http://lod.bco-dmo.org/id/dataset/679946
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2017-02-01
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Path analysis, run in Stata v. 11.1, for direct/indirect effects of upwelling on seabirds; data were collected at Dassen and Robben Islands, Malgas Island and in Lamberts Bay, South Africa
2017-02-01
publication
2017-02-01
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2019-08-06
publication
https://doi.org/10.1575/1912/bco-dmo.679946.1
Bryan Black
University of Texas at Austin
principalInvestigator
Steven Bograd
National Oceanic and Atmospheric Administration - Southwest Fisheries Science Center
principalInvestigator
Marisol Garcia Reyes
Farallon Institute for Advanced Ecosystem Research
principalInvestigator
William Sydeman
Farallon Institute for Advanced Ecosystem Research
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Black, B., Bograd, S., Garcia Reyes, M., Sydeman, W. (2017) Path analysis, run in Stata v. 11.1, for direct/indirect effects of upwelling on seabirds; data were collected at Dassen and Robben Islands, Malgas Island and in Lamberts Bay, South Africa. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2017-02-01 [if applicable, indicate subset used]. doi:10.1575/1912/bco-dmo.679946.1 [access date]
Path analysis for direct/indirect effects of upwelling on seabirds Dataset Description: <p>These data include total anchovy and sardine biomass west and southeast of Cape Agulhas (sampled in November), and anchovy and sardine recruitment west of Cape Infanta (sampled in May).&nbsp;Seabird variables included % of the diet comprised of anchovy, % of the diet comprised of sardine, breeding success, and survival.&nbsp;</p>
<p>Benguela Current African Penguin -&nbsp;These data were collected at two seabird colonies: Dassen Island (-33.4205 lat, 18.0872 lon) and Robben Island (-33.8067, 18.371 long), South Africa.</p>
<p>Benguela Current Cape Gannett - These data were collected at two seabird colonies: Lamberts Bay (-32.0896 lat, 18.3026 lon) and Malgas Island (-33.0526, 17.9254 long), South Africa.</p> Methods and Sampling: <p>These data include total anchovy and sardine biomass west and southeast of Cape Agulhas (sampled in November), and anchovy and sardine recruitment west of Cape Infanta (sampled in May). Seabird variables included % of the diet comprised of anchovy, % of the diet comprised of sardine, breeding success, and survival. African penguin data were collected at Dassen and Robben Islands, South Africa. Cape gannets data were collected at colonies on Malgas Island and in Lamberts Bay, South Africa.</p>
<p>These variables were entered into path analyses, run in Stata v. 11.1 (StataCorp). Path models were designed <em>a priori</em> with upwelling as the base predictor variable, fish biomass (both species) and anchovy recruitment as intermediate predictors, and a seabird metric as the response variable. Path analysis produces beta coefficients for each path segment of the model. To determine the dominant path of effect, the beta coefficients for each indirect path were multiplied together, then summed. This sum of the products of all of the indirect paths was compared to the beta coefficient of the direct path of effect. The greater value indicated if the dominant path was direct or indirect. If indirect, the path with the largest beta coefficient product was considered the dominant path of the model. Note that fish biomass, and anchovy recruitment data were ln-transformed prior to analysis. Anchovy and sardine biomass were lagged one year for analyses of penguin responses, to precede the penguin breeding season when those measurements were collected.</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1434732 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1434732
completed
Bryan Black
University of Texas at Austin
361-749-6789
Marine Science Institute 750 Channel View Drive
Port Aransas
TX
78373
USA
bryan.black@utexas.edu
pointOfContact
Steven Bograd
National Oceanic and Atmospheric Administration - Southwest Fisheries Science Center
831-648-8515
99 Pacific Street, Suite 255A
Monterey
CA
93940
USA
steven.bograd@noaa.gov
pointOfContact
Marisol Garcia Reyes
Farallon Institute for Advanced Ecosystem Research
707-478-1381
101 H St. Suite Q
Petaluma
CA
94952-1092
USA
marisolgr@gmail.com
pointOfContact
William Sydeman
Farallon Institute for Advanced Ecosystem Research
707-478-1381
101 H St. Suite Q
Petaluma
CA
94952-1092
USA
wsydeman@faralloninstitute.org
pointOfContact
asNeeded
Dataset Version: 1
Unknown
year
anc_tot_biomass
sar_tot_biomass
anc_recruitment
sardine_recruitment
ap_di_anc_pcnt_diet
ap_di_sar_pcnt_diet
ap_di_bs
ap_di_surv
ap_ri_anc_pcnt_diet
ap_ri_sar_pcnt_diet
ap_ri_bs
ap_ri_surv
cg_lb_anc_pcnt_diet
cg_lb_sar_pcnt_diet
cg_lb_bs
cg_lb_surv
cg_mi_anc_pcnt_diet
cg_mi_sar_pcnt_diet
cg_mi_bs
cg_mi_surv
theme
None, User defined
year
wet_weight_biomass
No BCO-DMO term
mass
featureType
BCO-DMO Standard Parameters
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
