1. UoP: 677644
1
Investigating the effect of implementing habitat
enhancement structures for brown trout (Salmo trutta) on
invertebrate abundance on the Bourne Rivulet.
677644
B.Sc. Year 3, 12/06/15
"A dissertation submitted in partial fulfilment of
the requirements for the B.Sc. degree
in Aquaculture and Fishery Management"

2. UoP: 677644
i
Abstract
A study was conducted on the Bourne Rivulet to investigate the effects of the
implementation of habitat enhancement for brown trout (Salmo trutta) on invertebrate
abundance.A site was chosen where no previous enhancement works had taken place and
an absence of Rannunculus weedcover.A site 10m upstream was used as a control site, the
middle site wasdirectlybehindthe installedbrushwoodwoody debris and upstream groyne
with the downstream site 10m below the structures. Invertebrate samples were collected
using three minute kick and analysed by species to common name level, counted for
abundance andallocateda Biological WorkingPartyScore (BMWP).Waterquality,depthand
flowmeasurementswere alsotaken.A significantdifference wasobservedbetweenthe sites
for total invertebrate count (P=0.045) whilst tukey analysis showed no difference between
the sites.The difference was attributed to a drop in total invertebrate count for the middle
site one weekafterthe habitatenhancementimplementation. A significant difference was
observed between all dates for total invertebrate count (P=0.000) and Baetidae count
(P=0.000) indicatingseasonalityandpotential changestoinvertebrate driftratesin response
to possible changesinflow regimes.Nosignificant differences were observed between the
sites for any water quality factors but were shown for cross section volume (P=0.000) and
discharge (P=0.000). The resultsindicatedthe implementationof habitatenhancementhada
short termeffecttoinvertebrate abundance butno longtermeffectsdue toa rapidrecovery
rate and a high resilience to disturbances.
Keywords:Invertebrates,abundance,habitatenhancement, invertebrate drift, brown trout

3. UoP: 677644
ii
Disclaimer
This dissertation is a product of my own work and is not the work of any collaboration. I
agree that this dissertation may be available for reference and photocopying at the
discretion of the college.
Signed:....................................... UoP: 677644
Date:..........................................

4. UoP: 677644
iii
Acknowledgements
The author wouldlike tothankthe followingpersonsfortheirhelpandsupportin
completion of this project:
Mr NickLawrence (FisheryManager) forallowingaccesstothe site on the Borne Rivulet and
the consentfor data collectionandforhisassistance andconsultationinthe installationof
habitatenhancementstructures.
Dr. Neil Crooksforassistinginthe initial concept ideaandhissupportandguidance forthe
durationof the projectand Mr AlanBlackfor hisassistance withthe reportsstatistical
analysis.
Mr and Mrs Hook for theirassistance duringthe datacollectionandrecording.
Mr Roy Niblettforassistance withlaboratoryanalysisandthe loanof college equipment.
Mr PhillipTurnbull forhisassistance inthe installationof habitatenhancementstructures.

5. UoP: 677644
iv
Contents
Table of Figures.................................................................................................................v
Table of Tables..................................................................................................................v
Introduction......................................................................................................................1
River Habitat Enhancement & Restoration ......................................................................1
Invertebrates.................................................................................................................3
Water Quality................................................................................................................6
The Bourne Rivulet........................................................................................................6
Aims & Objectives..........................................................................................................7
Hypotheses ...................................................................................................................7
Methodology.....................................................................................................................8
Site Selection.................................................................................................................8
Site Location..................................................................................................................8
Habitat Restoration......................................................................................................10
Kick Sampling..............................................................................................................12
Water Sampling...........................................................................................................13
Depth & Flow ..............................................................................................................14
Lab Analysis.................................................................................................................14
Statistical Analysis........................................................................................................14
Results............................................................................................................................15
Discussion.......................................................................................................................19
Invertebrates...............................................................................................................19
Water Quality..............................................................................................................21
Limitations ..................................................................................................................22
Future Work................................................................................................................23
Conclusion ......................................................................................................................24
Bibliography....................................................................................................................25
Appendix 1 Raw Data.......................................................................................................32
Appendix 2 Statistical Tests Minitab Output......................................................................36
Appendix 3 Standard Laboratory Procedures.....................................................................45
Appendix 4 Cross Sections................................................................................................46

6. UoP: 677644
v
Table of Figures
Figure 1 an example of brushwood woody debris on the River Whitewater, Basingstoke
(Authors own)...................................................................................................................2
Figure 2 an example of anupstreamgroyne onthe RiverLambourn, Newbury (Authors own)
.........................................................................................................................................2
Figure 3 the Bourne Rivuletlocation (Fishpal, 2014) ............................................................7
Figure 4 site location on Bourne Rivulet (Google, 2014) .......................................................8
Figure 5 the survey site (before habitat enhancement)........................................................9
Figure 6 habitatrestorationsite before workcompletedtakenfromwestbank(Authorsown)
.......................................................................................................................................10
Figure 7 woody debris and upstream groyne taken from downstream sample site looking
upstream (Authors own)..................................................................................................11
Figure 8 woody debris and upstream groyne taken from downstream sample site looking
upstream (Authors own)..................................................................................................11
Figure 9 the survey site after habitat enhancement work completed..................................12
Figure 10 the author conducting a kick sample on the middle survey site (Authors own) .....12
Figure 11 the total number of invertebrates counted at each site on each sampling date ....15
Figure 12 the total number Baetidae invertebrates counted at each site on each sampling
date................................................................................................................................16
Figure 13 the total number of Trichoptera invertebrates counted at each site on each
sampling date..................................................................................................................16
Figure 14 the total numberof invertebrate speciescountedbycommonname ateach site on
each sampling date..........................................................................................................17
Figure 15 the invertebrate BMWP score calculated for each site on each sampling date......17
Table of Tables
Table 1 survey dates and times...........................................................................................9
Table 2 adjusted BMWP scores of invertebrates................................................................13
Table 3 the range of water quality and flow results observedfor each site..........................18
Table 4 water quality and flow parameters analysed using general linear model .................18

7. UoP: 677644
1
Introduction
River Habitat Enhancement & Restoration
Crisp(2000) statesthe implementationof instreamstructurescanbe utilised to increase the
diversity of fish habitat through the aim of increasing the areas carrying capacity. A wide
range of habitatrestorationandenhancement techniques are being implemented on chalk
streams to improve the ecological status under the Water Framework Directive (WFD)
(Hendry et al., 2003; Newson and Large, 2006). Sternecker et al. (2013) states an important
part of riverrestorationandhabitatenhancementis toassessthe impactsonthe restoration
site andareas downstream,andtodetermine anypotential impactsasa result of changes to
flowdynamicsorincreasedordecreasedsedimentationlevels through monitoring and data
analysis.
Implementation of WFD management plans on chalk stream rivers has included river
restoration and habitat enhancement to improve and encourage wild brown trout
populations and reduce the need for stocking on river fisheries (Conallin et al., 2014).
Strategies have been implemented through enhancing habitat, stream velocities and silt
managementtohelprestore browntroutspawningareas(Hendryetal., 2003). Chalk stream
rivers are impacted and subjected to anthropogenic pressures including habitat
deterioration, pollution and introductions of invasive species which can affect the
biodiversity of a system (Muchan, 2013). The monitoring of fish, invertebrate and
macrophyte speciescoupledwith river restoration and habitat enhancement strategies are
beingimplemented to achieve good ecological status under the WFD (Van Ael et al., 2015).
The size and scale of projects is varied and is influenced by many factors including budget,
time andresource and equipment needs (Pretty et al., 2003). Everall et al. (2012) states the
majority of river enhancement and restoration works on chalk streams take place to
reinstate habitat and flow regimes that were lost as a result of river modification schemes
implemented in the twentieth century. River restoration projects are often prioritised to
focus on natural and semi-natural stretches to develop high value ecologically important
habitats for a range of fish, invertebrate and avian species (Harvey and Wallerstein, 2009).
River managers and land owners are increasingly utilising soft engineering solutions to
improve habitat for fish species as opposed to historical use of hard engineering solutions
and bank trimming and profiling (Palmer et al., 2005).
The use of instreamwoodydebrishasshowntoincrease the potentialgrowthof browntrout
by providing areas of slack water therefore reducing the amount of energy expended

8. UoP: 677644
2
(Gustaffson,2011).Langford etal. (2012) statesthe use of woodydebrisisbeneficial tolarge
brown trout (Salmo trutta). However juvenile brown trout have been shown to not utilise
these structures instead favouring marginal brushwood areas as they provide cover from
predators (Armstrong et al., 2003). The use of woody debris to form structures creates a
natural colonisable habitat for fish and invertebrate species (Hendry et al., 2003).
Figure 1 an example of brushwood woody debris on the River Whitewater, Basingstoke (Authors own)
Upstreamgroynes(flowdeflectors) (Figure 2) are installedonchalkstreams to increase flow
to reduce siltation in gravels, which improves salmon and brown trout spawning areas
(Hendryetal.,2003). The installationof upstreamgroynes,in-streambouldersandV-shaped
deflectorscanbe utilisedtomanipulate flow andincrease flowvelocitywhilstalsoimproving
habitat diversity (Smith et al., 2014).
Figure 2 an example of an upstream groyne on the River Lambourn, Newbury (Authors own)
River restoration and habitat enhancement methods can involve bank re-profiling, re-
meandering, narrowing and the creation of specific features including riffles, backwaters,

9. UoP: 677644
3
in-stream flow deflectors and woody debris areas (Pretty et al., 2003). The introduction of
gravels to aid spawning for salmonid species is a common conservation method in chalk
streams (Mueller et al., 2014)
Invertebrates
The high levels of secondary production in chalk streams ensure a large abundance and
speciesdiversityof invertebrates (Mann et al., 2006; Woodward et al., 2008). This results in
invertebratesrepresenting an important part of the diet for brown trout (Mann et al., 2006;
Woodward et al., 2008). Juvenile brown trout feed on small prey items such as micro
crustacea andsmall ChiromidaeandEphemeroptera larvae (Crisp,2000).Dineen et al. (2007)
states Baetidae and Trichoptera species represent the main species of invertebrates that
brown trout feed upon. Baetidae, Ephemera and Trichoptera species are most common
species of invertebrates found in southern England chalk streams with abundance levels
highest during May and June, due to their emergent life cycles (Wright et al., 1998).
Browntrout feedonall life stagesof invertebrateshoweveradultshave shown a preference
to feed on terrestrial surface drifting invertebrates, whilst juveniles show a preference to
feed on benthic invertebrates (Nilsson and Persson, 2005; Dineen et al., 2007). 0+ brown
trout utilise marginalhabitatswhichresultsintheirdietcompromisingmainlyof Chrironomid
and Plecoptera larvae (Skogland and Barlaup, 2006). Harrison (2000) states the marginal
habitatof chalkstreams is very important to the biodiversity of invertebrates with margins
often showing higher levels of abundance than mid channel habitats. Therefore
invertebratesshouldbe consideredinthe planningof restoration and habitat enhancement
methods for fish species (Spanhoff, and Arle, 2007).
Fish, invertebrate and macrophyte species have been comprehensively studied in chalk
streams however there have been limited studies on the response of invertebrates to the
implementationof habitatenhancementsforfishspecies (Haase et al., 2013). The following
studiesassesthe impactsof various methods of river restoration and habitat enhancement
on invertebrate abundance and populations.
A studyby Harrisonetal. (2004) ona lowlandriverfoundthatthe abundance,taxonrichness
and diversityof invertebratesare notaffectedbythe instillationof instreamflow deflectors.
Lepori etal. (2005) foundthatriverrestorationand enhancementtechniques,suchaswoody
debris,groynesorinstreambouldershave no effect on invertebrate population diversity or
abundance. A studyby Muelleretal.(2014) foundthe introductionof instreamboulders and

