Dissertation main updated tuesday

UoP: 677644

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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. degreein Aquaculture and Fishery Management"

UoP: 677644

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 weed cover. A site 10m upstream was used as a control site, the middle site was directly behind the installed brushwood woody 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 and allocated a Biological Working Party Score (BMWP). Water quality, depth and flow measurements were also taken. A significant difference was observed between the 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 week after the habitat enhancement implementation. A significant difference was observed between all dates for total invertebrate count (P=0.000) and Baetidae count (P=0.000) indicating seasonality and potential changes to invertebrate drift rates in response to possible changes in flow regimes. No significant 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 results indicated the implementation of habitat enhancement had a short term effect to invertebrate abundance but no long term effects due to a rapid recovery rate and a high resilience to disturbances.

Keywords: Invertebrates, abundance, habitat enhancement, invertebrate drift, brown trout

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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:..........................................

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Acknowledgements

The author would like to thank the following persons for their help and support in completion of this project:

Mr Nick Lawrence (Fishery Manager) for allowing access to the site on the Borne Rivulet and the consent for data collection and for his assistance and consultation in the installation of habitat enhancement structures.

Dr. Neil Crooks for assisting in the initial concept idea and his support and guidance for the duration of the project and Mr Alan Black for his assistance with the reports statistical analysis.

Mr and Mrs Hook for their assistance during the data collection and recording.

Mr Roy Niblett for assistance with laboratory analysis and the loan of college equipment.

Mr Phillip Turnbull for his assistance in the installation of habitat enhancement structures.

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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..............................................................................................................31

Appendix 2 Statistical Tests Minitab Output...........................................................................35

Appendix 3 Standard Laboratory Procedures..........................................................................44

Appendix 4 Cross Sections.......................................................................................................45

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Table of Figures

Figure 1 an example of brushwood woody debris on the River Whitewater, Basingstoke

(Authors own)...........................................................................................................................2

Figure 2 an example of an upstream groyne on the River Lambourn, Newbury (Authors own)

..................................................................................................................................................2

Figure 3 the Bourne Rivulet location (Fishpal, 2014).................................................................7

Figure 4 site location on Bourne Rivulet (Google, 2014)...........................................................8

Figure 5 the survey site (before habitat enhancement)............................................................9

Figure 6 habitat restoration site before work completed taken from west bank (Authors own)

................................................................................................................................................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 number of invertebrate species counted by common name at each 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 observed for each site............................18

Table 4 water quality and flow parameters analysed using general linear model..................18

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Introduction

River Habitat Enhancement & Restoration

Crisp (2000) states the implementation of instream structures can be utilised to increase the

diversity of fish habitat through the aim of increasing the areas carrying capacity. A wide

range of habitat restoration and enhancement 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 river restoration and habitat enhancement is to assess the impacts on the restoration

site and areas downstream, and to determine any potential impacts as a result of changes to

flow dynamics or increased or decreased sedimentation levels 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

management to help restore brown trout spawning areas (Hendry et al., 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 species coupled with river restoration and habitat enhancement strategies are

being implemented 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 and resource 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).

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The use of instream woody debris has shown to increase the potential growth of brown trout

by providing areas of slack water therefore reducing the amount of energy expended

(Gustaffson, 2011). Langford et al. (2012) states the use of woody debris is beneficial to large

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)

Upstream groynes (flow deflectors) (Figure 2) are installed on chalk streams to increase flow

to reduce siltation in gravels, which improves salmon and brown trout spawning areas

(Hendry et al., 2003). The installation of upstream groynes, in-stream boulders and V-shaped

deflectors can be utilised to manipulate flow and increase flow velocity whilst also improving

habitat diversity (Smith et al., 2014).

Figure 2 an example of an upstream groyne on the River Lambourn, Newbury (Authors own)

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River restoration and habitat enhancement methods can involve bank re-profiling, re-

meandering, narrowing and the creation of specific features including riffles, backwaters,

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

species diversity of invertebrates (Mann et al., 2006; Woodward et al., 2008). This results in

invertebrates representing 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 and small Chiromidae and Ephemeroptera 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).

