LiDAR reveals a preference for intermediate visibility by a forest-dwelling ungulate species.
fine-scale visibility
habitat selection
integrated step selection analysis
movement rate
red deer
viewshed
Journal
The Journal of animal ecology
ISSN: 1365-2656
Titre abrégé: J Anim Ecol
Pays: England
ID NLM: 0376574
Informations de publication
Date de publication:
07 2023
07 2023
Historique:
received:
03
04
2022
accepted:
21
10
2022
medline:
6
7
2023
pubmed:
23
11
2022
entrez:
22
11
2022
Statut:
ppublish
Résumé
Visibility (viewshed) plays a significant and diverse role in animals' behaviour and fitness. Understanding how visibility influences animal behaviour requires the measurement of habitat visibility at spatial scales commensurate to individual animal choices. However, measuring habitat visibility at a fine spatial scale over a landscape is a challenge, particularly in highly heterogeneous landscapes (e.g. forests). As a result, our ability to model the influence of fine-scale visibility on animal behaviour has been impeded or limited. In this study, we demonstrate the application of the concept of three-dimensional (3D) cumulative viewshed in the study of animal spatial behaviour at a landscape level. Specifically, we employed a newly described approach that combines terrestrial and airborne light detection and ranging (LiDAR) to measure fine-scale habitat visibility (3D cumulative viewshed) on a continuous scale in forested landscapes. We applied the LiDAR-derived visibility to investigate how visibility in forests affects the summer habitat selection and the movement of 20 GPS-collared female red deer Cervus elaphus in a temperate forest in Germany. We used integrated step selection analysis to determine whether red deer show any preference for fine-scale habitat visibility and whether visibility is related to the rate of movement of red deer. We found that red deer selected intermediate habitat visibility. Their preferred level of visibility during the day was substantially lower than that of night and twilight, whereas the preference was not significantly different between night and twilight. In addition, red deer moved faster in high-visibility areas, possibly mainly to avoid predation and anthropogenic risk. Furthermore, red deer moved most rapidly between locations in the twilight. For the first time, the preference for intermediate habitat visibility and the adaption of movement rate to fine-scale visibility by a forest-dwelling ungulate species at a landscape scale was revealed. The LiDAR technique used in this study offers fine-scale habitat visibility at the landscape level in forest ecosystems, which would be of broader interest in the fields of animal ecology and behaviour.
Identifiants
pubmed: 36413028
doi: 10.1111/1365-2656.13847
doi:
Banques de données
Dryad
['10.5061/dryad.15dv41p1d']
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1306-1319Informations de copyright
© 2022 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.
Références
Aben, J., Pellikka, P., Travis, J. M. J., & Parrini, F. (2018). A call for viewshed ecology: Advancing our understanding of the ecology of information through viewshed analysis. Methods in Ecology and Evolution, 9, 624-633.
Acebes, P., Malo, J. E., & Traba, J. (2013). Trade-offs between food availability and predation risk in desert environments: The case of polygynous monomorphic guanaco (Lama guanicoe). Journal of Arid Environments, 97, 136-142.
Adrados, C., Baltzinger, C., Janeau, G., & Pépin, D. (2008). Red deer Cervus elaphus resting place characteristics obtained from differential GPS data in a forest habitat. European Journal of Wildlife Research, 54(3), 487-494. https://doi.org/10.1007/s10344-008-0174-y
Alonso, J. C., Álvarez-Martínez, J. M., & Palacín, C. (2012). Leks in ground-displaying birds: Hotspots or safe places? Behavioral Ecology, 23, 491-501.
Altendorf, K. B., Laundré, J. W., López González, C. A., & Brown, J. S. (2001). Assessing effects of predation risk on foraging behavior of mule deer. Journal of Mammalogy, 82, 430-439.
Andersson, M., Wallander, J., & Isaksson, D. (2009). Predator perches: A visual search perspective. Functional Ecology, 23, 373-379.
Arenz, C. L., & Leger, D. W. (1997). Artificial visual obstruction, antipredator vigilance, and predator detection in the thirteen-lined ground squirrel (Spermophilus tridecemlineatus). Behaviour, 134, 1101-1114.