10. UoP: 677644
4
spawning gravels for salmonid fish species increased the invertebrate species density and
abundance.
Jahnig et al. (2010) states river restoration and habitat enhancement methods in rivers
implementedtocreate more diverse habitats do not result in any significant changes to the
abundance of invertebrate species. A study by Sternecker et al. (2013) found invertebrates
oftenshowa decrease inabundance inthe shorttermafterriverrestoration has taken place
with an increase in abundance observed after 3 months. Muehlbauer et al. (2010) found
invertebrate abundance declines after the disturbance caused by river restoration
implementation however the recovery process is rapid resulting in short term effects in
newly restored systems.
A study by Everall et al. (2012) on the River Manifold found a significant increase in
invertebrate abundance andbiodiversityfollowing the installation of bank revetment using
softbrushwoodtechniqueshoweverthe projectwasa large scale restorationcovering300m.
This suggests that although small scale projects conducted by others have shown no
significant affect or increase to invertebrate abundance large scale projects may be
beneficial to invertebrates (Lepori et al., 2005; Jahnig et al., 2010). The expense and time
requiredoftenlimitfisheriesmanagersandlandownerstosmall scale projects (Haase et al.,
2013).
Harrison and Harris (2002) state chalk streams with a high structural diversity of bankside
vegetation show increased diversity of aquatic macroinvertebrates and terrestrial adult
aquatic insects. Invertebrate populations often show greatest abundance and diversity in
marginal areas of rivers and chalk streams (Harrison et al., 2004).
Gore et al. (2001) states flow, water quality interactions of conditions and morphology are
the factors that have the greatest influence on the distribution and abundance of
invertebratesinrivers.The changesinchalkstreamflow regimescaused by natural seasonal
variation, channel diversions and abstraction have an impact in invertebrate productivity
thereby potentially affecting levels of abundance (Olsen et al., 2014). Carter et al. (2006)
statesseasonal variationmaycomplicate interpretationsorinfluence results of invertebrate
abundance andpopulationstudies. Chalk streams invertebrates are sensitive to changes in
discharge andchangesinwater qualitysuchas ammonia, phosphorus and dissolved oxygen
which affects levels of abundance (Durance and Omerod, 2008).

11. UoP: 677644
5
The abundance levels of invertebrates in chalk streams can be affected by the rate of
invertebrate drift (Dewson et al., 2007; Kennedy et al., 2014). Invertebrate drift is a
fundamental process which is governed by intrinsic factors (invertebrate life stage,
behaviour and benthic diversity) and extrinsic factors (discharge, light intensity and water
quality) (Kennedy et al., 2014). The absence of instream macrophytes in chalk stream
especially Ranunculus can lead to increased invertebrate drift (Dewson et al., 2007). The
presence of Ranunculus in chalk streams helps to provide a more diverse range of habitats
for invertebrates and fish by providing cover and by changing flow dynamics with clear
channelsoffingfasterflows with slacker areas behind the Ranunculus beds (Harrison et al.,
2005).
Dewsonetal.(2007) statesinvertebrate driftincreasesimmediatelyfollowing a reduction in
flowresultingindecreasedhabitatforsome speciesandincreasedhabitatfor others. During
periods of low flow conditions on chalk stream rivers invertebrates have been shown to
decrease in population abundance, due to the change in habitat conditions and therefore
the suitability of the habitat (Wood et al., 2010; Kennedy et al., 2014). A decrease in flow
velocitycanresultinan increase ininvertebrate driftforspeciessuch asmayflylarvae due to
habitatbecomingunusable (Dewsonetal., 2007; James et al., 2008). However species there
is an increase of species that are suited to low velocity conditions such as worms and
Chrironomid larvae (James et al., 2008).
Trichoptera speciescan be less susceptible to changes in flow than Baetidae species due to
upstream crawling aggregation (Pastuchova, 2006). Trichoptera species invertebrate drift
levels increase when flow increases due to individuals being dislodged by the increase d
current or changes in behaviour that have been observed in response to changes in flow
(Verdonschotetal.,2014). A reductioninflow causes a decrease in invertebrate abundance
in chalk streams as a result of increased predation rate and increase in invertebrate drift
(England, 2011).
The regular assessment of invertebrate populations is undertaken to monitor river water
quality and to assist the environment agency to measure the effects on rivers of pollution
incidents (Wright et al., 2003). Aquatic invertebrates have different tolerances to levels of
pollution and water quality (Chang et al., 2014). The Biological Monitoring Working Party
(BMWP) score usesinvertebratesasbiological indicatorstodeterminewaterquality (Paisley
et al., 2014).

12. UoP: 677644
6
BMWP scores onlyindicate animpactwhen a taxon disappears or appears which the case is
often during monitoring for low abundant species (Clarke and Murphy, 2006). Therefore
measuringabundance alongside BMWPscore providesmore accurate analysisof population
changes (Paisley et al., 2014). The BMWP score is an important part of invertebrate
monitoring but by assessing assemblages based on presence or absence seasonal changes
are difficulttodetect(Leundaetal.,2009). Therefore individual species and total counts are
important to help detect changes to invertebrate abundance (McCabe and Gotelli, 2000;
Leunda et al., 2009).
Water Quality
Chalkstreamsin southernEnglandhave highnutrientlevelsandflow regimes which provide
excellent conditions for the growth of aquatic plants and produces a large abundance and
varietyof invertebrate,macrophyte and fish species (Bowes et al., 2005). Chalk streams are
fedfromgroundwateraquifersthatcontribute between73-90% of total flow (Heywood and
Walling, 2007). The water has a high clarity a relative high water quality resulting in high
levels of primary and secondary production with high levels of biodiversity (Allen et al.,
2010).
The temperature can range between 4-18°C over a year with an average temperature of
10°C (Bowes et al., 2011; Shelly et al., 2015). The water temperature correlates with air
temperature (due towaterandair respondingtotemporal solarheatinputs) andcan also be
affected by the time of day measurements are taken and the levels of riparian shading
(Johnson,2004; Boweset al.,2011). Neal etal.(2000) stateslevelsof suspendedsolidsincan
vary between 1.4-17.8 mg/l with an average of 5.4 mg/l, with fluctuations often being a
result of surface run off (Crooks, 2011).
Ammonia levels can range between 0.00-0.15ppm with an average level of 0.03ppm and
dissolved oxygen ranges between 90-110 % saturation and often fluctuates daily due to
diurnal rhythm (Neal et al., 2000). The pH can fluctuate up to 0.9 in a day, as a result of in-
steambiological activitywitharange of approximately7.3-8.2(Neal et al., 2000; Flynn et al.,
2002). Phosphorus levels can range between 0.1-0.4ppm and are affected by changes to
flow, temperature, diffuse agricultural inputs, and sewage and watercress farm effluent
(Bowes et al., 2011).
The Bourne Rivulet
The Bourne Rivulet is a chalk steam tributary of the River Test in Hampshire. The source is
locatedjustnorthof Ibthorpe andithas a course of three milesbeforejoining the River Test

13. UoP: 677644
7
at Whitchurch (Figure 3,). The Bourne rivulet is famous for wild brown trout fishing, with
upstreamdryflyand nymphfishingthe acceptedmethods. The wildbrowntroutfishingwas
popularised by the book 'Where bright waters meet' by Harry Plunket Greene which
motivatesmanyanglerstovisitandfishthe Bourne Rivuleteachyear(FamousFishing,2011).
Figure 3 the Bourne Rivulet location (Fishpal, 2014)
Aims & Objectives
There are limitedstudies on the impact of habitat enhancement structures for brown trout
relatingtoinvertebrate abundance. The aimof the studywasto assessif the implementation
of habitatenhancementstructuresforbrowntroutaffectsinvertebrate abundance. The site
consideredonthe Bourne Rivuletenabledastudytotake place ona privatelyowned stretch
of chalk stream river. The Bourne Rivulet above Hurstbourne Priors is almost unique as a
stretch of chalk stream because brown trout are the only fish species present with the
exception of micro fish species such as Bullhead (Cottus gobio).
The aim of the river enhancement was to create an area of marginal brushwood woody
debris and upstream groyne to provide holding areas for both juvenile and large brown
trout.
Hypotheses
Null hypothesis:
The implementation of habitat enhancement structures for brown trout on the Bourne
Rivulet has no affect on invertebrate abundance.
Alternative hypothesis:
The implementation of habitat enhancement structures for brown trout on the Bourne
Rivulet causes short or long term changes to invertebrate abundance.

14. UoP: 677644
8
Methodology
Site Selection
The site for the implementhabitatrestorationforthe purpose of thisstudywas chosen after
consultation between the author and fishery manager Nick Lawrence. The site was chosen
for the following reasons;
 An absence of watercrowfoot(Rannunculusspp.) weedgrowthwhichwouldprovide
cover for brown trout.
 A high amount of siltation in the gravel substrate.
 The area had no previous habitat restoration measures implemented.
 The use of upstream groynes enabled the flow to be manipulated allowing the
creation of an artificial meander in an otherwise straight stretch of river.
 The absence of features to create holding areas for large brown trout.
 An absence of marginal coverandfeaturesforjuvenile browntroutandinvertebrate
species on the west bank
Site Location
The site was located approximately 250m upstream of the iron bridge above the village of
Hurstbourne Priors(Figure 4).Once the site was chosen the decision was made to install an
area of woody debris, incorporating an upstream groyne.
Figure 4 site location on Bourne Rivulet (Google, 2014)

15. UoP: 677644
9
Three areas of the site were chosen for sampling. They were 10m above (upstream site),
10m below(downstreamsite) andanarea immediatelybelowwhere the habitat restoration
was to be implemented (middle site) (Figure 5).
Figure 5 the survey site (before habitat enhancement)
Table 1 shows the dates and times for the sampling and the habitat enhancement
implementation.A periodof twoweekswasallowedbetweeneachsampledate to allow the
areas to recover.Anexceptionwasmade forthe firstsample afterthe habitat enhancement
implementation, as this enabled more potential short term affects to be assessed.
Table 1 survey dates and times

16. UoP: 677644
10
Habitat Restoration
Figure 6 showsthe site lookingfrom the west bank from the middle sample site before any
habitat restoration has taken place.
Figure 6 habitat restoration site before work completed taken from west bank (Authors own)
Willowbrancheswere cutfrom a tree which had fallen across the stream, creating material
for the woody debris structure and removing an obstacle to anglers and a potential flood
risk. The trunk of the fallen tree was utilised for the upstream groyne.
The willowcuttingswere pushed into the bank at the upstream end of the designated area
for restoration. Layers of branches were built up and pushed underneath each other to
create a living matrix with spaces created for juvenile brown trout habitat.
Utilising willow as the material for the woody debris means the branches will continue to
grow.Ongoingmanagementwillbe neededtoensure the structure retainsthe correctshape
and doesnotincrease insize. This is the preferred technique of the fishery manager and as
suggested by, Hendry et al. (2003). Through utilising willow this will provide him with a
supply of willow branches for future habitat enhancement material.
The trunk sectionwasmanoeuvredintoplace sothatitoverlappedthe woody debris, which
helpedtopinthe branchesinplace and to preventscouringanderosion taking place behind
the upstream groyne.
The upstream groyne was pinned in place with two chestnut stakes at either end and
securedwithwire.The chestnutstakeswere drivenapproximately0.4mintothe substrate to

