Eindhoven University of Technology MASTER Predicting the Oak Processionary Moth Population using Statistical Modeling Scholtens, Tim P.H. Award date: 2021 Link to publication Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration. 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Sadowski (TU/e) Eindhoven, January 12, 2021 ABSTRACT Context The oak processionary moth is an infamous insect within the Netherlands. During its caterpillar stage it develops hairs that cause health issues on physical contact. Current solutions to eradicate the OPM have their drawbacks as they too eradicate the OPM’s predators, or are too labour intensive to be effective. Therefore, experts conclude that total eradication is no longer an option and we should aim for controlling the OPM population [3]. AimOuraimfor thisstudyis toenableorganisations makinginformeddecisionsconcerningthe OPM population distribution. Using statistical modeling, a model can be defined for estimating the OPM population within a given area. By estimating the population size, organisations can allocate resources proportionally, thus allowing for more efficient decisions. Innovation Using the statistical framework Species Distribution Modeling, we defined, to the best of our knowledge, the first predictive model to estimate the OPM population within a given area. Additionally, using ecological theory, we conceptualized and evaluated a model of factors that affect the OPM population. Conclusion Our work provides a baseline predictive model and conceptual model which can be further extended upon. However, due to the limited availability of OPM occurrence data, our predictive model knows several limitations. Firstly, we have not accounted for spatial autocorrelation between neighbouring areas. Secondly, a temporal component is missing in our models. Therefore we strongly recommend the gathering of detailed (both spatial and temporal) data such that in future research these aspects can be taken into account. Keywords Oak processionary moth, Species Distribution Modeling, BIOCLIM. 2 PREFACE Before you lies my thesis performed at VAA, it contains my research on how statistical modeling can be used for estimating the oak processionary moth population within an area. I would like to express my gratitude towards my inspiring supervisors, whom without their guidance, this thesis would not have been possible. Rogier Brussee, my day-to-day supervisor, thank you for the good times, and to help me grow not only professionally, but also into a better person overall. Jakob de Vlieg, while going through an extremely difficult time, yet still keeps going strong, thank you for being an inspiration. Furthermore, I would like to thank my day-to-day supervisor at VAA. Arie Weeren, thank you for your expert guidance in statistics, and you never-ending patience in explaining me the mathematics behind. Lastly, I would like to thank the following parties for supplying data or their guidance thereof: Antea group, T. Grooten BomenMonitor, W. Tims BoomRegister, D. Voets Eikenprocessierups expertise centrum, H. Kuppen Gemeente Amsterdam, J. Bijleveld Gemeente Geldrop, G. Broeren Gemeente Leiden, R. Jonke, E. Hilgersom Nationale databank flora en fauna Naturalis, dr. M. Roos, P. van Aalst, J. Dercksen, V. Beckers Provincie Gelderland Provinciehuis Noord-brabant, S. op ’t Hof Sovon, J. Schoppers Vlinderstichting, J. van Deijk Vogelbescherming, M. Platel Wageningen Universiteit, F. Brouwer 3 Contents 1 Introduction 10 1.1 Context and topic ..................................... 10 1.2 State of the art ....................................... 10 1.3 Research question ..................................... 10 1.4 Research methodology .................................. 11 2 Preliminaries 12 2.1 Ecological Theory ..................................... 12 2.1.1 Environmental space ............................... 12 2.1.2 Environmental factors .............................. 13 2.2 Oak processionary moth ................................. 14 3 Literature review 16 3.1 Frameworks ......................................... 16 3.1.1 Species distribution modeling .......................... 16 3.1.2 Population dynamics ............................... 17 3.1.3 Conclusion ..................................... 18 3.2 State of the art ....................................... 19 4 Data 22 4.1 Conceptualization ..................................... 22 4.1.1 Conceptual model ................................. 22 4.1.2 Predictor variables ................................ 24 4.2 Data collection ....................................... 25 4.2.1 Oak processionary moths ............................ 25 4.2.2 Climate ....................................... 25 4.2.3 Geology ....................................... 26 4.2.4 Oak trees ...................................... 27 4.2.5 Predators ...................................... 27 4.3 Data transformation .................................... 28 4.3.1 BIOCLIM variables ................................ 28 4.3.2 Spatial scale .................................... 29 4.4 Data organisation ..................................... 30 4.4.1 Datasets ...................................... 30 4.4.2 Overview ...................................... 31 4 5 Analysis 32 5.1 Data visualization ..................................... 32 5.1.1 Geographic bounds ................................ 32 5.1.2 Oak processionary moths ............................ 33 5.1.3 Oak trees ...................................... 35 5.1.4 Great tits ...................................... 38 5.1.5 Soil ......................................... 41 5.1.6 BIOCLIM ...................................... 43 5.1.7 Conclusion ..................................... 44 5.2 Exploratory data analysis ................................. 45 5.2.1 Scatter plots .................................... 46 5.2.2 Correlation matrix ................................ 49 5.3 Feature selection ...................................... 53 5.3.1 Method ....................................... 53 5.3.2 Results ....................................... 53 5.3.3 Conclusion ..................................... 56 6 Models 57 6.1 Scaling ............................................ 57 6.2 Algorithm selection .................................... 57 6.3 Model building ....................................... 57 6.4 Model evaluation ..................................... 59 6.5 Results ............................................ 60 6.5.1 Spatial analysis .................................. 60 6.5.2 Test error ...................................... 64 7 Conclusion 65 7.1 Concluding summary ................................... 65 7.2 Contributions ........................................ 66 7.3 Limitations and future work ............................... 67 Bibliography 68 Appendix 69 A Data collection 70 A.1 BIOCLIM .......................................... 70 A.1.1 Variables ...................................... 70 B Feature selection 75 B.1 LASSO ............................................ 75 5 C Models 76 C.1 Generalized linear models ................................ 76 C.2 Random Forest ....................................... 78 C.3 Neural networks ...................................... 81 6 List of Figures 1 Research methodology .................................. 11 2 Hutchinsonian niche .................................... 12 3 Species distribution modeling cycle ........................... 17 4 Neural network architecture ............................... 20 5 Conceptual model of factors affecting the OPM’s population ............ 23 6 Provincial roads in Gelderland (light green) ...................... 25 7 Locations of the KNMI weatherstations ........................ 26 8 Neighbourhood geographic bounds .......................... 32 9 Distribution OPM in Amsterdam 2018 ......................... 33 10 Distribution OPM in Amsterdam 2019 ......................... 34 11 Distribution OPM in Gelderland ............................. 35 12 Distribution oak trees Gelderland ............................ 36 13 Distribution oak trees Amsterdam ........................... 37 14 Distribution great tits Amsterdam 2018 ........................ 38 15 Distribution great tits Amsterdam 2019 ........................ 39 16 Distribution great tits Gelderland