Brown trout feed on all life stages of invertebrates however adults have 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 marginal habitats which results in their diet compromising mainly of Chrironomid

and Plecoptera larvae (Skogland and Barlaup, 2006). Harrison (2000) states the marginal

habitat of chalk streams is very important to the biodiversity of invertebrates with margins

often showing higher levels of abundance than mid channel habitats. Therefore

invertebrates should be considered in the planning of 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

implementation of habitat enhancements for fish species (Haase et al., 2013). The following

studies asses the impacts of various methods of river restoration and habitat enhancement

on invertebrate abundance and populations.

A study by Harrison et al. (2004) on a lowland river found that the abundance, taxon richness

and diversity of invertebrates are not affected by the instillation of instream flow deflectors.

Lepori et al. (2005) found that river restoration and enhancement techniques, such as woody

debris, groynes or instream boulders have no effect on invertebrate population diversity or

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abundance. A study by Mueller et al. (2014) found the introduction of instream boulders and

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

implemented to create 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

often show a decrease in abundance in the short term after river restoration 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 and biodiversity following the installation of bank revetment using

soft brushwood techniques however the project was a large scale restoration covering 300m.

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

required often limit fisheries managers and land owners to small 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

invertebrates in rivers. The changes in chalk stream flow regimes caused 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)

states seasonal variation may complicate interpretations or influence results of invertebrate

abundance and population studies. Chalk streams invertebrates are sensitive to changes in

discharge and changes in water quality such as ammonia, phosphorus and dissolved oxygen

which affects levels of abundance (Durance and Omerod, 2008).

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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

channels offing faster flows with slacker areas behind the Ranunculus beds (Harrison et al.,

2005).

Dewson et al. (2007) states invertebrate drift increases immediately following a reduction in

flow resulting in decreased habitat for some species and increased habitat for 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

velocity can result in an increase in invertebrate drift for species such as mayfly larvae due to

habitat becoming unusable (Dewson et al., 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 species can 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 increased

current or changes in behaviour that have been observed in response to changes in flow

(Verdonschot et al., 2014). A reduction in flow 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 uses invertebrates as biological indicators to determine water quality (Paisley

et al., 2014).

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BMWP scores only indicate an impact when a taxon disappears or appears which the case is

often during monitoring for low abundant species (Clarke and Murphy, 2006). Therefore

measuring abundance alongside BMWP score provides more accurate analysis of 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 difficult to detect (Leunda et al., 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

Chalk streams in southern England have high nutrient levels and flow regimes which provide

excellent conditions for the growth of aquatic plants and produces a large abundance and

variety of invertebrate, macrophyte and fish species (Bowes et al., 2005). Chalk streams are

fed from groundwater aquifers that contribute between 73-90% 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 to water and air responding to temporal solar heat inputs) and can also be

affected by the time of day measurements are taken and the levels of riparian shading

(Johnson, 2004; Bowes et al., 2011). Neal et al. (2000) states levels of suspended solids in can

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-

steam biological activity with a range of approximately 7.3-8.2 (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

located just north of Ibthorpe and it has a course of three miles before joining the River Test

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at Whitchurch (Figure 3,). The Bourne rivulet is famous for wild brown trout fishing, with

upstream dry fly and nymph fishing the accepted methods. The wild brown trout fishing was

popularised by the book 'Where bright waters meet' by Harry Plunket Greene which

motivates many anglers to visit and fish the Bourne Rivulet each year (Famous Fishing, 2011).

Figure 3 the Bourne Rivulet location (Fishpal, 2014)

Aims & Objectives

There are limited studies on the impact of habitat enhancement structures for brown trout

relating to invertebrate abundance. The aim of the study was to assess if the implementation

of habitat enhancement structures for brown trout affects invertebrate abundance. The site

considered on the Bourne Rivulet enabled a study to take place on a privately owned 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:


Rivulet causes short or long term changes to invertebrate abundance.

