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English HM, Börger L, Kane A, Ciuti S. Advances in biologging can identify nuanced energetic costs and gains in predators. MOVEMENT ECOLOGY 2024; 12:7. [PMID: 38254232 PMCID: PMC10802026 DOI: 10.1186/s40462-024-00448-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 01/08/2024] [Indexed: 01/24/2024]
Abstract
Foraging is a key driver of animal movement patterns, with specific challenges for predators which must search for mobile prey. These patterns are increasingly impacted by global changes, principally in land use and climate. Understanding the degree of flexibility in predator foraging and social strategies is pertinent to wildlife conservation under global change, including potential top-down effects on wider ecosystems. Here we propose key future research directions to better understand foraging strategies and social flexibility in predators. In particular, rapid continued advances in biologging technology are helping to record and understand dynamic behavioural and movement responses of animals to environmental changes, and their energetic consequences. Data collection can be optimised by calibrating behavioural interpretation methods in captive settings and strategic tagging decisions within and between social groups. Importantly, many species' social systems are increasingly being found to be more flexible than originally described in the literature, which may be more readily detectable through biologging approaches than behavioural observation. Integrating the effects of the physical landscape and biotic interactions will be key to explaining and predicting animal movements and energetic balance in a changing world.
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Affiliation(s)
- Holly M English
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin, Ireland.
| | - Luca Börger
- Department of Biosciences, Swansea University, Swansea, UK
| | - Adam Kane
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin, Ireland
| | - Simone Ciuti
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin, Ireland
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Hanscom RJ, Hill JL, Patterson C, Marbach T, Sukumaran J, Higham TE, Clark RW. Cryptic behavior and activity cycles of a small mammal keystone species revealed through accelerometry: a case study of Merriam's kangaroo rats (Dipodomys merriami). MOVEMENT ECOLOGY 2023; 11:72. [PMID: 37919756 PMCID: PMC10621205 DOI: 10.1186/s40462-023-00433-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 10/18/2023] [Indexed: 11/04/2023]
Abstract
BACKGROUND Kangaroo rats are small mammals that are among the most abundant vertebrates in many terrestrial ecosystems in Western North America and are considered both keystone species and ecosystem engineers, providing numerous linkages between other species as both consumers and resources. However, there are challenges to studying the behavior and activity of these species due to the difficulty of observing large numbers of individuals that are small, secretive, and nocturnal. Our goal was to develop an integrated approach of miniaturized animal-borne accelerometry and radiotelemetry to classify the cryptic behavior and activity cycles of kangaroo rats and test hypotheses of how their behavior is influenced by light cycles, moonlight, and weather. METHODS We provide a proof-of-concept approach to effectively quantify behavioral patterns of small bodied (< 50 g), nocturnal, and terrestrial free-ranging mammals using large acceleration datasets by combining low-mass, miniaturized animal-borne accelerometers with radiotelemetry and advanced machine learning techniques. We developed a method of attachment and retrieval for deploying accelerometers, a non-disruptive method of gathering observational validation datasets for acceleration data on free-ranging nocturnal small mammals, and used these techniques on Merriam's kangaroo rats to analyze how behavioral patterns relate to abiotic factors. RESULTS We found that Merriam's kangaroo rats are only active during the nighttime phases of the diel cycle and are particularly active during later light phases of the night (i.e., late night, morning twilight, and dawn). We found no reduction in activity or foraging associated with moonlight, indicating that kangaroo rats are actually more lunarphilic than lunarphobic. We also found that kangaroo rats increased foraging effort on more humid nights, most likely as a mechanism to avoid cutaneous water loss. CONCLUSIONS Small mammals are often integral to ecosystem functionality, as many of these species are highly abundant ecosystem engineers driving linkages in energy flow and nutrient transfer across trophic levels. Our work represents the first continuous detailed quantitative description of fine-scale behavioral activity budgets in kangaroo rats, and lays out a general framework for how to use miniaturized biologging devices on small and nocturnal mammals to examine behavioral responses to environmental factors.
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Affiliation(s)
- Ryan J Hanscom
- Department of Biology, San Diego State University, San Diego, CA, USA.
- Department of Evolution, Ecology, and Organismal Biology, University of California, Riverside, CA, USA.
| | - Jessica L Hill
- Department of Biology, San Diego State University, San Diego, CA, USA
| | - Charlotte Patterson
- Department of Forestry and Wildlife Management, Inland Norway University of Applied Sciences, Koppang, Norway
| | - Tyler Marbach
- Department of Biology, San Diego State University, San Diego, CA, USA
| | - Jeet Sukumaran
- Department of Biology, San Diego State University, San Diego, CA, USA
| | - Timothy E Higham
- Department of Evolution, Ecology, and Organismal Biology, University of California, Riverside, CA, USA
| | - Rulon W Clark
- Department of Biology, San Diego State University, San Diego, CA, USA
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Shiratsuru S, Studd EK, Boutin S, Peers MJL, Majchrzak YN, Menzies AK, Derbyshire R, Jung TS, Krebs CJ, Boonstra R, Murray DL. When death comes: linking predator-prey activity patterns to timing of mortality to understand predation risk. Proc Biol Sci 2023; 290:20230661. [PMID: 37192667 PMCID: PMC10188243 DOI: 10.1098/rspb.2023.0661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 04/21/2023] [Indexed: 05/18/2023] Open
Abstract
The assumption that activity and foraging are risky for prey underlies many predator-prey theories and has led to the use of predator-prey activity overlap as a proxy of predation risk. However, the simultaneous measures of prey and predator activity along with timing of predation required to test this assumption have not been available. Here, we used accelerometry data on snowshoe hares (Lepus americanus) and Canada lynx (Lynx canadensis) to determine activity patterns of prey and predators and match these to precise timing of predation. Surprisingly we found that lynx kills of hares were as likely to occur during the day when hares were inactive as at night when hares were active. We also found that activity rates of hares were not related to the chance of predation at daily and weekly scales, whereas lynx activity rates positively affected the diel pattern of lynx predation on hares and their weekly kill rates of hares. Our findings suggest that predator-prey diel activity overlap may not always be a good proxy of predation risk, and highlight a need for examining the link between predation and spatio-temporal behaviour of predator and prey to improve our understanding of how predator-prey behavioural interactions drive predation risk.