Avgar, T., Lele, S. R., Keim, J. L., & Boyce, M. S. (2017). Relative selection strength: Quantifying effect size in habitat-and step-selection inference. Ecology and Evolution, 7, 5322-5330.
Avgar, T., Potts, J. R., Lewis, M. A., & Boyce, M. S. (2016). Integrated step selection analysis: Bridging the gap between resource selection and animal movement. Methods in Ecology and Evolution, 7, 619-630.
Belotti, E., Weder, N., Bufka, L., Kaldhusdal, A., Küchenhoff, H., Seibold, H., Woelfing, B., & Heurich, M. (2015). Patterns of lynx predation at the interface between protected areas and multi-use landscapes in Central Europe. PLoS One, 10, e0138139.
Brooks, M. E., Kristensen, K., Van Benthem, K. J., Magnusson, A., Berg, C. W., Nielsen, A., Skaug, H. J., Machler, M., & Bolker, B. M. (2017). glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal, 9, 378-400.
Burrough, P. A., & McDonnell, R. A. (1998). Principles of geographical information systems (p. 346). Oxford University Press.
Cailleret, M., Heurich, M., & Bugmann, H. (2014). Reduction in browsing intensity may not compensate climate change effects on tree species composition in the Bavarian Forest National Park. Forest Ecology and Management, 328, 179-192.
Camp, M., Rachlow, J., Woods, B., Johnson, T., & Shipley, L. (2013). Examining functional components of cover: The relationship between concealment and visibility in shrub-steppe habitat. Ecosphere, 4, 1-14.
Camp, M. J., Rachlow, J. L., Woods, B. A., Johnson, T. R., & Shipley, L. A. (2012). When to run and when to hide: The influence of concealment, visibility, and proximity to refugia on perceptions of risk. Ethology, 118, 1010-1017.
Chassagneux, A., Calenge, C., Marchand, P., Richard, E., Guillaumat, E., Baubet, E., & Saïd, S. (2020). Should I stay or should I go? Determinants of immediate and delayed movement responses of female red deer (Cervus elaphus) to drive hunts. PLoS ONE, 15, e0228865.
Ciuti, S., Tripke, H., Antkowiak, P., Gonzalez, R. S., Dormann, C. F., & Heurich, M. (2018). An efficient method to exploit Li DAR data in animal ecology. Methods in Ecology and Evolution, 9, 893-904.
Coppes, J., Burghardt, F., Hagen, R., Suchant, R., & Braunisch, V. (2017). Human recreation affects spatio-temporal habitat use patterns in red deer (Cervus elaphus). PLoS ONE, 12, e0175134.
Davies, A. B., Cromsigt, J. P., Tambling, C. J., le Roux, E., Vaughn, N., Druce, D. J., Marneweck, D. G., & Asner, G. P. (2021). Environmental controls on African herbivore responses to landscapes of fear. Oikos, 130, 171-186.
Davies, A. B., Marneweck, D. G., Druce, D. J., & Asner, G. P. (2016). Den site selection, pack composition, and reproductive success in endangered African wild dogs. Behavioral Ecology, 27, 1869-1879.
Davies, A. B., Tambling, C. J., Kerley, G. I., & Asner, G. P. (2016). Effects of vegetation structure on the location of lion kill sites in African thicket. PLoS ONE, 11, e0149098.
D'eon, R. G., & Delparte, D. (2005). Effects of radio-collar position and orientation on GPS radio-collar performance, and the implications of PDOP in data screening. Journal of Applied Ecology, 42, 383-388.
Duchesne, T., Fortin, D., & Rivest, L.-P. (2015). Equivalence between step selection functions and biased correlated random walks for statistical inference on animal movement. PLoS ONE, 10, e0122947.
Dupke, C., Bonenfant, C., Reineking, B., Hable, R., Zeppenfeld, T., Ewald, M., & Heurich, M. (2017). Habitat selection by a large herbivore at multiple spatial and temporal scales is primarily governed by food resources. Ecography, 40, 1014-1027.