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Methodology

Site Selection

The site for the implement habitat restoration for the purpose of this study was chosen after

consultation between the author and fishery manager Nick Lawrence. The site was chosen

for the following reasons;

An absence of water crowfoot (Rannunculus spp.) weed growth which would provide

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 cover and features for juvenile brown trout and invertebrate

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)

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Three areas of the site were chosen for sampling. They were 10m above (upstream site),

10m below (downstream site) and an area immediately below where 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 period of two weeks was allowed between each sample date to allow the

areas to recover. An exception was made for the first sample after the habitat enhancement

implementation, as this enabled more potential short term affects to be assessed.

Table 1 survey dates and times

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Habitat Restoration

Figure 6 shows the site looking from 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)

Willow branches were cut from 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 willow cuttings were 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. Ongoing management will be needed to ensure the structure retains the correct shape

and does not increase in size. 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 section was manoeuvred into place so that it overlapped the woody debris, which

helped to pin the branches in place and to prevent scouring and erosion taking place behind

the upstream groyne.

The upstream groyne was pinned in place with two chestnut stakes at either end and

secured with wire. The chestnut stakes were driven approximately 0.4m into the substrate to

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ensure the structure was stable, and would remain in place even during periods of high flows

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 woody debris was held in place with wire which was tightened between chestnut stakes

which will ensure the branches remain in place during high flows and in periods of flooding.

A large branch from another fallen tree 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)

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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 for all samples taken. Figure 10 shows the author conducting a kick sample on the

middle sample site.

Figure 10 the author conducting a kick sample on the middle survey site (Authors own)

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UPSTREAM GROYNE

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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

contents were emptied into the tray. Each sample was analysed with each species assigned a

category and the number estimated as accurately as possible. A modified Biological

Monitoring Working Party (BMWP) score was assigned to each sample (Table 2) with scores

being adjusted from Paisley et al. (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 kick sampling and sample analysis was completed by 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

analysis On each survey date. The samples were collected in 1L mineral water bottles which

were thoroughly washed with river water before the sample was collected.

The samples were collected starting at the downstream sample site, then working upstream

to ensure the results were not affected by particles being disturbed by wading the stream.

All samples across the three sites were taken from the midpoint of the stream. The samples

were frozen on the day of collection to allow for lab analysis to be completed at a later date

(Cabrita et al., 2014).

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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

quality tests and readings were taken from the same point at each site and all 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

flow rate. A River Form Channel Analysis software program was used in conjunction 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 bottles containing the water samples were defrosted at room temperature and analysed

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 ++

system continuous flow analyser). The filter papers were weighed before and after filtration

of the samples with the difference giving a measurement of suspended solids in milligrams

per 500ml of water (mg/500ml).

Approximately 15ml of filtered sample water was placed in labelled 15ml cuvette for analysis

in the skalar (Skalar, 2014) machine for ammonia, phosphorus and nitrite. Each sample was

completed in triplicate to reduce the possibility of errors and an average of the three results

taken to give the final result for ammonia, phosphorus and nitrates.

Statistical Analysis

Statistical analysis was conducted on the results for total abundance of all species (the total

sum of all individuals counted for every species for each 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

number of species by common name and BMWP score. Statistical tests were used to analyse

the water quality and flow parameters.

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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

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 linear model was 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

Date 05/08/201422/07/201408/07/201424/06/201417/06/201403/06/2014

800

700

600

500

400

300

200

100

0

Tota

l Inv

erte

brat

e Cou

nt

DownstreamMiddleUpstream

Site

Figure 11 the total number of invertebrates counted at each site on each sampling date

A general linear model analysing the total invertebrate count showed a significant difference

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

excluding the 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)

between the sites but a significant difference between the dates (P=0.000). The total count

was 293 which were much lower than the upstream control site (576 total invertebrate

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count) and the downstream site (522 total invertebrate count). The species showing the

biggest reduction were swimming mayflies.

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Date 05/08/201422/07/201408/07/201424/06/201417/06/201403/06/2014

500

400

300

200

100

0

Baet

idae

Cou

nt


Site

Figure 12 the total number Baetidae invertebrates counted at each site on each sampling date

A general linear model analysing the Baetidae count showed a significant difference between

the dates (P=0.000) and no significant difference between the sites (P=0.058).

