recent advances in the ecopath with ecosim food web ...€¦ · international collaborations, gis,...

Recent advances in the Ecopath with Ecosim

food web modelling approach15 November 2019, Institute for the Oceans and Fisheries

Jeroen Steenbeek, EII, Spain

My background

Brief overview of EwE

Challenges to ecosystem modelling

New spatial modelling capabilities and applications

Other ways to use EwE

The EwE ecosystem itself

Overview

My background

Classically trained software developer

Corporate years: The Netherlands 1992-1999

Industrial process software development

Media years: Canada 2000-2004

Multimedia, game development, web RIAs & GIS

Academic years: Canada 2004-2013

SAUP consultancy, EwE development and teaching

Best years: Spain 2013-

EwE development, consultancy, teaching, and software life cycle management

International collaborations, GIS, big data, serious gaming

Brief overview of EwE

Ecopath with Ecosim (EwE)

Ecological model that tracks the paths of energy through a food web

Functional groups, fleet/gears

Requires relatively few input parameters

Data often readily available(surveys, stock assessments, fisheries statistics, …)

Includes environment and human activities

Christensen and Walters 2004, EcoMod; Heymans et al. 2016, EcoMod

Ecopath with Ecosim

1984 Ecopath conceived (Polovina 1984)

1990 First desktop version released

1995 Ecosim introduced

1998 Ecospace introduced

2006 Re-engineered

2011 Ecopath R&D Consortium established

2012 Open source, community-driven

2019 Thirty-five years anniversary

Freely available from http://www.ecopath.org

http://www.ecopath.org/

http://ecobase.ecopath.orgColléter et al. 2015, EcoMod

EcoBase: 440 EwE models, 173 for download

8000+ users in 150+ countries (google analytics)

800+ peer-reviewed publication (ISI Web of Knowledge)

Ecopath with Ecosim

Ecopath with Ecosim

Three major components

Ecopath static mass-balanced model

Ecosim temporal dynamics

Ecospace spatial-temporal dynamics

Additional modules

Ecotracer contaminant tracing

‘Searches’ MCMC, spatial optimizations, MSE, fishing policy, …

Plug-ins extra features, interoperability, …

Heymans et al. 2016, EcoMod; Steenbeek et al. 2016, EcoMod

Ecopath

Main module of EwE, snapshot of the ecosystem

Define food web components and energy flows

Understand ecosystem structure and functioning

Evaluate impact of fisheries

Model of entire Mediterranean basin, Piroddi et al. 2018, MEPS

Ecosim

Temporal-dynamic module of EwE, initialized from Ecopath

Includes biomass and size structure dynamics

Introduces behaviour and temporal change

Used, among others, to assess

Quantify combined effect of species dynamics, fishing impacts, and environmental impacts on a food web over time

Replicate past scenarios (time series fitting)

Explore future scenarios

Explore fishing policy alternatives

Test model robustnessWalters et al. 1997, RFBF; Heymans et al. 2016, EcoMod Piroddi et al. 2017, SR

Time dynamic spatially explicit module of EwE, initialized from Ecosim. Introduces concepts of habitats, marine protected areas, and requires additional parameters related to movement and the use of space

Used, among others, to explore

Distribution of marine species and fishing effort

Effectiveness of management options

Ecosystem impacts of environmental change, habitat change, fishing

Combinations of the above

Ecospace

Walters et al. 1999, Ecosystems; Christensen et al. 2014, Ecosystems


After Cheung et al. 2010

Physical change in the ocean

SST increase

Retreat of sea ice

Acidification

Coastal hypoxic & oxygen min. zones

Rising sea surface levels

Biological / ecological change in the ocean

PhysiologyGrowth Body size

DistributionAbundanceRecruitment

Species compositionInvasion/extinction

ProductivitySpecies interactionEcosystem services

Ind

ividu

alPo

pu

lation

Co

mm

un

ityEco

system

Ecosystem modelling is more than considering biophysical impacts…


Christensen 2013, Fisheries; Cury 2013, pers com.

..it also requires clear objectives, that models can address through

rigorous execution of scenarios


Ecosystems are staggeringly complex

Feedback effects throughout entire system

Processes cross traditional scientific boundaries

Processes and time scales can span orders of magnitude

Cumulative impacts are often poorly understood (climate change, anthropogenic)

“Essentially, all models are wrong, but some are useful”

- George P. Box (1987)


Ideas about model scope, abilities and purpose

vary greatly

One thing is clear

Models need to be able to work together

What does this mean for models?


