Environmental factors aff ecting the occurrence of periglacial landforms in Finnish Lapland: a numerical approach Jan Hjort Department of Geography Faculty of Science University of Helsinki Academic dissertation To be presented, with the permission of the Faculty of Science of the University of Helsinki, for public criticism in the Auditorium XII of the Main Building (Unioninkatu 34) on May 6th, 2006, at 10 a.m. I Supervisors Professor Matti Seppälä Department of Geography University of Helsinki Finland and Dr Miska Luoto Finnish Environment Institute, Helsinki / Th ule Institute University of Oulu Finland Pre-Examiners Professor Bernd Etzelmüller Department of Physical Geography University of Oslo Norway and Professor Charles Harris School of Earth, Ocean and Planetary Sciences Cardiff University United Kingdom Offi cial Opponent Reader Julian Murton Department of Geography University of Sussex United Kingdom Copyright © Shaker Verlag 2006 ISBN 3-8322-5008-5 (paperback) ISSN 0945-0777 (paperback) ISBN 952-10-3080-1 (PDF) http://ethesis.helsinki.fi Shaker Verlag GmbH, Aachen II Contents Abstract VII Acknowledgements VIII List of Figures IX List of Tables XII List of Appendices XIII Abbreviations XIII Symbols XIV 1 INTRODUCTION 1 2 PERIGLACIAL PHENOMENA 5 2.1 Classifi cation of periglacial landforms 6 2.2 Description of periglacial landforms 9 2.2.1 Permafrost landforms 9 2.2.2 Thermokarst features 10 2.2.3 Patterned ground 10 2.2.4 Solifl uction and other slope phenomena 16 2.2.5 Periglacial weathering features 19 2.2.6 Nival phenomena 20 2.2.7 Aeolian processes and landforms 21 3 STUDY AREA 23 3.1 Location and topography 23 3.2 Bedrock and general geology 23 3.3 Weichselian glaciation, deglaciation and soil types 23 3.4 Geomorphology of the Báišduattar – Áilegas 25 3.5 Previous periglacial research in the study region 29 3.6 Past and present climate 30 3.7 Hydrology 32 3.8 Vegetation 32 4 MATERIALS AND METHODS 35 4.1 Modelling data 35 4.1.1 Resolution 35 4.1.2 Periglacial landforms 35 4.1.3 Predictor variables 37 4.1.4 Predictor variable selection and data split 44 4.2 Statistical modelling 44 4.2.1 Statistical formulation 44 4.2.2 Model calibration 46 4.2.3 Model evaluation 46 5 RESULTS 49 5.1 Predictor variables 49 5.2 Periglacial landforms in Báišduattar – Áilegas 49 5.2.1 Palsas 51 5.2.2 Convex non-sorted circles 53 5.2.3 Stony earth circles 53 5.2.4 Earth hummocks 56 5.2.5 Peat pounus 59 5.2.6 Stone pits 60 5.2.7 Sorted nets 61 5.2.8 Sorted stripes 62 5.2.9 Non-sorted solifl uction terraces 64 5.2.10 Sorted solifl uction sheets 64 5.2.11 Sorted solifl uction streams 66 5.2.12 Defl ations 66 V 5.3 Distribution and abundance models 67 5.3.1 Palsas 67 5.3.2 Convex non-sorted circles 71 5.3.3 Stony earth circles 74 5.3.4 Earth hummocks 75 5.3.5 Peat pounus 80 5.3.6 Stone pits 84 5.3.7 Sorted nets 86 5.3.8 Sorted stripes 88 5.3.9 Non-sorted solifl uction terraces 90 5.3.10 Sorted solifl uction sheets 91 5.3.11 Sorted solifl uction streams 94 5.3.12 Defl ations 95 5.3.13 Modelling results: a summary 97 6 DISCUSSION 101 6.1 Periglacial landforms: prevalence, distribution, activity and morphology 101 6.2 Environmental factors affecting periglacial landform occurrence 106 6.2.1 Palsas 106 6.2.2 Convex non-sorted circles 108 6.2.3 Stony earth circles 109 6.2.4 Earth hummocks 110 6.2.5 Peat pounus 111 6.2.6 Stone pits 112 6.2.7 Sorted nets 113 6.2.8 Sorted stripes 114 6.2.9 Non-sorted solifl uction terraces 115 6.2.10 Sorted solifl uction sheets 116 6.2.11 Sorted solifl uction streams 117 6.2.12 Defl ations 118 6.3 Data and methodological issues – advantages and shortcomings 119 6.3.1 Periglacial landform data 119 6.3.2 Predictor data 120 6.3.3 Statistical modelling 122 7 SUMMARY 125 8 CONCLUSIONS 129 REFERENCES 131 OTHER SOURCE MATERIAL 149 APPENDICES 151 VI ABSTRACT The conclusions about the determinants of earth surface processes and landform patterns are often derived from traditional fi eld survey methods. Recent developments in the spatial and numerical analysing techniques have improved the possibility to study different aspects of geomorphological phenomena in extensive regions. The objective of this research was to map and quantitatively analyse the occurrence of cryogenic phenomena in subarctic Finland in the zone of discontinuous perma- frost. More precisely, utilising a grid-based approach the distribution and abundance of periglacial landforms were modelled to identify important landscape scale environmental factors and potential methodological limitations. The study was performed using a comprehensive empirical data set of periglacial landforms from an area of 600 km2 at a 25-ha resolution. The utilised statistical methods were generalized linear modelling (GLM) and hierarchical partitioning (HP). GLMs were used to produce distribution and abundance models and HP to reveal independently the most likely causal variables. The