Guinness, brown lakes and LTER

posted in: Lake model blog | 0

In this post, Dr. Elvira de Eyto (@edeeyto) introduces one of the PROGNOS case study sites, Lough Feeagh, and describes the historical development of the data collection that is now used in the modelling and forecasting WPs of PROGNOS.

Lough Feeagh is one of five lakes that are being used in the PROGNOS project, linking short term weather forecasts with lake physical and biogeochemical models. Lough Feeagh is the largest lake in the Burrishoole catchment, a watershed in the Nephin Beg mountains which drains into the north east corner of Clew bay (Fig. 1). Here in the west of Ireland, the weather is dominated by frequent depressions rolling in off the north Atlantic, bringing lots of rain (~1.5 m, annual average) and wind. The gulf stream gives us mild weather – snow is rare in winter, as are hot days in summer. This is the perfect climate for development of blanket bog over millennia, and the resulting humic peat soils of the Burrishoole catchment give Lough Feeagh its typical brown colour and dystrophic lake characteristics.

While Feeagh is similar to many of the hundreds of deep, humic lakes found in the west of Ireland, it is unique in terms of the long term monitoring effort that centres around its catchment. Back in the mid 1950’s, the Guinness company were looking for a location to site a research station dedicated to understanding the dynamics of salmon and sea trout populations. The interest was largely based on angling, and understanding how the fishery for much prized “springers” (large salmon returning to freshwater early in the season after more than one winter at sea) could be improved (Fig. 2).

Following negotiations with Major C. Roberts, the fishery owner of Burrishoole, a small lab and hatchery were built on the east shore of Lough Feeagh, and the Salmon Research Trust (SRT) was formed in 1955. For the first decade of its existence, the trust operated on an annual stipend of £3,000 from Guinness, supplemented by some small income from the state. The annual reports of the research station were used to disseminate the results of rearing programs and investigations into the biology of the resident and migratory fish populations. These can be accessed through the open access repository of the Marine Institute at oar.marine.ieand provide a unique insight into the running of a LTER site. The annual reports also catalogue the many staff and students who have worked and studied in Burrishoole over the years. In 1990, Guinness gifted the SRT to the Irish state and it was run as an independent research agency, the Salmon Research Agency of Ireland, until 1999, when it was amalgamated into the newly formed national Marine Institute.

The siting of the original SRT was, in hindsight, ideal for diadromous fish stock analysis, owing to the fact that the Burrishoole catchment is typographically well defined, with high mountains delineating the 100km2 area which drains into Lough Feeagh. From there, two short channels drop 15 metres into Lough Furnace, a coastal lagoon with a direct tidal connection to the Atlantic Ocean (Fig. 3). The structure of these two channels, the natural Salmon Leap, and the man-made Mill Race, lent themselves to the construction of fish traps which can totally capture the migration of salmon (Salmo salar) and trout (Salmo trutta) entering and exiting the catchment, and silver eel (Anguilla anguilla) returning to the Sargasso sea to spawn. These traps have allowed a complete census of all migratory fish movements since 1970. Long term data of this kind are very rare, but play an important role in understanding and conserving fish stocks (e.g. 1, 2). During the lifetime of the research station, many scientific advances have been made in areas including salmonid rearing (e.g. 3, 4), impacts of introgression between wild and reared fish (e.g. 5, 6), phenology (e.g. 7–9) and fish evolution (e.g. 10–13).

While the main work of the research station has always been focussed on fish, scientists working in Burrishoole were acutely aware of the role of climate and catchment processes in determining fish production. The annual reports of the last 60 years describe a host of catchment research projects, often carried out by visiting students with the help of staff based in Burrishoole. The first long term monitoring instruments installed in Burrishoole in the late 1950s included a weather station (in partnership with Met Éireann) and a paper chart recorder of the surface water temperature of Lough Feeagh. These data now form one of the longest running continuous records of lake surface water temperature in the world and are used to assess the impact of our warming climate on lake temperature (e.g. 14, 15). Increasing concern in the 1980s about how land use changes such as afforestation and overgrazing were affecting the catchment kick-started a concerted effort to monitor the catchment upstream of the fish traps. In order to provide a context for these changes, palaeolimnological reconstructions of catchment processes were carried out on both Lough Feeagh and Furnace, which chronicle the development of these two lakes in response to climate and land use changes (16, 17).
During the 1990s, fruitful collaboration with European partners, particularly CEH in the UK (formerly the Institute of Freshwater Ecology), led to the development and deployment of several automatic water quality monitoring stations in Burrishoole which allowed water quality data to be collected at high frequency (sub-hourly) and remotely (18) (Fig. 4). In the 20 years since these initial deployments, this monitoring network has been maintained and developed by the Marine Institute, and is now a central part of the research work at the station (real-time data can be viewed here: Burrishoole Dashboard).

