an ecohydrological investigation into the relationship
TRANSCRIPT
Rob Starkie
Supervisors: Professor Neil Macdonald and Dr Thea Wingfield
Dissertation submitted as partial fulfilment for the degree of M.Sc. in Environmental Science
School of Environmental Sciences, University of Liverpool, 2020-21
Word count: 9350
An ecohydrological investigation
into the relationship between river
flow regime and juvenile Salmonid
populations in the River Ribble
catchment, NW England.
Declaration
I hereby declare that the following dissertation is based on the results of investigations conducted by myself, and that this dissertation is of composition. This dissertation has not, in whole, or part, been previously submitted, to any university of institution for any degree, diploma, or other qualification. Work other than my own is clearly indicated in the text by reference to the relevant researcher or publications. Signed: R. Starkie Date: 09/09/2021 The work presented in this dissertation is the work of the candidate. Conditions of the relevant ordinance and regulations of the University of Liverpool have been fulfilled.
Acknowledgments
I would like to thank my supervisors Professor Neil Macdonald and Dr. Thea
Wingfield for their advice and guidance throughout my MSc Dissertation
project. I would also like to thank Mike Forty, from The Ribble Rivers Trust for
his help and advice during this project. Finally, I would like to thank The
Ribble Rivers Trust, as this project would not have been possible without
them sharing their electrofishing data with me.
Abstract
Atlantic Salmon (Salmo salar) and Brown Trout (Salmo trutta) are key species
in the river systems in the UK and are protected as priority species under the
UK POST-2010 Biodiversity Framework. They require ecological stability and
are an indicator of water and habitat quality. The number of juvenile Atlantic
Salmon and Brown Trout have been decreasing in River Ribble and its sub-
catchments, the Calder and Hodder since 2009. The aim of this study is to
determine if high flow events are negatively impacting the number of juvenile
Salmonids in the Ribble system and to determine if the number of adult
Salmonids returning to spawn is decreasing.
Cumulative densities of Atlantic Salmon fry and Brown Trout fry for the Ribble,
Calder and Hodder were obtained from The Ribble Rivers Trust who undertake
annual electrofishing surveys in the summer. Hydrological data from the
National River Flow Archive (NRFA) was analysed using the Indicators of
Hydrologic Alteration (IHA) software. The flow regimes of the Ribble, Calder
and Hodder all indicate an increase in annual median flow since 2009 and an
increase in December median flow. Statistically significant relationships
between March median flow and the cumulative densities of Atlantic Salmon
and Brown Trout fry were observed in each of the Ribble, Hodder and Calder,
indicating that high flows in March result in lower cumulative densities of fry in
the summer.
Table of Contents
1. Introduction 1
1.1. Flow Regime 1
1.1.1. Human Impacts on Flow Regime 2
1.2. Salmonids 2
1.2.1. Lifecyle of Salmonids 3
1.2.2. Salmonids and Flow Regime Requirements 4
1.2.2.1. Spawning 5
1.2.2.2. Incubation 5
1.2.2.3. Fry emergence 6
1.2.3. Temperature and early life stages of Salmonids 6
1.2.4. Other pressures on Salmonids 7
1.2.5. Salmonid trends in the UK 8
1.2.6. Salmonids in the Ribble Catchment 8
1.3. Aims of research 10
2. Methodology 11
2.1. Study area 11
2.2. Electrofishing Data 12
2.3. Daily Flow Data 14
2.3.1. Indicators of Hydrologic Alteration (IHA) 14
2.4. Rod Catch and Fish Counter Data 15
2.4.1. Limitations of Rod Catch and Fish Counter Data 15
2.5. Atmospheric Temperature Data 16
2.6. Statistical Analysis 16
3. Results 17
3.1. Hydrological Data 17
3.1.1. Annual Flow Data 17
3.1.2. Indicators of Hydrologic Alteration (IHA) Analysis: IHA Parameter 1 18
3.2. Salmonid Data 21
3.2.1. Cumulative Density of Atlantic Salmon fry 21
3.2.2. Cumulative Density of Brown Trout fry 22
3.3. Rod Catch Data 24
3.4. Waddow Fish Counter Data 25
3.5. Analysis of Flow and Salmonids 26
3.6. Atmospheric temperature and Salmonids 30
4. Discussion 31
4.1. Hydrological Data 31
4.2. Salmonid Data 32
4.2.1. Rod Catch and Fish Counter 33
4.2.2. Juvenile Salmonids and Median Monthly Flow 33
4.2.3. Salmonids and Atmospheric Temperature 36
4.3. Future Climate Scenarios 37
4.4. Management Solutions 37
5. Conclusion 38
Bibliography 41
Appendices 50
Appendix A: NFCS Trout fry Classifications (2009-2020) 50
Appendix B: NFCS Salmon Fry Classifications (2009-2020). 62
Appendix C: Data used for Dissertation 74
Record of Meetings 75
List of Figures
Figure 1: Basic life cycle of Atlantic Salmon (Salmo salar) from freshwater phase to
salt water phase (Taken from, Marsh (2020) …………………………………………….4
Figure 2: (a) Total declared rod catch of Salmon (1956-2019) and (b) total declared
rod catch of Trout (1978-2019) for England and Wales (Environment Agency (EA),
2020) …………………………………………….…………………………………………...8
Figure 3: Cumulative densities of Atlantic Salmon fry recorded on the Ribble, Calder
and Hodder from electrofishing surveys conducted by The Ribble Rivers Trust (The
Ribble Rivers Trust, 2020) …………………………………………………………………9
Figure 4: Cumulative densities of Atlantic Salmon fry recorded on the Ribble, Calder
and Hodder from electrofishing surveys conducted by The Ribble Rivers Trust (The
Ribble Rivers Trust, 2020) ……………………………………………………………….10
Figure 5: The location of the River Ribble, Calder and Hodder in North West
England (The Ribble Rivers Trust, 2015) ……………………………………………….12
Figure 6: Locations of sites used from The River Ribble Trust electrofishing surveys
of Atlantic Salmon and Brown Trout for the River Ribble (42 sites), Calder (48 sites)
and Hodder (35 sites) ……………………………………………………………………..13
Figure 7: Ribble (71006) annual median flow (m3s-1) and long term annual median
flow (m3s-1) (1969-2019) ………………………………………………………………….17
Figure 8: Calder (71004) annual median flow (m3s-1) and long term annual median
flow (m3s-1) (1964-2019) ………………………………………………………………….18
Figure 9: Hodder (71008) annual median flow (m3s-1) and long term annual median
flow (m3s-1) (1976-2019) ………………………………………………………………….18
Figure 10: IHA Parameter 1 Median monthly flows (m3s-1) for (a) Ribble (1969-
2019); (b) Calder (1964-2019); (c) Hodder (1976-2019) …………………………......19
Figure 11: Comparison of Median monthly flows (m3s-1) for (a) Ribble (1969-2019
and 2009-2019); (b) Calder (1964-2019 and 2009-2019); (c) Hodder (1976-2019 and
2009-2019) …………………………………………………………………………………20
Figure 12: Cumulative density (Fish/100m2) of Atlantic Salmon fry in the: (a) Ribble;
(b) Calder; (c) Hodder (2009-2020) …………………………………………….............22
Figure 13: Cumulative density (Fish/100m2) of Brown Trout fry in the: (a) Ribble; (b)
Calder; (c) Hodder (2009-2020) ………………………………………………...............23
Figure 14: Total declared rod catch of Atlantic Salmon in the Ribble (1996-2019)
(Environment Agency, 2020) …………………………………………...........................24
Figure 15: Total declared rod catch of Brown Trout in the Ribble (1996-2019)
(Environment Agency, 2020) …………………………………………...........................25
Figure 16: Number of rod licenses sold in Lancashire and Cumbria (2010-2018)
(Environment Agency, 2015) …………………………………………...........................25
Figure 17: Number of fish counted moving (a) upstream and (b) downstream at
Waddow weir fish counter (1996-2019) (The Ribble Rivers Trust) ……………….....26
Figure 18: Relationship between March median monthly flow (m3s-1) and the
cumulative density of Brown Trout fry (Fish/100m2) for (a) Ribble, (b) Calder and (c)
Hodder (2009-2019) …………………………………………........................................28
Figure 19: Relationship between March median monthly flow (m3s-1) and the
cumulative density of Atlantic Salmon fry (Fish/100m2) for (a) Ribble, (b) Calder and
(c) Hodder (2009-2019) …………………………………………..................................29
List of Tables
Table 1: National Fisheries Classification System (NFCS) for Brown Trout and
Atlantic Salmon 14
Table 2: IHA Parameter Groups (Nature Conservancy, 2009) 15
Table 3: Spearman correlation matrix of median monthly flow (m3s-1) and cumulative
density (fish/100m2) of Atlantic Salmon and Brown Trout Fry for the Ribble,
Calder and Hodder. 27
Table 4: Spearman correlation matrix of mean air temperature (°c) and cumulative
density of Brown Trout and Atlantic Salmon (2009-2019). 31
1
1. Introduction
1.1. Flow Regime
The flow regime of a river is an important factor in determining the structure and
function of stream ecosystems (Poff et al., 1997; Poff and Zimmerman, 2010;
Warren et al., 2015). It is widely recognized and accepted that flow regime is
critical for sustaining the health of riverine ecosystems, creating, and
maintaining river morphology and sustaining water quality via the flushing of
nutrients and contaminants (Old and Acreman, 2006, Warren et al., 2015).
