Agency Through Design: Behavior-Specific Use Patterns of Horses Across Four Different Turnout Areas in the Netherlands

Inga Wolframm; Kerstin Vogel; Yteke Elte; Mattias  Lindström; Karl Forssman; Thomas Engels

doi:10.64292/ijes.236

Authors

Inga Wolframm Applied Research Centre, Van Hall Larenstein University of Applied Sciences, 6882 CT Velp, the Netherlands; Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands https://orcid.org/0000-0002-0394-8417
Kerstin Vogel Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands https://orcid.org/0009-0008-1752-5272
Yteke Elte Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands https://orcid.org/0000-0002-9633-9871
Mattias Lindström Hoofstep, Inc. HQ, P.O. Box 1334, Wrightwood, CA 92397, United States https://orcid.org/0009-0000-7571-2801
Karl Forssman Hoofstep, Inc. HQ, P.O. Box 1334, Wrightwood, CA 92397, United States https://orcid.org/0009-0008-3341-5057
Thomas Engels Applied Research Centre, Van Hall Larenstein University of Applied Sciences, 6882 CT Velp, the Netherlands https://orcid.org/0009-0001-1290-8791

DOI:

https://doi.org/10.64292/ijes.236

Keywords:

Equine welfare, spatial behavior, landscape heterogeneity, environmental enrichment, behavioral agency, sensor technology

Abstract

Equine turnout areas are commonly designed to maximize open space. However, research in more naturalistic settings suggests that horses use landscape features selectively. This study examined how horses' spatial use patterns vary across turnout designs with different levels of structural complexity, and whether the use of specific features differs according to behavioral state and time of day. Horses (N = 26) at four Dutch yards (A–D; size range: 6,477 m²–37,489 m²) differing in landscape design were monitored for 10 consecutive days using Hoofstep® GPS–IMU sensors. Behavior was automatically classified into four categories (Eating, Resting, Active, Highly Active). Spatial preprocessing was conducted in Python, with ArcGIS used for cartographic checking, yielding a final dataset of 3,856.50 monitoring hours. Feature selection relative to availability was quantified using Manly's Selection Ratios (MSR). Log-transformed MSR values were analyzed using yard-specific linear mixed models. Landscape features significantly influenced spatial selection across all yards (A: F(12,940) = 98.199, P < 0.001; B: F(7,1460) = 124.663, P < 0.001; C: F(4,273) = 19.326, P < 0.001; D: F(6,498) = 38.691, P < 0.001). Behavior × landscape feature interactions were also significant in all models (all P < 0.001), indicating behavior-specific spatial selection. Significant interactions involving time of day were observed primarily in the more structurally heterogeneous environments. Findings indicate that behavior-specific spatial organization was fundamentally shaped by structural environment. Landscape heterogeneity therefore appears to support behavioral agency by providing horses with functionally distinct spatial options. These findings support landscape design as an important consideration for equine welfare, with potential co-benefits for biodiversity.

References

Elgåker HE. The new equine sector and its influence on multifunctional land use in peri-urban areas. GeoJournal 2012;77:591–613. https://doi.org/10.1007/s10708-010-9398-y.

Rzekęć A, Vial C, Bigot G. Green assets of equines in the European context of the Ecological Transition of Agriculture. Animals 2020;10:106. https://doi.org/10.3390/ani10010106.

Krueger K, Esch L, Farmer K, Marr I. Basic needs in horses?—a literature review. Animals 2021;11:1798. https://doi.org/10.3390/ani11061798.

Lesimple C, Reverchon-Billot L, Galloux P, Stomp M, Boichot L, Coste C, et al. Free movement: A key for welfare improvement in sport horses? Applied Animal Behaviour Science 2020;225:104972. https://doi.org/10.1016/j.applanim.2020.104972.

Mouncey R, Arango-Sabogal JC, de Mestre A, Verheyen KL. Associations between turn out practices and rates of musculoskeletal disease and injury in Thoroughbred foals and yearlings on stud farms in the United Kingdom. Equine Veterinary Journal 2024;56:892–901. https://doi.org/10.1111/evj.14038.

Mellor D. Updating animal welfare thinking: moving beyond the "five freedoms" towards "a life worth living." Animals 2016;6:21. https://doi.org/10.3390/ani6030021.

Mellor DJ, Beausoleil NJ, Littlewood KE, McLean AN, McGreevy PD, Jones B, et al. The 2020 five domains model: including human–animal interactions in assessments of animal welfare. Animals 2020;10:1870. https://doi.org/10.3390/ani10101870.

Arndt SS, Goerlich VC, van der Staay FJ. A dynamic concept of animal welfare: The role of appetitive and adverse internal and external factors and the animal's ability to adapt to them. Frontiers in Animal Science 2022;3:908513. https://doi.org/10.3389/fanim.2022.908513.

