How do offenders choose where to offend? Perspectives from animal foraging

Purpose Research suggests that offender spatial decision-making is not random. However, little is known about if or how offences in a series influence where an offender will target next. Drawing on concepts and empirical findings from environmental criminology and the ecology literature, in this article I consider what spatial patterns might be expected in the sequential crimes committed by serial offenders and provide an empirical example. Methods Data for detected burglars are analysed and patterns in the inter-event distances for sequential offences compared with those signatures typically associated with three types of foraging behaviour – central place foraging, Brownian walks and Levy walks. Analyses involve the use of a Monte Carlo simulation to derive an expected distribution for central place foraging, while the observed probability density function of sequential inter-event distances is compared to exponential and power law distributions to test for evidence of Brownian and Levy walks, respectively. Results Analyses suggest that patterns in burglar sequential inter-event distances cannot be explained by a simple central place foraging strategy. The distribution of sequential inter-event distances is found to be consistent with both Brownian and Levy walks. Conclusions The findings suggest that there are regularities in the sequential spatial choices made by offenders, and that these are similar to those observed across species. Reasons for why there is evidence of both Brownian and Levy walks are discussed. The implications of the findings for forensic techniques such as crime linkage analysis, geographic offender profiling and crime forecasting are discussed.

[1]  Richard Block,et al.  Robberies in Chicago: A Block-Level Analysis of the Influence of Crime Generators, Crime Attractors, and Offender Anchor Points , 2011 .

[2]  Shane D. Johnson,et al.  The Use of Maps in Offender Interviews , 2010 .

[3]  Ken Pease,et al.  Prospective hot-spotting - The future of crime mapping? , 2004 .

[4]  Richard Block,et al.  WHERE OFFENDERS CHOOSE TO ATTACK: A DISCRETE CHOICE MODEL OF ROBBERIES IN CHICAGO* , 2009 .

[5]  Aiden Sidebottom,et al.  ALL OFFENDERS ARE EQUAL, BUT SOME ARE MORE EQUAL THAN OTHERS: VARIATION IN JOURNEYS TO CRIME BETWEEN OFFENDERS* , 2010 .

[6]  K. Pease,et al.  Repeat victimisation: offenders accounts , 1998 .

[7]  P. Brantingham,et al.  Offender Mobility and Crime Pattern Formation from First Principles , 2008 .

[8]  M. Fortin,et al.  Spatial Analysis: A Guide for Ecologists 1st edition , 2005 .

[9]  P. Levy,et al.  Calcul des Probabilites , 1926, The Mathematical Gazette.

[10]  David V. Canter,et al.  The environmental range of serial rapists , 1993 .

[11]  Craig Bennell,et al.  Between a ROC and a hard place: a method for linking serial burglaries by modus operandi , 2005 .

[12]  Shane D. Johnson,et al.  The use of maps in offender interviewing , 2013 .

[13]  E. Charnov Optimal foraging, the marginal value theorem. , 1976, Theoretical population biology.

[14]  George F. Rengert,et al.  Near-Repeat Patterns in Philadelphia Shootings , 2008 .

[15]  Amos H. Hawley,et al.  Human Ecology: A Theory of Community Structure , 1950 .

[16]  Ray Bull,et al.  The linking of burglary crimes using offender behaviour: Testing research cross-nationally and exploring methodology , 2012 .

[17]  S. Ayis,et al.  Linking serious sexual assaults , 1997 .

[18]  K. Bowers,et al.  NEW INSIGHTS INTO THE SPATIAL AND TEMPORAL DISTRIBUTION OF REPEAT VICTIMIZATION , 1997 .

[19]  Alasdair M. Goodwill,et al.  The development of a filter model for prioritising suspects in burglary offences , 2006 .

[20]  Michael Kenneth Townsley,et al.  Space-time dynamics of maritime piracy , 2015 .

[21]  Shane D. Johnson,et al.  Space–Time Modeling of Insurgency and Counterinsurgency in Iraq , 2012 .

[22]  Shane D. Johnson,et al.  TARGET CHOICE DURING EXTREME EVENTS: A DISCRETE SPATIAL CHOICE MODEL OF THE 2011 LONDON RIOTS , 2013 .

[23]  Shane D. Johnson,et al.  Space–Time Patterns of Risk: A Cross National Assessment of Residential Burglary Victimization , 2007 .

[24]  Nicolas E. Humphries,et al.  Environmental context explains Lévy and Brownian movement patterns of marine predators , 2010, Nature.

[25]  Shane D. Johnson,et al.  The Stability of Space-Time Clusters of Burglary , 2004 .

[26]  P. Jeffrey Brantingham,et al.  Prey selection among Los Angeles car thieves , 2013 .

[27]  Ken Pease,et al.  THE TIME COURSE OF REPEAT BURGLARY VICTIMIZATION , 1991 .

[28]  F. Marlowe,et al.  Evidence of Lévy walk foraging patterns in human hunter–gatherers , 2013, Proceedings of the National Academy of Sciences.

[29]  Richard Frank,et al.  Power of Criminal Attractors: Modeling the Pull of Activity Nodes , 2011, J. Artif. Soc. Soc. Simul..

[30]  Brent Snook,et al.  Computerized Crime Linkage Systems , 2012 .

[31]  Mark E. J. Newman,et al.  Power-Law Distributions in Empirical Data , 2007, SIAM Rev..

[32]  Shane D. Johnson,et al.  Spatial, Temporal and Spatio-Temporal Patterns of Maritime Piracy , 2013, The Journal of research in crime and delinquency.