17. UoP: 677644
11
ensure the structure wasstable,andwouldremaininplace evenduringperiodsof highflows
and floods. Figure 7 shows the completed habitat enhancement with woody debris and
upstream groyne in place.
Figure 7 woody debris and upstream groyne taken from downstream sample site looking upstream (Authors
own)
The woodydebriswasheldinplace withwire whichwastightenedbetween chestnut stakes
whichwill ensure the branchesremaininplace duringhigh flows and in periods of flooding.
A large branch fromanotherfallentree was placed over the woody debris branches to help
pin the small branches in place (Figure 8).
Figure 8 woody debris and upstream groyne taken from downstream sample site looking upstream (Authors
own)

18. UoP: 677644
12
Figure 9 shows the site scale drawing after habitat enhancement works were completed.
Figure 9 the survey site after habitat enhancement work completed
Kick Sampling
A standard three minute kick sample was taken across the width of the stream (Mercer et
al., 2014). An assistant timed and called out at 30 second intervals to ensure a consistent
procedure forall samplestaken.Figure 10showsthe author conductinga kicksample on the
middle sample site.
Figure 10 the author conducting a kick sample on the middle survey site (Authors own)
UPSTREAM GROYNE

19. UoP: 677644
13
Once each kick sample was completed the contents of the net were emptied into a white
tray (43x28x7.5cm) with water. The nets were twice washed through to ensure the entire
contentswere emptiedintothe tray.Each sample wasanalysedwitheachspeciesassigned a
category and the number estimated as accurately as possible. A modified Biological
MonitoringWorkingParty(BMWP) score was assigned to each sample (Table 2) with scores
beingadjustedfromPaisleyetal.(2014) to allow identification by the common name rather
than species level.
Table 2 adjusted BMWP scores of invertebrates
The samples were returned to the river from the area they were taken once fully analysed
and recorded. Each of the three areas of the site was sampled once on each survey date.
All kicksamplingandsample analysiswascompletedby the author to ensure a constant and
consistent effort to reduce error, inaccuracies and bias in the results.
Water Sampling
Water samples were collected for suspended solids, ammonia, phosphorus and nitrite
analysisOneachsurveydate.The sampleswere collected in 1L mineral water bottles which
were thoroughly washed with river water before the sample was collected.
The sampleswere collectedstartingatthe downstreamsample site, then working upstream
to ensure the results were not affected by particles being disturbed by wading the stream.
All samplesacrossthe three siteswere takenfromthe midpoint of the stream. The samples
were frozenonthe day of collectiontoallow for lab analysis to be completed at a later date
(Cabrita et al., 2014).

20. UoP: 677644
14
Dissolved oxygen and temperature were measured using a HI 9146 portable waterproof
dissolved oxygen meter. The pH was measured using a VWR pH 100 probe. Carbonate
hardness (KH) and general hardness (GH) were measured using Tetra test kits. All water
qualitytestsandreadingswere takenfromthe same pointateach site andall samples dated
and labelled with the location they were collected from.
Depth & Flow
The flow rate measurements were taking with a MFP126-S advanced stream flowmeter.
Flow rate measurements were taken at three points across the stream to calculate a mean
flowrate.A RiverFormChannel Analysissoftwareprogramwasusedinconjunction with the
mean flow velocity, depths and width data to provide a cross sectional area and flow
discharge (cumecs). Flow rates and depth were measured for each site on all survey dates.
Lab Analysis
The bottlescontainingthe watersamplesweredefrostedatroomtemperature andanalysed
in the Sparsholt college analytical laboratory. The samples were filtered to test for
suspended solids (Appendix 3) and for preparation for the skalar machine analysis (San ++
systemcontinuousflow analyser).The filterpaperswere weighedbefore and after filtration
of the sampleswiththe difference giving a measurement of suspended solids in milligrams
per 500ml of water (mg/500ml).
Approximately15ml of filteredsample waterwasplacedinlabelled15ml cuvette foranalysis
in the skalar (Skalar, 2014) machine for ammonia, phosphorus and nitrite. Each sample was
completedintriplicatetoreduce the possibilityof errorsand an average of the three results
taken to give the final result for ammonia, phosphorus and nitrates.
Statistical Analysis
Statistical analysiswasconductedonthe resultsfor total abundance of all species (the total
sumof all individualscountedforeveryspeciesforeach site). The abundance of Trichoptera
species (cased caddis and caseless caddis) and Baetidae species (burrowing mayfly,
swimming mayfly, blue winged olives and flat bodied olives) is significant as they are the
most important part of the brown trout diet in chalk streams (Dineen et al., 2007). The
numberof speciesbycommonname andBMWP score.Statistical testswere usedto analyse
the water quality and flow parameters.
On completion of data collection tests for normal distribution and equal variance were
conducted with the result being that not all data was normally ditributed and with equal

21. UoP: 677644
15
variance. Littell et al. (2002) states that a general linear model can be used for normally
ditributed and not normally distributed data, with or without equal variance. Therefore
general linearmodelwas chosen to statistically test the data. This enabled multiple factors
be analysed assesing if any significant differences between factors were present between
the sites and the dates.
Results
Figure 11 the total number of invertebrates counted at each site on each sampling date
A general linearmodelanalysingthe total invertebratecountshowedasignificantdifference
between the dates (P=0.000) and a significant difference between the sites (P=0.045).
However a tukey analysis shows all sites are in the same group. A general linear model
excludingthe middle site on 24/06/2014 shows no significant difference (P=0.117)between
the sites but a significant difference between the dates (P=0.000). A general linear model
excluding all site data from 24/06/2014 also shows no significant diference (P=0.143)
betweenthe sitesbutasignificantdifference between the dates (P=0.000). The total count
was 293 which were much lower than the upstream control site (576 total invertebrate
count) and the downstream site (522 total invertebrate count). The species showing the
biggest reduction were swimming mayflies.
Date 05/08/201422/07/201408/07/201424/06/201417/06/201403/06/2014
800
700
600
500
400
300
200
100
0
TotalInvertebrateCount
Downstream
Middle
Upstream
Site

22. UoP: 677644
16
Figure 12 the total number Baetidae invertebrates counted at each site on each sampling date
A general linearmodelanalysingthe Baetidaecountshowedasignificantdifference between
the dates (P=0.000) and no significant difference between the sites (P=0.058).
Figure 13 the total number of Trichoptera invertebrates counted at each site on each sampling date
A general linear model analysing the trichoptera count showed no significant difference
between the dates (P=0.208) and no significant difference between the sites (P=0.176).
Date 05/08/201422/07/201408/07/201424/06/201417/06/201403/06/2014
500
400
300
200
100
0
BaetidaeCount
Downstream
Middle
Upstream
Site
Date 05/08/201422/07/201408/07/201424/06/201417/06/201403/06/2014
30
25
20
15
10
5
0
TrichopteraCount
Downstream
Middle
Upstream
Site

23. UoP: 677644
17
Figure 14 the total number of invertebrate species counted by common name at each site on each sampling
date
A general linear model analysing the total number of invertebrate species counted by
common name showed no significant difference between the dates (P=0.939) and no
significant difference between the sites (P=0.416).
Figure 15 the invertebrate BMWP score calculated for each site on each sampling date
A general linearmodelanalysingthe BMWPscore showednosignificantdifference between
the dates (P=0.989) and no significant difference between the sites (P=0.453)
Date 05/08/201422/07/201408/07/201424/06/201417/06/201403/06/2014
12
10
8
6
4
2
0
NumberofSpeciesbyCommonName
Downstream
Middle
Upstream
Site
Date 05/08/201422/07/201408/07/201424/06/201417/06/201403/06/2014
80
70
60
50
40
30
20
10
0
BMWPscore
Downstream
Middle
Upstream
Site

24. UoP: 677644
18
Table 3 the range of water quality and flow results observed for each site
The ranges of valuesforwaterquality and flow parameters for each site are shown in Table
3. The results show little variation between the sites for most factors except middle site
results for discharge and cross section volume which were higher than the upstream and
downstream sites. All raw data for the study can be seen in Appendix 1.
Table 4 water quality and flow parameters analysed using general linear model
The water quality and flow parameters analysed using general linear model showed a
significantdifferencebetweenthe dates for pH (P=0.000), temperature (P=0.000), ammonia
(P=0.005), phosphorus (P=0.002), nitrite (P=0.000), discharge (P=0.000), mean velocity
(P=0.007) and cross section volume (P=0.002). No significant difference between the dates
was observedfordissolvedoxygen(P=0.142) and suspended solids (P=0.795). No significant
difference was observed between the sites for pH (P=0.864), temperature (P=0.400),
ammonia (P=0.701), phosphorus (P=0.402), nitrite (P=0.402) and mean velocity (P=0.409). A
significant difference between the sites was observed for discharge (P=0.000) and cross
section volume (P=0.000). A tukey test showing all sites were significantly different from
each other for both discharge and cross section volume.

25. UoP: 677644
19
Discussion
Invertebrates
The drop ininvertebrate abundance observed for the middle site on the 24th June coupled
with changes to flow dynamics suggest the disturbance caused by the installation of the
habitat enhancement have caused a short term effect to invertebrate abundance. The
effectspotentiallyaresultof the subsequent changes to the cross sectional profile or slight
variationsinflow.ThisconcurswithstudiesbySterneckeretal.(2013) and Muehlbaueretal.
(2010) which found Invertebrates abundance decreases in the short term after river
restoration and habitat enhancement. The effects are limited to the short term as
invertebrate recovery process is rapid as many species show high levels of resilience to
disturbances(Muehlbauer et al., 2010; Ledger et al., 2012). The recovery of invertebrates is
supplemented by immigration occurring from invertebrate drift (Ledger et al., 2012).
The resultsshowthat nolongterm effectswere evidentoninvertebrate abundance afterthe
implementation of the habitat enhancement structures. A study by Harrison et al. (2004)
alsofoundthat invertebrateabundance wasnotaffectedbythe installationof instreamflow
deflectors in a lowland stream. Leprori et al. (2005) showed similar findings where the
installation of woody debris, groynes and boulder enhancement techniques and river
restorationprojectshasnoeffecton invertebrate abundance. Jahnig et al. (2010) found the
implementationof riverrestorationandhabitatenhancementmethodscausednosignificant
changes to invertebrate abundance. However Everall et al. (2012) found a significant
increase in invertebrate abundance and biodiversity after the implementation of a 300m
restoration project on the River Manifold which used soft brushwood bank revetment
techniques.Therefore the resultsof thisstudyconcurwithpreviousfindings that small scale
projectshave nolongterm effectsoninvertebrate abundance,whilstlarge scale projectscan
be beneficialand improve invertebrate abundance and diversity (Lepori et al., 2005; Jahnig
et al., 2010).
The total invertebrate count showed a significant difference (P=0.000) for the dates which
can be contributed to all sites showing a decrease in abundance. The average total count
decreasedfrom509 onthe firstsample date to260 onthe lastsample date. The decrease in
abundance can be explained through seasonality, with Wright et al. (1998) suggesting that
invertebrate abundance levels in chalk streams are highest during May and June due to the
emergent life cycle of species such as Baetidae, Ephemera and Trichoptera. Carter et al.
(2006) suggestsseasonal variation can influence the results of invertebrate population and