These processes influence the abundance and distribution of biota and in turn
also determine the spatial and temporal distribution of fish (Jowett et al., 2005,
Poff and Zimmerman, 2010; Warren et al., 2015). Aquatic organisms are
adapted to a range of natural flow variations (Poff et al., 1997; Richter et al,
2003; Enders et al., 2009), which refer to the historical status of the river before
the development of the river catchment (Enders et al., 2009). Flow regime is of
the upmost importance in sustaining the ecological integrity of riverine
ecosystems (Poff et al., 1997). Poff et al., (1997) outlines the 5 main elements
that define the variability in flow regime and thus also the ecological processes
of the river ecosystems, these include:
(1) The magnitude of discharge of a given time period
(2) The occurrence frequency of different magnitudes of discharge
(3) The duration of flow events
(4) The timing
(5) The rate of change of hydrological condition
These 5 factors influence ecological integrity both directly and indirectly and so
any modification to flow will have a cascading impact on the ecological integrity
of a river ecosystem (Karr, 1991; Poff et al., 1997).
2
1.1.1. Human Impacts on Flow Regime
Human activities can also influence and alter the natural flow regime both
directly and indirectly. These changes can result in reduced or increased flow,
and cause temporal and spatial changes to flow regimes (Poff et al., 1997).
Direct activities include flow regulation using weirs and damns and/or water
extraction (Benejam et al., 2010). Indirect activities such as land use patterns
also impact fish populations (Warren et al., 2015).
The amount of water abstracted from non-tidal surface water and groundwater
per year in England has declined from a peak of 11.6 billion cubic metres in
2001 to 8.2 billion cubic metres in 2008 (Defra, 2019). However, following the
increase in water usage for the generation of electricity, abstraction has
increased to 10.4 billion cubic metres in 2017 (Defra, 2019). Due to the
influence that human activities can have on the flow regime of rivers, the Water
Framework Directive (WFD) was developed by the European Commission
(EC). The WFD requires the development of relevant procedures to help ensure
there is sufficient mitigation of any negative impacts created as a result of water
abstraction and/or impoundments (Old and Acreman, 2010).
1.2. Salmonids
Atlantic Salmon (Salmo salar) and Brown Trout (Salmo trutta) are migratory fish
native to the UK. They are anadromous, meaning they spend their early life
stages in freshwater, before travelling into saltwater environments to feed,
before returning back to freshwater to spawn (Crisp, 1999; Jonsson and
Jonsson, 2011). Atlantic Salmon and Brown Trout are protected priority species
under the UK Post-2010 Biodiversity Framework (Warren et al., 2015) and are
both considered to be economically important species (Pennel and Prouzet,
2009; Gillson et al., 2020).
As both species require good water quality they are often used as an indicator
species for sound management and conservation of fluvial and riverine
resources (Crisp, 2000). Both species are also considered to be a useful
3
indicator of the impact of flow regime on ecosystems across a variety of scales
(Milner et a., 2012).
1.2.1. Lifecyle of Salmonids
Atlantic Salmon and Brown Trout are known for their variable life history
strategies and adaptations to their local environments (Bjørnås, 2020). A basic
life cycle (Figure 1) is common of both the Atlantic Salmon and Brown Trout
(Crisp, 2000). On the spawning grounds the female creates a depression in the
gravel of the riverbed called a Redd and deposits her eggs into it (Crisp, 2000).
In the United Kingdom (UK) this typically occurs between November and
February.
The embryos then develop over winter within the gravel substratum and hatch
in the subsequent spring (Jonsson and Jonsson, 2011). Once hatched they
become known as alevins, and for the first several weeks they dwell in the
bottom substratum, feeding on yolk, located in a sac on their bellies (Crisp,
2000; Jonsson and Jonsson, 2011; Bjørnås, 2020). Once the yolk sacs are
nearly depleted the alevins emerge from the gravel and become known as fry
(Crisp, 2000). The fry begin externally feeding on small invertebrates found in
the water column and within the substrate (Jonsson and Jonsson, 2011). This
period is associated with high mortality (Armstrong and Nislow, 2006; Bjørnås,
2020).
Over autumn the fry develop into parr and are recognizable by the dark vertical
bars along their bodies (Jonsson and Jonsson, 2011). They feed on aquatic
insects and growth continues until they reach a body length of 10-15cm, at
which the parr transform to smolts (Jonsson and Jonsson, 2011) through a
process typically referred to as smolting or smoltification. Atlantic Salmon
smolts typically migrate to sea in the spring and very rarely return to spawn the
year they move to sea, instead they stay at sea for 1-4 years before attaining
maturity and returning to spawn (Jonsson and Jonsson, 2011). Brown Trout
smolts however feed mainly in estuaries and coastal waters and rarely migrate
into open sea, with the majority of the Brown Trout feeding within 100km of the
4
river mouth (Jonsson and Jonsson, 2011). Unlike Atlantic Salmon, Brown Trout
often return to their home river to spawn or for wintering.
1.2.2. Salmonids and Flow Regime Requirements
The complex freshwater life cycle of Atlantic Salmon and Brown Trout have
evolved to utilize the natural variations in flow regime (Enders et al., 2009) and
the general flow requirements of Atlantic Salmon and Brown Trout are well
established. Due to their importance, Salmonids have been the chief focus of
research into the impacts of altered flow regimes (Milner et al., 2011; Warren
et al., 2015; Quinn, 2018)
Despite the widespread view that Salmonids prefer high velocity habitats,
different life stages require different flow regime characteristics (Nislow and
Armstrong, 2012; Warren et al., 2015). The effects, both direct and indirect, of
river flow will impact different Salmonid life stages in different and often
contrasting ways (Milner et al., 1998; Nislow and Armstrong, 2012; Warren et
Figure 1: Basic life cycle of Atlantic Salmon (Salmo salar) from freshwater phase to salt water phase (Taken from, Marsh (2020).
5
al., 2015). The impact on the different life stages of salmonids is dependent on
timing and duration of low and high flow events (Solomon and Sandbrook,
2004; Warren et al., 2015). High flow events typically have a greater impact
upon juvenile Salmonids, and low flow events are more likely to impact adult
Salmonids returning to spawn (Nislow and Armstrong, 2012). As the focus of
this research is on juvenile Salmonids, the flow requirements of the relevant
freshwater life stages will be outlined below.
1.2.2.1. Spawning
The flow conditions in autumn and early winter will have an impact on the
spawning location and spawning success of both Atlantic Salmon and Brown
Trout (Gray, 2015). Low flow conditions in these months will have a significant
impact on spawning location, due to the inaccessibility of upstream spawning
grounds (Crisp, 1999). This is likely to have a marked effect upon the
subsequent Salmonid parr production (Gray, 2015). The choice of spawning
location is believed to be strongly influenced by the characteristics of the
riverbed, which is determined by the hydraulic conditions that distribute and sort
the sediment (Gray, 2015). There is evidence to suggest that Salmonids may
choose not to spawn during periods of rapidly changing flow conditions, this
may also impact spawning success (Moir et al., 2006; Gray, 2015).
1.2.2.2. Incubation
The survival of the egg to fry is largely dependent on winter flow conditions and
temperature (Crisp, 1999). Winter flood events are correlated with low egg
survival, as they result in the displacement and mobilization of sediment which
can damage and/or entrap the eggs (Crisp, 1999; Warren et al., 2015). Egg
survival is also correlated with low discharge and cold winters, as low flow
conditions leaves the eggs exposed and vulnerable to freezing and desiccation
(Crisp, 1999).
High flows in the spring can scour the Redds and result in the transport of eggs
and/or alevins downstream to less favourable conditions, this phenomenon is
6
referred to as ‘wash out’ (Crisp, 1999; Warren et al., 2015). Wash out can cause
mortality to intra-gravel stages of Salmonid (Jensen and Johnsen, 1999; Gray,
2015). This can occur by physical shock to the egg, damage to the Redd,
predation of the eggs during transportation in the water column and due to the
deposition of the egg in sup-optimal locations for development (Crisp, 1999;
Jensen and Johnsen, 1999; Cowx and Fraser, 2003, Gray, 2015).
1.2.2.3. Fry emergence
The emergence of fry is thought to be a compromise between the fry gaining
an advantage through the early establishment of territory against the risk of
early season high flow events (Fausch et al., 2001; Armstrong and Nislow,
2006). However, climate change and more extreme weather patterns may be
impacting this adaptation. After emergence Salmonid fry typically travel less
than 100m (Cowx and Fraser, 2003), and seek out low velocity nursery
grounds, due to their limited swimming ability and size (Crisp, 1999; Gray,
2015). During this stage, the Salmonid fry are still susceptible to high flow
events and wash out downstream (Crisp, 1999; Gray, 2015).