Increase scope and complexity of existing models (“Frankenmodel”, Mackinson et al 2009)

Merge existing models

Make existing models communicate

Make models collaborate

Make models exchange componentsComplexity

Popularity

How do models deal with these challenges?


Where we need to go…


What does this mean for the EwE approach?

EwE all-over strategy

Focus on core food-web science

Link / connect to everything else

Facilitate extending EwE with external functionality

Facilitate switching hypothesis (modularity)

Separate scientific and technical issues

Ground-breaking developments in spatial-temporal modelling and software capabilities

New capabilities and applications

Ecospace niche modelling

Christensen et al. 2014, Ecosystems

Original Ecospace offered limited capabilities to explain species distributions. Habitat usage was an aggregated assumption implying environmental preferences

Since EwE version 6.3+, Ecospace derives cell suitability from species’ responses to local environmental conditions (depth, temperature, salinity, oxygen, pH, …) and/or habitat use.

Ecospace is now an integrated food-web / species envelope model

Functional groups respond to (changing) environmental conditions

Each group has unique preferences for these conditions

Dynamic habitat model predicts how productive individual cells are for each species

Adapted from Christensen et al. 2014, Ecosystems


Niche priors

SDM results

Original Ecospace(habitat affinities)

New Ecospace(environmental prefs.)

Combining hypotheses


Case study 1: protection

Temporal resolution Vertical integration

Parameter Original unit Annual

Monthly Surface Surface 150m

Bottom Total Column

Phytoplankton biomass mmolN/m2 Yes Yes Yes Yes Yes Zooplankton biomass mmolN/m2 Yes Yes Yes Yes Yes

Chlorophyll-a biomass mmolN/m2 Yes Yes Yes Yes Yes

PP mmolN/m2 Yes Yes Yes Yes Yes

Oxygen mg/L Yes Yes Yes Yes Yes Salinity PSU Yes Yes Yes Yes Yes Temperature °C Yes Yes Yes Yes Yes Currents m/s Yes Yes Yes Yes

Models

Drivers

Coll et al. 2019, Safenet

Case study 1: protection

h)

i) j)

g)

a) b)

c) d)

Protection scenarios Many, many simulations

Summaries

Case study 2: Link BH-SDM and Ecospace

Use Bayesian-HSDM model and Ecospace-HFCM to estimate and predict the occurrence and biomass distribution of 5 demersal fish species

Explored the complementarity of both approaches, aside from their applicability as independent techniques

Explored how to use Bayesian SDM models to incorporate uncertainty into the FWM

Merluccius merluccius Lophius piscatoriusLophius budegassa

Mullus barbatusMullus surmuletus Study area: 4,000 km2

Coll et al. 2019. EcoMod

Case study 2: Link BH-SDM and Ecospace

Path 1

Path 2

a) b)

c) d)

Pelagic Demersal

Tro

ph

ic L

evel

Correlations with data

Coll et al. 2019. EcoMod

The internal data model of Ecospace was hard to access – almostimpossible to vary input maps over time

Changing environmental conditions could not be included in spatial temporal analysis

A new spatial-temporal framework was developed:Can drive most Ecospace input layers Can build Ecospace maps from external GIS files Produces Ecospace results as GIS files

Is connected to the habitat capacity model (!)

Spatial temporal data framework

Steenbeek et al. 2013, EcoMod.

STDF can provide Ecospace with temporal-spatial variation in:

Environmental drivers (SST, Salinity, Oxygen, …)

Primary productivity

Currents

Species niches

Biomass distributions

Contaminants

Fishing cost

Habitats

Migration routes

MPA placements


Case study: Adriatic productivity


Extensions to EwEPlug-ins and new tools

Ecological indicators communicate historical and future changes in ecosystems

Functional group taxonomic composition and species traits

EcoIND plug-in calculates standardized ecological indicators from Ecopath, Ecosim, Ecospace, and Monte Carlo

Indicators include biomass, catch, trophic level, size, and species

Highly extensible (MSFD, others)

EcoIND extends EwE into biodiversity and conservation-based frameworks, and management applications

Ecological indicators plug-in

Coll and Steenbeek 2017, EMS

Ecological indicators application

Coll and Steenbeek 2017, EMS

Ecosampler plug-in

Simple engine that facilitates analysing input parameter uncertainty on potentially any EwE output.

