Bruneel, Stijn

Goethals, Peter

Moens, Tom

Reubens, Jan

Verhelst, Pieterjan

English

Bruneel, S.

Verhelst, P.

Reubens, J.

Moens, T.

Goethals, P.

Open Marine Archive

Innovative sampling technique: Acoustic telemetry
Fish are surgically tagged with a transmitter which can be detected by receivers
(point-locations) scattered in the environment, allowing to reconstruct 
individual fish trajectories.
> Telemetry > Point-measurements of  recognizable individuals > Trajectories
> Comprehensive view on how individuals move in the environment
> Requires comprehensive view on the environment itself
Abiotic modelling options of  estuarine areas as building blocks for ecological predictions
Stijn Bruneel 1,2, Pieterjan Verhelst 1,2, Jan Reubens 3, Tom Moens 2, Peter Goethals 1
1 Laboratory of  Environmental Toxicology and Aquatic Ecology, Faculty of  Bioscience Engineering, UGent. E-mail: stijn.bruneel@ugent.be
2 Marine Biology Research Group, Faculty of  Sciences, Ghent University
3 VLIZ (Vlaams Instituut voor de Zee) 
An upcoming topic of ecological research is the implementation of movement in habitat suitability models (HSM). These models, also known as species distribution
models (SDM), aim at identifying the relationship between environment and organisms. Fish, especially potamodromous and diadromous fish such as eel (Anguilla
anguilla L.), are highly mobile and might interact with each other and the environment. Therefore, fish sampling techniques and modelling tools which do not account
for movement or interaction, introduce considerable uncertainties. Only recently the incorporation of ecological knowledge regarding movement and the evolution of
more individual based sampling techniques such as telemetry, have opened the door to more movement dependent models such as individual based models (IBM).
However, this new approach to model species distributions should not only drive researchers to use new fish sampling techniques and biotic modelling tools but
should also offer an opportunity to rethink existing environmental modelling tools used in SDMs.
Kriging (interpolation)
• Strong link with point data
• Accounts for spatial 
autocorrelation
• Measure of  uncertainty 
(geostatistics) 
Mechanistic model
• Based on universal laws
• High extrapolation reliability
• Requires little data input
Remote sensing
• Surface covering
• Evolving technology
Conclusion: The new generation of  biotic data acquisition (e.g. telemetry) and processing (e.g. IBM) tools are individual based with a high spatial and temporal 
coverage potential, enabling the reproduction of  fish trajectories. Therefore used environmental datasets should be expanded from point-based to area-covering in 
order to identify effects of  environmental changes between sampling points on movement of  fish. Different methods, using point measurements, physical-chemical 
knowledge, remotely sensed data or a combination are promising ways to integrate environmental data into ecological models. 
Biotic data > Point-based < Environmental data
• Water sampling during fish sampling
• Nearby fixed measurement stations
• Point-based population fish sampling
• Unprocessed in-situ abiotic point-measurements
• Point-based individual fish sampling (allowing trajectory description)
• Processed in-situ abiotic point-measurements and remote sensing
E
n
v
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n
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en
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ata 
F
ish
 S
am
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iq
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es
Traditional sampling techniques: Fykes, trawls and electrofishing
• Groups of  fish (populations)
• At point locations 
No idea of  the behavior of  individual fish and how it is related 
to environmental changes.
A
B
C
?
??
? Fish sampled at 
one location 
cannot be 
identified at 
another 
location 
Which individual is ? and ?? 
Is it A, B, C … or another individual?
The Belgian fish 
acoustic telemetry 
network is part of  
the LifeWatch
observatory, which 
aims at describing 
the movement and 
habitat use of  
migratory fish. 
Environmental layers instead of  point data 
Point measurements > Interpolation methods (kriging)
Knowledge incorporation > Mechanistic models (process-based)
Satellite imagery > Remote sensing


Abiotic modelling options of estuarine areas as building blocks for ecological predictions