However, over time, as the fry increase in size through feeding, the risk of wash
out is reduced due to increased swimming ability meaning they can withstand
higher velocities (Heggenes, 1990; Crisp, 1999; Hendry and Cragg-Hine,
2000). Research by Heggenes and Traaen (1998) showed that over an eight-
week period of feeding, the velocity needed to displace fry increased from 19
cm/s-1 to 50 cm/s-1.
1.2.3. Temperature and early life stages of Salmonids
There has been a significant amount of research into other factors that impact
Salmonid numbers, including the impacts of atmospheric temperature and
water temperature. Salmonids have very limited control over their body
temperature (Crisp, 1991; Environment Agency, 2008; Jonsson and Jonsson,
2011), and therefore temperature has an impact upon the distribution,
migration, growth, reproduction, and survival of Salmonids (Environment
Agency, 2008).
7
The rate of Salmonid egg development is temperature dependent (Crisp, 1988;
Environment Agency, 2008; Jonsson and Jonsson, 2011). Research has
shown the relationship between the duration of the incubation period and
temperature, with lower temperatures resulting in longer incubation periods and
higher temperatures resulting in shorter incubation periods (Crisp, 1988; Kane
1988). Eggs which develop at lower temperatures typically hatch much smaller
in size but with more yolk, compared to eggs which develop at medium-high
temperatures, which are larger in size but have less yolk (Jonsson and
Jonsson, 2011).
Temperature also impacts Salmonids at the alevins life stage in a similar way,
with lower temperatures resulting in a longer period between hatching and first
feeding, whilst higher temperatures result in a shorter period between hatching
and first feeding (Kane, 1988; Jensen et al., 1989; Environment Agency, 2008).
1.2.4. Other pressures on Salmonids Salmonids are affected by several other pressures not just alterations to the
flow regime or temperature changes. These include but are not limited to
(Hendry and Cragg-Hine, 2000; Hansen et al., 2012; Gray, 2015):
• Water pollution from chemicals and organic wastes
• Physical barriers to migration
• Over exploitation at sea and over exploitation in freshwater
environments
• Siltation of spawning gravels caused by soil erosion
• Eutrophication caused by excess nutrients and fertilizers, in particular
phosphate-based fertilizers
• Habitat loss and destruction of spawning grounds
• Parasites and disease such as to Ulcerative dermal necrosis (UDN)
• Climate Change
• Invasive species
8
1.2.5. Salmonid trends in the UK
Rod catch data from the Environment Agency (EA) for the Atlantic Salmon and
Brown Trout appear to show that their numbers have been decreasing over
time (Figure 2a and Figure 2b). With numbers of Atlantic Salmon caught falling
below the long-term average since 2013 and Brown Trout since 2012.
1.2.6. Salmonids in the Ribble Catchment
Since 2008 the Ribble Trust have carried out electrofishing every summer in
the Ribble catchment, along with the catchments of its two main tributaries, the
Hodder, and the Calder. Annual fisheries reports, by The Ribble Rivers Trust,
shows that cumulative densities of both Atlantic Salmon fry (Figure 3) and
Brown Trout fry (Figure 4) have decreased since 2010 (The Ribble Rivers Trust,
2020). The Ribble Trust have hypothesized that high flow events during critical
1956 1966 1976 1986 1996 2006 2016
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
Year
Tota
l dec
lear
ed S
alm
on
ro
d c
atch
Total Long term mean (a)
1978 1988 1998 2008 2018
0
10,000
20,000
30,000
40,000
50,000
60,000
Year
Tota
l dec
lear
ed T
rou
t ro
d
catc
h
Total Long term mean(b)
Figure 2: (a) Total declared rod catch of Salmon (1956-2019) and (b) total declared rod catch of Trout (1978-2019) for England and Wales (Environment Agency (EA), 2020).
9
early life stages may be a potential reason for the decline in both Atlantic
Salmon and Brown Trout fry (The Ribble Rivers Trust, 2020).
There is also anecdotal evidence that the decline in Atlantic Salmon is not a
new phenomenon, and that the decrease has been occurring over a much
longer period of time. In the book ‘The River Ribble’ by Freethy (1988) it states
that the people of Lancashire used to travel to Paythorne Bridge, typically
during the third week of November, for the event known locally as ‘Salmon
Sunday’. The people would watch as the Salmon travelled upstream to their
spawning grounds. However, Freethy (1988) also explains that the locals state
there appears to be fewer fish returning each year.
The history of reduced number of Salmonids in the Ribble also goes back even
further. Walshingham (1993) refers to the work of Houghton (1952) who traced
the history of Salmon and Trout numbers in the Ribble back to medieval times.
In 1899 and 1900 a total number of zero Salmon were caught in the Ribble,
which was attributed to pollution from heavy industry, overfishing and the
number of weirs preventing upstream migration (Walshingham, 1993). The
recovery of the Ribble from the levels seen in 1900 was largely due to the
introduction of the Fisheries Act in 1923 and the restocking of the Ribble using
20,000 Fry from the River Thurso in Scotland (Walshingham, 1993).
Furthermore, the Witcherwell hatchery which was located in the upper section
of the Hodder also stocked the Ribble system, before closing in 1997.
Figure 3: Cumulative densities of Atlantic Salmon fry recorded on the Ribble, Calder and Hodder from electrofishing surveys conducted by The Ribble Rivers Trust (The Ribble Rivers Trust, 2020)
10
1.3. Aims of research
This study will assume that flow is the major determinant affecting juvenile
Salmonid populations in the River Ribble and its sub-catchments. However,
impacts of other important factors such as temperature will be highlighted but
discussed in less detail. Furthermore, this study will focus solely on the
freshwater catchment phase of the Atlantic Salmon and Brown Trout life cycle
in the River Ribble, Calder and Hodder. The aims and objectives of this
research are:
1. To determine if high flow events in the River Ribble and its sub-catchments
are negatively impacting the number of juvenile Salmonids
a. Assess the flow regime of the Ribble, Calder and Hodder
2. To determine if a decrease in returning Salmonid fish stock is responsible
for the decrease in the number of juvenile Salmonids
a. Use fish counter data and rod catch data as a proxy for the number
of adult Salmonids returning to spawn
3. To determine if there is a relationship between temperature and the number
of juvenile Salmonids in the River Ribble and its sub-catchments
a. Use local atmospheric temperature data to assess if there is a
relationship between temperature and juvenile Salmonids.
Figure 4: Cumulative densities of Atlantic Salmon fry recorded on the Ribble, Calder and Hodder from electrofishing surveys conducted by The Ribble Rivers Trust (The Ribble Rivers Trust, 2020)
11
2. Methodology
2.1. Study area
The Ribble catchment is located in the North West of England in the United
Kingdom (Figure 5). The source of the River Ribble is at the confluence of Gayle
Beck and Cam Beck, located near the Ribblehead viaduct in the Yorkshire
Dales (The Ribble Rivers Trust, 2021a). The Ribble flows 121km through
Yorkshire and Lancashire (Gray, 2015), before flowing out into the Irish Sea
between Southport and Lytham (Figure 5).
The upper Ribble is sparsely populated and is primarily used for sheep farming.
As the River Ribble flows towards Lancashire, the land becomes more fertile
resulting in dairy farming and increased areas of pasture (The Ribble Rivers
Trust, 2021a). The River Ribble grows considerably in the lower regions of the
catchment, where the River Hodder and River Calder join just after Mitton
forming the ‘Big Ribble’. This region again consists of fertile land used for
pasture and dairy farming (NRFA, 2021). The Ribble becomes tidal in Preston
and flows through the fertile Fylde plain and out into the Irish Sea.
The River Hodder originates within the Forest of Bowland, an area of
Outstanding Natural Beauty, with the uplands being in the Bowland Fells Site
of Special Scientific Interest (SSSI) (The Ribble Rivers Trust, 2021b). The
Hodder catchment is mostly agricultural, with small towns such as Slaidburn,
and Dunsop Bridge. Stocks Reservoir is also within the Hodder catchment and
is an important water source for the population of the North West (The Ribble
Rivers Trust, 2021b).
The River Calder originates in the moorlands above Colne, before joining the
Ribble at Whalley. The Calder catchment is predominately urban, and its
tributaries all flow through historically industrialised areas (The Ribble Rivers
Trust, 2021c). Much of the Calder and its tributaries have been heavily modified
in the past by industrial development.
