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Plankton Data Products

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(1)

A Showcase for the European

A Showcase for the European

Atlas of Marine Life

Atlas of Marine Life

Plankton gridded products

Plankton gridded products

(2)

A work by

A work by

Olivier BEAUCHARD (data preparation and processing)

Alexander BARTH (code development and data interpolation)

Peter HERMAN (data preparation and interpretation)

Jean-Marie BECKERS (code development)

(3)

Collect once,

Collect once,

(4)

Collect once,

Collect once,

Use many times

Use many times

(5)

Collect once,

Collect once,

Use many times

Use many times

And create products with DIVA

And create products with DIVA

(6)

1. How do we perform

1. How do we perform

interpolation?

interpolation?

(7)

Data interpolation

Data interpolation

(8)
(9)

2. Example of products

2. Example of products

(10)

Benthic macroinvertebrate

Benthic macroinvertebrate

living modes

living modes

in European seas

in European seas

(11)

Data sources

Data sources

Available from EMODnet Biology (see list on the web) 3 main living modes

(12)

Resistant

Resistant

strong mobility

1-short life cycle

2-high offspring survival probability

(13)

3-Opportunistic/resilient

Opportunistic/resilient

Relatively short life span

1-Not very habitat-speci c

(14)

2-Vulnerable

Vulnerable

Years/decades to achieve a minimum of reproductive success

1-Negatively affected by bottom trawling

(15)

2-Data location

(16)

Interpolated fields (relative)

(17)

Error fields

(18)

Neural network modelling

Neural network modelling

of Baltic zooplankton abundances

of Baltic zooplankton abundances

(19)

Method: neural network

Method: neural network

Using co-variables to help for the interpolation

Main datasets: Zooplankton observations in the Baltic

the Swedish from EMODnet Biology

1- SHARK database the Finnish data from the

2- NOAA Copepod database

the German and Polish from the

(20)

Co-variables

Co-variables

(from EMODnet Chemistry)

1-Dissolved oxygen

(from SeaDataNet)

2-Salinity

(from SeaDataNet)

3-Temperature

(MODIS-Aqua from NASA)

4-Chlorophyll concentration (from GEBCO)

5-Bathymetry

(from GSFC, NASA)

(21)

Examples of fields

(22)

Examples of fields

(23)

Examples of fields

(24)
(25)

3.

(26)

3.

Findability

Accessibility

(27)

3.

Findability

Accessibility

Interoperability

(28)

3.

Findability

Accessibility

Interoperability

(29)

Towards reproducibility

Towards reproducibility

 Data 

 Tool  DIVAnd v2.1.1:

 Code and procedure  Jupyter-notebooks:

 Products available for download  netCDF les: EMODnet Biology

http://doi.org/10.5281/zenodo.1407912 

(30)

Towards reproducibility

Towards reproducibility

 Tool  DIVAnd v2.1.1:

 Code and procedure  Jupyter-notebooks:

 Products available for download  netCDF les:

a 

EMODnet Biology

http://doi.org/10.5281/zenodo.1407912 

(31)

Towards reproducibility

Towards reproducibility

 Code and procedure  Jupyter-notebooks:

 Products available for download  netCDF les:

a 

EMODnet Biology

DIVAnd v2.1.1:

http://doi.org/10.5281/zenodo.1407912

(32)

Towards reproducibility

Towards reproducibility

 Products available for download  netCDF les:

a 

EMODnet Biology

DIVAnd v2.1.1:

http://doi.org/10.5281/zenodo.1407912

e and procedure  Jupyter-notebooks:

(33)

Towards reproducibility

Towards reproducibility

a 

EMODnet Biology

DIVAnd v2.1.1:

http://doi.org/10.5281/zenodo.1407912

e and procedure  Jupyter-notebooks:

ducts available for download  netCDF les:

(34)

Thanks for

Thanks for

your attention

Références

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