Date 05/08/201422/07/201408/07/201424/06/201417/06/201403/06/2014

30

25

20

15

10

5

0

Trich

opte

ra C

ount


Site

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).

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Date 05/08/201422/07/201408/07/201424/06/201417/06/201403/06/2014

12

10

8

6

4

2

0

Num

ber o

f Spe

cies b

y Com

mon

Nam

e


Site

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).

Date 05/08/201422/07/201408/07/201424/06/201417/06/201403/06/2014

80

70

60

50

40

30

20

10

0

BMW

P sc

ore


Site

Figure 15 the invertebrate BMWP score calculated for each site on each sampling date

A general linear model analysing the BMWP score showed no significant difference between

the dates (P=0.989) and no significant difference between the sites (P=0.453)

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Table 3 the range of water quality and flow results observed for each site

The ranges of values for water quality 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

significant difference between the 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 observed for dissolved oxygen (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.

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Discussion

Invertebrates

The drop in invertebrate 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

effects potentially a result of the subsequent changes to the cross sectional profile or slight

variations in flow. This concurs with studies by Sternecker et al. (2013) and Muehlbauer et al.

(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 results show that no long term effects were evident on invertebrate abundance after the

implementation of the habitat enhancement structures. A study by Harrison et al. (2004) also

found that invertebrate abundance was not affected by the installation of instream flow

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

restoration projects has no effect on invertebrate abundance. Jahnig et al. (2010) found the

implementation of river restoration and habitat enhancement methods caused no significant

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 results of this study concur with previous findings that small scale

projects have no long term effects on invertebrate abundance, whilst large scale projects can

be beneficial and 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

decreased from 509 on the first sample date to 260 on the last sample 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) suggests seasonal variation can influence the results of invertebrate population and

20

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abundance studies. Throughout the study minimal changes were observed to the abundance

categories for most invertebrate species. The changes to the abundance categories that did

occur help confirm the effect of seasonality on the results of this study (Wright et al., 1998;

Carter et al., 2006).

The abundance of Baetidae species followed the same trend as the total abundance with no

significant difference between the sites shown (P=0.058). A decrease was seen on the middle

site for the 24th June with a significant difference being shown between the 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; Kennedy et al., 2014).The reduction in abundance can also be explained by seasonality

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

upstream site showed a higher abundance category than the middle and downstream sites.

This would suggest that the implementation of the habitat enhancement does have an effect

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

changes in abundance in response to changes in flow (Pastuchova, 2006; Verdonschot et al.,

2014).

A significant difference was shown for 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 implementation of the habitat enhancement 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/sec before the structures were installed. The changes show that the habitat enhancement

affected the middle site flow dynamics resulting in potential changes to invertebrate habitat

conditions (Durance and Omerod, 2008; Kennedy et al., 2014). Gore et al. (2001) states flow

is one of the most influential factors on the abundance of invertebrates in rivers. Kennedy et

al. (2014) states invertebrate abundance levels are affected by the 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

21

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changes to abundance levels (Durance and Omerod, 2008; Olsen et al., 2014). The changes in

velocity will have influenced the rate of invertebrate drift that occurred (England, 2011). A

study by Dewson et al. (2007) found invertebrate drift increases when flow 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

(Dewson et al., 2007). The presence of Ranunculus provides cover for invertebrates as well 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

enhancement techniques implemented for trout had no effect on invertebrate diversity or

taxon richness. The number of species by common name and BMWP score showed no

significant difference between 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).

However Leunda et al. (2009) states seasonal changes are difficult to detect when analysing

invertebrates using BMWP scores. The presence or absence of low abundant species can

affect BMWP scores and make assessment of changes in population structure and diversity

due to seasonality difficult to analyse (Paisley et al., 2014).