12
2.2. Electrofishing Data
Electrofishing data was obtained from The River Ribble Trust. They have
carried out electrofishing surveys every summer since 2008 on sites on the
Ribble, Calder, and Hodder. The River Ribble Trust applied methodology is
adapted from Crozier and Kennedy (1994) method and is outlined in detail in
their 2020 Fisheries Monitoring Report of the Ribble Catchment (The River
Ribble Trust, 2020). Through the combination of their adapted Crozier and
Kennedy (1994) method and the Zippin (1956) K-Pass removal method, they
generate Fry densities per 100m2 for each of the sites and individual
catchments (The River Ribble Trust, 2017; 2018; 2019; 2020)
From this data sites were manually selected on the basis that they needed to
have been continually surveyed since 2009. In total 42 sites were selected
within the Ribble catchment, 48 sites from within the Calder catchment and 35
Figure 5: The location of the River Ribble, Calder and Hodder in North West England (The Ribble Rivers Trust, 2015).
13
sites from within the Hodder catchment (Figure 6). These sites were then
inputted into a CSV file in Microsoft Excel and uploaded into Quantum
Geographic Information System (QGIS) 3.4.10 and mapped using their XY
National Grid coordinates (Figure 6). The sites were then classified for each
year (between 2009 and 2019) for both Atlantic Salmon and Brown Trout using
the National Fisheries Classification System (NFCS) (Table 1) and mapped
using QGIS (Appendix A and Appendix B).
Figure 6: Locations of sites used from The River Ribble Trust electrofishing surveys of Atlantic Salmon and Brown Trout for the River Ribble (42 sites), Calder (48 sites) and Hodder (35 sites).
14
2.3. Daily Flow Data
Daily flow data was obtained from the National River Flow Archives (NRFA)
database. NRFA gauging stations were selected for each of the Ribble (station
number 71006 Ribble at Henthorn), Calder (71004 Calder at Whalley Weir) and
Hodder (71008 Hodder at Hodder Place) and daily flow data downloaded.
2.3.1. Indicators of Hydrologic Alteration (IHA)
The daily flow data for the Ribble, Calder and Hodder was then analysed using
the Indicators of Hydrologic Alteration (IHA) method, developed by Richter et
al., (1996) using the software available from the Conservation Gateway website
and detailed instructions are outlined by Nature Conservancy (2009) in the IHA
version 7.1 user manual.
IHA analyses the NRFA daily flow data to statistically analyse inter-annual
variation by using a range of biologically relevant hydrological parameters
(Richter et al., 1996; Nature Conservancy, 2009). The IHA model uses 33
different parameters in order to analyse the daily flow data, with each parameter
being calculated for each year in the NRFA data series (Richter et al., 1996;
Gray, 2015). The 33 parameters are organised into five parameter groups
(Table 2).
Grade Description Trout fry per 100m2 Salmon fry per 100m2
A Excellent >38 >86
B Good 17-38 45-86
C Fair 8-16 23-44
D Poor 3-7 9-22
E Very Poor 1-2 1-8
F No Fish Present 0 0
Table 1: National Fisheries Classification System (NFCS) for Brown Trout and Atlantic Salmon
15
IHA then calculates the general tendency and dispersion of the 33 attributes
based on the values from the previous step in order to produce inter-annual
statistics for the daily flow data (Richter et al., 1996; Nature Conservancy, 2009;
Gray, 2015). The IHA software produces a series of tables and graphs that can
be used to analyse the NRFA daily flow data. A full list can be found in the IHA
version 7.1 user manual (Nature Conservancy, 2009).
2.4. Rod Catch and Fish Counter Data
Atlantic Salmon and Brown Trout rod and net catch data (1996-2020) was
obtained from the Environment Agency (EA) Salmonid Statistics report on the
Government website. Rod licence data was also obtained from the EA for the
Lancashire and Cumbria region. The number of rod licenses will be used as a
proxy for fisheries effort.
Fish counter data was provided by The River Ribble Trust, for the fish counter
located at Waddow weir, located near Waddow Hall (located on the Ribble
upstream of the confluence with both the Calder and Hodder). The rod and net
catch data and the fish counter data will be used as a proxy for the number of
Salmonids returning to the Ribble system.
2.4.1. Limitations of Rod Catch and Fish Counter Data The introduction of the Salmon and Freshwater Fisheries act in 1975 made it
compulsory for all fisheries to declare the total number of Salmon caught
annually in their rivers (Gray, 2015). However, there are some significant
IHA Parameter Description
1 Magnitude of monthly water conditions
2 Magnitude and duration of extreme water
conditions
3 Timing of annual extreme water conditions
4 Frequency and timing of high and low pulses
5 Rate and frequency of water condition change
Table 2: IHA Parameter Groups (Nature Conservancy, 2009)
16
flaws in this process which may impact the accuracy of the data, such as
there is no quantifiable estimate given of fisheries effort with the rod catch
data (Thorley et al., Gray, 2015).
Limitations of the fish counter data includes the fact that Waddow weir is
located further up the Ribble, above the confluence with the Calder and
Hodder. This means that the fish counter does not represent the entire
system. It does not count any fish travelling upstream or downstream on the
Calder or Hodder, only the areas available for spawning upstream of that point
on the Ribble. The fish counter also does not discriminate between species,
but they are typically considered to be reflective of Atlantic Salmon and Brown
Trout numbers.
2.5. Atmospheric Temperature Data
Atmospheric Temperature Data was obtained from the Met Office. The time-
series data included monthly, seasonal, and annual values of mean
temperature for the North West England and North Wales.
2.6. Statistical Analysis
Statistical analysis of flow characteristics (median monthly flows), and
atmospheric temperature in relation to the cumulative densities of Atlantic
Salmon and Brown Trout fry were all carried out in Minitab 19, in the form of
Spearman’s correlation.
17
3. Results
3.1. Hydrological Data
3.1.1. Annual Flow Data
Preliminary analysis of the NRFA data shows the presence of ‘wet’ and ‘dry’
years. ‘Wet’ years are considered to be when the annual median flow is higher
than the median flow for the whole data set, and ‘dry’ years are when the annual
median falls below the median for the whole data set.
Analysis of the Ribble (71006) shows that since 2009, a total of 8 years have
been above the long term median annual flow (6.30 m3 s-1) (Figure 7). Analysis
of the Calder shows that since 2009 total of 6 years have been above the long
term median annual flow (4.94 m3 s-1) (Figure 8). The Hodder has experienced
a total of 9 years above the long term median annual flow (4.21 m3 s-1) since
2009 (Figure 9). The Ribble, Calder and Hodder all experienced the lowest
annual median flow in 1996 (2.58 m3 s-1, 2.46 m3 s-1 and 1.74 m3 s-1 respectively)
(Figure 7, 8 and 9). The Ribble experienced its highest annual median flow in
2007, with 10.85 m3 s-1, however it is closely followed by 10.79 m3 s-1 in 2012
(Figure 7). The Calder experienced its highest annual median flow of 6.94 m3
s-1 in 2012 (Figure 8) as did the Hodder with 7.25 m3 s-1 (Figure 9).
0
2
4
6
8
10
12
1969 1979 1989 1999 2009 2019
An
nu
al M
edia
n F
low
(m
3 s
-1)
Year
Annual Median Median 1969-2019
Figure 7: Ribble (71006) annual median flow (m3s-1) and long term annual median flow (m3s-1) (1969-2019).
18
3.1.2. Indicators of Hydrologic Alteration (IHA) Analysis: IHA Parameter 1
The Ribble, Calder and Hodder all show peaks in median monthly flows in
January (14. 70 m3 s-1, 9.02 m3 s-1 and 9.37 m3 s-1) (Figure 10). Although the
Calder does not have a singular dominant peak, as January and December
(9.26 m3 s-1) are relatively similar (Figure 10b). The Ribble, Calder and Hodder
all experience a large decrease in median monthly flow between January and
February (Figure 10). The Hodder shows an increase in median monthly flow
in March, unlike the Ribble and Calder which show more of a plateau (Figure
10). All 3 rivers show decreases in median flow through spring, and all reach a
0
1
2
3
4
5
6
7
8
1964 1974 1984 1994 2004 2014
An
nu
al M
edia
n F
low
(m
3 s
-1)
Year
Annual Median Median 1964-2019
Figure 8: Calder (71004) annual median flow (m3s-1) and long term annual median flow (m3s-1) (1964-2019).
0
1
2
3
4
5
6
7
8
1976 1986 1996 2006 2016
An
nu
al M
edia
n F
low
(m
3 s
-1)
Year
Annual Median Median 1976-2019
Figure 9: Hodder (71006) annual median flow (m3s-1) and long term annual median flow (m3s-1) (1976-2019).
19
minimum median flow in July (2.21 m3 s, 2.40 m3 s-1 and 1.63 m3 s-1) (Figure
10).
IHA parameter 1 is applied to the daily flow data for the Ribble, Calder and
Hodder for the time period 2009-2019 and compared to the median flows of the
long-term data. The Ribble shows a much higher December median flow (24.25
m3s-1) between 2009 and 2019 compared to 1969-2019 (13.53 m3s-1) (Figure
11a). The Calder also shows the same trend, with 2009-2019 December
median flow (11.20 m3s-1) being higher than the long-term December median
flow (9.26 m3s-1) (Figure 11b), as does the Hodder (12.70 m3s-1 and 8.81 m3s-
1) (Figure 11c).