26. UoP: 677644
20
abundance studies.Throughoutthe studyminimal changeswere observedtothe abundance
categoriesformostinvertebrate species. The changes to the abundance categories that did
occur helpconfirmthe effect of seasonality on the results of this study (Wright et al., 1998;
Carter et al., 2006).
The abundance of Baetidae speciesfollowedthe same trend as the total abundance with no
significantdifferencebetweenthe sitesshown(P=0.058). A decrease wasseenonthe middle
site forthe 24th June witha significantdifference beingshownbetweenthe dates (P=0.000).
This concurs with studies by that found as flow decreases, invertebrate drift in Baetidae
species increases due to a reduction in suitable habitat (James et al., 2008; Wood et al.,
2010; Kennedyetal.,2014).The reductioninabundance canalso be explainedbyseasonality
due to the emergent life cycle of Baetidae species (Wright et al., 1998).
The abundance of Trichoptera species also showed no significant difference between the
sites (P=0.176) and no significant differences between the dates (P=0.208). However the
upstreamsite showedahigherabundance category than the middle and downstream sites.
Thiswouldsuggest thatthe implementationof the habitatenhancement doeshave aneffect
of Trichoptera abundance. However the counts were all between 10 and 30 individuals
meaning the species are of low abundance and small differences in counts are magnified
(Leunda et al., 2009). The absence of a significant difference between the dates suggests
Trichoptera species are potentially less affected by seasonality and less susceptible to
changesinabundance inresponse tochangesin flow (Pastuchova, 2006; Verdonschot et al.,
2014).
A significantdifference wasshownfor mean velocity for all sites across the dates (P=0.007),
which can be attributed to the 0.09m drop in river level that occurred during the study
period. The implementationof the habitatenhancement structures did not affect the mean
velocity for the middle site, however the nearside flow measurements reduced to 0.00
m/sec from 0.45 m/sec and the middle measurements increased from 0.25 m/sec to 0.50
m/secbefore the structureswere installed.The changesshow thatthe habitatenhancement
affectedthe middlesite flow dynamics resultinginpotential changesto invertebrate habitat
conditions(Durance andOmerod,2008; Kennedyet al., 2014). Gore et al. (2001) states flow
isone of the most influentialfactorsonthe abundance of invertebratesinrivers.Kennedy et
al.(2014) statesinvertebrate abundancelevelsare affectedbythe rate of invertebrate drift,
which can be influenced extrinsic factors including flow and discharge. Invertebrates are
sensitive to changes in flow regimes caused by natural seasonal variation which results in

27. UoP: 677644
21
changesto abundance levels(Durance andOmerod,2008; Olsenetal.,2014). The changesin
velocity will have influenced the rate of invertebrate drift that occurred (England, 2011). A
studyby Dewsonetal.(2007) foundinvertebratedriftincreaseswhenflow decreases due to
changes to habitat conditions. The changes to habitat as a result of reduced flow increases
invertebrate drift in mayflies and caddis larvae whilst species which prefer low velocity
conditions can potentially increase (James et al., 2008; Wood et al., 2010; Kennedy et al.,
2014).
The absence of instream macrophytes (especially Ranunculus) in the study site will have
contributed to the level of invertebrate drift potentially increasing as the flow decreased
(Dewsonetal.,2007). The presence of Ranunculus providescoverforinvertebrates aswell as
changing flow dynamics therefore creating a more diverse area of habitat (Harrison et al.,
2005).
No significant difference was observed for number of species by common name (P=0.416)
and BMWP score (P=0.453) between the sites. This concurs with the studies by Harrison et
al. (2004) and Lepori et al. (2005) which found that river restoration and habitat
enhancementtechniques implemented for trout had no effect on invertebrate diversity or
taxon richness. The number of species by common name and BMWP score showed no
significantdifferencebetween the dates, which suggests the availability of suitable habitat
was reduced as opposed to being removed (Dewson et al., 2007). The similar number of
species by common name and BMWP score found through the duration of the study
suggests seasonality affects abundance rather than species diversity (Wright et al., 1998).
HoweverLeundaetal.(2009) statesseasonal changesare difficult to detect when analysing
invertebrates using BMWP scores. The presence or absence of low abundant species can
affectBMWP scores and make assessment of changes in population structure and diversity
due to seasonality difficult to analyse (Paisley et al., 2014).
Water Quality
The significantdifferencesobserved in water quality parameters between the dates can be
attributed to the weather conditions for the duration of the study with temperature being
the driving factor that influences changes (Johnson, 2004; Bowes et al., 2011). The only
significant differences between the sites for water quality and flow parameters observed
were for discharge and cross sectional volume. The absence of a significant difference
between the sites can be attributed to the stable conditions of chalk streams and suggests
the implementation of the habitat enhancement structures had no effect on water quality

28. UoP: 677644
22
(Bowes et al., 2005). However short term fluctuations in water quality could have occurred
but not recorded due to the weekly or fortnightly sampling dates (Wade et al., 2012). The
waterqualityresultswere asexpected due the similarities to results from previous studies
conducted on chalk streams (Neal et al., 2000; Flynn et al., 2002; Johnson, 2004; Heywood
and Walling, 2007; Allen et al., 2010; Bowes et al., 2011; Crooks, 2011; Bowes et al., 2011;
Shelly et al., 2015).
The significant difference between the sites for discharge (P=0.000) was unexpected as all
sites should have been the same. The difference could have been caused by errors by the
author in data collection. Bradford (2002) suggests digital flow metres can have a 2% error
margin,and thatmanual readingof depths to the nearest centimetre can also result in a 2%
error which can affect discharge calculations. Walling et al. (2006) suggests differences in
discharge can be observed in short distances of rivers due to variation in surface and
groundwaterinteractionresultingin flow accretion or depletion. A significant difference in
discharge was observed between the dates for discharge (P=0.000) and cross sectional
volume (P=0.000) whichcan be attributedtothe drop inriverlevel that that occurred during
the study period. The significant difference between the sites observed for cross sectional
volume could have been caused by the variations in site (Madsen et al., 2001) or potential
errors during the data collection (Bradford, 2002).
Limitations
The high levels of silt and detritus in the kick samples made counting all individuals very
difficult(Tayloretal.,2001). Therefore the counts of each species were estimated however
the abundance categories were used as a guide in an endeavour to achieve a count which
was accurate as possible.Asthe total countsof speciesindividuals were estimated this may
have affectedthe accuracyof the results.Howeverthe same processwasusedby the author
inanalysingeachsample,inanattemptto avoidsubjectification and gain as accurate results
as possible. A larger tray size may have helped to spread out the samples and make counts
and identification easier for the author.
The invertebrateswere identified to species level but by common name and identification
guideswere useditwould have been more accurate to identify all invertebrates to species
level.Howeverthiswasbeyondthe capabilitiesof the author and would have been difficult
to achieve whenanalysingsamplesinthe field. The slightvariations in flow rate, depths and
widths(therefore crosssectional volume) and habitat (for example the large slack silty area
on the middle site) couldhave affected the results (Franken, 2008). Although the variations

29. UoP: 677644
23
in habitat have been noted, a full habitat assessment of the sites including substrate type,
macrophyte coverage and a more in depth flow analysis, would have allowed for a greater
understanding of any effects the habitat enhancement structures had on the river
morphology. A parallel survey to measure the levels of invertebrate drift occurring would
have helped understand the effects of changes to flow caused by the installation of the
habitatenhancementand due tothe drop inriverlevel thatoccurredduringthe study(Neale
et al.,2008). Howevermeasuringinvertebrate driftwasnotconsideredwhenthe experiment
was designed and the limited access to the river and the time needed to conduct the extra
survey would not have made it feasible for the author.
Whilstthe large numbers of variables where possible have been taken into account, whilst
collectingandanalysingdataforthisstudythe conclusionsfound are potentially subjective.
Therefore it is suggested further work is needed to help provide more conclusive results
(Nilsson et al., 2003).
The numberof watersamples collected was restricted to one sample per site for each date
because of limitedfreezer space availability. Ideally at least two samples would have been
taken from each site on all dates to allowing the replicates to be averaged ensure results
were as accurate as possible (Haley, 2009).
Future Work
The following future works have been identified which would eliminate some of the
limitationsandprogressthe ideasandfindingsof thisstudy.The three minutecrosssectional
kicksample collectionmethodisstandardprocedure,butit only provides an overview of all
habitat types and invertebrate abundance across the stream. The effects of the
implementation of small scale habitat enhancement for brown trout may be limited to
specific habitat areas and invertebrates often show a higher abundance in marginal areas
than mid channel habitats (Harrison, 2000). Therefore a repeat of this study using a similar
technique toHarrisonetal. (2004) which utilised 30 second kick samples on specific habitat
areas and their location in relation to the introduced structures would be preferable.
The Identificationof invertebratescouldbe completedtospecieslevel bypreservingsamples
and taking them to be identified in a laboratory. The identification to species level would
allowanaccurate assessmentof the diversityof invertebrates,withaShannonWienerindex
which would provide a greater understanding of any affects of habitat enhancement
implementation (Spellerberg and Fedor, 2003). Analysing samples in laboratory conditions
would also allow more accurate counts of species, and total counts for abundance analysis

30. UoP: 677644
24
rather thanthe estimatedcountsthe authorusedwhenanalysingsamplesinthe field (Baker
and Huggins, 2005).
The study should be replicated on the Bourne rivulet and other chalk stream rivers with a
variety of structures, including woody debris, upstream groynes, boulders and faggoting
should being utilised. Increasing the number of structures, and the rivers the studies are
conducted on, will provide larger data set, and through data analysis would help to gain a
greater understanding of the effects on invertebrate abundance of river restoration and
habitat enhancement methods. Future studies should include fish population surveys, to
access the potential success of habitat enhancement for brown trout.
The removal of a number of trees around the study site to allow more light penetration is
recommended as future habitat works on the study site to improve fish habitat (Wood,
2012). The removal of trees will decrease the level of riparian shading and help resolve
absence of Ranunculus on the study area (Taniguchi et al., 2003; Wood, 2012). Studies have
shown Ranunculus coverage in chalk streams help improve habitat for brown trout and
invertebrate species by increasing the physical complexity and providing a variety of flow
dynamics (Taniguchi et al., 2003; McCormick and Harrison, 2011).
Conclusion
In conclusionthe resultsof thisstudyshow thatthe implementationof habitatenhancement
structuresforbrown trouthave a shorttermlocalisedeffectoninvertebrate abundance.The
rapidrecoveryof invertebratesdue toahighresilience todisturbance means that there was
no observedlong term effect to invertebrate abundance. The drop in abundance observed
across all sites during the study can be attributed to seasonality, the invertebrate life cycle
and invertebrate drift caused by responses to changes in flow and habitat suitability. The
Baetidae species followed the same trend as the total counts whilst Trichoptera species
showing less effects in response to changes in flow and habitat availability. The level of
invertebrate driftthatoccurred may be affected by the lack of macrophyte coverage on the
study sites especially Ranunculus.
The results suggest that the implementation of habitat enhancement structures have no
effect on the number of species by common name and BMWP score for the sites. The
absence of a significantdifference betweenthe datesforthe number of species by common
name and BMWP score suggestthatany changesto abundance caused by seasonality affect