Embar, K., Kotler, B. P., & Mukherjee, S. (2011). Risk management in optimal foragers: The effect of sightlines and predator type on patch use, time allocation, and vigilance in gerbils. Oikos, 120, 1657-1666.
Ensing, E. P., Ciuti, S., de Wijs, F. A., Lentferink, D. H., Ten Hoedt, A., Boyce, M. S., & Hut, R. A. (2014). GPS based daily activity patterns in European red deer and north American elk (Cervus elaphus): Indication for a weak circadian clock in ungulates. PLoS ONE, 9, e106997.
Ewald, J., Braun, L., Zeppenfeld, T., Jehl, H., & Heurich, M. (2014). Estimating the distribution of forage mass for ungulates from vegetation plots in Bavarian Forest National Park. Tuexenia, 34, 53-70.
Ewald, M., Dupke, C., Heurich, M., Müller, J., & Reineking, B. (2014). LiDAR remote sensing of Forest structure and GPS telemetry data provide insights on winter habitat selection of European roe deer. Forests, 5, 1374-1390.
Fahse, L., & Heurich, M. (2011). Simulation and analysis of outbreaks of bark beetle infestations and their management at the stand level. Ecological Modelling, 222, 1833-1846.
Farmer, C. J., Person, D. K., & Bowyer, R. T. (2006). Risk factors and mortality of black-tailed deer in a managed forest landscape. The Journal of Wildlife Management, 70, 1403-1415.
Fieberg, J. R., Forester, J. D., Street, G. M., Johnson, D. H., ArchMiller, A. A., & Matthiopoulos, J. (2018). Used-habitat calibration plots: A new procedure for validating species distribution, resource selection, and step-selection models. Ecography, 41, 737-752.
Fieberg, J. R., Signer, J., Smith, B., & Avgar, T. (2021). A ‘how to’ guide for interpreting parameters in habitat-selection analyses. Journal of Animal Ecology, 90, 1027-1043.
Filla, M., Premier, J., Magg, N., Dupke, C., Khorozyan, I., Waltert, M., Bufka, L., & Heurich, M. (2017). Habitat selection by Eurasian lynx (Lynx lynx) is primarily driven by avoidance of human activity during day and prey availability during night. Ecology and Evolution, 7, 6367-6381.
Forester, J. D., Im, H. K., & Rathouz, P. J. (2009). Accounting for animal movement in estimation of resource selection functions: Sampling and data analysis. Ecology, 90, 3554-3565.
Fortin, D., Beyer, H. L., Boyce, M. S., Smith, D. W., Duchesne, T., & Mao, J. S. (2005). Wolves influence elk movements: Behavior shapes a trophic cascade in Yellowstone National Park. Ecology, 86, 1320-1330.
Fortin, D., Fortin, M.-E., Beyer, H. L., Duchesne, T., Courant, S., & Dancose, K. (2009). Group-size-mediated habitat selection and group fusion-fission dynamics of bison under predation risk. Ecology, 90, 2480-2490.
Fox, J., & Weisberg, S. (2018). An R companion to applied regression (3rd ed.). Sage publications.
Frair, J. L., Merrill, E. H., Visscher, D. R., Fortin, D., Beyer, H. L., & Morales, J. M. (2005). Scales of movement by elk (Cervus elaphus) in response to heterogeneity in forage resources and predation risk. Landscape Ecology, 20, 273-287.
Godvik, I. M. R., Loe, L. E., Vik, J. O., Veiberg, V., Langvatn, R., & Mysterud, A. (2009). Temporal scales, trade-offs, and functional responses in red deer habitat selection. Ecology, 90, 699-710.
Gower, C. N., Garrott, R. A., & White, P. (2008). Elk foraging behavior: Does predation risk reduce time for food acquisition? Terrestrial Ecology, 3, 423-450.
Green, R. A., & Bear, G. D. (1990). Seasonal cycles and daily activity patterns of Rocky Mountain elk. The Journal of Wildlife Management, 54, 272-279.