0
2
4
6
8
10
12
14
16
18O
ct
No
v
Dec Jan
Feb
Mar
Ap
r
May Jun
Jul
Au
g
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Med
ian
mo
nth
ly f
low
(m
3s-1
)
Month
(a)
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12
Oct
No
v
Dec Jan
Feb
Mar
Ap
r
May Jun
Jul
Au
g
Sep
Med
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mo
nth
ly f
low
(m
3s-1
)Month
(b)
0
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8
10
12
Oct
No
v
Dec Jan
Feb
Mar
Ap
r
May Jun
Jul
Au
g
Sep
Med
ian
mo
nth
ly f
low
(m
3s-1
)
Month
(c)
Figure 10: IHA Parameter 1 Median monthly flows (m3s-1) for (a) Ribble (1969-2019); (b) Calder (1964-2019); (c) Hodder (1976-2019).
20
The January median flows for the Ribble and Hodder are relatively similar for
both periods, however, the Calder shows a lower January median flow in the
2009-2019 period (7.12 m3s-1 compared to 9.02 m3s-1) (Figure 11b). All 3 rivers
also show a similar increase in February median flows in the 2009-2019 period
compared to the long-term median flows (Figure 11). Median flows in March,
April, May, June, and July for the 3 rivers are all relatively similar for both
periods (Figure 11). However, August and September median flows are
noticeably higher in the 2009-2019 period (Figure 11) particularly in the Ribble
and Hodder.
0
5
10
15
Oct
No
v
Dec Jan
Feb
Mar
Ap
r
May Jun
Jul
Au
g
Sep
Med
ian
mo
nth
ly f
low
(m
3s-1
)
Month
1976-2019 2009-2019
(c)
0
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15
Oct
No
v
Dec Jan
Feb
Mar
Ap
r
May Jun
Jul
Au
g
Sep
Med
ian
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nth
ly f
low
(m
3s-1
)
Month
1964-2019 2009-2019(b)
0
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15
20
25
30
Oct
No
v
Dec Jan
Feb
Mar
Ap
r
May Jun
Jul
Au
g
Sep
Med
ian
mo
nth
ly f
low
(m
3s-1
)
Month
1969-2019 2009-2019
(a)
Figure 11: Comparison of Median monthly flows (m3s-1) for (a) Ribble (1969-2019 and 2009-2019); (b) Calder (1964-2019 and 2009-2019); (c) Hodder (1976-2019 and 2009-2019).
21
3.2. Salmonid Data
3.2.1. Cumulative Density of Atlantic Salmon fry
There is a clear decrease in the cumulative density of Atlantic Salmon fry in the
Ribble (Figure 12a). A sharp drop in the cumulative density occurs in 2012,
where levels drop from a cumulative density of 1057 fish/100m2 to 285
fish/100m2 in 2013 (Figure 12a). This is then followed by a further decrease in
in 2016 (91 fish/100m2) before recovering slightly in 2018 (304 fish/100m2).
However, this is followed by a decrease to a low point in the data in 2019 (61
fish/100m2).
There is also a clear decrease cumulative density of Atlantic Salmon fry in the
Calder (Figure 12b). The Calder also shows a similar pattern to the Ribble, with
a series of peaks and troughs starting with the peak in 2010 (215 fish/100m2)
(Figure 12b). The 48 sites in Calder recorded a cumulative density of 0
fish/100m2 in 2016, 2019 and 2020 (Figure 12b).
The Hodder (Figure 12c) also shows a clear decrease in the cumulative density
of Atlantic Salmon Fry. The Hodder is also characterized by the same trend as
the Ribble and Calder, starting with a peak in 2012 (1600 fish/100m2) before
decreasing in 2013 (905 fish/100m2) followed by a recovery in 2014 (1363
fish/100m2). After 2014 there is a sharp decline in the cumulative density of
Atlantic Salmon fry reaching 280 fish/100m2 in 2017, with a low point in 2020
(74 fish/100m2) (Figure 12c).
22
3.2.2. Cumulative Density of Brown Trout fry
There is also a clear decrease in the cumulative density of Brown Trout fry in
the Ribble (Figure 13a), showing a peak in 2012 (2703 fish/100m2), before a
declining to a cumulative density of 877 fish/100m2 in 2015. This is followed by
an increase in 2016 (1315 fish/100m2) and 2017 (1479 fish/100m2) (Figure
13a), before a low point is reached in 2019 (154 fish/100m2).
The Calder also shows a clear decrease in the cumulative density of Brown
Trout fry (Figure 13b). The Calder shows similar levels between 2009 and 2011
before experiencing a sharp increase and peaking in 2012 (2565 fish/100m2)
(Figure 13b). Following this peak, the cumulative density of Brown Trout in the
0
50
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20
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Cu
mu
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h/1
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m²)
Year
(b)
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Cu
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m²)
Year
(a)
0
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1750
20
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2
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Cu
mu
lati
ve d
ensi
ty o
f Sa
lmo
n
fry
(Fis
h/1
00
m²)
Year
(c)
Figure 12: Cumulative density (fish/1002) of Atlantic Salmon fry in the: (a) Ribble; (b) Calder; (c) Hodder (2009-2020).
23
Calder decreases in 2013 (1600 fish/100m2) before increasing slightly in 2014
(1728 fish/100m2). There is a sharp decrease in 2016 (364 fish/100m2), which
is then followed by a sharp increase over a 2-year period to 1718 fish/100m2 in
2018 (Figure 13a). Following the 2018 high point, the Calder experiences a
large crash in the cumulative density of Brown Trout fry in 2019 (149
fish/100m2) and shows no sign of recovering in 2020 (143 fish/100m2) (Figure
13a).
The cumulative density of Brown Trout fry in the Hodder (Figure 13c) is
relatively similar in 2009 and 2010 (1159 fish/100m2 and 938 fish/100m2). A
sharp increase occurs in 2011 (3877 fish/100m2) and following this the
cumulative density of Brown Trout fry experiences several decreases, with the
largest decline occurring between 2012 and 2013 (3550 fish/100m2 to 1799
fish/100m2). Both 2019 and 2020 are poor years, with the lowest point in the
data occurring in 2020 (132 fish/100m2) (Figure 13c).
0
500
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3000
20
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20C
um
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tive
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sity
of
Tro
ut
fry
(Fis
h/1
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Year
(a)
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Cu
mu
lati
ve d
ensi
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f Tr
ou
t fr
y (F
ish
/10
0m
²)
Year
(b)
0500
10001500200025003000350040004500
20
09
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10
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11
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20C
um
ula
tive
den
sity
of
Tro
ut
fry
(Fis
h/1
00
m²)
Year
(c)
Figure 13: Cumulative density (fish/100m2) of Brown Trout fry in the: (a) Ribble; (b) Calder; (c) Hodder (2009-2020).
24
3.3. Rod Catch Data
Rod catch data for Atlantic Salmon (Figure 14) and Brown Trout (Figure 15)
shows that, there appears to be ‘good’ and ‘bad’ years for both species. The
number of Atlantic Salmon caught peaks in 2004 (1442) while the number of
Brown Trout caught peaks in 2011 (1838). The number of Atlantic Salmon
caught is lowest in 1997 (348) and the number of Brown Trout caught is lowest
in 2018 (487). Relatively similar low recordings of Atlantic Salmon were
recorded in 2018 (370) and 2019 (380). Between 1996 and 2019, a total of 12
years fall below the average number of Atlantic Salmon caught in the Ribble
system (804 per year) and a total of 11 years exceed the average of this period
(Figure 14). Despite the ‘good’ and ‘bad’ periods, statistically the number of
Atlantic Salmon being caught is relatively stable over the period between 1996
and 2019 (R2= 0.04).
Between 1996 and 2019, a total of 14 years exceed the average number of
Brown Trout caught in the Ribble (1221 per year) and a total of 9 years fall
below this average, including the last 3 years (Figure 15). Statistically, the
number of Brown Trout caught per year appears to have been relatively stable
in the period between 1996 and 2019 (R2 =0.01). Data from the EA regarding
the number of Rod licenses sold within Lancashire and Cumbria between 2010
and 2018, show a sharp decline from 58,479 in 2010 to 31,874 in 2018, a
decrease of 26,605 (-45.5%) in just 8 years (Figure 16).
0
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19
96
19
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18
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Nu
mb
er o
f A
tlan
tic
Salm
on
ca
ugh
t p
er y
ear
YearFigure 14: Total declared rod catch of Atlantic Salmon in the Ribble (1996-2019) (Environment Agency, 2020)
25
3.4. Waddow Fish Counter Data
The number of fish movements upstream (Figure 17a) shows a peak in 1999,
(7447 upstream movements recorded) and a low point in 2017 (2268 upstream
movements recorded) (Figure 17a). However, between the period of 1996-
2019, the number of upstream fish movements has remained relatively stable
over time (R2 =0.15).