31. UoP: 677644
25
the numberof individualsratherthanthenspeciesdiversity,andthat any changes to habitat
are in reduction rather than removal.
The water quality results for the study are as expected, due to the similarity with those
foundinexistingliterature.Whilstchangesinflow andmorphologywere observed after the
habitatenhancementimplementation,the resultsof the studysuggestthe structures had no
effectonwaterquality.The significant differences observed between water quality factors
and the dates can be attributed to the weather conditions as temperature is the driving
factor behind water quality changes.
The results of this study suggest the null hypothesis should be rejected with the alternate
hypothesisbeingaccepted due the short term effect on invertebrate abundance caused by
the implementation of habitat enhancement structures for brown trout.
Null hypothesis: Rejected.
The implementation of habitat enhancement structures for brown trout on the Bourne
Rivulet has no affect on invertebrate abundance.
Alternative hypothesis: Accepted for short term effects.
The implementation of habitat enhancement structures for brown trout on the Bourne
Rivulet causes short or long term effects to invertebrate abundance.
Bibliography
Allen,D.J.,Darling,W.G., Gooddy,D. C.,Lapworth,D. J., Newell,A. J., Williams, A. T., Allen,
D., Abesser, C. (2010). Interaction between groundwater, the hyporheic zone and a Chalk
stream: a case study from the River Lambourn, UK. Hydrogeology journal. 18(5):1125-1141.
Armstrong, J.D., Kemp, P.K., Kennedy, G.J.A., Ladle, M., Milner, N.J. (2003). Habitat
requirements of Atlantic salmon and brown trout in rivers and streams. Fisheries Research.
62(2):143-170.
Baker,D. S. and Huggins,D.G. (2005). Sub-samplingtechniquesformacroinvertebrates, fish
and benthicalgae sampledin biological monitoring of streams and rivers. Kansas biological
survey report. 132:25.
Bowes,M. J.,Leach, D. V.,House,W.A. (2005). Seasonal nutrientdynamicsinachalkstream:
the River Frome, Dorset, UK. Science of the total environment. 336(1):225-241.
Bowes,M. J.,Smith,J.T., Neal, C.,Leach,D. V.,Scarlett, P. M., Wickham, H. D., Harman, S.A.,
Armstrong,L.K.,Davy-Bowkers, J., Haft, M., Davies, C. E. (2011). Changes in water quality of
the River Frome (UK) from 1965 to 2009: Is phosphorus mitigation finally working?. Science
of the total environment. 409(18):3418-3430.

32. UoP: 677644
26
Bradford, R. B. (2002). Controls on the discharge of Chalk streams of the Berkshire Downs,
UK. Science of the total environment. 282:65-80.
Cabrita, M.T., Raimundo, J., Pereira, P., Vale, C. (2013). Immobilised Phaeodactylum
tricornutum as biomonitorof trace elementavailabilityinthe watercolumnduringdredging.
Environmental science and pollution research. 21(5):3572-3581.
Carter, J.L., Resh, V.H., Hannaford, M.J., Myers, M.J. (2006). Macroinvertebrates as biotic
indicatorsof environmental quality.InF.R.HalverandG.A.Lamberti (Eds.), Methodsin stream
ecology (pp.108-116). Elsevier: London.
Chang, F-H., Lawrence, J.E., Rios-Touma, B., Resh, V.H. (2014). Tolerance values of benthic
macroinvertebratesforstreambiomonitoring:assessmentof assumptionsunderlyingscoring
systems worldwide. Environmental Monitoring and Assessment. 186(4):2135-2149.
Clarke, R.T. and Murphy, J.F. (2006). Effects of locally rare taxa on the precision and
sensitivityof RIVPACSbioassessment of freshwaters. Freshwater biology. 51(10):1924-1940.
Conallin, J., Boegh, E., Olsen, M., Pedersen, S., Dunbar, M. J., and Jensen, J. K. (2014).
Daytime habitat selection for juvenile parr brown trout (Salmo trutta) in small lowland
streams. Knowledge and Management of Aquatic Ecosystems. 413(09).
Crisp, D.T. (2000). Trout and salmon: ecology, conservation and rehabilitation. Oxford:
Fishing news books.
Crooks, L. (2011). Organic contaminants in salmonid spawning grounds: occurrences and
effects on the early life stages of salmonids. Retrieved February 4, 2015, from,
http://eprints.port.ac.uk/7686/.
Dewson,Z.S.,James,A.B.W.,Death,R.G.(2007). A review of the consequences of decreased
flow for instream habitat and macroinvertebrates. Journal of the North American
benthological society. 26(3):401-415.
Dineen, G., Harrison, S. S. C., Giller, P. S. (2007). Diet partitioning in sympatric Atlantic
salmon and brown trout in streams with contrasting riparian vegetation. Journal of fish
biology. 71(1):17-38.
Durance, I. and Ormerod, S.J. (2008). Trends in water quality and discharge confound long-
term warming effects on river macroinvertebrates. Freshwater biology. 54(2):388-405.
England, G. B. N. (2011). An evidence base for setting flow targets to protect river habitat.
Retrieved February 2, 2015, from, http://www.envia.bl.uk/handle/123456789/4061.
Everall,N.C.,Farmer,A.,Heath,A. F., Jacklin, T. E., Wilby, R. L. (2012). Ecological benefits of
creating messy rivers. Area. 44(4):470-478.
Famous Fishing (2011). The Bourne Rivulet. Retrieved July 25, 2014, from,
http://www.famousfishing.co.uk/bourne-rivulet-fly-fishing_23.php.
Fishpal (2014). Hampshire chalk streams. Retrieved August 8, 2014, from,
http://www.fishpal.com/England/ChalkStreams/Hampshire.asp?dom=Pal.

33. UoP: 677644
27
Flynn, N. J., Snook, D. L., Wade, A. J., Jarvie, H. P. (2002). Macrophyte and periphyton
dynamics in a UK Cretaceous chalk stream: the River Kennet, a tributary of the
Thames. Science of the total environment. 282:143-157.
Google (2014). Google maps. Retrieved July 25, 2014, from, https://maps.google.co.uk
Gore, J.A., Layzer, J.B., Mead, J. (2001). Macroinvertebrate instream flow studies after 20
years: a role in stream management and restoration. Regulated rivers: research &
management. 17(4-5):527-542.
Gustaffson,P.(2011). Foreststreamlinkages:brown trout(Salmo trutta) responsesto woody
debris, terrestrial invertebrates and light. Retrieved September 25, 2014, from,
http://www.diva-portal.org/smash/get/diva2:387321/FULLTEXT01.pdf.
Haase, P., Hering, D., Jähnig, S. C., Lorenz, A. W., Sundermann, A. (2013). The impact of
hydromorphological restoration on river ecological status: a comparison of fish, benthic
invertebrates, and macrophytes. Hydrobiologia. 704(1):475-488.
Harrison, S. S. (2000). The importance of aquatic margins to invertebrates in English chalk
streams. Archiv für Hydrobiologie. 149(2):213-240.
Harrison, S. S., Bradley, D. C., Harris, I. T. (2005). Uncoupling strong predator–prey
interactions in streams: the role of marginal macrophytes. Oikos. 108(3):433-448.
Harrison, S.C. and Harris, I.T. (2002). The effects of bankside management on chalk stream
invertebrate communities. Freshwater biology. 47(11):2233-2245.
Harrison, S.S.C., Pretty, J.L., Shepherd, D., Hildrew, A.G., Smith, C., Hey, R.D. (2004). The
effectof instreamrehabilitationstructuresonmacroinvertebrates in lowland rivers. Journal
of applied ecology.41(6):1140-1154.
Harvey,G. L. and Wallerstein,N.P.(2009). Exploringthe interactionsbetweenflooddefence
maintenance works and river habitats: the use of River Habitat Survey data. Aquatic
conservation: marine and freshwater ecosystems. 19(6):689-702.
Haley,M. A. (2009). The impactof stream supporton the hydrology and macrophytes of the
upper Bristol Avon. Bioscience horizons. 2(1):44-54.
Hendry, K., Cragg-Hine, D., O'Grady, M., Sambrook, H., Stephen, A. (2003). Management of
habitatfor rehabilitationandenhancementof salmonidstocks.Fisheriesresearch. 62(2):171-
192.
Heywood,M.J. T. and Walling,D.E. (2007). The sedimentationof salmonidspawninggravels
in the Hampshire Avon catchment, UK: implications for the dissolved oxygen content of
intragravel water and embryo survival. Hydrological processes. 21(6):770-788.
Jahnig, S.C., Brabec, K., Buffagni, A., Erba, S., Lorenz, A.W., Ofenbock, T., Verdonschot,
P.F.M., Hering, D. (2010). A comparative analysis of restoration measures and their effects
on hydromorphologyandbenthicinvertebrates in 26 central and southern European rivers.
Journal of applied ecology. 47(3):671-680.

34. UoP: 677644
28
James, A. B. W., Dewson, Z. S., Death, R. G. (2008). The effect of experimental flow
reductions on macroinvertebrate drift in natural and streamside channels. River research
and applications. 24(1):22-35.
Johnson, S. L. (2004). Factors influencing stream temperatures in small streams: substrate
effects and a shading experiment. Canadian journal of fisheries and aquatic sciences.
61(6):913-923.
Kennedy, T. A., Yackulic, C. B., Cross, W. F., Grams, P. E., Yard, M. D., Copp, A. J. (2014). The
relation between invertebrate drift and two primary controls, discharge and benthic
densities, in a large regulated river. Freshwater biology. 59(3):557-572.
Langford,T.E.L., Langford, J. and Hawkins, S.J. (2012) Conflicting effects of woody debris on
stream fish populations: implications for management. Freshwater Biology. 57:1096-1111.
Ledger, M. E., Harris, R. M., Armitage, P. D., Milner, A. M. (2012). 3 Climate Change Impacts
on Community Resilience: Evidence from a Drought Disturbance Experiment. Advances in
ecological research. 46:211.
Lepori, F., Palm, D., Brännäs, E., and Malmqvist, B. (2005). Does restoration of structural
heterogeneity in streams enhance fish and macroinvertebrate diversity?. Ecological
Applications. 15(6):2060-2071.
Leunda,P.M., Oscoz, J.,Miranda,R., Ariño,A.H. (2009). Longitudinal and seasonal variation
of the benthicmacroinvertebrate communityandbiotic indices in an undisturbed Pyrenean
river. Ecological indicators. 9(1):52-63.
Littell, R. C., Stroup, W. W., Freund, R. J. (2002). SAS for linear models. North Carolina: SAS
Institute inc.
Madsen, J. D., Chambers, P. A., James, W. F., Koch, E. W., Westlake, D. F. (2001). The
interaction between water movement, sediment dynamics and submersed
macrophytes. Hydrobiologia. 444(1-3):71-84.
Mann, R.H.K., Blackburn, J.H., Beaumont, W.R.C. (2006). The ecology of brown trout Salmo
trutta in English chalk streams. Freshwater biology. 21(1):57-70.
McCabe, D. J. and Gotelli, N. J. (2000). Effects of disturbance frequency, intensity, and area
on assemblages of stream macroinvertebrates. Oecologia. 124(2):270-279.
Mercer, E.V., Mercer, T.G., Sayok, A.K. (2014). Effects of forest conversions to oil palm
plantationsonfreshwatermacroinvertebrates: a case study from Sarawak Malaysia. Journal
of land use science. 9(3):260-277.
Muchan, K. (2013). Hyporheic invertebrate community response to flow permanence in a
chalk stream. Retrieved February 17, 2015, from, http://nora.nerc.ac.uk/501369/.
Muehlbauer, J. D., Doyle, M. W., & Bernhardt, E. S. (2010). Macroinvertebrate community
responses to a dewatering disturbance gradient in a restored stream. Hydrology and earth
system sciences discussions. 7(6):9599-9630.