[33]  M. Lammers,et al.  Are Arrested and Non-Arrested Serial Offenders Different? A Test of Spatial Offending Patterns Using DNA Found at Crime Scenes , 2014 .

[34]  Amanda S. Hering,et al.  Characterizing spatial and chronological target selection of serial offenders , 2014 .

[35]  R. Sampson,et al.  Community Structure and Crime: Testing Social-Disorganization Theory , 1989, American Journal of Sociology.

[36]  Shane D. Johnson,et al.  Space Time Dynamics of Insurgent Activity in Iraq , 2008 .

[37]  T. Geisel,et al.  The scaling laws of human travel , 2006, Nature.

[38]  Frank Morgan,et al.  Repeat Burglary in a Perth Suburb: Indicator of Short-Term or Long-Term Risk , 2001 .

[39]  P. Barthelemy,et al.  A Lévy flight for light , 2008, Nature.

[40]  M. Felson Crime and nature , 2006 .

[41]  D V Canter,et al.  Linking commercial burglaries by modus operandi: tests using regression and ROC analysis. , 2002, Science & justice : journal of the Forensic Science Society.

[42]  Shane D. Johnson Repeat burglary victimisation: a tale of two theories , 2008 .

[43]  P. Nonacs State dependent behavior and the Marginal Value Theorem , 2001 .

[44]  P. Brantingham,et al.  Criminality of place , 1995 .

[45]  R. Golledge,et al.  Spatial Behavior: A Geographic Perspective , 1996 .

[46]  Alasdair M. Goodwill,et al.  Sequential angulation, spatial dispersion and consistency of distance attack patterns from home in serial murder, rape and burglary , 2005 .

[47]  Shane D. Johnson,et al.  Consistency and specificity in burglars who commit prolific residential burglary: Testing the core assumptions underpinning behavioural crime linkage , 2016 .

[48]  Shane D. Johnson,et al.  Exploring Theories of Victimization Using a Mathematical Model of Burglary , 2011 .

[49]  A. Daves The Use of DNA Profiling and Behavioural Science in the Investigation of Sexual Offences , 1991 .

[50]  P. Brantingham,et al.  Environment, Routine, and Situation: Toward a Pattern Theory of Crime (1993) , 2010 .

[51]  Ken Pease,et al.  Offender as Forager? A Direct Test of the Boost Account of Victimization , 2009 .

[52]  G. Pyke Optimal Foraging Theory: A Critical Review , 1984 .

[53]  R. Clarke,et al.  Modeling Offenders' Decisions: A Framework for Research and Policy , 1985, Crime and Justice.

[54]  Gandhimohan M. Viswanathan,et al.  Ecology: Fish in Lévy-flight foraging , 2010, Nature.

[55]  George E. Tita,et al.  Self-Exciting Point Process Modeling of Crime , 2011 .

[56]  H. Stanley,et al.  Optimizing the success of random searches , 1999, Nature.

[57]  Lawrence E. Cohen,et al.  Social Change and Crime Rate Trends: A Routine Activity Approach , 1979 .

[58]  Richard F. Sparks,et al.  Multiple Victimization: Evidence, Theory, and Future Research , 1981 .

[59]  George E. Tita,et al.  Measuring and Modeling Repeat and Near-Repeat Burglary Effects , 2009 .

[60]  W. Bernasco A SENTIMENTAL JOURNEY TO CRIME: EFFECTS OF RESIDENTIAL HISTORY ON CRIME LOCATION CHOICE* , 2010 .

[61]  Bret M. Territo,et al.  Crime analysis through computer mapping: By C.B. Block M. Dabdoub, and S. Fregly, Police Executive Research Forum, Washington D.C., 1995, paperback, xiv + 287 pp., US$29.95 (+ $3.75 s and h), ISBN 1-878734-34-2 , 1996 .

[62]  Shane D. Johnson,et al.  Permeability and Burglary Risk: Are Cul-de-Sacs Safer? , 2010 .

[63]  Rebecca Meaney,et al.  Commuters and marauders: an examination of the spatial behaviour of serial criminals , 2004 .

[64]  James F. Nelson Multiple Victimization in American Cities: A Statistical Analysis of Rare Events , 1980, American Journal of Sociology.

[65]  P. Sham,et al.  A note on the calculation of empirical P values from Monte Carlo procedures. , 2002, American journal of human genetics.

[66]  D. Kim Rossmo,et al.  Spatial-temporal crime paths , 2012 .

[67]  Ray Bull,et al.  The psychology of linking crimes: A review of the evidence , 2007 .

[68]  Ken Pease,et al.  Predictive Mapping of Crime by ProMap: Accuracy, Units of Analysis, and the Environmental Backcloth , 2009 .

[69]  Patrick R. Gartin,et al.  Hot Spots of Predatory Crime: Routine Activities and the Criminology of Place , 1989 .

[70]  M. Townsley,et al.  Infectious Burglaries. A Test of the Near Repeat Hypothesis , 2003 .

[71]  Matthew P. J. Ashby,et al.  A comparison of methods for temporal analysis of aoristic crime , 2013 .

[72]  Ken Pease,et al.  Prospective mapping in operational context , 2007 .

[73]  Grover Maurice Godwin Criminal Psychology and Forensic Technology : A Collaborative Approach to Effective Profiling , 2000 .

[74]  Wim Bernasco,et al.  Same-Offender Involvement in Repeat and Near Repeat Burglaries , 2008 .