The downstream movements of fish recorded at Waddow weir (Figure 17b)
shows a peak in 1996 (2858 downstream movements recorded). A low point of
downstream fish movements was recorded in 2018, (183 downstream
0200400600800
100012001400160018002000
19
96
19
98
20
00
20
02
20
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18
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Nu
mb
er o
f B
row
n T
rou
t
cau
ght
per
yea
r
Year
Figure 15: Total declared rod catch of Brown Trout in the Ribble (1996-2019) (Environment Agency, 2020).
0
10,000
20,000
30,000
40,000
50,000
60,000
2010 2011 2012 2013 2014 2015 2016 2017 2018
Nu
mb
er o
f R
od
lice
nse
s so
ld
Year
Figure 16: Number of rod licenses sold in Lancashire and Cumbria (2010-2018) (Environment Agency, 2015).
26
movements) (Figure 17b). Downstream movements again appear to have
remained relatively stable over the period between 1996 and 2019 (R2 = 0.27).
3.5. Analysis of Flow and Salmonids
Table 3 shows the correlations between median monthly flow and the
cumulative density of both Atlantic Salmon and Brown Trout fry in the Ribble,
Calder and Hodder. March median flow shows a strong negative correlation
with the cumulative density of both Atlantic Salmon fry and Brown Trout fry in
each of the Ribble, Calder and Hodder (Table 3).
The strongest relationship between median flow and the cumulative density of
Brown Tout is seen in the Ribble (Figure 18a), which displays a statistically
significant negative correlation between cumulative density and March median
flow (r (9) = -0.73, p <0.05). The Calder (Figure 18b) and Hodder (Figure 18c)
also display statistically significant negative correlations between cumulative
density and March median flows (r (9) = -0.61, p <0.05 and r (9) = 0.65, p <0.05).
Positive correlations between October Median flow and the cumulative density
of Atlantic Salmon and Brown Trout are also shown in Table 3, although the
only statistically significant relationship is shown with Brown Trout in the Calder
(r (9) = 0.64, p<0.05).
0
500
1000
1500
2000
2500
3000
3500
19
96
20
00
20
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20N
um
ber
of
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co
un
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do
wn
Year
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19
96
20
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Nu
mb
er o
f fi
sh c
ou
nte
d u
p
Year
(b)
(a)
Figure 17: Number of fish counted moving (a) upstream and (b) downstream at Waddow weir fish counter (1996-2019) (The Ribble Rivers Trust).
27
Figure 19 shows the relationship between cumulative density of Atlantic Salmon
fry and March median flows. The strongest relationship is seen in the Calder
(Figure 19b), which displays a statistically significant negative correlation
between the cumulative density of Atlantic Salmon and March median flows (r
(9) = -0.77, p <0.05). The Ribble (Figure 19a) also displays a negative
correlation between cumulative density and March median flow, which is also
statistically significant (r (9) = -0.64, p <0.05). The Hodder (Figure 19c) also
shows a negative correlation between cumulative density and March median
flow; however, it is not statistically different (r (9) = -0.48, p >0.05).
Monthly
Median flow
Ribble Calder Hodder
Trout Salmon Trout Salmon Trout Salmon
Jan -0.13 -0.05 0.11 -0.39 0.11 0.15
Feb 0.05 -0.07 0.21 -0.23 0.28 0.22
Mar -0.73 -0.64 -0.61 -0.77 -0.65 -0.48
Apr 0.06 0.11 0.30 -0.18 -0.15 -0.22
May 0.36 0.28 0.32 0.26 0.50 0.37
Jun -0.07 -0.26 -0.26 -0.42 0.04 0.06
Jul 0.61 0.39 -0.24 0.08 0.30 0.24
Aug -0.09 -0.31 -0.33 -0.26 0.11 0.11
Sep 0.18 0.21 -0.02 0.28 -0.04 0.10
Oct 0.48 0.53 0.64 0.52 0.36 0.45
Nov -0.05 -0.07 -0.06 0.09 0.05 -0.16
Dec 0.01 -0.15 -0.05 -0.33 -0.15 -0.03
Table 3: Spearman correlation matrix of median monthly flow (m3s-1) and cumulative density (fish/100m2) of Atlantic Salmon and Brown Trout Fry for the Ribble, Calder and Hodder.
28
0
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19 C
um
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Bro
wn
Tro
ut
fry
Den
siti
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Fish
/10
0m
²)
Mar
ch M
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n M
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)
Year
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ch M
edia
n M
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050010001500200025003000350040004500
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19 Cu
mu
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(F
ish
/10
0m
²)
Mar
ch M
edia
n M
on
thly
Flo
w
(m3s-1
)
Year
(a)
(b)
(c)
Figure 18: Relationship between March median monthly flow (m3s-1) and the cumulative density of Brown Trout fry (Fish/100m2) for (a) Ribble, (b) Calder and (c) Hodder (2009-2019).
29
0
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0
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Cu
mu
lati
ve A
tlan
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Salm
on
fr
y D
ensi
ties
(Fi
sh/1
00
m²)
Mar
ch M
edia
n M
on
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Flo
w
(m3s-1
)
Year
(a)
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tlan
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Salm
on
fr
y D
ensi
ties
(Fi
sh/1
00
m²)
Mar
ch M
edia
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on
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w
(m3s-1
)
Year
(b)
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Cu
mu
lati
ve A
tlan
tic
Salm
on
fr
y D
ensi
ties
(Fi
sh/1
00
m²)
Mar
ch M
edia
n M
on
thly
Flo
w
(m3s-1
)
Year
(c)
Figure 19: Relationship between March median monthly flow (m3s-1) and the cumulative density of Atlantic Salmon fry (Fish/100m2) for (a) Ribble, (b) Calder and (c) Hodder (2009-2019).
30
3.6. Atmospheric temperature and Salmonids
Table 4 shows that there is a relationship between mean winter temperature
and the cumulative density of Atlantic Salmon and Brown Trout. Atlantic Salmon
show a stronger relationship with mean winter temperature in comparison to
Brown Trout. The negative correlation is strongest in the Calder (Table 4) and
is statistically significant (r (9) = -0.68, p < 0.05). The Ribble also shows a
statistically significant correlation between mean December temperature and
the cumulative density of Atlantic Salmon (r (9) = -0.62, p < 0.05). The Hodder
shows a negative correlation; however, this is not statistically significant (r (9)
= -0.42, p > 0.05).
There is no statistically significant correlation between mean December
temperature and the cumulative density of Brown Trout fry (Table 4). It is clear
that the correlation between mean winter temperature and the cumulative
density of Atlantic Salmon in the Ribble and Calder is due mainly to mean
December and January temperatures (Table 4).
It is worth noting that the Hodder also displays statistically significant negative
correlations between mean June temperature and the cumulative density of
both Atlantic Salmon fry and Brown Trout fry (r (9) = -0.69, p < 0.05 and r (9) =
-0.65, p < 0.05).
31
4. Discussion
4.1. Hydrological Data In the 11 years since 2009, the Ribble has experienced 8 years above the long
term median annual flow (72.7%), the Calder has experienced 6 years above
the long term median annual flow (54.5%) and the Hodder 9 of the last 11 years
(81.8%). A possible reason for the increase in annual flow of these Rivers is
anthropogenically driven climate change (Gudmundsson et al., 2021) as
climate change is expected to intensify the hydrological cycle and result in
modified river flow regimes (Huntington, 2006; Hannaford, 2015). With
anthropogenic driven climate change we are seeing more extreme weather
patterns, including increased probability of high intensity rainfall events as well
as prolonged dry periods (IPCC, 2014; The River Ribble Trust, 2020).
This is evident by the fact that 2009-2018 was 1% wetter than 1981-2010 and
5% wetter than 1961-1990 for the UK overall (Met Office, 2021). Also, between
Ribble Calder Hodder
Mean Air Temperature (°c)
Trout Salmon Trout Salmon Trout Salmon
Winter -0.51 -0.61 -0.26 -0.70 -0.43 -0.29
Spring 0.09 0.05 -0.06 -0.08 0.08 0.17
Summer -0.26 -0.44 -0.02 -0.30 -0.53 -0.37
Autumn 0.06 -0.06 -0.09 -0.13 0.35 0.11
Annual -0.36 -0.33 -0.11 -0.52 -0.13 -0.11
January -0.27 -0.29 0.16 -0.45 -0.24 -0.16
February -0.19 -0.36 -0.40 -0.45 0.01 0.09
March 0.11 0.08 -0.05 -0.05 0.12 0.31
April -0.08 0.09 -0.08 -0.07 0.02 0.25
May -0.16 -0.16 -0.06 -0.31 -0.28 -0.33
June -0.43 -0.33 -0.22 -0.32 -0.69 -0.65
July -0.25 -0.32 0.11 -0.13 -0.41 -0.26
August -0.14 -0.43 -0.31 -0.30 -0.35 -0.27
September -0.09 -0.13 -0.23 -0.14 0.02 0.13
October 0.21 0.11 -0.03 0.00 0.42 -0.05
November 0.07 0.16 0.22 -0.05 0.36 0.24
December -0.56 -0.62 -0.25 -0.68 -0.26 -0.48
Table 4: Spearman correlation matrix of mean air temperature (°c) and cumulative density of Brown Trout and Atlantic Salmon (2009-2019).