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Affiliation(s)
- Shotaro Shiratsuru
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2R3
| | - Emily K. Studd
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2R3
- Department of Biological Sciences, Thompson Rivers University, Kamloops, British Columbia, Canada V2C 0B8
| | - Stan Boutin
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2R3
| | - Michael J. L. Peers
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2R3
| | - Yasmine N. Majchrzak
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2R3
| | - Allyson K. Menzies
- Department of Natural Resource Sciences, McGill University, St-Anne-de-Bellevue, Québec, Canada H9X 3V9
| | | | - Thomas S. Jung
- Department of Environment, Government of Yukon, Whitehorse, Yukon, Canada
- Department of Renewable Resources, University of Alberta, Edmonton, Alberta, Canada
| | - Charles J. Krebs
- Department of Zoology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Rudy Boonstra
- Department of Biological Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada
| | - Dennis L. Murray
- Department of Biology, Trent University, Peterborough, Ontario, Canada
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Masello JF, Rast W, Schumm YR, Metzger B, Quillfeldt P. Year-round behavioural time budgets of common woodpigeons inferred from acceleration data using machine learning. Behav Ecol Sociobiol 2023. [DOI: 10.1007/s00265-023-03306-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
Abstract
Abstract
Accelerometers capture rapid changes in animal motion, and the analysis of large quantities of such data using machine learning algorithms enables the inference of broad animal behaviour categories such as foraging, flying, and resting over long periods of time. We deployed GPS-GSM/GPRS trackers with tri-axial acceleration sensors on common woodpigeons (Columba palumbus) from Hesse, Germany (forest and urban birds) and from Lisbon, Portugal (urban park). We used three machine learning algorithms, Random Forest, Support Vector Machine, and Extreme Gradient Boosting, to classify the main behaviours of the birds, namely foraging, flying, and resting and calculated time budgets over the breeding and winter season. Woodpigeon time budgets varied between seasons, with more foraging time during the breeding season than in winter. Also, woodpigeons from different sites showed differences in the time invested in foraging. The proportion of time woodpigeons spent foraging was lowest in the forest habitat from Hesse, higher in the urban habitat of Hesse, and highest in the urban park in Lisbon. The time budgets we recorded contrast to previous findings in woodpigeons and reaffirm the importance of considering different populations to fully understand the behaviour and adaptation of a particular species to a particular environment. Furthermore, the differences in the time budgets of Woodpigeons from this study and previous ones might be related to environmental change and merit further attention and the future investigation of energy budgets.
Significance statement
In this study we took advantage of accelerometer technology and machine learning methods to investigate year-round behavioural time budgets of wild common woodpigeons (Columba palumbus). Our analysis focuses on identifying coarse-scale behaviours (foraging, flying, resting) using various machine learning algorithms. Woodpigeon time budgets varied between seasons and among sites. Particularly interesting is the result showing that urban woodpigeons spend more time foraging than forest conspecifics. Our study opens an opportunity to further investigate and understand how a successful bird species such as the woodpigeon copes with increasing environmental change and urbanisation. The increase in the proportion of time devoted to foraging might be one of the behavioural mechanisms involved but opens questions about the costs associated to such increase in terms of other important behaviours.
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Tobajas J, Díaz-Ruiz F. Fishing behavior in the red fox: Opportunistic-caching behavior or surplus killing? Ecology 2022; 103:e3814. [PMID: 35841191 PMCID: PMC10078576 DOI: 10.1002/ecy.3814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 06/02/2022] [Accepted: 06/13/2022] [Indexed: 11/11/2022]
Affiliation(s)
- Jorge Tobajas
- Departamento de Botánica, Ecología y Fisiología Vegetal, Universidad de Córdoba, Córdoba, Spain.,Instituto de Investigación en Recursos Cinegéticos (IREC), CSIC-UCLM-JCCM, Ronda de Toledo n° 12, 13071, Ciudad Real, Spain.,Biodiversity Research Institute (CSIC - Oviedo University - Principality of Asturias), University of Oviedo, Mieres, Spain
| | - Francisco Díaz-Ruiz
- Biogeography, Diversity, and Conservation Research Team, Dept. Biología Animal, Facultad de Ciencias, Universidad de Málaga, Málaga, Spain
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