECOPOTENTIAL: IMPROVING FUTURE ECOSYSTEM BENEFITS THROUGH EARTH OBSERVATIONS (641762), Peer reviewed

Proyecto: EC/H2020/641762
DOI: http://hdl.handle.net/10261/285756
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285756
HANDLE: http://hdl.handle.net/10261/285756
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285756
PMID: http://hdl.handle.net/10261/285756
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285756
Ver en: http://hdl.handle.net/10261/285756
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285756

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285758
Dataset. 2019

NDVIS DOÑANA 1984/2019

  • Díaz-Delgado, Ricardo
  • Afán, Isabel
  • Aragonés, David
  • García, Diego
  • Bustamante, Javier
Time Series of NDVI derived from Landsat TM, ETM+ & OLI in the Path 202 Row 34 (Doñana). Also, the product and its metadata are freely available to consult or downloaded in the LAST-EBD Cartography Server: http://mercurio.ebd.csic.es/imgs/, European Commission: ECOPOTENTIAL - ECOPOTENTIAL: IMPROVING FUTURE ECOSYSTEM BENEFITS THROUGH EARTH OBSERVATIONS (641762), Peer reviewed

Proyecto: EC/H2020/641762
DOI: http://hdl.handle.net/10261/285758
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285758
HANDLE: http://hdl.handle.net/10261/285758
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285758
PMID: http://hdl.handle.net/10261/285758
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285758
Ver en: http://hdl.handle.net/10261/285758
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285758

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285759
Dataset. 2019

HYDROPERIOD DOÑANA 1974/2019

  • Díaz-Delgado, Ricardo
  • Afán, Isabel
  • Aragonés, David
  • García, Diego
  • Bustamante, Javier
Time Series of annual Hydroperiods derived from Landsat MSS, TM, ETM+ & OLI in the Path 202 Row 34 (Doñana) cover the period 1974-2018., European Commission: ECOPOTENTIAL - ECOPOTENTIAL: IMPROVING FUTURE ECOSYSTEM BENEFITS THROUGH EARTH OBSERVATIONS (641762), Peer reviewed

Proyecto: EC/H2020/641762
DOI: http://hdl.handle.net/10261/285759
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285759
HANDLE: http://hdl.handle.net/10261/285759
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285759
PMID: http://hdl.handle.net/10261/285759
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285759
Ver en: http://hdl.handle.net/10261/285759
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285759

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285761
Dataset. 2019

FLOOD MASKS DOÑANA 1984/2019

  • Díaz-Delgado, Ricardo
  • Afán, Isabel
  • Aragonés, David
  • García, Diego
  • Bustamante, Javier
Time Series of flooded areas derived from Landsat TM, ETM+ & OLI in the Path 202 Row 34 (Doñana). Also, these products and its metadata are freely available to consult or downloaded in the LAST-EBD Cartography Server: http://mercurio.ebd.csic.es/imgs/ Methodology is described in this paper: Remote Sensing 8(9):775 · September 2016. DOI: 10.3390/rs8090775, European Commission: ECOPOTENTIAL - ECOPOTENTIAL: IMPROVING FUTURE ECOSYSTEM BENEFITS THROUGH EARTH OBSERVATIONS (641762), Peer reviewed

Proyecto: EC/H2020/641762
DOI: http://hdl.handle.net/10261/285761
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285761
HANDLE: http://hdl.handle.net/10261/285761
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285761
PMID: http://hdl.handle.net/10261/285761
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285761
Ver en: http://hdl.handle.net/10261/285761
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285761