Auer U, Kelemen Z, Engl V, Jenner F. Activity time budgets—a potential tool to monitor equine welfare? Animals 2021;11:850. https://doi.org/10.3390/ani11030850.

Lamanna M, Buonaiuto G, Colleluori R, Raspa F, Valle E, Cavallini D. Time-activity budget in horses and ponies: A systematic review and meta-analysis on feeding dynamics and management implications. Journal of Equine Veterinary Science 2025;154:105684. https://doi.org/10.1016/j.jevs.2025.105684.

Miggitsch N, Naydani CJ, Lancaster BE. Prevalence and perceived effects of enrichment elements in outdoor areas on the behavior and welfare of group-housed horses. International Journal of Equine Science 2025;4:17–28. https://doi.org/10.64292/ijes.192.

Veissier I, Lesimple C, Brunet V, Aubé L, Botreau R. Review: Rethinking environmental enrichment as providing opportunities to acquire information. Animal 2024;18:101251. https://doi.org/10.1016/j.animal.2024.101251.

Benhajali H, Richard-Yris M-A, Ezzaouia M, Charfi F, Hausberger M. Foraging opportunity: a crucial criterion for horse welfare? Animal 2009;3:1308–12. https://doi.org/10.1017/s1751731109004820.

Perron B, Bridges W, Ali A, Aguerre M, Burns M, Vernon K. 78 Effects of maneuvering required maintenance elements to monitor the grazing behaviors of horses. Journal of Equine Veterinary Science 2021;100:103541. https://doi.org/10.1016/j.jevs.2021.103541.

de Laat MA, Hampson BA, Sillence MN, Pollitt CC. Sustained, low-intensity exercise achieved by a dynamic feeding system decreases body fat in ponies. Journal of Veterinary Internal Medicine 2016;30:1732–8. https://doi.org/10.1111/jvim.14577.

Hampson BA, de Laat MA, Monot J, Bailliu D, Pollitt CC. Adaption of horses to a novel dynamic feeding system: Movement and behavioural responses. Equine Veterinary Journal 2013;45:481–4. https://doi.org/10.1111/evj.12002.

Farmer J, Duberstein J, Callaway T, Duberstein K, Wassel B, Toal K, et al. 98 Environmental impacts and daily voluntary movement of horses housed in pasture tracks as compared to conventional pasture housing. Journal of Equine Veterinary Science 2023;124:104400. https://doi.org/10.1016/j.jevs.2023.104400.

Wolframm I, Engels T, Lindström M, Forssman K. Landscape of choice: The influence of landscape features on the behavior of sport horses. International Journal of Equine Science 2025;4:3–16. https://doi.org/10.64292/j2jkvt50.

Wolframm I, Scheer T, Linnenberg L, Rechterschot S. The meaning of the place – a socio-spatial analysis of equine yards. International Journal of Equine Science 2025;4:30–51. https://doi.org/10.64292/ijes.153.

Wolframm I, Arrabal D, van den Brink E, Korterink de Vries J. Motivation without means? Behavioral drivers and barriers to biodiversity implementation on Dutch equine yards. Conservation 2026;6:4. https://doi.org/10.3390/conservation6010004.

Oksuz DP, Aguiar CAS, Tápia S, Llop E, Lopes P, Serrano ARM, et al. Increasing biodiversity in wood-pastures by protecting small shrubby patches. Forest Ecology and Management 2020;464:118041. https://doi.org/10.1016/j.foreco.2020.118041.

Perez-Alvarez R, Chará J, Snyder LD, Bonatti M, Sieber S, Martin EA. Meta-analysis shows overall benefits of cattle silvopastoral systems for biodiversity in fragmented forest landscapes. Ecological Applications 2026;36:e70255. https://doi.org/10.1002/eap.70255.

Brück M, Benra F, Duguma DW, Fischer J, Jiren TS, Law EA, et al. A social-ecological approach to support equitable land use decision-making. Ambio 2024;53:1752–67. https://doi.org/10.1007/s13280-024-02056-x.

Liu M, Wei H, Dong X, Wang X-C, Zhao B, Zhang Y. Integrating land use, ecosystem service, and human well-being: a systematic review. Sustainability 2022;14:6926. https://doi.org/10.3390/su14116926.

Kelemen Z, Grimm H, Vogl C, Long M, Cavalleri JMV, Auer U, et al. Equine activity time budgets: the effect of housing and management conditions on geriatric horses and horses with chronic orthopaedic disease. Animals 2021;11:1867. https://doi.org/10.3390/ani11071867.

