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: Temperature.Data@marlab.ac.uk

• Web: http://www.gov.scot/Topics/marine/Salmon-Trout-Coarse/Freshwater/Monitoring/temperature