Water Quality

The significant differences observed 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

22

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(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

water quality results were as expected 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 that manual reading of 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

groundwater interaction resulting in 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) which can be attributed to the drop in river level 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 (Taylor et al., 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. As the total counts of species individuals were estimated this may

have affected the accuracy of the results. However the same process was used by the author

in analysing each sample, in an attempt to avoid subjectification 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 invertebrates were identified to species level but by common name and identification

guides were used it would have been more accurate to identify all invertebrates to species

level. However this was beyond the capabilities of the author and would have been difficult

to achieve when analysing samples in the field. The slight variations in flow rate, depths and

widths (therefore cross sectional volume) and habitat (for example the large slack silty area

on the middle site) could have affected the results (Franken, 2008). Although the variations

23

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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

habitat enhancement and due to the drop in river level that occurred during the study (Neale

et al., 2008). However measuring invertebrate drift was not considered when the 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.

Whilst the large numbers of variables where possible have been taken into account, whilst

collecting and analysing data for this study the conclusions found are potentially subjective.

Therefore it is suggested further work is needed to help provide more conclusive results

(Nilsson et al., 2003).

The number of water samples collected was restricted to one sample per site for each date

because of limited freezer 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

limitations and progress the ideas and findings of this study. The three minute cross sectional

kick sample collection method is standard procedure, but it 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 to Harrison et al. (2004) which utilised 30 second kick samples on specific habitat

areas and their location in relation to the introduced structures would be preferable.

The Identification of invertebrates could be completed to species level by preserving samples

and taking them to be identified in a laboratory. The identification to species level would

allow an accurate assessment of the diversity of invertebrates, with a Shannon Wiener index

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

24

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rather than the estimated counts the author used when analysing samples in the 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 conclusion the results of this study show that the implementation of habitat enhancement

structures for brown trout have a short term localised effect on invertebrate abundance. The

rapid recovery of invertebrates due to a high resilience to disturbance means that there was

no observed long 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 drift that occurred 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 significant difference between the dates for the number of species by common

name and BMWP score suggest that any changes to abundance caused by seasonality affect

25

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the number of individuals rather than then species diversity, and that 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

found in existing literature. Whilst changes in flow and morphology were observed after the

habitat enhancement implementation, the results of the study suggest the structures had no

effect on water quality. 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

hypothesis being accepted due the short term effect on invertebrate abundance caused by

the implementation of habitat enhancement structures for brown trout.

Null hypothesis: Rejected.


Rivulet has no affect on invertebrate abundance.

Alternative hypothesis: Accepted for short term effects.


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-sampling techniques for macroinvertebrates, fish and benthic algae sampled in biological monitoring of streams and rivers. Kansas biological survey report. 132:25.

Bowes, M. J., Leach, D. V., House, W. A. (2005). Seasonal nutrient dynamics in a chalk stream: 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.

26

UoP: 677644

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 biomonitor of trace element availability in the water column during dredging. 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 indicators of environmental quality. In F.R.Halver and G.A.Lamberti (Eds.), Methods in stream ecology (pp.108-116). Elsevier: London.

Chang, F-H., Lawrence, J.E., Rios-Touma, B., Resh, V.H. (2014). Tolerance values of benthic macroinvertebrates for stream biomonitoring: assessment of assumptions underlying scoring 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 sensitivity of RIVPACS bioassessment 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.

27

UoP: 677644

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). Forest stream linkages: brown trout (Salmo trutta) responses to 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 effect of instream rehabilitation structures on macroinvertebrates in lowland rivers. Journal of applied ecology.41(6):1140-1154.

Harvey, G. L. and Wallerstein, N. P. (2009). Exploring the interactions between flood defence 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 impact of stream support on 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 habitat for rehabilitation and enhancement of salmonid stocks. Fisheries research. 62(2):171-192.

Heywood, M. J. T. and Walling, D. E. (2007). The sedimentation of salmonid spawning gravels 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 hydromorphology and benthic invertebrates in 26 central and southern European rivers. Journal of applied ecology. 47(3):671-680.

28

UoP: 677644

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 benthic macroinvertebrate community and biotic 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 plantations on freshwater macroinvertebrates: 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.

29

UoP: 677644

Mueller, M., Pander, J., Geist, J. (2014). The ecological value of stream restoration measures: 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 water quality of the River Kennet: 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: derivation of 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). Standards for ecologically successful river restoration. Journal of applied ecology. 42(2):208-217.