GLM models were assessed utilising statistical evaluation measures, prediction maps, fi eld observations and the results of HP analyses. A total of 40 different landform types and subtypes were identifi ed. At lower altitudes with gentle slope angles occurred earth hummock, stone pit, peat pounu and palsa continuums and at higher altitudes with steeper slopes sorted stripe, solifl uction stream and solifl uction sheet sequences were prevalent. At present, the environmental conditions promote the formation of different cryoturba- tion and peat accumulation based non-sorted features, whereas most of the sorted landforms were probably formed before the climatic optimum over 8000 years ago. Topographical, soil property and vegetation variables were the primary correlates for the occur- rence and cover of active periglacial landforms on the landscape scale. From the pure topographical factors, mean slope angle and mean altitude were commonly in the fi nal models. Peat cover was the most important soil type variable because of its varying thermal properties and moisture holding capacity. Topographical wetness index was a crucial surrogate of environmental factor exhibiting the general soil moisture distribution. From vegetation variables, the shrub cover affected the distribution of several periglacial landforms. In the model evaluation, most of the GLMs were shown to be rather robust although the explana- tion power, prediction ability as well as the selected explanatory variables varied between the mod- els. The most robust distribution models were constructed with palsa, earth hummock, peat pounu, sorted solifl uction sheet and sorted solifl uction stream data. Earth hummock and peat pounu models obtained the best prediction and explanation ability in the abundance modelling, respectively. The great potential of the combination of a spatial grid system, terrain data and novel statistical techniques to map the occurrence of periglacial landforms was demonstrated in this study. GLM proved to be a useful modelling framework for testing the shapes of the response functions and signifi cances of the variables describing environmental gradients and the HP method helped to make better deductions of the important factors of earth surface processes. Hence, the numerical ap- proach presented in this study can be a useful addition to the current range of techniques available to researchers to map and monitor different geographical phenomena. However, the data related limita- tions and method-based weaknesses may bias the modelling results and the model outcomes should not be interpreted uncritically. Keywords: periglacial geomorphology, patterned ground, solifl uction, numerical analyses, generalized linear modelling, logistic regression, hierarchical partitioning, GIS, subarctic, Lapland, Finland Jan Hjort, Department of Geography P.O. Box 64, FIN-00014 University of Helsinki, Finland VII ACKNOWLEDGEMENTS I am grateful to my supervisors Professor Matti Seppälä (Department of Geography, University of Helsinki) and Dr Miska Luoto (Finnish Environment Institute, Helsinki; Thule Institute, University of Oulu) for providing me with the idea and opportunity to do this research. They also have always found time for discussion, advice, comments and constructive criticism throughout the study. In addition, Professors Bernd Etzelmüller and Charles Harris gave several valuable comments on the manuscript. Most of the GIS and statistical analyses as well as the writing were carried out at the Department of Geog- raphy, University of Helsinki, and I wish to express my thanks to all my colleagues there, especially IT Adviser Hilkka Ailio (computing issues and preparation of the layout), PhD student Janne Heiskanen (introduction to the biotope database), PhD student Tommi Sirviö (GIS advice) and IT Administrator Tom Blom (computing problems) as well as PhD student Barnaby Clark who greatly helped with correction of the English text. Kevo Subarctic Research Institute provided good facilities during the fi eld surveys, especially Saini Heino and Kaisu Vierma-Laine who kindly put me up after hard fi eld trips regardless of the day of the week or time. Furthermore, I want to thank Mikko Lantz for fi eld work companion during the summers of 2002 and 2003. I would like to thank the following persons from the Scott Polar Research Institute (SPRI), University of Cam- bridge: Archivist and Curator Robert Headland, Information Assistant Shirley Sawtell and Librarian Heather Lane, who all greatly helped me during the visit to SPRI in May 2005. I wish to express heartfelt special thanks to my wife, PhD student Paula Kuusisto-Hjort, who provided fi eld work companion during the summers of 2002 and 2003, commented on the manuscript at different stages and supported me with love and warmth at every step from the beginning of the study to the fi nishing of the manu- script.