Ghent University Academic Bibliography

Innovative sampling technique: Acoustic telemetryFish are surgically tagged with a transmitter which can be detected by receivers(point-locations) scattered in the environment, allowing to reconstruct individual fish trajectories.> Telemetry > Point-measurements of  recognizable individuals > Trajectories> Comprehensive view on how individuals move in the environment> Requires comprehensive view on the environment itselfAbiotic modelling options of  estuarine areas as building blocks for ecological predictionsStijn Bruneel 1,2, Pieterjan Verhelst 1,2, Jan Reubens 3, Tom Moens 2, Peter Goethals 11 Laboratory of  Environmental Toxicology and Aquatic Ecology, Faculty of  Bioscience Engineering, UGent. E-mail: stijn.bruneel@ugent.be2 Marine Biology Research Group, Faculty of  Sciences, Ghent University3 VLIZ (Vlaams Instituut voor de Zee) An upcoming topic of ecological research is the implementation of movement in habitat suitability models (HSM). These models, also known as species distributionmodels (SDM), aim at identifying the relationship between environment and organisms. Fish, especially potamodromous and diadromous fish such as eel (Anguillaanguilla L.), are highly mobile and might interact with each other and the environment. Therefore, fish sampling techniques and modelling tools which do not accountfor movement or interaction, introduce considerable uncertainties. Only recently the incorporation of ecological knowledge regarding movement and the evolution ofmore individual based sampling techniques such as telemetry, have opened the door to more movement dependent models such as individual based models (IBM).However, this new approach to model species distributions should not only drive researchers to use new fish sampling techniques and biotic modelling tools butshould also offer an opportunity to rethink existing environmental modelling tools used in SDMs.Kriging (interpolation)• Strong link with point data• Accounts for spatial autocorrelation• Measure of  uncertainty (geostatistics) Mechanistic model• Based on universal laws• High extrapolation reliability• Requires little data inputRemote sensing• Surface covering• Evolving technologyConclusion: The new generation of  biotic data acquisition (e.g. telemetry) and processing (e.g. IBM) tools are individual based with a high spatial and temporal coverage potential, enabling the reproduction of  fish trajectories. Therefore used environmental datasets should be expanded from point-based to area-covering in order to identify effects of  environmental changes between sampling points on movement of  fish. Different methods, using point measurements, physical-chemical knowledge, remotely sensed data or a combination are promising ways to integrate environmental data into ecological models. Biotic data > Point-based < Environmental data• Water sampling during fish sampling• Nearby fixed measurement stations• Point-based population fish sampling• Unprocessed in-situ abiotic point-measurements• Point-based individual fish sampling (allowing trajectory description)• Processed in-situ abiotic point-measurements and remote sensingEnvironmental data Fish Sampling techniquesTraditional sampling techniques: Fykes, trawls and electrofishing• Groups of  fish (populations)• At point locations No idea of  the behavior of  individual fish and how it is related to environmental changes.ABC???? Fish sampled at one location cannot be identified at another location Which individual is ? and ?? Is it A, B, C … or another individual?The Belgian fish acoustic telemetry network is part of  the LifeWatchobservatory, which aims at describing the movement and habitat use of  migratory fish. Environmental layers instead of  point data Point measurements > Interpolation methods (kriging)Knowledge incorporation > Mechanistic models (process-based)Satellite imagery > Remote sensing

Verhelst, P.-J.

- 9 - 
 
 
Abiotic modelling options of estuarine areas as building blocks for 
ecological predictions 
Bruneel Stijn
1-2
, Verhelst Pieter-Jan
1-2
, Reubens Jan
3
, Moens Tom
2
 and Goethals Peter
1 
1 
Laboratory of Environmental Toxicology and Aquatic Ecology, Faculty of Bioscience Engineering, 
Ghent University, Coupure Links 653, 9000 Gent, Belgium  
E-mail: stijn.bruneel@ugent.be 
2 
Marine Biology Research Group, Ghent University, Campus Sterre S8, Krijgslaan 281, 9000 Gent, 
Belgium 
3
 Flanders Marine Institute (VLIZ), InnovOcean site, Wandelaarkaai 7, 8400 Oostende, Belgium 
 
Most current ecological models focus on the improvement of underlying biological processes which are 
of course inherent to any model trying to simulate ecosystem components and processes. However, the 
importance of both the physical and chemical dimensions of an environment cannot be overlooked as 
ecological model performances are often limited by oversimplified, not representative or mismatching 
abiotic data of current velocity, DO, water temperature, conductivity, etc. 
 
Estuaries, being characterized by their complex interplay of tidal movements, freshwater discharges, 
topography, geometry and atmospheric influences, show a high variability in their physical and 
chemical properties over both time and space. Researchers of estuarine phytoplankton dynamics, 
larvae dispersal and fish movement patterns are faced with a complex ecosystem and a wide range of 
data-driven and process-based methods to choose from. This choice is most often guided by limited 
data availability, previous modelling efforts and required temporal and spatial resolutions but often 
goes without a profound justification or recognition of the unknown uncertainty. This could therefore 
lead to the identification of key processes and variables based on artefacts, resulting from bad 
coupling between hydrodynamic, biogeochemical or ecological components of the model, rather than 
identifying real ecological trends. 
 
In this study, we explored different modelling approaches in the Scheldt Estuary. Namely, within the 
framework of the European LifeWatch Observatory, a network of acoustic receivers was installed in the 
Scheldt Estuary to track fish with an acoustic tag. To analyse their behaviour, it is necessary to relate 
knowledge about the abiotic environment to the tracking data. Nevertheless, to deal with the major 
concern of the limited use of a wide spectrum of modelling approaches, the review is expanded to 
other estuaries and the simulation of their abiotic dimensions as a reference for the current set of 
modelling options in the Scheldt estuary. This setup allows us to provide a general overview of existing 
modelling approaches in estuaries and to characterize them in the light of different objectives. 
 
Keywords: abiotic models; ecological models; estuaries; Scheldt estuary  


https://biblio.ugent.be/publication/8651380/file/8651382

Abiotic modelling options of estuarine areas as building blocks for ecological predictions

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Ghent University Academic Bibliography

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