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Durham E-Theses CATCHMENT SCALE INFLUENCES ON BROWN TROUT FRY POPULATIONS IN THE UPPER URE CATCHMENT, NORTH YORKSHIRE. HIGGINS, DAVID,IAN How to cite: HIGGINS, DAVID,IAN (2011) CATCHMENT SCALE INFLUENCES ON BROWN TROUT FRY POPULATIONS IN THE UPPER URE CATCHMENT, NORTH YORKSHIRE., Durham theses, Durham University. Available at Durham E-Theses Online: http://etheses.dur.ac.uk/3571/ Use policy The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that: • a full bibliographic reference is made to the original source • a link is made to the metadata record in Durham E-Theses • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders. Please consult the full Durham E-Theses policy for further details. Academic Support Oce, Durham University, University Oce, Old Elvet, Durham DH1 3HP e-mail: [email protected] Tel: +44 0191 334 6107 http://etheses.dur.ac.uk 2 CATCHMENT SCALE INFLUENCES ON BROWN TROUT FRY POPULATIONS IN THE UPPER URE CATCHMENT, NORTH YORKSHIRE. David Ian Higgins PhD Department of Geography University of Durham 2011 David Ian Higgins Catchment-scale influences on brown trout fry populations in the upper Ure catchment. A multi-scale approach for restoration site selection is presented and applied to an upland catchment, the River Ure, North Yorkshire. Traditional survey methods, advances in remote sensing, Geographical Information Systems (GIS) and risk-based fine sediment modelling using the SCIMAP module are combined to gather data at the catchment-scale through to the in-stream habitat-scale. The data gathered have been assessed against spatially distributed brown trout fry populations using Pearson’s correlation and multiple stepwise regressions. Fine sediment was shown to have a positive correlation with fry populations when upland drainage channels (grips) were added to the SCIMAP model. This suggests risk from peatland drainage is realised further down the catchment where eroded sediments are deposited. Farm-scale SCIMAP modelling was tested against farmers’ knowledge with variable results. It appears there is a cultural response to risk developed over generations. Management of meadows and pasture land through sub-surface drainage and stock rotation resulted in the risk being negated or re-routed across the holding. At other locations apparently low-risk zones become risky through less sensitive farming methods. This multi-scale approach reveals that the largest impacts on brown trout recruitment operate at the habitat-adjacent scale in tributaries with small upstream areas. The results show a hierarchy of impact, and risk-filters, arising from different intensity land management. This offers potential for targeted restoration site selection. In low-order streams it seems that restoration measures which exclude livestock, and provide bankside shading, can be effective. At such sites the catchment-scale shows a reduced signal on in-stream biota. Thus, brown trout stocks could be significantly enhanced by targeting restoration at riffle-habitat zones and adjacent land in order to disconnect the stream from farm-derived impacts and through adding structure to the stream channel. ii Acknowledgements This research was supported by a Durham University PhD studentship and a Sustainable Development Fund grant awarded to the Yorkshire Dales Rivers Trust. This was ‘topped-up’ with funds from the Environment Agency and the local branch of the Salmon and Trout Association, all of whom I owe a debt of gratitude. The support of Professor Stuart Lane and Professor Tim Burt of Durham University together with Dr. John Shillcock and Nick Buck of the Yorkshire Dales Rivers Trust has been invaluable over the last five years. Dr. Sim Reaney, Dr. Dave Milledge and Dr. Nick Odoni of Durham University deserve a mention for their patient help and support. Durham University IT and laboratory technicians provided assistance throughout the project. Paul Frear and Mike Lee of the Environment Agency offered their help from the beginning of this project. They provided training in electrofishing, organised the loan of EA electrofishing equipment and happily passed on their knowledge of salmonid species. Dr. Liz Chalk and Jeff Pacey, also of the EA, deserve a special mention. They have given support to the trust and myself over many years. The Yorkshire Dales National Park Authority and Yorkshire Dales Millennium Trust also warrant a mention. Without their assistance much of this work would not have been possible. The team of National Park rangers, and volunteers, provided assistance with the electrofishing surveys and with the use of their quad bike we surveyed sites impossible