State-of-the-art in modelling riverine habitats

1
State-of-the-art in modelling riverine habitats

• COST Action 626
• 2001 2004

2
Introduction

• Habitat models predict (changes in) the
  suitability of faunal and floral habitats in
  response to (changes in) environmental factors.
• Habitat models generally consist of a combination
  of physics and habitat preference information.

3
Physical habitat parameters
4
Physical habitat parameters

• Key parameters were listed on different scales
  from microhabitats to landscape scale.
• Limiting factors for habitat modelling were
  identified for example predator-prey
  relationships, spatial links in habitat use or
  extreme events.

5
Interface between physics and ecology

• Two types of interfaces
• Empirical-based habitat preference models
• Biological process-based models

6
Habitat preference curves

• Univariate preference functions
• Multivariate preference functions
• Ordination techniques
• Artificial neural networks
• Fuzzy rule-based functions
• Logistic regression
• Decision trees
• Biological indicator systems

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8
flow velocity
water depth
1
1
0,8
0,8
0,6
0,6
membership -
membership -
0,4
0,4
0,2
0,2
0
0
0
0,3
0,6
0,9
1,2
1,5
0
0,3
0,6
0,9
h m
v m/s
substrate
habitat suitability
1
1
0,8
0,8
0,6
0,6
membership -
membership -
0,4
0,4
0,2
0,2
0
0
0
1
2
3
4
5
6
7
8
9
0
0,2
0,4
0,6
0,8
1
Index
SI
9
Biological process-based models

• Population dynamics
• reproduction, growth, mortality, feeding,
  digestion, migration.
• Bioenergetic models
• the budget of energy intake (food) and energy
  loss (swimming) denotes optimal location.

10
Inventory of models

• Model techniques were classified
• statistical or mechanistic methods
• applied on biology, hydraulics, water quality,
  hydrology, morphodynamics and spatial analysis.
• Details were listed for 27 different modelling
  tools used by COST626 members.