Halofsky, J. S., & Ripple, W. J. (2008). Fine-scale predation risk on elk after wolf reintroduction in Yellowstone National Park, USA. Oecologia, 155, 869-877.
Higgins, K. F., Oldemeyer, J., Jenkins, K., Clambey, G., & Harlow, R. (1996). Vegetation sampling and Measurement. Research and Management Techniques for Wildlife and Habitats, 5, 567-591.
Hopcraft, J. G. C., Sinclair, A. R. E., & Packer, C. (2005). Planning for success: Serengeti lions seek prey accessibility rather than abundance. Journal of Animal Ecology, 74, 559-566.
Jarnemo, A., & Wikenros, C. (2014). Movement pattern of red deer during drive hunts in Sweden. European Journal of Wildlife Research, 60, 77-84.
Johnson, B. K., Kern, J. W., Wisdom, M. J., Findholt, S. L., & Kie, J. G. (2000). Resource selection and spatial separation of mule deer and elk during spring. The Journal of Wildlife Management, 64, 685-697.
Johnson, D. H. (1980). The comparison of usage and availability measurements for evaluating resource preference. Ecology, 61, 65-71.
Kuijper, D. P., Bubnicki, J. W., Churski, M., Mols, B., & Van Hooft, P. (2015). Context dependence of risk effects: Wolves and tree logs create patches of fear in an old-growth forest. Behavioral Ecology, 26, 1558-1568.
Lecigne, B., Eitel, J. U., & Rachlow, J. L. (2020). viewshed3d: An r package for quantifying 3D visibility using terrestrial lidar data. Methods in Ecology and Evolution, 11, 733-738.
Lima, S. L., & Dill, L. M. (1990). Behavioral decisions made under the risk of predation: A review and prospectus. Canadian Journal of Zoology, 68, 619-640.
Loarie, S. R., Tambling, C. J., & Asner, G. P. (2013). Lion hunting behaviour and vegetation structure in an African savanna. Animal Behaviour, 85, 899-906.
Lone, K., Loe, L. E., Gobakken, T., Linnell, J. D., Odden, J., Remmen, J., & Mysterud, A. (2014). Living and dying in a multi-predator landscape of fear: Roe deer are squeezed by contrasting pattern of predation risk imposed by lynx and humans. Oikos, 123, 641-651.
Lone, K., Loe, L. E., Meisingset, E. L., Stamnes, I., & Mysterud, A. (2015). An adaptive behavioural response to hunting: Surviving male red deer shift habitat at the onset of the hunting season. Animal Behaviour, 102, 127-138.
Moll, R. J., Redilla, K. M., Mudumba, T., Muneza, A. B., Gray, S. M., Abade, L., Hayward, M. W., Millspaugh, J. J., & Montgomery, R. A. (2017). The many faces of fear: A synthesis of the methodological variation in characterizing predation risk. Journal of Animal Ecology, 86, 749-765.
Möst, L., Hothorn, T., Müller, J., & Heurich, M. (2015). Creating a landscape of management: Unintended effects on the variation of browsing pressure in a national park. Forest Ecology and Management, 338, 46-56.
Muff, S., Signer, J., & Fieberg, J. (2020). Accounting for individual-specific variation in habitat-selection studies: Efficient estimation of mixed-effects models using Bayesian or frequentist computation. Journal of Animal Ecology, 89, 80-92.
Mysterud, A., & Østbye, E. (1999). Cover as a habitat element for temperate ungulates: Effects on habitat selection and demography. Wildlife Society Bulletin, 27, 385-394.
Mysterud, A., Vike, B. K., Meisingset, E. L., & Rivrud, I. M. (2017). The role of landscape characteristics for forage maturation and nutritional benefits of migration in red deer. Ecology and Evolution, 7, 4448-4455.
Norum, J. K., Lone, K., Linnell, J. D., Odden, J., Loe, L. E., & Mysterud, A. (2015). Landscape of risk to roe deer imposed by lynx and different human hunting tactics. European Journal of Wildlife Research, 61, 831-840.
O'brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & Quantity, 41, 673-690.