Flauger B, Krueger K. Aggression level and enclosure size in horses (Equus caballus). Pferdeheilkunde Equine Medicine 2013;29:495-504-495–504. https://doi.org/10.21836/pem20130404.

Kjellberg L, Dahlborn K, Roepstorff L, Morgan K. Frequency and nature of health issues among horses housed in an active open barn compared to single boxes—A field study. Equine Veterinary Journal 2025;57:54–61. https://doi.org/10.1111/evj.14054.

McDonnell SM. The equid ethogram: A practical field guide to horse behavior. Eclipse Press; 2003.

McKinney W. Data structures for statistical computing in Python, SciPy; 2010, p. 56–61. https://doi.org/10.25080/majora-92bf1922-00a.

Harris CR, Millman KJ, van der Walt SJ, Gommers R, Virtanen P, Cournapeau D, et al. Array programming with NumPy. Nature 2020;585:357–62. https://doi.org/10.1038/s41586-020-2649-2.

Manly BF, McDonald L, Thomas DL, McDonald TL, Erickson WP. Resource selection by animals: statistical design and analysis for field studies. London, UK: Kluwer Academic Publishers; 2007.

Bates D, Mächler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. Journal of Statistical Software 2015;67:1–48. https://doi.org/10.18637/jss.v067.i01.

Kuznetsova A, Brockhoff PB, Christensen RHB. Lmertest package: Tests in linear mixed effects models. Journal of Statistical Software 2017;82:1–26. https://doi.org/10.18637/jss.v082.i13.

Bartoń K. Mumin: Multi-model inference 2010. https://doi.org/10.32614/CRAN.package.MuMIn.

Lenth RV, Piaskowski J. emmeans: Estimated marginal means, aka least-squares means 2017. https://doi.org/10.32614/CRAN.package.emmeans.

Gibson JJ. The ecological approach to visual perception. New York: Psychology Press; 2014. https://doi.org/10.4324/9781315740218.

Freeman DE. Effect of feed intake on water consumption in horses: relevance to maintenance fluid therapy. Frontiers in Veterinary Science 2021;8:626081. https://doi.org/10.3389/fvets.2021.626081.

McDonnell SM, Freeman DA, Cymbaluk NF, Schott HC, Hinchcliff K, Kyle B. Behavior of stabled horses provided continuous or intermittent access to drinking water. American Journal of Veterinary Research 1999;60:1451–6. https://doi.org/10.2460/ajvr.1999.60.11.1451.

Seligman MEP, Csikszentmihalyi M. Positive psychology: An introduction. American Psychologist 2000;55:5–14. https://doi.org/10.1037/0003-066x.55.1.5.

Lesimple C, Hausberger M. How accurate are we at assessing others' well-being? The example of welfare assessment in horses. Frontiers in Psychology 2014;5:21. https://doi.org/10.3389/fpsyg.2014.00021.

Goodale L. Opportunities for agency in domestic horses: Applying the behavioural domain to increase equine welfare. Animal Welfare 2026;35:e26. https://doi.org/10.1017/awf.2026.10085.

Browning H, Veit W. Animal welfare, agency, and animal–computer interaction. Animals 2025;15:219. https://doi.org/10.3390/ani15020219.

Rust K, Clegg I, Fernandez EJ. The voice of choice: a scoping review of choice-based animal welfare studies. Applied Animal Behaviour Science 2024;275:106270. https://doi.org/10.1016/j.applanim.2024.106270.

Englund MD, Cronin KA. Choice, control, and animal welfare: definitions and essential inquiries to advance animal welfare science. Frontiers in Veterinary Science 2023;10:1250251. https://doi.org/10.3389/fvets.2023.1250251.

Bishop MJ, Vozzo ML, Mayer-Pinto M, Dafforn KA. Complexity–biodiversity relationships on marine urban structures: reintroducing habitat heterogeneity through eco-engineering. Philosophical Transactions of the Royal Society B 2022;377:20210393. https://doi.org/10.1098/rstb.2021.0393.

Riva F, Fahrig L. The disproportionately high value of small patches for biodiversity conservation. Conservation Letters 2022;15:e12881. https://doi.org/10.1111/conl.12881.

Furtado T, King M, Perkins E, McGowan C, Chubbock S, Hannelly E, et al. An exploration of environmentally sustainable practices associated with alternative grazing management system use for horses, ponies, donkeys and mules in the UK. Animals 2022;12:151. https://doi.org/10.3390/ani12020151.

Wolframm IA, Heric L, Allen AM. Green treasures: Investigating the biodiversity potential of equine yards through the presence and quality of landscape features in the Netherlands. PLOS ONE 2024;19:e0301168. https://doi.org/10.1371/journal.pone.0301168.