to access otherwise. Deborah Millward, Phil Lyth, Michael Broadwith and Tom Wheelwright of the Yorkshire Dales Rivers Trust have all willingly assisted over the duration of this work. I would also like to acknowledge the many landowners and farmers of Wensleydale who granted access to their land, helped to test the SCIMAP model and took time out of their busy schedules in order to help. Finally, my friends and family have been a great support and they deserve the warmest of thanks. iii Declaration of copyright I confirm that no part of the material presented in this thesis has previously been submitted by me or any other person for a degree in this or any other university. In all cases, where it is relevant, material from the work of others has been acknowledged. The copyright of this thesis rests with the author. No quotation from it should be published without prior written consent and information derived from it should be acknowledged. Signed: iv List of Figures Page Figure 2.1 Trends in salmonid populations 18 Figure 2.2 Biotic controls on salmon parr 19 Figure 2.3 Abiotic controls on salmon parr 20 Figure 2.4 The salmonid life cycle 21 Figure 2.5 Salmonids and scales of space and time 24 Figure 2.6 Dispersal and migration barriers 27 Figure 2.7 Cascade of impacts 1: Gripping 53 Figure 2.8 Cascade of impacts 2: Slurry and fertilizer 55 Figure 2.9 Cascade of impacts 3: overstocking and poaching 58 Figure 2.10 Flow of energy between streams and land 61 Figure 2.11 Scales and links of diffuse pollution 78 Figure 3.1 Algal bloom, River Ure 91 Figure 3.2 Supplementary feeding practices 91 Figure 3.3 Poaching of soils by livestock 92 Figure 3.4 Stock access to riverbank, river Ure 92 Figure 3.5 A well buffered patch, River Ure 93 Figure 3.6 Bank side management on low order streams of the same farm 93 Figure 3.7 Following a stream through one farm holding 94 Figure 3.8 Following a stream through a different farm holding 95 Figure 3.9 Severe bank erosion due to stock access, River Ure 96 Figure 3.10 Eroding bank due to different vegetation types 97 Figure 3.11 Using rubble to shore up eroding banks 97 Figure 3.12 Location of the upper Ure catchment 100 Figure 3.13 Elevation map of the catchment 101 Figure 3.14 Landcover map of the catchment 101 Figure 3.15 Geology of the catchment 103 Figure 3.16 Area of moorland within the catchment 104 Figure 3.17 Strahler stream orders 105 Figure 3.18 WFD criteria 106 Figure 3.19 Sub-catchments of the upper Ure 107 Figure 3.20 Gauging sites on the river Ure 116 Figure 3.21 Medium term temperature data, Askrigg 118 Figure 3.22 Medium term temperature data, Bainbridge 119 Figure 3.23 Medium term precipitation data, Burtersett 121 Figure 3.24 Burtersett T10 events 122 Figure 3.25 Mean stream flow at the Snaizeholme gauge 124 Figure 3.26 5 % percentile flows, Snaizeholme 125 Figure 3.27 Phosphate sampling at Bainbridge WWTW 126 Figure 3.28 Phosphate sampling at Hawes WWTW 127 Figure 3.29 Nitrate samples taken in Raydale 128 Figure 3.30 Brown trout populations of the upper Ure catchment 129 Figure 3.31 Species found in the river system 131 Figure 4.1 Location of electrofishing surveys 145 Figure 4.2 Locations within the catchment 146 Figure 4.3 Location of the triple pass surveys 147 Figure 4.4 Images of some of the electrofishing sites 148 Figure 4.5 Kick sampling for macroinvertebrates 149 Figure 4.6 Algal bloom at Worton Bridge, River Ure 154 Figure 4.7 The raw inputs for SCIMAP 164 Figure 4.8 Schematic of the SCIMAP process 165 v Figure 4.9 SIMAP fine-sediment risk 167 Figure 4.10 SCIMAP surface flow index 168 Figure 4.11 SCIMAP fine-sediment delivery index 169 Figure 4.12 Remote sensing of upland drainage channels 172 Figure 4.13 Creation of the grip map 173 Figure 4.14 Adding the grip map to the DEM 175 Figure 4.15 SCIMAP in-stream categories 177 Figure 4.17 The land holdings explored for SCIMAP at the farm-scale 182 Figure 4.18 Links between data and methods 188 Figure 5.1 Triple pass electrofishing results 199 Figure 5.2 Farm-scale SCIMAP locations 203 Figure 5.3 Widdale Foot Farm 206 Figure 5.4 Traditional underdrain style 208 Figure 5.5 Raygill House Farm 209 Figure 5.6 Low Blean Farm 212 Figure 5.7 School House Farm 215 Figure 5.8 Redshaw Farm 218 Figure 5.9 Town Head Farm 221 Figure 5.10 Raydale Grange Farm 224 Figure 5.11 Semerdale Hall Farm 227 Figure 5.12 Catchment-scale SCIMAP outputs 229 Figure 5.13 Catchment-scale SCIMAP results at the in-stream scale 231 Figure 5.14 Capturing the SCIMAP risk categories 232 Figure 5.15 Correlations with the three catchment-scale SCIMAP runs 239 - 241 Figure 5.16 Brown trout relationships with substrate form 243 Figure 5.17 Brown