Oeser, J., Heurich, M., Senf, C., Pflugmacher, D., & Kuemmerle, T. (2021). Satellite-based habitat monitoring reveals long-term dynamics of deer habitat in response to forest disturbances. Ecological Applications, 31, e2269.
Olsoy, P. J., Forbey, J. S., Rachlow, J. L., Nobler, J. D., Glenn, N. F., & Shipley, L. A. (2014). Fearscapes: Mapping functional properties of cover for prey with terrestrial LiDAR. Bioscience, 65, 74-80.
Proffitt, K. M., Grigg, J. L., Hamlin, K. L., & Garrott, R. A. (2009). Contrasting effects of wolves and human hunters on elk behavioral responses to predation risk. The Journal of Wildlife Management, 73, 345-356.
Rearden, S. N., Anthony, R. G., & Johnson, B. K. (2011). Birth-site selection and predation risk of Rocky Mountain elk. Journal of Mammalogy, 92, 1118-1126.
Riley, S. J., DeGloria, S. D., & Elliot, R. (1999). Index that quantifies topographic heterogeneity. Intermountain Journal of Sciences, 5, 23-27.
Ripple, W. J., & Beschta, R. L. (2003). Wolf reintroduction, predation risk, and cottonwood recovery in Yellowstone National Park. Forest Ecology and Management, 184, 299-313.
Rivrud, I. M., Heurich, M., Krupczynski, P., Müller, J., & Mysterud, A. (2016). Green wave tracking by large herbivores: An experimental approach. Ecology, 97, 3547-3553.
Röder, J., Bässler, C., Brandl, R., Dvořak, L., Floren, A., Goßner, M. M., Gruppe, A., Jarzabek-Müller, A., Vojtech, O., & Wagner, C. (2010). Arthropod species richness in the Norway Spruce (Picea abies (L.) karst.) canopy along an elevation gradient. Forest Ecology and Management, 259, 1513-1521.
Salvatori, M., De Groeve, J., van Loon, E., De Baets, B., Morellet, N., Focardi, S., Bonnot, N., Gehr, B., Griggio, M., & Heurich, M. (2022). Day versus night use of forest by red and roe deer as determined by Corine Land Cover and Copernicus Tree Cover Density: Assessing use of geographic layers in movement ecology. Landscape Ecology, 37, 1453-1468.
Signer, J., Fieberg, J., & Avgar, T. (2019). Animal movement tools (amt): R package for managing tracking data and conducting habitat selection analyses. Ecology and Evolution, 9, 880-890.
Silveyra Gonzalez, R., Latifi, H., Weinacker, H., Dees, M., Koch, B., & Heurich, M. (2018). Integrating LiDAR and high-resolution imagery for object-based mapping of forest habitats in a heterogeneous temperate forest landscape. International Journal of Remote Sensing, 39, 8859-8884.
Stankowich, T., & Blumstein, D. T. (2005). Fear in animals: A meta-analysis and review of risk assessment. Proceedings of the Royal Society B: Biological Sciences, 272, 2627-2634.
Tandy, C. R. V. (1967). The isovist method of landscape survey. In H. C. Murray (Ed.), Methods of landscape analysis (pp. 9-10). UK: Landscape Research Group.
Wiens, J. A. (1989). Spatial scaling in ecology. Functional Ecology, 3, 385-397.
Zong, X., Wang, T., Skidmore, A. K., & Heurich, M. (2021a). Estimating fine-scale visibility in a temperate forest landscape using airborne laser scanning. International Journal of Applied Earth Observation and Geoinformation, 103, 102478.
Zong, X., Wang, T., Skidmore, A. K., & Heurich, M. (2021b). The impact of voxel size, forest type, and understory cover on visibility estimation in forests using terrestrial laser scanning. GIScience & Remote Sensing, 58(3), 1-17.
Zong, X., Wang, T., Skidmore, A., & Heurich, M. (2022). Data from: LiDAR reveals a preference for intermediate visibility by a forest-dwelling ungulate species. Dryad Digital Repository. https://doi.org/10.5061/dryad.15dv41p1d