The Integrated Ecosystem Assessment InitiativeEnabling the Assessment of Impacts on Large Marine Ecosystems:

Informatics to the Forefront of Science Based Decision Support Massimo DiStefano 1,2, Peter Fox 1, Stace Beaulieu 2, Andrew Maffei 2

[1] Tetherless World Constellation, Rensselaer Polytechnic Institute, Troy - NY - [2] Woods Hole Oceanographic Institution, Woods Hole - MA.

2012 ICES Annual Science Conference 17 - 21 September - Bergen, Norway

Objectives

We are developing cyberinfrastructure to facilitate collaboration and knowledge sharing for marine Integrated Ecosystem Assessments (IEAs). In this poster, we highlight our work with natural and social scientists at the NOAA Northeast Fisheries Science Center, promoting community participation in integrating models, data and knowledge using software tools as shown here. The main tool is based on a web application that provides the ability to work on very diverse and heterogeneous data and information sources, providing an effective way to share the source code used to generate data products and associated metadata as well as save and take track of the workflows provenance to allow the reproducibility of a data product.

Our objectives are to facilitate the deployment of an integrated ecosystem approach to management in the Northeast Shelf and California Current Large Marine Ecosystems (LMEs). The direct result of our activities will be application-level data and information enhanced communication for developing the consensus networks to define the specific components of interest to support the implementation of NOAA’s Driver-Pressure- State-Impact Response (DPSIR) decision framework and the cyberinfrastructure technologies to ensure data interoperability and reuse. This new capability will serve as the essential foundation for the formal synthesis and quantitative analysis of information on relevant natural and socio–economic factors in relation to specified ecosystem management goals which can be applied in other LMEs.

We are developing a successful method to implement and sustain informatics solutions to modern application problems, such as environmental and climate assessments, that provide interoperability among very diverse and heterogeneous data and information sources, as well as multi-disciplinary organizations and people. Existing data will be leveraged via semantic web technologies to capture knowledge. These technologies can leverage extant vocabularies and data repositories used by the stakeholders and define the meaning of that data by providing language constructs understood by computers that closely reflect how people think and pose questions of the data.

Here we show the actors and basic workflow for our ESR Use Case. The software tools that we present here represent the box outlining the iterative and interactive processing and visualization of the data, indicators, and information products.

RPI Semantic development methodology with Use Case as focus.

In software development, a use case describes the sequence of interactions between a primary actor and a system, such that the primary actor's objective is successfully achieved. Use cases are about describing system behavior from the perspective of the user and, as such, can be considered user requirements. Use cases shift the perspective of requirements development to discussing what users need to accomplish, in contrast to the traditional elicitation approach of asking users what they want the system to do.

We developed a Use Case for the Ecosystem Status Report (ESR) for the Northeast Shelf (NES) Large Marine Ecosystem (LME) and are iterating through the cycle above to evaluate our software tools.

Use Case Goal - Efficient generation of figures and tables representing ecosystem data and information products for the bi-annual ESR.

The ESR addresses the Driver-Pressure-State portion of the greater Integrated Ecosystem Assessment (IEA) Driver-Pressure-State-Impact-Response (D, P, S, I, R) framework and presents the ecosystem status based on data and information products representing climate forcing (D), physical pressures (P), primary and secondary production (S), benthos (S), upper trophic levels (S), anthropogenic factors (D, P), and integrated ecosystem measures (S). Data and information products include indicators, time series, thematic maps and uni-variate and multi-variate analyses. Data and information products are derived for the NES LME as a whole and for sub-regions (ecological production units).

Here, we show a simplified schematic of our software design, starting with a source dataset and ending with a final product for an Ecosystem Status Report. A key feature is that metadata are acquired during the processing and plotting of the data, and metadata are embedded in the final product. In this way we are able to record the provenance needed to reproduce the data products.

Activity Diagram

Software Design

Acknowledgements

We would like to thank Jon Hare and Kim Hyde of the Northeast Fisheries Science Center, NOAA, for providing the phytoplankton data and satellite-derived chl a. All data on the poster are included in the 2011 Ecosystem Status Report for the Northeast Shelf Large Marine Ecosystem, available online at http://www.nefsc.noaa.gov/publications/crd/crd1207/index.html. In addition, we would like to thank Jon, Kim, and others at NEFSC (M. Fogarty, R. Gamble, M. Jones, and S. Lucey) for beta-testing the ECO-OP GUI and IPython notebook. Our work is supported by NSF OCI #0955649.

Semantic Web Metodology & Technology Development Process

Example IPython Notebook

The IPython notebook interface showed on the left is used to run interactively the code developed to produce figures and tables for the Ecosystem Status Report. We chose IPython because it can be run over the web with open source software. In this example we are generating plots for several datasets, including climate indices, phytoplankton abundance anomalies, and satellite-derived chlorophyll a. We perform an overlay for time-series datasets, as well as display geospatial information in a map of the Ecological Production Units of the NES LME. The notebook is used to retrieve data, conduct standard analyses, provide iterative and interactive visualization, and generate data products. The interactive visualization tools include a GUI that also can be run outside of the IPython notebook, on its own through a web application.

Data sources used in these plots:

- North Atlantic Oscillation (NAO) Index Station Based (DJFM) http://climatedataguide.ucar.edu/guidance/hurrell-north-atlantic-oscillation-nao-index-station-based

- Atlantic Multidecadal Oscillation (AMO) http://www.esrl.noaa.gov/psd/data/correlation/amon.us.long.data

- Niño 3.4 (5°North-5°South)(170-120°West) (NIN) http://www.cpc.ncep.noaa.gov/data/indices/sstoi.indices

- Continuous Plankton Recorder (CPR) time series:Kane (2011) Multiyear variability of phytoplankton abundance in the Gulf of Maine. ICES J. Mar. Sci. 68 (9): 1833-1841, doi: 10.1093/icesjms/fsr122.

- Satellite-derived chlorophyll a from SeaWiFS ocean color, mean for October 1997

- HYDROGL020 - U.S. National Atlas Water Feature Areas: aqueducts, canals, dams, intercoastal waterways, rivers, and streams [U.S. Geological Survey] http://nationalatlas.gov/atlasftp.html

- NOS80K - Medium Resolution Digital Vector U.S. Shoreline shapefile for the contiguous United States [NOAA/NOS/ORCA/SEA] http://coastalgeospatial.noaa.gov/shoreline.html

- Ecological Production Units dataset from NEFSC EcoAP