Pastuchová, Z. (2006). Macroinvertebrate assemblages in conditions of low-discharge streams of the Cerová vrchovina highland in Slovakia. 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 rehabilitation and fish 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.

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UoP: 677644

Skalar (2014). Skalar methods. Retrieved October 7, 2014, from, http://www.fh-bingen.de/uploads/media/SKALAR-Methode_Ngesamt_UV-Aufschluss_02.pdf

Skoglund, H. and Barlaup, 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. and Arle, J. (2007). Setting attainable goals of stream habitat restoration from a macroinvertebrate view. Restoration ecology. 15(2):317-320.

Spellerberg, I. F. and Fedor, 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.

Van Ael, 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 aquatic macroinvertebrates during severe low flow conditions. Fundamental and applied limnology. 176(4):377-390.

Wood, K. A. (2012). Swan-plant interactions in a chalk river catchment. Retrieved February 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.

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

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Appendix 1 Raw Data

Sample dates and times

Water Quality

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Invertebrate Data

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Flow

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Widths & Depths

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Appendix 2 Statistical Tests Minitab Output

General Linear Model: pH versus Date, Site

Factor coding (-1, 0, +1)Factor InformationFactor Type Levels ValuesDate Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014Site Fixed 3 Downstream, Middle, UpstreamAnalysis of VarianceSource 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 0.864Error 10 0.028356 0.002836Total 17 0.217294Model Summary S R-sq R-sq(adj) R-sq(pred)0.0532499 86.95% 77.82% 57.72%

Coefficients

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Term Coef SE Coef T-Value P-Value VIFConstant 7.4694 0.0126 595.12 0.000Date 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 1.67Site Downstream 0.0089 0.0177 0.50 0.627 1.33 Middle -0.0011 0.0177 -0.06 0.951 1.33Regression EquationpH = 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_UpstreamFits and Diagnostics for Unusual Observations StdObs pH Fit Resid Resid 1 7.4600 7.3556 0.1044 2.63 RR Large residual

General Linear Model: Total Inverts versus Date, Site

Factor coding (-1, 0, +1)Factor InformationFactor Type Levels ValuesDate Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014Site Fixed 3 Downstream, Middle, UpstreamAnalysis of VarianceSource DF Adj SS Adj MS F-Value P-Value Date 5 487066 97413 22.26 0.000 Site 2 37719 18860 4.31 0.045Error 10 43768 4377Total 17 568553Model Summary S R-sq R-sq(adj) R-sq(pred)66.1571 92.30% 86.91% 75.06%CoefficientsTerm Coef SE Coef T-Value P-Value VIFConstant 420.9 15.6 27.00 0.000Date 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 1.67Site Downstream 26.9 22.1 1.22 0.251 1.33 Middle -64.4 22.1 -2.92 0.015 1.33Regression EquationTotal 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_UpstreamFits and Diagnostics for Unusual Observations TotalObs Inverts Fit Resid Std Resid 9 293.0 399.2 -106.2 -2.15 RR Large residual

Tukey Pairwise Comparisons: Response = Total Inverts, Term = Site Grouping Information Using the Tukey Method and 95% ConfidenceSite N Mean GroupingUpstream 6 458.500 ADownstream 6 447.833 AMiddle 6 356.500 AMeans that do not share a letter are significantly differentGeneral Linear Model: Baetidae Count versus Date, Site

MethodFactor coding (-1, 0, +1)Factor InformationFactor Type Levels ValuesDate Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014Site Fixed 3 Downstream, Middle, Upstream

Analysis of VarianceSource DF Adj SS Adj MS F-Value P-Value Date 5 166680 33336 12.90 0.000 Site 2 19877 9938 3.85 0.058Error 10 25837 2584Total 17 212394Model Summary S R-sq R-sq(adj) R-sq(pred)50.8303 87.84% 79.32% 60.59%

CoefficientsTerm Coef SE Coef T-Value P-Value VIF

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Constant 202.3 12.0 16.88 0.000Date 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 1.67Site Downstream 30.2 16.9 1.78 0.105 1.33 Middle -46.3 16.9 -2.73 0.021 1.33Regression EquationBaetidae 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_UpstreamFits and Diagnostics for Unusual Observations Baetidae StdObs Count Fit Resid Resid 1 327.0 244.2 82.8 2.18 RR Large residual