While our initial interest in HFM (high frequency monitoring) was directly related to understanding fish dynamics and production, it became apparent that the data can be used in a much wider context. For example, data from the HFM stations in Burrishoole have been used to investigate carbon cycling (19, 20), whole lake ecosystem metabolism (21–23), deep chlorophyll maxima (24), water to air heat fluxes (25) and lake physical processes (26, 27). Many of these papers were the result of our involvement with the GLEON (Global Lake Ecological Observatory Network ) and NETLAKE ( communities, which has brought our data to a wider audience and has strengthened our resolve to maintain these datasets as a national and international resource.

High frequency monitoring really starts to pay dividends when we start to think about the response of aquatic ecosystems to episodic events, such as heat waves, excessive rainfall and drought. Having the monitoring infrastructure in place to catch such events is crucial in quantifying impacts and determining how long it might take a lake or river to recover (28, 29). For the PROGNOS project, we are working on coupling catchment and lake models with short range weather forecasts to understand how episodic events such as Atlantic storms affect the flux of DOM (Dissolved Organic Matter) into Lough Feeagh. DOM is a costly substance to treat in water treatment plants, and being able to predict significant pulses could bring about better management and cost efficiencies. Although Feeagh itself is not currently used as a water supply, it is a useful index for many humic lakes along the Atlantic seaboard of Ireland which are a significant source of drinking water to the country. As we already have the requisite monitoring infrastructure in place in Burrishoole, we are well placed to “catch” these DOM pulses, and the wealth of data available from the catchment will hopefully mean that we can develop an accurate model of how these pulses move through Lough Feeagh. Check back here for more updates from Tadhg Moore (@tadhg_moore) and Dr. Eleanor Jennings (@EleanorJennin11) who are the other Irish participants working with Burrishoole LTER data.

References mentioned in this post:

1. E. de Eyto et al., The response of North Atlantic diadromous fish to multiple stressors, including land use change: a multidecadal study. Can. J. Fish. Aquat. Sci. 73, 1759–1769 (2016).
2. W. R. Poole et al., in Sea Trout: Biology, Conservation and Management, G. Harris, N. Milner, Eds. (Blackwell, Oxford, 2006;, pp. 279–306.
3. D. Cotter et al., Comparison of freshwater and marine performances of all-female diploid and triploid Atlantic salmon (Salmo salar L.). Aquac. Res. 33, 43–53 (2002).
4. A. Moore et al., The impact of a pesticide on the physiology and behaviour of hatchery-reared Atlantic salmon, Salmo salar, smolts during the transition from fresh water to the marine environment. Fish. Manag. Ecol. 15, 385–392 (2008).
5. P. McGinnity et al., Impact of naturally spawning captive-bred Atlantic salmon on wild populations: depressed recruitment and increased risk of climate-mediated extinction. Proc. R. Soc. Lond. B Biol. Sci. 283, 3601–3610 (2009).
6. P. McGinnity et al., Fitness reduction and potential extinction of wild populations of Atlantic salmon, Salmo salar, as a result of interactions with escaped farm salmon. Proc. R. Soc. Lond. B Biol. Sci. 270, 2443–2450 (2003).
7. C. J. Byrne, R. Poole, M. Dillane, G. Rogan, K. F. Whelan, Temporal and environmental influences on the variation in sea trout (Salmo trutta L.) smolt migration in the Burrishoole system in the west of Ireland from 1971 to 2000. Fish. Res. 66, 85–94 (2004).
8. P. McGinnity et al., Population specific smolt development, migration and maturity schedules in Atlantic salmon in a natural river environment. Aquaculture. 273, 257–268 (2007).
9. O. T. Sandlund et al., Timing and pattern of annual silver eel migration in two European watersheds are determined by similar cues. Ecol. Evol. 7, 5956–5966 (2017).
10. E. de Eyto et al., Varying disease-mediated selection at different life-history stages of Atlantic salmon in fresh water. Evol. Appl. 4TY–JOUR, 749–762 (2011).
11. C. L. O’Toole et al., The signature of fine scale local adaptation in Atlantic salmon revealed from common garden experiments in nature. Evol. Appl. 8, 881–900 (2015).
12. M. Ravinet et al., Where the Lake Meets the Sea: Strong Reproductive Isolation Is Associated with Adaptive Divergence between Lake Resident and Anadromous Three-Spined Sticklebacks. PLOS ONE. 10, e0122825 (2015).
13. T. E. Reed et al., Quantifying heritable variation in fitness-related traits of wild, farmed and hybrid Atlantic salmon families in a wild river environment. Heredity. 115, 173–184 (2015).
14. C. M. O’Reilly et al., Rapid and highly variable warming of lake surface waters around the globe. Geophys. Res. Lett. 42, 10773–10781 (2015).
15. R. I. Woolway et al., Global climate–lake surface temperatures. Bull. Am. Meteorol. Soc. 97, S17–S18 (2016).
16. F. Cassina et al., A multi-proxy palaeolimnological study to reconstruct the evolution of a coastal brackish lake (Lough Furnace, Ireland) during the late Holocene. Palaeogeogr. Palaeoclimatol. Palaeoecol. 383–384, 1–15 (2013).
17. C. Dalton et al., Anthropocene environmental change in an internationally important oligotrophic catchment on the Atlantic seaboard of western Europe. Anthropocene. 5, 9–21 (2014).
18. M. Rouen, G. George, J. Kelly, M. Lee, E. Moreno-Ostos, High-resolution automatic water quality monitoring systems applied to catchment and reservoir monitoring. Freshw. Forum. 23, 20–37 (2010).
19. E. Jennings et al., in The Impact of Climate Change on European Lakes, G. George, Ed. (Springer, London, 2010), Aquatic Ecology Series, pp. 199–220.
20. E. Ryder, E. de Eyto, M. Dillane, R. Poole, E. Jennings, Identifying the role of environmental drivers in organic carbon export from a forested peat catchment. Sci. Total Environ. 490, 28–36 (2014).
21. K. C. Rose et al., Improving the precision of lake ecosystem metabolism estimates by identifying predictors of model uncertainty. Limnol. Oceanogr. Methods. 12, 303–312 (2014).
22. C. T. Solomon et al., Ecosystem respiration: Drivers of daily variability and background respiration in lakes around the globe. Limnol. Oceanogr. 58, 849–866 (2013).
23. G. Yvon-Durocher et al., Reconciling the temperature dependence of respiration across timescales and ecosystem types. Nature. advance online publication (2012) (available at
24. J. A. Brentrup et al., The potential of high-frequency profiling to assess vertical and seasonal patterns of phytoplankton dynamics in lakes: An extension of the Plankton Ecology Group (PEG) model. Inland Waters. 6, 565–580 (2016).
25. G. A. Weyhenmeyer et al., Citizen science shows systematic changes in the temperature difference between air and inland waters with global warming. Sci. Rep. 7 (2017) (available at
26. J. S. Read et al., Lake-size dependency of wind shear and convection as controls on gas exchange. Geophys. Res. Lett. 39, L09405 (2012).
27. R. I. Woolway et al., Diel Surface Temperature Range Scales with Lake Size. PLOS ONE. 11, e0152466 (2016).
28. E. de Eyto et al., The response of a humic lake ecosystem to an extreme precipitation event: physical, chemical and biological implications. Inland Waters. 6, 483–498 (2016).
29. E. Jennings et al., Effects of weather-related episodic events in lakes: an analysis based on high-frequency data. Freshw. Biol. 57, 589–601 (2012).