35. UoP: 677644
29
Mueller,M.,Pander,J.,Geist,J.(2014). The ecological value of streamrestorationmeasures:
An evaluation on ecosystem and target species scales. Ecological engineering. 62:129-139.
Neal,C.,Jarvie,H.P.,Howarth,S. M., Whitehead,P.G., Williams, R. J., Neal, M., Harrow, M.,
Wickham,H. (2000). The waterqualityof the RiverKennet:initial observations on a lowland
chalk stream impacted by sewage inputs and phosphorus remediation. Science of the total
environment. 251:477-495.
Neale, M. W., Dunbar, M. J., Jones, J., Ibbotson, A. T. (2008). A comparison of the relative
contributions of temporal and spatial variation in the density of drifting invertebrates in a
Dorset (UK) chalk stream. Freshwater biology. 53(8):1513-1523.
Newson, M. and Large, A. R. (2006). Natural rivers, hydromorphological quality and river
restoration: a challenging new agenda for applied fluvial geomorphology. Earth surface
processes and landforms. 31(13):1606-1624.
Nilsson, C., Pizzuto, J. E., Moglen, G. E., Palmer, M. A., Stanley, E. H., Bockstael, N. E.,
Thompson, L. C. (2003). Ecological forecasting and running water systems: Challenges for
economists, hydrologists, geomorphologists, and ecologists. Ecosystems.
Nilsson, E. and Persson, A. (2005). Do instream habitat variables and the abundance of
brown trout Salmo trutta (L.) affect the distribution and growth of stone loach, Barbatula
barbatula (L.)?. Ecology of freshwater fish. 14(1):40-49.
Olsen, D. A., Hayes, J. W., Booker, D. J., & Barter, P. J. (2014). A model incorporating
disturbance and recovery processes in benthic invertebrate habitat-flow time series. River
research and applications. 30(4):413-426.
Paisley, M.F., Trigg, D.J., Walley, W.J. (2014). Revision of the biological monitoring working
party (BMWP) score system:derivationof present-only and abundance-related scores from
field data. River research and applications. 30(7):887-904.
Palmer, M. A., Bernhardt, E. S., Allan, J. D., Lake, P. S., Alexander, G., Brooks, S., Carr, J.,
Clayton, S., Dahm, C.N., Follstad Shah, J., Galat, D., Loss, S.G., Goodwin, P., Hart, D.D.,
Hassett,B.,Jenkinson,R.,Kondolf,G.M.,Lave,R.,Meyer,J.L.,O'Donnell,T.K.,Pagano,L., and
Sudduth,E.(2005). Standardsfor ecologicallysuccessful river restoration. Journal of applied
ecology. 42(2):208-217.
Pastuchová, Z. (2006). Macroinvertebrate assemblages in conditions of low-discharge
streamsof the CerovávrchovinahighlandinSlovakia. Limnologica-ecology and management
of inland waters. 36(4):241-250.
Pretty, J.L., Harrison, S.S.C., Shepherd, D.J., Smith, C., Hildrew, A.G., Hey, R.D. (2003). River
rehabilitationandfish populations: assessing the benefit of instream structures. Journal of
applied ecology. 40(2):251-265.
Shelley,F.,Abdullahi, F., Grey, J., Trimmer, M. (2015). Microbial methane cycling in the bed
of a chalk river: oxidation has the potential to match methanogenesis enhanced by
warming. Freshwater biology. 60(1):150-160.
Skalar (2014). Skalar methods. Retrieved October 7, 2014, from, http://www.fh-
bingen.de/uploads/media/SKALAR-Methode_Ngesamt_UV-Aufschluss_02.pdf

36. UoP: 677644
30
Skoglund,H.andBarlaup, B. T. (2006). Feeding pattern and diet of first feeding brown trout
fry under natural conditions. Journal of Fish Biology. 68(2):507-521.
Smith, B., Clifford, N. J., Mant, J. (2014). Analysis of UK river restoration using broad‐scale
data sets. Water and environment journal. 28(4):490-501.
Spanhoff,B.andArle,J.(2007). Settingattainable goalsof stream habitat restoration from a
macroinvertebrate view. Restoration ecology. 15(2):317-320.
Spellerberg,I.F.andFedor, P. J. (2003). A tribute to Claude Shannon (1916–2001) and a plea
for more rigorous use of species richness, species diversity and the ‘Shannon–
Wiener’Index. Global ecology and biogeography. 12(3):177-179.
Sternecker, K., Wild, R., Geist, J. (2013). Effects of substratum restoration on salmonid
habitat quality in a subalpine stream. Environmental biology of fishes. 96(12):1341-1351.
VanAel,E.,De Cooman,W., Blust, R., Bervoets, L. (2015). Use of a macroinvertebrate based
biotic index to estimate critical metal concentrations for good ecological water
quality. Chemosphere. 119:138-144.
Verdonschot, P. F. M., Besse-Lototskaya, A. A., Dekkers, T. B. M., Verdonschot, R. C. M.
(2014). Directional movement in response to altered flow in six lowland stream
Trichoptera. Hydrobiologia. 740(1):219-230.
Wade,A. J.,Palmer-Felgate,E.J.,Halliday,S.J.,Skeffington, R. A., Loewenthal, M., Jarvie, H.
P., Bowes, M.J., Greenway, G.M., Haswell, S.J., Bell, I.M., Joly, E., Fallatah, A., Neal, C.,
Williams,R.J.,Gozzard,E.,Newman,J.R.(2012). Hydrochemical processes in lowland rivers:
insights from in situ, high-resolution monitoring. Hydrology and earth system sciences.
16(11):4323-4342.
Walling, D. E., Collins, A. L., Jones, P. A., Leeks, G. J. L., Old, G. (2006). Establishing fine-
grained sediment budgets for the Pang and Lambourn LOCAR catchments, UK. Journal of
hydrology. 330(1):126-141.
Wood,P.J.,Boulton,A.J.,Little.,S.,Stubbington, R. (2010). Is the hyporheic zone a refugium
for aquaticmacroinvertebratesduringsevere low flow conditions. Fundamental and applied
limnology. 176(4):377-390.
Wood,K. A.(2012). Swan-plantinteractionsin a chalk river catchment. RetrievedFebruary 2,
2015, from, http://core.ac.uk/download/pdf/9636848.pdf.
Woodward, G., Papantoniou, G., Edwards, F., Lauridsen, R. B. (2008). Trophic trickles and
cascades in a complex food web: impacts of a keystone predator on stream community
structure and ecosystem processes. Oikos. 117(5):683-692.
Wright, J. F., Blackburn, J. H., Gunn, R. J. M., Symes, K. L., & Bowker, J. (1998). A Scoping
study on the Ephemeroptera of southern chalk streams. Retrieved February 2, 2015, from,
http://nora.nerc.ac.uk/502099/1/N502099RE.pdf.

37. UoP: 677644
31
Wright, J. F., Clarke, R. T., Gunn, R. J. M., Winder, J. M., Kneebone, N. T., Davy‐Bowker, J.
(2003). Response of the floraandmacroinvertebratefauna of a chalk stream site to changes
in management. Freshwater Biology. 48(5):894-911.

38. UoP: 677644
32
Appendix 1 Raw Data
Sample dates and times
Water Quality

39. UoP: 677644
33
Invertebrate Data

40. UoP: 677644
34
Flow

41. UoP: 677644
35
Widths & Depths

42. UoP: 677644
36
Appendix 2 Statistical Tests Minitab Output
General Linear Model: pH versus Date, Site
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 0.188094 0.037619 13.27 0.000
Site 2 0.000844 0.000422 0.15 0.864
Error 10 0.028356 0.002836
Total 17 0.217294
Model Summary
S R-sq R-sq(adj) R-sq(pred)
0.0532499 86.95% 77.82% 57.72%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 7.4694 0.0126 595.12 0.000
Date
03/06/2014 -0.1228 0.0281 -4.37 0.001 1.67
17/06/2014 0.1806 0.0281 6.43 0.000 1.67
24/06/2014 -0.0894 0.0281 -3.19 0.010 1.67
08/07/2014 0.0772 0.0281 2.75 0.020 1.67
22/07/2014 -0.0194 0.0281 -0.69 0.504 1.67
Site
Downstream 0.0089 0.0177 0.50 0.627 1.33
Middle -0.0011 0.0177 -0.06 0.951 1.33
Regression Equation
pH = 7.4694 - 0.1228 Date_03/06/2014 + 0.1806 Date_17/06/2014 - 0.0894 Date_24/06/2014
+ 0.0772 Date_08/07/2014 - 0.0194 Date_22/07/2014 - 0.0261 Date_05/08/2014
+ 0.0089 Site_Downstream - 0.0011 Site_Middle - 0.0078 Site_Upstream
Fits and Diagnostics for Unusual Observations
Std
Obs pH Fit Resid Resid
1 7.4600 7.3556 0.1044 2.63 R
R Large residual
General Linear Model: Total Inverts versus Date, Site
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 487066 97413 22.26 0.000
Site 2 37719 18860 4.31 0.045
Error 10 43768 4377
Total 17 568553
Model Summary
S R-sq R-sq(adj) R-sq(pred)
66.1571 92.30% 86.91% 75.06%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 420.9 15.6 27.00 0.000
Date
03/06/2014 88.4 34.9 2.53 0.030 1.67
17/06/2014 293.1 34.9 8.40 0.000 1.67
24/06/2014 42.7 34.9 1.23 0.249 1.67
08/07/2014 -75.6 34.9 -2.17 0.055 1.67
22/07/2014 -187.9 34.9 -5.39 0.000 1.67
Site
Downstream 26.9 22.1 1.22 0.251 1.33
Middle -64.4 22.1 -2.92 0.015 1.33
Regression Equation
Total Inverts = 420.9 + 88.4 Date_03/06/2014 + 293.1 Date_17/06/2014 + 42.7 Date_24/06/2014
- 75.6 Date_08/07/2014 - 187.9 Date_22/07/2014 - 160.6 Date_05/08/2014
+ 26.9 Site_Downstream - 64.4 Site_Middle + 37.6 Site_Upstream
Fits and Diagnostics for Unusual Observations
Total
Obs Inverts Fit Resid Std Resid
9 293.0 399.2 -106.2 -2.15 R
R Large residual
Tukey Pairwise Comparisons: Response = Total Inverts, Term = Site
Grouping Information Using the Tukey Method and 95% Confidence
Site N Mean Grouping
Upstream 6 458.500 A
Downstream 6 447.833 A
Middle 6 356.500 A
Means that do not share a letter are significantly different