Climate Change and Upwelling -- Comparative Analysis of Current and Future Responses of the California and Benguela Ecosystems
https://osprey.bco-dmo.org/project/564665
Climate Change and Upwelling -- Comparative Analysis of Current and Future Responses of the California and Benguela Ecosystems
<p><em>Desciption from NSF award abstract:</em><br />
Along the west coasts of North and South America, Africa, and Iberia, alongshore equatorward winds bring nutrient-rich waters to the sunlit surface of the ocean, stimulating phytoplankton blooms that support robust, rich and diverse ecosystems. This process is known as "upwelling". Because upwelling is driven by winds, and winds are related to atmospheric conditions, upwelling is highly vulnerable to the effects of climate change. However, the potential impacts of climate change on upwelling and biology remain largely uncertain. In earlier work in the California Current upwelling system, off the west coast of the United States, researchers found that upwelling occurs in distinct winter and summer "modes" that have different impacts on biology. In this project, oceanographic and atmospheric data from the Benguela Current system, off South Africa and Namibia, will be analyzed for similar seasonal patterns and relationships with the ecosystem. Comparisons between these two upwelling systems will allow researchers to investigate if previous findings of regional climate impacts on biology are applicable at a global scale and consider how these systems may change in the future. The project will facilitate collaboration between researchers from South Africa, Namibia, and the United States, integrating a team of young and senior scientists from the three countries and providing them with opportunities for broad-scale scientific synthesis early in their careers.</p>
<p>This project will be a comparative analyses of climate forcing and biological responses in the California Current (CCS) and Benguela Current systems (BCS), the two upwelling systems with the most similar time series of atmospheric and oceanographic conditions, seabird demography, and lower (chlorophyll) and mid (forage fish) trophic data. The project will determine whether changes in the ecosystems can be attributed to regional or global climate processes. Growth-increment chronologies from fish in the BCS (deep-water hake) will be developed as indicators of upper-trophic fish growth, and compared to rockfish growth chronologies developed in the CCS. Mid-trophic level fish abundance will be modeled as indices of prey availability for integration between climate and upper-trophic-level parameters. Oceanographic and atmospheric data will be analyzed from global observational and reanalysis data sets, as well as from earth system model projections of climate change. The project will address the following questions:<br />
1) are seasonal upwelling modes (winter and summer) discernible in the BCS as they are in the CCS?<br />
2) are upwelling modes forced by similar or contrasting atmospheric forcing mechanisms?<br />
3) is there evidence of coherence/covariance among mid-trophic fish, upper-trophic fish, and seabirds (and at which lags) within and between the CCS and BCS?<br />
4) will the positioning and amplitude of the atmospheric pressure systems that result in upwelling-favorable winds change coherently between ecosystems under various climate-change scenarios? and<br />
5) what are the fisheries and wildlife management implications for variability in the seasonality and spatial distribution of upwelling in a changing climate?</p>
CalBenJI
largerWorkCitation
project
eng; USA
oceans
17.9254
18.371
-33.8067
-32.0896
2017-02-01
California Current Ecosystem and Benguela Current Ecosystem
0
BCO-DMO catalogue of parameters from Path analysis, run in Stata v. 11.1, for direct/indirect effects of upwelling on seabirds; data were collected at Dassen and Robben Islands, Malgas Island and in Lamberts Bay, South Africa
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/679981.rdf
Name: year
Units: unitless
Description: <p>4-digit year of sampling</p>
http://lod.bco-dmo.org/id/dataset-parameter/679982.rdf
Name: anc_tot_biomass
Units: tons
Description: <p>Total anchovy biomass for the southwestern Benguela Current Ecosystem along the west coast of South Africa southeast through Cape Agulhas. Sampling season: November.</p>
http://lod.bco-dmo.org/id/dataset-parameter/679983.rdf
Name: sar_tot_biomass
Units: millions of tons
Description: <p>Total sardine biomass for the southwestern Benguela Current Ecosystem along the west coast of South Africa southeast through Cape Agulhas. Sampling season: November.</p>
http://lod.bco-dmo.org/id/dataset-parameter/679984.rdf
Name: anc_recruitment
Units: billions of fish
Description: <p>Total anchovy recruitment for the southwestern Benguela Current Ecosystem along the west coast of South Africa southeast through Cape Infanta. Sampling season: May.</p>
http://lod.bco-dmo.org/id/dataset-parameter/679985.rdf
Name: sardine_recruitment
Units: billions of fish