General Linear Model: DO % Saturation versus Date, Site


Analysis of VarianceSource 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 0.400Error 10 3.8856 0.3886Total 17 8.8444Model Summary S R-sq R-sq(adj) R-sq(pred)0.623342 56.07% 25.32% 0.00%

CoefficientsTerm Coef SE Coef T-Value P-Value VIFConstant 101.056 0.147 687.81 0.000Date 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 1.67Site Downstream 0.194 0.208 0.94 0.371 1.33 Middle 0.094 0.208 0.45 0.659 1.33Regression EquationDO % 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

General Linear Model: Temp (°C) versus Date, Site




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Constant 12.8444 0.0102 1253.86 0.000Date 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 1.67Site Downstream -0.0111 0.0145 -0.77 0.461 1.33 Middle 0.0056 0.0145 0.38 0.709 1.33Regression EquationTemp (°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_UpstreamFits and Diagnostics for Unusual Observations StdObs 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



CoefficientsTerm Coef SE Coef T-Value P-Value VIFConstant 7.111 0.634 11.22 0.000Date 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 1.67Site Downstream 0.639 0.896 0.71 0.492 1.33 Middle -0.094 0.896 -0.11 0.918 1.33Regression EquationSS (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 StdObs (mg/500ml) Fit Resid Resid 4 13.60 8.91 4.69 2.34 RR Large residual

General Linear Model: Ammonia (ppm) versus Date, Site




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Constant 0.06167 0.00824 7.48 0.000Date 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 1.67Site Downstream 0.0050 0.0117 0.43 0.677 1.33 Middle 0.0050 0.0117 0.43 0.677 1.33Regression EquationAmmonia (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_UpstreamFits and Diagnostics for Unusual Observations Ammonia StdObs (ppm) Fit Resid Resid 5 0.1300 0.0750 0.0550 2.11 RR Large residual

General Linear Model: Phosphorus (ppm) versus Date, Site



CoefficientsTerm Coef SE Coef T-Value P-Value VIFConstant -0.00056 0.00401 -0.14 0.892Date 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 1.67Site Downstream -0.00778 0.00567 -1.37 0.200 1.33 Middle 0.00222 0.00567 0.39 0.703 1.33Regression EquationPhosphorus (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_UpstreamFits and Diagnostics for Unusual Observations Phosphorus StdObs (ppm) Fit Resid Resid 13 0.0600 0.0289 0.0311 2.46 RR Large residual

General Linear Model: Discharge (m³/sec) versus Date, Site



Coefficients

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Term Coef SE Coef T-Value P-Value VIFConstant 1.3399 0.0256 52.36 0.000Date 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 1.67Site Downstream -0.2954 0.0362 -8.16 0.000 1.33 Middle 0.2751 0.0362 7.60 0.000 1.33Regression EquationDischarge (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% ConfidenceSite N Mean GroupingMiddle 6 1.61500 AUpstream 6 1.36033 BDownstream 6 1.04450 CMeans that do not share a letter are significantly different.Tukey Simultaneous 95% CIs General Linear Model: Mean Velocity (m/sec) versus Date, Site



CoefficientsTerm Coef SE Coef T-Value P-Value VIFConstant 0.33056 0.00586 56.37 0.000Date 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 1.67Site Downstream 0.00111 0.00829 0.13 0.896 1.33 Middle -0.01056 0.00829 -1.27 0.232 1.33Regression EquationMean 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

General Linear Model: Number species common name versus Date, Site




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Constant 9.500 0.295 32.20 0.000Date 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 1.67Site Downstream -0.500 0.417 -1.20 0.258 1.33 Middle -0.000 0.417 -0.00 1.000 1.33Regression EquationNumber 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_UpstreamFits and Diagnostics for Unusual Observations Number species commonObs name Fit Resid Std Resid 3 11.000 8.833 2.167 2.32 R 9 7.000 9.333 -2.333 -2.50 RR Large residual