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285773
Dataset. 2022

DATA FROM PATI CIENTIFIC 2022-04-27 TD-5

  • Carrasco, Oriol
  • Bardají, Raúl
  • Vallès Casanova, Ignasi Berenguer
  • Pelegrí, Josep Lluís
  • Hoareau, Nina
  • Salvador, Joaquín
  • Simon, Carine
  • Rodero García, Carlos
  • Piera, Jaume
  • Ortigosa Barragán, Inma
  • Mateu, Jordi
  • Castells-Sanabra, Marcel·la
  • Barberan, Victor
  • González Fernández, Óscar
  • Puigdefàbregas, Joan
  • Yannoukakou, Iphygenia
  • Carretero, Igor
  • Verger, Elisabet
Sea temperature vs depth measured by the Pati Cientific at Somorrostro, Barcelona, on 2022-04-27., BIT Habitat, Barcelona Science Plan 2019, MONOCLE and EMSO - Laboratorios Submarinos Profundo, Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/285773
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285773
HANDLE: http://hdl.handle.net/10261/285773
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285773
PMID: http://hdl.handle.net/10261/285773
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285773
Ver en: http://hdl.handle.net/10261/285773
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285773

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285779
Dataset. 2022

DATA FROM PATI CIENTIFIC 2022-03-10 TD-3

  • Carrasco, Oriol
  • Bardají, Raúl
  • Vallès Casanova, Ignasi Berenguer
  • Pelegrí, Josep Lluís
  • Hoareau, Nina
  • Salvador, Joaquín
  • Simon, Carine
  • Rodero García, Carlos
  • Piera, Jaume
  • Ortigosa Barragán, Inma
  • Mateu, Jordi
  • Castells-Sanabra, Marcel·la
  • Barberan, Victor
  • González Fernández, Óscar
  • Puigdefàbregas, Joan
  • Yannoukakou, Iphygenia
  • Carretero, Igor
  • Verger, Elisabet
Sea temperature vs depth measured by the Pati Cientific at Somorrostro, Barcelona, on 2022-03-10., BIT Habitat, Barcelona Science Plan 2019, MONOCLE and EMSO - Laboratorios Submarinos Profundo, Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/285779
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285779
HANDLE: http://hdl.handle.net/10261/285779
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285779
PMID: http://hdl.handle.net/10261/285779
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285779
Ver en: http://hdl.handle.net/10261/285779
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285779

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285816
Dataset. 2022

DATA FROM PATI CIENTIFIC 2022-05-23 TD-3

  • Carrasco, Oriol
  • Bardají, Raúl
  • Vallès Casanova, Ignasi Berenguer
  • Pelegrí, Josep Lluís
  • Hoareau, Nina
  • Salvador, Joaquín
  • Simon, Carine
  • Rodero García, Carlos
  • Piera, Jaume
  • Ortigosa Barragán, Inma
  • Mateu, Jordi
  • Castells-Sanabra, Marcel·la
  • Barberan, Victor
  • González Fernández, Óscar
  • Puigdefàbregas, Joan
  • Yannoukakou, Iphygenia
  • Carretero, Igor
  • Verger, Elisabet
Sea temperature vs depth measured by the Pati Cientific at Somorrostro, Barcelona, on 2022-05-23., BIT Habitat, Barcelona Science Plan 2019, MONOCLE and EMSO - Laboratorios Submarinos Profundo, Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/285816
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285816
HANDLE: http://hdl.handle.net/10261/285816
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285816
PMID: http://hdl.handle.net/10261/285816
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285816
Ver en: http://hdl.handle.net/10261/285816
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285816

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285821
Dataset. 2022

DATA FROM PATI CIENTIFIC 2022-04-19 TD-5

  • Carrasco, Oriol
  • Bardají, Raúl
  • Vallès Casanova, Ignasi Berenguer
  • Pelegrí, Josep Lluís
  • Hoareau, Nina
  • Salvador, Joaquín
  • Simon, Carine
  • Rodero García, Carlos
  • Piera, Jaume
  • Ortigosa Barragán, Inma
  • Mateu, Jordi
  • Castells-Sanabra, Marcel·la
  • Barberan, Victor
  • González Fernández, Óscar
  • Puigdefàbregas, Joan
  • Yannoukakou, Iphygenia
  • Carretero, Igor
  • Verger, Elisabet
Sea temperature vs depth measured by the Pati Cientific at Somorrostro, Barcelona, on 2022-04-19., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/285821
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285821
HANDLE: http://hdl.handle.net/10261/285821
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285821
PMID: http://hdl.handle.net/10261/285821
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285821
Ver en: http://hdl.handle.net/10261/285821
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/285821

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