43. UoP: 677644
37
General Linear Model: Baetidae Count versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 166680 33336 12.90 0.000
Site 2 19877 9938 3.85 0.058
Error 10 25837 2584
Total 17 212394
Model Summary
S R-sq R-sq(adj) R-sq(pred)
50.8303 87.84% 79.32% 60.59%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 202.3 12.0 16.88 0.000
Date
03/06/2014 11.7 26.8 0.44 0.671 1.67
17/06/2014 178.4 26.8 6.66 0.000 1.67
24/06/2014 29.4 26.8 1.10 0.298 1.67
08/07/2014 -6.9 26.8 -0.26 0.801 1.67
22/07/2014 -113.3 26.8 -4.23 0.002 1.67
Site
Downstream 30.2 16.9 1.78 0.105 1.33
Middle -46.3 16.9 -2.73 0.021 1.33
Regression Equation
Baetidae Count = 202.3 + 11.7 Date_03/06/2014 + 178.4 Date_17/06/2014 + 29.4 Date_24/06/2014
- 6.9 Date_08/07/2014 - 113.3 Date_22/07/2014 - 99.3 Date_05/08/2014
+ 30.2 Site_Downstream - 46.3 Site_Middle + 16.1 Site_Upstream
Fits and Diagnostics for Unusual Observations
Baetidae Std
Obs Count Fit Resid Resid
1 327.0 244.2 82.8 2.18 R
R Large residual
General Linear Model: DO % Saturation versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 4.1778 0.8356 2.15 0.142
Site 2 0.7811 0.3906 1.01 0.400
Error 10 3.8856 0.3886
Total 17 8.8444
Model Summary
S R-sq R-sq(adj) R-sq(pred)
0.623342 56.07% 25.32% 0.00%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 101.056 0.147 687.81 0.000
Date
03/06/2014 0.511 0.329 1.56 0.151 1.67
17/06/2014 0.811 0.329 2.47 0.033 1.67
24/06/2014 -0.456 0.329 -1.39 0.196 1.67
08/07/2014 -0.389 0.329 -1.18 0.264 1.67
22/07/2014 -0.222 0.329 -0.68 0.514 1.67
Site
Downstream 0.194 0.208 0.94 0.371 1.33
Middle 0.094 0.208 0.45 0.659 1.33
Regression Equation
DO % Saturation = 101.056 + 0.511 Date_03/06/2014 + 0.811 Date_17/06/2014
- 0.456 Date_24/06/2014 - 0.389 Date_08/07/2014 - 0.222 Date_22/07/2014
- 0.256 Date_05/08/2014 + 0.194 Site_Downstream + 0.094 Site_Middle
- 0.289 Site_Upstream

44. UoP: 677644
38
General Linear Model: Temp (°C) versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 4.94444 0.988889 523.53 0.000
Site 2 0.00111 0.000556 0.29 0.751
Error 10 0.01889 0.001889
Total 17 4.96444
Model Summary
S R-sq R-sq(adj) R-sq(pred)
0.0434613 99.62% 99.35% 98.77%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 12.8444 0.0102 1253.86 0.000
Date
03/06/2014 -0.7778 0.0229 -33.95 0.000 1.67
17/06/2014 -0.5111 0.0229 -22.31 0.000 1.67
24/06/2014 0.6222 0.0229 27.16 0.000 1.67
08/07/2014 0.2556 0.0229 11.16 0.000 1.67
22/07/2014 0.5556 0.0229 24.25 0.000 1.67
Site
Downstream -0.0111 0.0145 -0.77 0.461 1.33
Middle 0.0056 0.0145 0.38 0.709 1.33
Regression Equation
Temp (°C) = 12.8444 - 0.7778 Date_03/06/2014 - 0.5111 Date_17/06/2014
+ 0.6222 Date_24/06/2014 + 0.2556 Date_08/07/2014 + 0.5556 Date_22/07/2014
- 0.1444 Date_05/08/2014 - 0.0111 Site_Downstream + 0.0056 Site_Middle
+ 0.0056 Site_Upstream
Fits and Diagnostics for Unusual Observations
Std
Obs Temp (°C) Fit Resid Resid
2 12.4000 12.3222 0.0778 2.40 R
R Large residual
General Linear Model: SS (mg/500ml) versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 16.764 3.353 0.46 0.795
Site 2 4.281 2.141 0.30 0.750
Error 10 72.272 7.227
Total 17 93.318
Model Summary
S R-sq R-sq(adj) R-sq(pred)
2.68835 22.55% 0.00% 0.00%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 7.111 0.634 11.22 0.000
Date
03/06/2014 -0.34 1.42 -0.24 0.813 1.67
17/06/2014 -0.74 1.42 -0.53 0.611 1.67
24/06/2014 -0.78 1.42 -0.55 0.595 1.67
08/07/2014 1.16 1.42 0.82 0.434 1.67
22/07/2014 -0.81 1.42 -0.57 0.580 1.67
Site
Downstream 0.639 0.896 0.71 0.492 1.33
Middle -0.094 0.896 -0.11 0.918 1.33
Regression Equation
SS (mg/500ml) = 7.111 - 0.34 Date_03/06/2014 - 0.74 Date_17/06/2014 - 0.78 Date_24/06/2014
+ 1.16 Date_08/07/2014 - 0.81 Date_22/07/2014 + 1.52 Date_05/08/2014
+ 0.639 Site_Downstream - 0.094 Site_Middle - 0.544 Site_Upstream
Fits and Diagnostics for Unusual Observations
SS Std
Obs (mg/500ml) Fit Resid Resid
4 13.60 8.91 4.69 2.34 R
R Large residual

45. UoP: 677644
39
General Linear Model: Ammonia (ppm) versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 0.043117 0.008623 7.05 0.005
Site 2 0.000900 0.000450 0.37 0.701
Error 10 0.012233 0.001223
Total 17 0.056250
Model Summary
S R-sq R-sq(adj) R-sq(pred)
0.0349762 78.25% 63.03% 29.54%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 0.06167 0.00824 7.48 0.000
Date
03/06/2014 0.0617 0.0184 3.35 0.007 1.67
17/06/2014 0.0583 0.0184 3.16 0.010 1.67
24/06/2014 -0.0217 0.0184 -1.18 0.267 1.67
08/07/2014 -0.0750 0.0184 -4.07 0.002 1.67
22/07/2014 0.0083 0.0184 0.45 0.661 1.67
Site
Downstream 0.0050 0.0117 0.43 0.677 1.33
Middle 0.0050 0.0117 0.43 0.677 1.33
Regression Equation
Ammonia (ppm) = 0.06167 + 0.0617 Date_03/06/2014 + 0.0583 Date_17/06/2014
- 0.0217 Date_24/06/2014 - 0.0750 Date_08/07/2014 + 0.0083 Date_22/07/2014
- 0.0317 Date_05/08/2014 + 0.0050 Site_Downstream + 0.0050 Site_Middle
- 0.0100 Site_Upstream
Fits and Diagnostics for Unusual Observations
Ammonia Std
Obs (ppm) Fit Resid Resid
5 0.1300 0.0750 0.0550 2.11 R
R Large residual
General Linear Model: Phosphorus (ppm) versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 0.012228 0.002446 8.47 0.002
Site 2 0.000578 0.000289 1.00 0.402
Error 10 0.002889 0.000289
Total 17 0.015694
Model Summary
S R-sq R-sq(adj) R-sq(pred)
0.0169967 81.59% 68.71% 40.36%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant -0.00056 0.00401 -0.14 0.892
Date
03/06/2014 0.02389 0.00896 2.67 0.024 1.67
17/06/2014 0.04389 0.00896 4.90 0.001 1.67
24/06/2014 -0.03278 0.00896 -3.66 0.004 1.67
08/07/2014 -0.01944 0.00896 -2.17 0.055 1.67
22/07/2014 -0.00944 0.00896 -1.05 0.317 1.67
Site
Downstream -0.00778 0.00567 -1.37 0.200 1.33
Middle 0.00222 0.00567 0.39 0.703 1.33
Regression Equation
Phosphorus (ppm) = -0.00056 + 0.02389 Date_03/06/2014 + 0.04389 Date_17/06/2014
- 0.03278 Date_24/06/2014 - 0.01944 Date_08/07/2014
- 0.00944 Date_22/07/2014 - 0.00611 Date_05/08/2014
- 0.00778 Site_Downstream + 0.00222 Site_Middle + 0.00556 Site_Upstream
Fits and Diagnostics for Unusual Observations
Phosphorus Std
Obs (ppm) Fit Resid Resid
13 0.0600 0.0289 0.0311 2.46 R
R Large residual

46. UoP: 677644
40
General Linear Model: Discharge (m³/sec) versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 0.8478 0.16956 14.38 0.000
Site 2 0.9802 0.49008 41.57 0.000
Error 10 0.1179 0.01179
Total 17 1.9459
Model Summary
S R-sq R-sq(adj) R-sq(pred)
0.108578 93.94% 89.70% 80.37%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 1.3399 0.0256 52.36 0.000
Date
03/06/2014 0.2297 0.0572 4.01 0.002 1.67
17/06/2014 0.2814 0.0572 4.92 0.001 1.67
24/06/2014 -0.0199 0.0572 -0.35 0.735 1.67
08/07/2014 0.0211 0.0572 0.37 0.721 1.67
22/07/2014 -0.1596 0.0572 -2.79 0.019 1.67
Site
Downstream -0.2954 0.0362 -8.16 0.000 1.33
Middle 0.2751 0.0362 7.60 0.000 1.33
Regression Equation
Discharge (m³/sec) = 1.3399 + 0.2297 Date_03/06/2014 + 0.2814 Date_17/06/2014
- 0.0199 Date_24/06/2014 + 0.0211 Date_08/07/2014
- 0.1596 Date_22/07/2014 - 0.3526 Date_05/08/2014
- 0.2954 Site_Downstream + 0.2751 Site_Middle + 0.0204 Site_Upstream
Tukey Pairwise Comparisons: Response = Discharge (m³/sec), Term = Site
Grouping Information Using the Tukey Method and 95% Confidence
Site N Mean Grouping
Middle 6 1.61500 A
Upstream 6 1.36033 B
Downstream 6 1.04450 C
Means that do not share a letter are significantly different.
Tukey Simultaneous 95% CIs
General Linear Model: Mean Velocity (m/sec) versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 0.019294 0.003859 6.24 0.007
Site 2 0.001211 0.000606 0.98 0.409
Error 10 0.006189 0.000619
Total 17 0.026694
Model Summary
S R-sq R-sq(adj) R-sq(pred)
0.0248775 76.82% 60.59% 24.88%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 0.33056 0.00586 56.37 0.000
Date
03/06/2014 0.0261 0.0131 1.99 0.074 1.67
17/06/2014 0.0461 0.0131 3.52 0.006 1.67
24/06/2014 -0.0039 0.0131 -0.30 0.773 1.67
08/07/2014 0.0061 0.0131 0.47 0.651 1.67
22/07/2014 -0.0172 0.0131 -1.31 0.218 1.67
Site
Downstream 0.00111 0.00829 0.13 0.896 1.33
Middle -0.01056 0.00829 -1.27 0.232 1.33
Regression Equation
Mean Velocity (m/sec) = 0.33056 + 0.0261 Date_03/06/2014 + 0.0461 Date_17/06/2014
- 0.0039 Date_24/06/2014 + 0.0061 Date_08/07/2014
- 0.0172 Date_22/07/2014 - 0.0572 Date_05/08/2014
+ 0.00111 Site_Downstream - 0.01056 Site_Middle
+ 0.00944 Site_Upstream