32
2009-2018 winters in the UK have been 5% wetter when compared to the
period 1981-2010 and 12% wetter than 1961-1990 (Met Office, 2021). This
trend is also reflected in UK summer precipitation, which has been 11% and
13% higher respectively for each period (Met Office, 2021). This data from the
Met Office clearly illustrates reasons why the median annual flow of the Ribble,
Calder and Hodder have increased, as shown by the analysis of NRFA data in
Figures 7, 8 and 9.
Analysis of the long term NRFA daily flow data using the Indicators of
Hydrologic Alteration Parameter 1 (Figure 10), shows that The Ribble and
Hodder both show a dominant peak in January, whilst the Calder has a much
less clear peak, as December and January are very similar. These flow regimes
are typical of UK rivers, showing a peak in flow in December and January,
before decreasing in Spring with lowest points occurring in summer (Gray,
2015).
However, when comparing the median monthly flows for the period between
2009 and 2019 (Figure 11) with long term median monthly flows (Figure 10) it
is clear that winter flows have increased, particularly December median flows
in the Ribble, Calder and Hodder. This further highlights that the UK is
experiencing increased winter precipitation due to climate change and therefore
increased river flow (Huntington, 2006; IPPC, 2014 Hannaford, 2015,
Gudmundsson et al., 2021, Met Office, 2021).
4.2. Salmonid Data
It is clear that the number of Atlantic Salmon and Brown Trout in the Ribble,
Calder and Hodder have experienced a decline in the period since The Ribble
Rivers Trust began carrying out electrofishing surveys. The cumulative
densities of both Atlantic Salmon fry and Brown Trout fry have decreased
dramatically in the period between 2009 and 2019 (Figure 12 and Figure 13). It
is worth noting that the UK as a whole experienced a strong recruitment ‘crash’
in 2016 (ICES, 2017; Marsh, 2020), so the trends shown in Figures 12 and 13
33
also reflect national trends and not just the recruitment trends experienced in
the Ribble system.
4.2.1. Rod Catch and Fish Counter
This decrease in cumulative density of fry for both Salmonid species has
occurred despite the rod catch data between 1996 and 2019 showing the
number of Atlantic Salmon (Figure 14) and Brown Trout (Figure 15) caught
have remained stable over time (R2= 0.04 and R2= 0.01) despite experiencing
‘good’ and ‘bad’ years when compared to the long-term average. However, it is
worth considering that both the Atlantic Salmon and Brown Trout have
experienced several ‘bad’ years in recent years (2012-2019 and 2017-2019),
which is likely having some effect on the number of Salmonid fry, although no
statistically significant relationships were detected from the data available.
The rod catch for both species has remained stable despite the number of rod
licenses dropping drastically by 45.4% in an 8-year period (Figure 16), although
caution is needed when assessing this, as rod licence data is for Lancashire
and Cumbria, and not solely for the Ribble catchment. Fish counter data from
Waddow weir (Figure 17) also indicates that the number of fish returning
(travelling upstream) to spawn has remained relatively constant between 1996
and 2019 (R2= 0.15). These factors suggests that the cause of decreasing
salmonid fry in the Ribble, Calder and Hodder is not due to a decrease in adults
returning to spawn.
4.2.2. Juvenile Salmonids and Median Monthly Flow
When the cumulative density of Atlantic Salmon and Brown Trout fry were
analysed in relation to median monthly flow conditions several correlations were
found (Table 3). Statistically significant negative correlations were found
between March median flows and the cumulative density of Atlantic Salmon fry
and Brown Trout fry in the Ribble and Calder, but only for Brown Trout in the
Hodder (Figure 18 and Figure 19).
34
March flows are likely to coincide with the emergence phase of Salmonids from
their eggs, thus meaning that higher March flows are more likely to transport
Alevins out of the Redd and downstream into less favourable conditions,
potentially resulting in mortality (Crisp, 1999; Warren et al., 2015). Depending
on the timing of the increased flows, eggs may also experience wash out from
the Redd, again increasing the chance of mortality. This can occur either
through physical shock and damage to egg, predation, or the egg being
deposited in an inhospitable downstream environment (Jensen and Johnsen,
1999; Cowx and Fraser, 2003; Gray, 2015). These factors explain why there is
a statistically significant negative correlation between March median flows and
the cumulative density of Salmonid fry, as intra-gravel life stages are most
susceptible to high flow events (Nislow and Armstrong, 2012; Gillson et al.,
2020).
As Alevins grow and become fry their swimming ability and size increases,
meaning the likelihood of them being able to survive high flow events also
increases, (Heggenes, 1990; Hendry and Cragg-Hine, 2000). This reduces the
chance of mortality caused directly by high flow events and explains why the
correlation between median monthly flows and cumulative density of Salmonid
fry are not significant in later months (Table 3). So higher median flows in March
result in an increased probability of mortality for intra-gravel stages and result
in lower cumulative densities of Salmonid fry in the summer.
High flows in March will also affect the growth of juvenile Salmonids, as the
higher flows reduce the abundance of food available to the juveniles (The
Ribble Rivers Trust, 2018). In comparison, lower median flows increase the
likelihood of survival and potentially explain why higher cumulative densities of
Salmonid fry are found in summers following lower March flows. These findings
are supported by the growing body of evidence that suggests high discharge
events between spawning and fry emergence have a significant effect on
juvenile Salmonid densities (Malcolm et al., 2012; Gillson et al., 2020; Bergerot
and Cattaneo, 2017).
35
Although, a statistically significant positive correlation was found between
October Median flows and Brown Trout cumulative density in the Calder, all of
the Ribble, Calder and Hodder displayed positive correlations between both
Salmonid species and October median flow (Table 3). These positive
correlations can be explained by fact that high flows enable earlier access to
rivers for Salmonids (Jonsson et al., 2007; Parry et al., 2018; Gillson et al.,
2020). This allows the Salmonids to travel further upstream and disperse their
eggs in a more even manner throughout the catchment (Einum et al., 2008;
Gillson et al., 2020). In turn, this can increase the growth size and survival
chances of juvenile Salmonids through the reduction of intra-specific
competition relating to territory and food (Gillson et al., 2020).
Brown Trout have more plastic life histories, compared to Atlantic Salmon
(Klementsen et al., 2003) and the proportion of Brown Trout fry which are
offspring from fresh-water resident parents is also unknown. This may impact
the relationship between October median flow and cumulative density, as they
do not require high discharge to access spawning areas (Gillson et al., 2020).
Also, Brown Trout typically bury their eggs at shallower depths when compared
to Atlantic Salmon (De Vries, 1997), making them more susceptible to washout,
and damage or entrapment by sediment during high flow events (Crisp, 1996;
Gillson et al., 2020). Brown Trout are also more at risk to wash out and
displacement during high flow events when compared to Atlantic Salmon, due
to their smaller pectoral fins (Arnold et al., 1991; Gillson et al., 2020).
The low cumulative densities of Salmonids in 2019 and 2020 can be linked to
the number and timing of named storms occurring in February and March. In
2019, storms Freya, Gareth, and Hannah, had resulted in twice the expected
monthly rainfall (The Ribble Rivers Trust, 2020). This period of exceptionally
high rainfall coincided with Fry beginning to emerge from the Redd to feed (The
Ribble Rivers Trust) and high flows occurring within this period will have likely
resulted in high levels of egg and fry mortality (Jensen and Johnsen, 1999).
The low cumulative densities of Salmonids in 2020 can also be linked to timing
of storms, with storms Ciara, Dennis and Jorge occurring in February (The
36
Ribble Rivers Trust, 2020). February is a period when Salmonid fry are still
feeding on their yolk-sacs and have limited swimming ability and are still in their
Redds (ICES, 2017; Marsh, 2020; The Ribble Rivers Trust, 2020). The high
rainfall in both 2019 and 2020 resulted in high flows and will have resulted in
increased movement of larger sediment, causing the wash out of Redds and
therefore mortality (The Ribble Rivers Trust, 2020). The combination of the
factors outlined above, explains the low cumulative density of Salmonids seen
in both 2019 and 2020.
4.2.3. Salmonids and Atmospheric Temperature
Another reason which may explain the reduction in the cumulative density of
Salmonids is the correlation with mean air temperature (Table 4). The
incubation period of eggs is directly dependent on water temperature (Hendry
and Cragg-Hine, 2000), lasting 145 days at 3°c and around 40 days at 10-12°c
(Drummond and Segwick, 1982; Hendry and Cragg-Hine, 2000). The
correlations between mean December, January and winter temperature and
cumulative density of Atlantic Salmon and Brown Trout can be explained by the
correlation between cold winters and egg survival (Crisp, 1999). Colder winters
increase the probability of eggs succumbing to freezing and desiccation (Crisp,
1999). This explains why lower winter temperatures correlate with lower
cumulative densities of Salmonid fry in the summer, as colder temperatures
increase the risk of mortality during the incubation period.