General Linear Model: BMWP score versus Date, Site



CoefficientsTerm Coef SE Coef T-Value P-Value VIFConstant 59.39 2.22 26.75 0.000Date 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 1.67Site Downstream -2.22 3.14 -0.71 0.495 1.33 Middle -1.89 3.14 -0.60 0.561 1.33Regression EquationBMWP 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_UpstreamFits and Diagnostics for Unusual Observations BMWPObs score Fit Resid Std Resid 3 74.00 56.44 17.56 2.50 R 9 39.00 56.78 -17.78 -2.53 RR Large residualGeneral Linear Model: trichoptera number versus Date, Site




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Constant 18.06 1.75 10.34 0.000Date 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 1.67Site Downstream -0.56 2.47 -0.23 0.826 1.33 Middle -4.06 2.47 -1.64 0.131 1.33Regression Equationtrichoptera 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_UpstreamFits and Diagnostics for Unusual Observations trichopteraObs number Fit Resid Std Resid 1 28.00 16.11 11.89 2.15 R 13 10.00 21.28 -11.28 -2.04 RR Large residual

General Linear Model: NO2 skalar versus Date, Site



CoefficientsTerm Coef SE Coef T-Value P-Value VIFConstant 0.012778 0.000556 23.00 0.000Date 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 1.67Site Downstream 0.000556 0.000786 0.71 0.496 1.33 Middle 0.000556 0.000786 0.71 0.496 1.33Regression EquationNO2 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_UpstreamFits and Diagnostics for Unusual ObservationsObs NO2 skalar Fit Resid Std Resid 16 0.00000 0.00556 -0.00556 -3.16 RR Large residual

General Linear Model: NO2 skalar versus Date, Site

MethodFactor coding (-1, 0, +1)Factor InformationFactor Type Levels ValuesDate Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014Site Fixed 3 Downstream, Middle, UpstreamAnalysis of VarianceSource 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 0.402Error 10 0.000056 0.000006Total 17 0.000561Model Summary S R-sq R-sq(adj) R-sq(pred)0.0023570 90.10% 83.17% 67.92%CoefficientsTerm Coef SE Coef T-Value P-Value VIFConstant 0.012778 0.000556 23.00 0.000Date

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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 1.67Site Downstream 0.000556 0.000786 0.71 0.496 1.33 Middle 0.000556 0.000786 0.71 0.496 1.33Regression EquationNO2 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_UpstreamFits and Diagnostics for Unusual ObservationsObs NO2 skalar Fit Resid Std Resid 16 0.00000 0.00556 -0.00556 -3.16 RR Large residual

General Linear Model: Cross section voloume versus Date, Site MethodFactor coding (-1, 0, +1)Factor InformationFactor Type Levels ValuesDate Fixed 6 03/06/2014, 17/06/2014, 24/06/2014, 08/07/2014, 22/07/2014, 05/08/2014Site 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 0.000Error 10 0.9513 0.0951Total 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 VIFConstant 5.1333 0.0727 70.61 0.000Date 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 1.67Site 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

Test without middle site data for 24/6/14General Linear Model: Total Inverts_1 versus Date_1, Site_1


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 0.117Error 9 23458 2606Total 16 551220

Model Summary

S R-sq R-sq(adj) R-sq(pred)51.0532 95.74% 92.43% 85.41%

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Test without all site data for 24/6/14General Linear Model: Total Inverts_1_1 versus Date_1_1, Site_1_1


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 0.143Error 8 22331 2791Total 14 516834

Model Summary

S R-sq R-sq(adj) R-sq(pred)52.8337 95.68% 92.44% 84.81%

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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 ++ system continuous flow analyser). Glass microfiber filters (110mm)

were numbered (for identifying purposes), prewashed in distilled water and dried in an oven

at 105°C (between two sheets of A4 paper). The filter papers were 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

contamination took place. The filter was placed in a Buckner flask with vacuum filtration. 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 filter papers were placed between two 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

weights recorded. The first weight was subtracted from the second weight giving 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.

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Appendix 4 Cross Sections

Downstream site (descending in date order)

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Middle site (descending in date order)

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Upstream site (descending in date order)

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Middle site slack area (descending in date order)

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