Record modeStore alternate mass-balanced parameter sets, ‘samples’, from EwE built-in Monte Carlo routines

Replay modeRun samples through Ecopath, Ecosim, and Ecospace

Defines unique output path for each sample

Sample parameter set is written to file

All triggered and auto-saving EwE components and plug-ins write outputs for a sample

Statistical analysis must be performed outside EwE

Steenbeek et al. 2018, SoftwareX

Ecosampler plug-in

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Time (yr)

Bio

ma

ss

(t/k

m2)

(f) Rays and skates

(e) Earlier alien demersal

fishes

p-value = 0.02

rho = 0.59

p-value < 0.001

rho = 0.99

(a) Alien crabs (b) Goatfishes

(c) Hake

(d) Rocky fishes

p-value < 0.01

rho = -0.62

p-value < 0.001

rho = -0.84

p-value < 0.001

rho = 0.96p-value < 0.001

rho = 0.82

Steenbeek et al. 2018, SoftwareX


Steenbeek et al. 2016, EcoMod

EwE is available in a number of programming languages to cater to different audiences and modelling environments

This story focuses on the .NET version – the EwE mothership


Modular structure of EwE version 6



Plug-ins

Independently of EwE

Auto-loaded on start-up

Included in program flow

Replace or extend computations and user interface

Perform external analysis and do other really neat things!



A few plug-ins

Aquamaps response fn. import EII, JRC

Ecological indicators IRD, ICM, EII

Ecotroph analysis Agrocampus Ouest

WoRMS taxon search EII

Multi-Sim DFO

Network analysis SAMS

Result extractor CEFAS

Value Chain UBC

MPA Dynamics UBC

Transect extractions EII, CEFAS

CEFAS MSE CEFASSteenbeek et al. 2016, EcoMod


Standard use: EwE6 desktop interface


Power use through EwE source code. Batch runs, large scale analysis, integrated modelling, sky := limit;



Distributed computing,model interoperability


OceanViz – modelling for policy



MSP Challenge 2050

A serious game to educate stakeholders about the MSP process

Up to 80 players, in teams, make spatial plans for their share of a marine region, trying to obtain set goals

Plans are designed in a GIS-like interface

Plans can cover shipping, fishing, dredging, recreation, mineral extraction (oil and gas), blue energy (offshore wind, tidal, wave), aquaculture (fish farming), deep sea mining, etc

Planning requires information discovery, negotiations with affected neighbours, etc.

During simulation phases, plans are put into action, where Ecospace calculates how the ecosystem is affected by plans

http://mspchallenge.info.

MSP Challenge 2050

http://mspchallenge.info.

MSP Challenge 2050

1. Game users design plans for a marine area

2. The MSP server aggregates these plans

3. The plans are translated into environmental pressures

4. Pressures influence the ecology of the embedded Ecospace model

5. Indicators (biomass, catch, diversity) are returned to game users

Steenbeek et al. (in review)

Action Pressures Ecological impact

MSP Challenge 2050

Steenbeek et al. (in review)

MSP Challenge 2050

Full-day test sessions with stakeholders – Firth of Clyde / SIMCELT

User comments:

“It has endless potential for all sorts of audiences and is an exciting innovation.”

“This would be a great tool for actual consultations and responses.”

“Easy to use once I learned commands; useful to non-planners and users not familiar with GIS (ARC10.1) programs.”

“The balance between realism and entertainment makes it a fantastic educational tool.”

Reprinted from J. Bentley

The EwE ecosystemKeeping a scientific software alive and healthy

The EwE ecosystem

EwE is a community-driven software without core funding

Ideas and funding from users translate to new features

New features are released with EwE once published

Software is free and open-source

Projects can purchase a professional license with tech. support

Ecopath R&D Consortium: improving and applying EwE

High quality training courses

Pursuing and executing projects

Release new versions of EwE – EwE 6.6 coming soon!

Organizing development, user support, co-development

Open for any institute to join

The EwE ecosystem

EwE thus relies on active users to continue!

Online user community

Support contracts for using EwE

Co-development ideas and funding

Training courses

Consortium membership

http://ecopath.org/consortium

http://facebook.com/eweconsortium

http://www.ecopath35.org


http://facebook.com/eweconsortium


Thank [email protected]

recent advances in the ecopath with ecosim food web ...€¦ · international collaborations, gis,...

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