47. UoP: 677644
41
General Linear Model: Number species common name versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 1.833 0.3667 0.23 0.939
Site 2 3.000 1.5000 0.96 0.416
Error 10 15.667 1.5667
Total 17 20.500
Model Summary
S R-sq R-sq(adj) R-sq(pred)
1.25167 23.58% 0.00% 0.00%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 9.500 0.295 32.20 0.000
Date
03/06/2014 -0.167 0.660 -0.25 0.806 1.67
17/06/2014 0.500 0.660 0.76 0.466 1.67
24/06/2014 -0.167 0.660 -0.25 0.806 1.67
08/07/2014 -0.500 0.660 -0.76 0.466 1.67
22/07/2014 0.167 0.660 0.25 0.806 1.67
Site
Downstream -0.500 0.417 -1.20 0.258 1.33
Middle -0.000 0.417 -0.00 1.000 1.33
Regression Equation
Number species common name = 9.500 - 0.167 Date_03/06/2014 + 0.500 Date_17/06/2014
- 0.167 Date_24/06/2014 - 0.500 Date_08/07/2014
+ 0.167 Date_22/07/2014 + 0.167 Date_05/08/2014
- 0.500 Site_Downstream - 0.000 Site_Middle
+ 0.500 Site_Upstream
Fits and Diagnostics for Unusual Observations
Number
species
common
Obs name Fit Resid Std Resid
3 11.000 8.833 2.167 2.32 R
9 7.000 9.333 -2.333 -2.50 R
R Large residual
General Linear Model: BMWP score versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 46.28 9.256 0.10 0.989
Site 2 152.44 76.222 0.86 0.453
Error 10 887.56 88.756
Total 17 1086.28
Model Summary
S R-sq R-sq(adj) R-sq(pred)
9.42102 18.29% 0.00% 0.00%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 59.39 2.22 26.75 0.000
Date
03/06/2014 -2.06 4.97 -0.41 0.688 1.67
17/06/2014 2.94 4.97 0.59 0.566 1.67
24/06/2014 -0.72 4.97 -0.15 0.887 1.67
08/07/2014 -0.06 4.97 -0.01 0.991 1.67
22/07/2014 0.94 4.97 0.19 0.853 1.67
Site
Downstream -2.22 3.14 -0.71 0.495 1.33
Middle -1.89 3.14 -0.60 0.561 1.33
Regression Equation
BMWP score = 59.39 - 2.06 Date_03/06/2014 + 2.94 Date_17/06/2014 - 0.72 Date_24/06/2014
- 0.06 Date_08/07/2014 + 0.94 Date_22/07/2014 - 1.06 Date_05/08/2014
- 2.22 Site_Downstream - 1.89 Site_Middle + 4.11 Site_Upstream
Fits and Diagnostics for Unusual Observations
BMWP
Obs score Fit Resid Std Resid
3 74.00 56.44 17.56 2.50 R
9 39.00 56.78 -17.78 -2.53 R
R Large residual

48. UoP: 677644
42
General Linear Model: trichoptera number versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 484.3 96.86 1.77 0.208
Site 2 228.1 114.06 2.08 0.176
Error 10 548.6 54.86
Total 17 1260.9
Model Summary
S R-sq R-sq(adj) R-sq(pred)
7.40645 56.50% 26.04% 0.00%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 18.06 1.75 10.34 0.000
Date
03/06/2014 -1.39 3.90 -0.36 0.729 1.67
17/06/2014 11.28 3.90 2.89 0.016 1.67
24/06/2014 -3.06 3.90 -0.78 0.452 1.67
08/07/2014 -3.39 3.90 -0.87 0.406 1.67
22/07/2014 -0.06 3.90 -0.01 0.989 1.67
Site
Downstream -0.56 2.47 -0.23 0.826 1.33
Middle -4.06 2.47 -1.64 0.131 1.33
Regression Equation
trichoptera number = 18.06 - 1.39 Date_03/06/2014 + 11.28 Date_17/06/2014
- 3.06 Date_24/06/2014 - 3.39 Date_08/07/2014 - 0.06 Date_22/07/2014
- 3.39 Date_05/08/2014 - 0.56 Site_Downstream - 4.06 Site_Middle
+ 4.61 Site_Upstream
Fits and Diagnostics for Unusual Observations
trichoptera
Obs number Fit Resid Std Resid
1 28.00 16.11 11.89 2.15 R
13 10.00 21.28 -11.28 -2.04 R
R Large residual
General Linear Model: NO2 skalar versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 0.000494 0.000099 17.80 0.000
Site 2 0.000011 0.000006 1.00 0.402
Error 10 0.000056 0.000006
Total 17 0.000561
Model Summary
S R-sq R-sq(adj) R-sq(pred)
0.0023570 90.10% 83.17% 67.92%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 0.012778 0.000556 23.00 0.000
Date
03/06/2014 -0.00278 0.00124 -2.24 0.049 1.67
17/06/2014 -0.00278 0.00124 -2.24 0.049 1.67
24/06/2014 -0.00278 0.00124 -2.24 0.049 1.67
08/07/2014 -0.00611 0.00124 -4.92 0.001 1.67
22/07/2014 0.00722 0.00124 5.81 0.000 1.67
Site
Downstream 0.000556 0.000786 0.71 0.496 1.33
Middle 0.000556 0.000786 0.71 0.496 1.33
Regression Equation
NO2 skalar = 0.012778 - 0.00278 Date_03/06/2014 - 0.00278 Date_17/06/2014
- 0.00278 Date_24/06/2014 - 0.00611 Date_08/07/2014 + 0.00722 Date_22/07/2014
+ 0.00722 Date_05/08/2014 + 0.000556 Site_Downstream + 0.000556 Site_Middle
- 0.001111 Site_Upstream
Fits and Diagnostics for Unusual Observations
Obs NO2 skalar Fit Resid Std Resid
16 0.00000 0.00556 -0.00556 -3.16 R
R Large residual

49. UoP: 677644
43
General Linear Model: NO2 skalar versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05 /08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 0.000494 0.000099 17.80 0.000
Site 2 0.000011 0.000006 1.00 0.402
Error 10 0.000056 0.000006
Total 17 0.000561
Model Summary
S R-sq R-sq(adj) R-sq(pred)
0.0023570 90.10% 83.17% 67.92%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 0.012778 0.000556 23.00 0.000
Date
03/06/2014 -0.00278 0.00124 -2.24 0.049 1.67
17/06/2014 -0.00278 0.00124 -2.24 0.049 1.67
24/06/2014 -0.00278 0.00124 -2.24 0.049 1.67
08/07/2014 -0.00611 0.00124 -4.92 0.001 1.67
22/07/2014 0.00722 0.00124 5.81 0.000 1.67
Site
Downstream 0.000556 0.000786 0.71 0.496 1.33
Middle 0.000556 0.000786 0.71 0.496 1.33
Regression Equation
NO2 skalar = 0.012778 - 0.00278 Date_03/06/2014 - 0.00278 Date_17/06/2014
- 0.00278 Date_24/06/2014 - 0.00611 Date_08/07/2014 + 0.00722 Date_22/07/2014
+ 0.00722 Date_05/08/2014 + 0.000556 Site_Downstream + 0.000556 Site_Middle
- 0.001111 Site_Upstream
Fits and Diagnostics for Unusual Observations
Obs NO2 skalar Fit Resid Std Resid
16 0.00000 0.00556 -0.00556 -3.16 R
R Large residual
General Linear Model: Cross section voloume versus Date, Site
Method
Factor coding (-1, 0, +1)
Factor Information
Factor Type Levels Values
Date Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014
Site Fixed 3 Downstream, Middle, Upstream
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date 5 2.8443 0.5689 5.98 0.008
Site 2 90.6899 45.3449 476.65 0.000
Error 10 0.9513 0.0951
Total 17 94.4855
Model Summary
S R-sq R-sq(adj) R-sq(pred)
0.308436 98.99% 98.29% 96.74%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 5.1333 0.0727 70.61 0.000
Date
03/06/2014 0.578 0.163 3.56 0.005 1.67
17/06/2014 0.358 0.163 2.20 0.052 1.67
24/06/2014 0.085 0.163 0.52 0.612 1.67
08/07/2014 -0.087 0.163 -0.53 0.606 1.67
22/07/2014 -0.338 0.163 -2.08 0.064 1.67
Site
Downstream -1.995 0.103 -19.40 0.000 1.33
Middle 3.136 0.103 30.50 0.000 1.33
Regression Equation
Cross section voloume = 5.1333 + 0.578 Date_03/06/2014 + 0.358 Date_17/06/2014
+ 0.085 Date_24/06/2014 - 0.087 Date_08/07/2014
- 0.338 Date_22/07/2014 - 0.597 Date_05/08/2014
- 1.995 Site_Downstream + 3.136 Site_Middle - 1.141 Site_Upstream

50. UoP: 677644
44
Test without middle site data for 24/6/14
General Linear Model: Total Inverts_1 versus Date_1, Site_1
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date_1 5 502537 100507 38.56 0.000
Site_1 2 14338 7169 2.75 0.117
Error 9 23458 2606
Total 16 551220
Model Summary
S R-sq R-sq(adj) R-sq(pred)
51.0532 95.74% 92.43% 85.41%
Test without all site data for 24/6/14
General Linear Model: Total Inverts_1_1 versus Date_1_1, Site_1_1
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Date_1_1 4 480496 120124 43.03 0.000
Site_1_1 2 14007 7003 2.51 0.143
Error 8 22331 2791
Total 14 516834
Model Summary
S R-sq R-sq(adj) R-sq(pred)
52.8337 95.68% 92.44% 84.81%

51. UoP: 677644
45
Appendix 3 Standard Laboratory Procedures
Suspended Solids
The samples were filtered to test for suspended solids and for preparation for the skalar
machine analysis(San ++
systemcontinuousflow analyser). Glass microfiber filters (110mm)
were numbered(foridentifyingpurposes),prewashedindistilledwaterand dried in an oven
at 105°C (betweentwosheetsof A4paper).The filterpaperswere handled delicately at the
edge with tweezers at all times to ensure no contamination occurred. Once dried the filter
papers were weighed and the weights recorded.
A clean measuring cylinder was washed with 100ml of sample water to ensure no
contaminationtookplace.The filterwasplacedina Bucknerflaskwithvacuumfiltration.The
sample water was discarded and 500ml of sample water measured.
200ml of sample water was put through the filter and used to wash the Buckner flask to
ensure no contamination took place. The sample water was discarded and the remaining
300ml of sample water put through the filter system.
The filterpaperswere placedbetweentwo sheets of A4 paper and returned to the oven for
two hours to dry at 105°C. Once completely dry the filter papers were reweighed and the
weightsrecorded.The firstweightwassubtractedfromthe secondweightgiving a result for
suspended solids of g/500ml.
Approximately 100ml of filtered sample water was used to wash corresponding labelled
conical flasks and discarded. The remaining 200ml of filtered sample water was retained in
the conical flasks to be used for skalar analysis.

52. UoP: 677644
46
Appendix 4 Cross Sections
Downstream site (descending in date order)

53. UoP: 677644
47

54. UoP: 677644
48
Middle site (descending in date order)

55. UoP: 677644
49

56. UoP: 677644
50
Upstream site (descending in date order)

57. UoP: 677644
51

58. UoP: 677644
52
Middle site slack area (descending in date order)

59. UoP: 677644
53