Description: <p>Total sardine recruitment for the southwestern Benguela Current Ecosystem along the west coast of South Africa southeast through Cape Infanta. Sampling season: May.</p>
http://lod.bco-dmo.org/id/dataset-parameter/679986.rdf
Name: ap_di_anc_pcnt_diet
Units: percent (%)
Description: <p>Percent of the Dassen Island African penguin diet mass that was anchovy</p>
http://lod.bco-dmo.org/id/dataset-parameter/679987.rdf
Name: ap_di_sar_pcnt_diet
Units: percent (%)
Description: <p>Percent of the Dassen Island African penguin diet mass that was sardine</p>
http://lod.bco-dmo.org/id/dataset-parameter/679988.rdf
Name: ap_di_bs
Units: number of chicks fledged/pair
Description: <p>Dassen Island African penguin breeding success</p>
http://lod.bco-dmo.org/id/dataset-parameter/679989.rdf
Name: ap_di_surv
Units: unitless (fraction)
Description: <p>Dassen Island African penguin adult survival (fraction surviving)</p>
http://lod.bco-dmo.org/id/dataset-parameter/679990.rdf
Name: ap_ri_anc_pcnt_diet
Units: percent (%)
Description: <p>Percent of the Robben Island African penguin diet mass that was anchovy</p>
http://lod.bco-dmo.org/id/dataset-parameter/679991.rdf
Name: ap_ri_sar_pcnt_diet
Units: percent (%)
Description: <p>Percent of the Robben Island African penguin diet mass that was sardine</p>
http://lod.bco-dmo.org/id/dataset-parameter/679992.rdf
Name: ap_ri_bs
Units: number of chicks fledged/pair
Description: <p>Robben Island African penguin breeding success</p>
http://lod.bco-dmo.org/id/dataset-parameter/679993.rdf
Name: ap_ri_surv
Units: unitless (fraction)
Description: <p>Robben Island African penguin adult survival (fraction surviving)</p>
http://lod.bco-dmo.org/id/dataset-parameter/679994.rdf
Name: cg_lb_anc_pcnt_diet
Units: percent (%)
Description: <p>Percent of the Lamberts Bay Cape gannett diet mass that was anchovy</p>
http://lod.bco-dmo.org/id/dataset-parameter/679995.rdf
Name: cg_lb_sar_pcnt_diet
Units: percent (%)
Description: <p>Percent of the Lamberts Bay Cape gannett diet mass that was sardine</p>
http://lod.bco-dmo.org/id/dataset-parameter/679996.rdf
Name: cg_lb_bs
Units: number of chicks fledged/pair
Description: <p>Lamberts Bay Cape gannett breeding success</p>
http://lod.bco-dmo.org/id/dataset-parameter/679997.rdf
Name: cg_lb_surv
Units: unitless (fraction)
Description: <p>Lamberts Bay Cape gannett adult survival (fraction surviving)</p>
http://lod.bco-dmo.org/id/dataset-parameter/679998.rdf
Name: cg_mi_anc_pcnt_diet
Units: percent (%)
Description: <p>Percent of the Malgas Island Cape gannett diet mass that was anchovy</p>
http://lod.bco-dmo.org/id/dataset-parameter/679999.rdf
Name: cg_mi_sar_pcnt_diet
Units: percent (%)
Description: <p>Percent of the Malgas Island Cape gannett diet mass that was sardine</p>
http://lod.bco-dmo.org/id/dataset-parameter/680000.rdf
Name: cg_mi_bs
Units: number of chicks fledged/pair
Description: <p>Malgas Island Cape gannett breeding success</p>
http://lod.bco-dmo.org/id/dataset-parameter/680001.rdf
Name: cg_mi_surv
Units: unitless (fraction)
Description: <p>Malgas Island Cape gannett adult survival (fraction surviving)</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
4158
https://darchive.mblwhoilibrary.org/bitstream/1912/24420/1/dataset-679946_benguela-current-ecosystem-path-analysis__v1.tsv
download
https://doi.org/10.1575/1912/bco-dmo.679946.1
download
onLine
dataset
<p>These data include total anchovy and sardine biomass west and southeast of Cape Agulhas (sampled in November), and anchovy and sardine recruitment west of Cape Infanta (sampled in May). Seabird variables included % of the diet comprised of anchovy, % of the diet comprised of sardine, breeding success, and survival. African penguin data were collected at Dassen and Robben Islands, South Africa. Cape gannets data were collected at colonies on Malgas Island and in Lamberts Bay, South Africa.</p>
<p>These variables were entered into path analyses, run in Stata v. 11.1 (StataCorp). Path models were designed <em>a priori</em> with upwelling as the base predictor variable, fish biomass (both species) and anchovy recruitment as intermediate predictors, and a seabird metric as the response variable. Path analysis produces beta coefficients for each path segment of the model. To determine the dominant path of effect, the beta coefficients for each indirect path were multiplied together, then summed. This sum of the products of all of the indirect paths was compared to the beta coefficient of the direct path of effect. The greater value indicated if the dominant path was direct or indirect. If indirect, the path with the largest beta coefficient product was considered the dominant path of the model. Note that fish biomass, and anchovy recruitment data were ln-transformed prior to analysis. Anchovy and sardine biomass were lagged one year for analyses of penguin responses, to precede the penguin breeding season when those measurements were collected.</p>
Specified by the Principal Investigator(s)
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact