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Scotland River Temperature Monitoring Network
Temperature and salmonids• Influences:
– spawning location and timing– Embryo development and timing of hatch
and emergence– Feeding and growth– Productivity– Size at age– Population demographics (age at
smolting, lifetime mortality)– Survival at temperature extremes
Background• 2010 CAMERAS (co-ordinated agenda for marine,
environment and rural affairs science) monitoring strategy
• No systematic, large scale, quality controlled temperature data collection in Scotland
• Freshwater MAP (monitoring action plan) monitoring gaps– Stream temperature change– Efficacy of riparian woodlands to mitigate change
• Action: Develop a co-ordinated network for river temperature monitoring
• 2013 NERC funding for PhD support (Faye Jackson)
Previous Research
Moorland
2km woodland
Malcolm, I. A., Soulsby, C., Hannah, D. M., Bacon, P. J., Youngson, A. F. and Tetzlaff, D. (2008). The influence of riparian woodland on stream temperatures: implications for the performance of juvenile salmonids. Hydrol. Process. 22, 968–979. doi: 10.1002/hyp.6996
Previous research•Multiple Linear regression models of river temperature
•Single river (Dee)
•Predictions of current and future river T
•Simplistic representation of forest effects
•No spatial correlation
•Sampling spatial rather than targeted
Hrachowitz, M., Soulsby, C., Imholt, C., Malcolm, I. A. and Tetzlaff, D. (2010). Thermal regimes in a large upland salmon river: a simple model to identify the influence of landscape controls and climate change on maximum temperatures. Hydrological Processes. 24, 3374–3391. doi: 10.1002/hyp.7756
Objectives of SRTMN1. Characterise river T across Scotland
2. Identify areas susceptible to climate change
3. Improve understanding of controls on T
4. Develop models to predict T change
5. Determine optimum areas for riparian tree planting
6. Assess long-term trends in T
Managed within a quality controlled (JCoP) network with common standards for data collection and storage (FLEObs)
Design of the SRTMN
• Identify landscape controls on T
• Select some representative catchments
• Generate GIS based proxies– Location (x,y coordinates), elevation, slope, upstream catchment area, channel
orientation, channel width, hillshading, distance to coast , riparian woodland
• Ensure sites cover environmental range
• Consider use of existing monitoring sites
Ensuring coverage of the environmental range
Black points = evenly spread grid over the environmental range Green points = potential sites Red points = selected site
Blue points = alternative sites Yellow points = current monitoring sites
Check adequate coverage • Grey points = potential
sites• Red sites = selected
sites• Good coverage of
environmental range
Jackson F.L. Malcolm I.A. Hannah D.M. (in press) A novel approach for designing large-scale river temperature monitoring networks. Hydrology Research. DOI: 10.2166/nh.2015.106
Logger deployment • Loggers deployed winter 2014 - spring 2015• MSS in collaboration with local fisheries
trusts / SEPA where possible
Trusts: • River Dee Trust• Tweed Foundation• Caithness District Salmon Fishery Board• River Brora District Salmon Fishery Board• Kyle of Sutherland Fisheries Trust• Argyll Fisheries Trust• Ayrshire Rivers Trust• Galloway Fisheries Trust• Spey Foundation
Preliminary results • 25 sites on River Spey 2015 ‘proof of
concept’ for upscaling
• Develop a model to predict 7 day
mean maximum water temperature
(Tmax)
• Elevation ↑ = Tw ↓• River distance to sea ↑ = Tw ↑• Woodland ↑ = Tw ↓
Further information• E-mail: [email protected]
• Web: http://www.gov.scot/Topics/marine/Salmon-Trout-Coarse/Freshwater/Monitoring/temperature