This document discusses Lake Mjøsa and Gudbrandsdalslågen river in Norway. It provides long-term data on water quality, plankton populations, and a trout species (Hunder trout) over 40 years. The data shows decreases in phosphorus levels, algal biomass, and zooplankton biomass in the lake coinciding with water quality improvements. Population data on Hunder trout consists of 7,000 individuals marked and monitored from 1966-2002. The document discusses how the SUSTAIN project can combine these extensive long-term datasets and local expertise to model and understand changes in these ecosystems over time in relation to environmental conditions and climate change.
6. The Hunder Trout
“Regular” Brown Trout Hunder Trout
• One of Europe’s largest trout
• 40 years of mark-recapture data
• Recent changes:
Decreasing body size (shrinking)
Altered maturity reaction norm
• Evolutionary response to dam (1966)?(Haugen et al. 2008)
• Reaction to climate change?
Chloé R. Nater
7. Hunder trout - main objectives
Stock
1) Estimation of vital rates and growth (temperature)
2) Extending to population dynamics
3) Effects of environmental conditions
4) Effects of climate change and management scenarios
Chloé R. Nater
8. Data on the Hunder trout
• 7000 individuals
• 1966-2002 (+ later)
• Mark-Recapture-Recovery
and life-history data
• Owned by Per Aass and
Atle Rustadbakken
(County Gov. of Hedmark)
• Harvesting: scattered data
(County Gov. of Oppland)
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10. The "Save Mjøsa Campaign" 1977-1981
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Foto: J. E. Løvik
11. 1980 1990 2000 2010
4
6
8
10
År
TotalP(µg/L)
... has altered the water quality
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Less phosphours
1980 1990 2000 2010
1
2
3
4
5
6
År
Klf.a(µg/L)
Less algae
1980 1990 2000 2010
1000
1500
2000
2500
År
Tørrvekt(mg/m2)
Less zooplankton
Løvik & Kjellberg (2003)
Hobæk, Løvik, Rohrlack, Moe m.fl. (2012)
Løvik m.fl. (NIVA-rapport 2015)
12. 16 20 24 28 32 36 40 44
0.0
0.5
1.0
1.5
2.0
2.5
Tid på året (uke nr.)
Biomasse(mg/L)
Total biovolume
1975-1984
1985-1994
1995-2004
2005-2014
Phytoplankton:
• Lower biomass
• Later peak biomass
than in the 70s
Zooplankton:
• Lower biomass
• Earlier peak biomass
than in the 70s
• Towards mismatch?
Seasonal dynamics of plankton has
changed through the decades
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16 20 24 28 32 36 40 44
0
1000
2000
3000
Tid på året (uke nr.)
Tørrvekt(mg/m2)
ZP
1975-1984
1985-1994
1995-2004
2005-2014
13. Data on water quality and plankton:
1972-2015
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14. Data and knowledge - summary
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Excellent data
40 years
12 samples per year
All species
Great data
40 years
7,000 ind.
Few data, but
knowledge
Few data, but
knowledge
15. How can SUSTAIN best combine
and make use of...
• Extensive long-term datasets
• ... missing intermediate trophic levels
• Knowledge on Mjøsa/Lågen:
environment, species, management
• Including data owners and end-users
• Expertise on modelling and statistics
• Bayesian methods
• Participatory modelling
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16. References
Haugen, T. O. et al. 2008. Changes in selection and evolutionary responses in
migratory brown trout following the construction of a fish ladder. Evol. Appl. 1:
319–335.
Hobæk, A., J. E. Løvik, T. Rohrlack, S. J. Moe, M. Grung, H. Bennion, G. Clarke and
G. T. Piliposyan (2012). "Eutrophication, recovery and temperature in Lake
Mjøsa: detecting trends with monitoring data and sediment records."
Freshwater Biology 57(10): 1998-2014.
Løvik, J. E.; Bækken, T.; Kile, M. R.; Skjelbred, B. (2015): Tiltaksorientert
overvåking i vannområde Mjøsa. Årsrapport for 2014. NIVA-rapport 6848.
Løvik, J. E. and G. Kjellberg (2003). "Long-term changes of the crustacean
zooplankton community in Lake Mjøsa, the largest lake in Norway." Journal of
Limnology 62(2): 143-150.
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Editor's Notes
Step 3: Make model more complex and realistic by adding additional (interacting) factors such as…
Phytoplankton biomass
Phosphorus content (eutrophication)
Nitrogen content
Water availability
Stocked vs. wild fish
Harvesting impacts
Will increase predictive power of the model
Step 4: Ask questions to our model
e.g. which factors are most important for population dynamics?
Differences between stocked and wild fish?
Make predictions regarding climate change and managemet scenarios
- Studier av fenologi / timing: ofte konkrete hendelser (f.eks. blomstring)
Sesongdynamikk her styres av flere prosesser: bottom-up, top-down og konkuranse
Prøver å se nærmere på hvilke forklaringsvariabler har mest å si
For utvalgte arter
Dyreplankton:
1 art har senere topp (p=0.<)