Research has suggested that the 2016 recruitment crash of Salmonids is due
to the combination of an unusually warm and wet winter followed by a wet spring
(Marsh, 2020). The warm winter resulted in unfavorable conditions for spawning
(ICES, 2017; Gregory et al., 2019; Game and Wildlife Conservation Trust,
2019) and the eggs that were spawned and hatched experienced large spring
floods (Gregory et al., 2019). The combination of these conditions resulted in
high egg and Alevin mortality in 2016 across England and Wales (Gregory et
al., 2019; ICES, 2017; Game and Wildlife Conservation Trust, 2020; Marsh,
2020).
37
4.3. Future Climate Scenarios
As future climate change scenarios show that the UK is set to experience wetter
winters, with reduced rainfall in the summer months (IPCC, 2014) it is likely that
Salmonids are going to feel the impacts of these anthropogenically driven
changes in climate. There are also indications that the UK may experience up
to 30% more precipitation in the winter by 2100 (Met Office, 2019), so
Salmonids across the UK and within the Ribble system are going to be affected
by winter high flow events more frequently in the future.
With these projections, it is clear that Salmonids in the Ribble are going to
continue to come under pressure due to anthropogenic driven climate change.
Despite the fact that Salmonids have evolved to deal with temporal variations
in flow, it is evident that the increasing rate of environmental change is
exceeding their ability and capacity as a population to adapt to new flow regime
conditions (The Ribble Rivers Trust, 2020), which is shown by the year-on-year
reductions of Salmonid fry in the Ribble, Calder and Hodder in recent years.
4.4. Management Solutions
It is clear that some form of management is needed in order to help the numbers
of Atlantic Salmon and Brown Trout in the Ribble system. The NFCS maps
(Appendix A and Appendix B) can be used to determine which sites within the
Ribble, Calder and Hodder have seen the largest reduction in NFCS grade for
Atlantic Salmon and Trout in recent years. This analysis can be used to help
inform the decision-making process for management solutions, in relation to
juvenile Atlantic Salmon and Brown Trout numbers in the Ribble system.
Further research could be undertaken at sites to determine if any other factors,
such as sediment composition and water temperature are having an impact on
juvenile numbers.
Potential management solutions for mitigating the impact of high flows in the
Ribble system could include Nature Based Solutions (NBS) and Natural Flood
Management (NFM). NFM uses natural hydrological processes to slow water
38
flowing through the landscape (Wingfield et al., 2019). This concept could be
used to target certain areas within the Ribble system, with the aim of increasing
the time it takes for water to enter the system and potentially reduce the
likelihood of large flows. In turn this would benefit juvenile Salmonids and help
reduce the likelihood of wash out events occurring.
NFM techniques aim to reduce flow by intervening at each stage of the
hydrological cycle by increasing interception, infiltration, water storage and
channel flow (Wingfield et al., 2019). These concepts can be used at various
scales and are suitable for different budgets. Techniques which could be utilised
in the Ribble system in order to reduce flow include interception ponds;
restoring peatlands; planting new woodland; creating buffer strips; encouraging
farmers to reduce tilling and the creation of wetland areas (Wingfield et al.,
2019). These techniques have been proven to reduce flow and would therefore
likely help mitigate the impact of high flows on juvenile Salmonids.
5. Conclusion
The cumulative densities of Atlantic Salmon fry and Brown Trout fry have
declined since 2009, with 2019 and 2020 showing some of the lowest levels in
the 11-year period. There is also a noticeable drop in the cumulative density of
both species in 2016, which coincides with a wider crash in recruitment of
Salmonids seen within many UK rivers. These trends have occurred despite
rod catch data and data from a fish counter located in the Ribble system
indicating that there has been no significant change in the number of Salmonids
returning to spawn in the Ribble system, despite the presence of good and bad
years in comparison to long term averages. This suggests that the cause of the
decline is due to in river factors.
The flow regime of the Ribble, Calder and Hodder all show an increased peak
in median monthly flow in December between 2009 and 2019 when compared
to their long term median monthly flows. The Ribble, Calder and Hodder have
also experienced several ‘wet’ years since 2009. The Ribble has experienced
39
8 years above the long term annual median flow since 2009, whilst the Calder
and Hodder have experienced 6 years and 9 years above the long term annual
median flow since 2009 also. This demonstrates that the Ribble system is
experiencing much higher annual median flows in recent years when compared
to the long term annual median flow of each river.
This increase in annual median flow and the increased peaks in median
monthly flow can likely be explained by anthropogenic driven climate change,
resulting in wetter winters and higher intensity rainfall in the summer months.
The increase in winter precipitation and therefore flow, will increase the
probability of mortality occurring during the intra-gravel life stages of Salmonids
as they are at most risk from high flows during these life stages, due to their
small size and limited swimming ability.
This idea is reinforced, by the statistically significant negative correlations found
between March median flow and the cumulative density of both Atlantic Salmon
fry and Brown Trout fry. Higher March median flows resulted in lower
cumulative densities of Salmonid fry in the Ribble, Calder and Hodder and lower
March median flows resulted in higher cumulative densities of Salmonids. This
is due to the emergence phase of Salmonids occurring in March, meaning that
the Alevins are feeding on their yolk-sac within the gravel Redds and so are
very susceptible to wash out during high flow events. The increase in March
median flows in 2019 and 2020 and the decrease in cumulative densities of
Salmonids can be attributed to the number of named storms occurring during
this period in both years.
Another reason for the possible decline in the recruitment of Salmonids in the
Ribble system is temperature. Negative correlations were observed between
mean winter temperature and the cumulative density of Salmonids, as cold
winter temperatures have been found to correlate with egg survival. Colder
temperatures increase the risk of mortality during the incubation period.
The results of this research show that there is a clear need for further research
into the impact of changing river flow regime on juvenile Salmonids in the Ribble
40
and its sub-catchments. Although this study primarily focused on flow regime
with some emphasis placed on temperature, it is clear that due to their complex
life histories, further research is needed into the impacts of other factors, such
as water temperature and water pollution in the Ribble system. There is also
potential for the use of Natural Flood Management techniques in order to
reduce the impact of high flow events on juvenile Salmonids. However, further
research is needed in order to target viable areas of the Ribble system for these
techniques to be implemented.
41
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Appendices
Appendix A: NFCS Trout fry Classifications (2009-2020)
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52
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55
56
57
58
59
60
61
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Appendix B: NFCS Salmon Fry Classifications (2009-2020).
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Appendix C: Data used for Dissertation
Dissertation_Data.zi
p
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Record of Meetings
Date Type of Meeting Key points discussed 16/02/21
Teams meeting Discussed the background of the
project. Talked about potential data
sets that could be used. Discussed
directions that I could take the
research.
22/02/21
Teams meeting Meeting with Dr. Thea Wingfield.
Discussed aims and objectives of the
project and methodology. Information
and discussion helped to frame ideas
ready for the dissertation proposal and
presentation.
23/02/21 Email Dr. Thea Wingfield emailed to tell me
about a webinar from CIWEM which
may be of use for my research
04/03/21
Teams meeting Meeting with Dr. Thea Wingfiled and
Mike Forty from The Ribble Rivers
Trust. I gave a presentation on my
project aims and the IHA software.
Mike Forty gave me guidance on the
directions my research could take. He
also gave me an insight into the Ribble
catchment.
05/03/21 Email Dr. Thea Wingfiled emailed the folder
containing the data that she had been
sent by Mike Forty from The Ribble
Rivers Trust.
76
15/03/21
Teams meeting Meeting with Dr. Thea Wingfiled.
Discussed about the potential of using
fish counter data as a proxy and spoke
about how the data had not been
looked into. Potentially important in
regard to the work done by The Ribble
Rivers Trust. Spoke in greater detail
about the IHA method and graphs.
19/04/21 Email Dr. Thea Wingfiled emailed to check in
on my progress and asked if I wanted
to have a meeting or wait until later on
in the month.
02/06/21 Email I emailed Dr. Thea Wingfield to ask
advice in relation to site selection
methods.
14/06/21 Email Dr. Thea Wingfield emailed over the
Fish counter data from Mike Forty at
The Ribble Rivers Trust.
18/06/21 Email Received an email to say that Dr.
Thea Wingfield would no longer be my
supervisor and that Professor Neil
Macdonald would be taking over as
my new supervisor.
28/07/21
Teams meeting Results meeting with Professor Neil
Macdonald and Dr. Thea Wingfield.
Gave a short PowerPoint presentation
on the results of my research.
Discussed other areas, such as
temperature, pollution and stocking
that should be looked into further. This
also acted as a ‘handover’ meeting as
Professor Neil Macdonald became my
dissertation supervisor.
77
31/08/21
Teams meeting Meeting with Professor Neil
Macdonald. Discussed where I was up
to with my write up. Discussed what
sections certain information should go
in.