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Conners MG, Green JA, Phillips RA, Orben RA, Cui C, Djurić PM, Heywood E, Vyssotski AL, Thorne LH. Dynamic soaring decouples dynamic body acceleration and energetics in albatrosses. J Exp Biol 2024; 227:jeb247431. [PMID: 39246116 DOI: 10.1242/jeb.247431] [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: 02/05/2024] [Accepted: 08/19/2024] [Indexed: 09/10/2024]
Abstract
Estimates of movement costs are essential for understanding energetic and life-history trade-offs. Although overall dynamic body acceleration (ODBA) derived from accelerometer data is widely used as a proxy for energy expenditure (EE) in free-ranging animals, its utility has not been tested in species that predominately use body rotations or exploit environmental energy for movement. We tested a suite of sensor-derived movement metrics as proxies for EE in two species of albatrosses, which routinely use dynamic soaring to extract energy from the wind to reduce movement costs. Birds were fitted with a combined heart-rate, accelerometer, magnetometer and GPS logger, and relationships between movement metrics and heart rate-derived V̇O2, an indirect measure of EE, were analyzed during different flight and activity modes. When birds were exclusively soaring, a metric derived from angular velocity on the yaw axis provided a useful proxy of EE. Thus, body rotations involved in dynamic soaring have clear energetic costs, albeit considerably lower than those of the muscle contractions required for flapping flight. We found that ODBA was not a useful proxy for EE in albatrosses when birds were exclusively soaring. As albatrosses spend much of their foraging trips soaring, ODBA alone was a poor predictor of EE in albatrosses. Despite the lower percentage of time flapping, the number of flaps was a useful metric when comparing EE across foraging trips. Our findings highlight that alternative metrics, beyond ODBA, may be required to estimate energy expenditure from inertial sensors in animals whose movements involve extensive body rotations.
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Affiliation(s)
- Melinda G Conners
- School of Marine and Atmospheric Sciences, Stony Brook University, NY 11794-5000, USA
- Western EcoSystems Technology, Inc., 415 West 17th Street, Cheyenne, WY 82001, USA
| | - Jonathan A Green
- School of Environmental Sciences, University of Liverpool, Liverpool L69 3GP, UK
| | - Richard A Phillips
- British Antarctic Survey, Natural Environment Research Council, High Cross, Madingley Road, Cambridge CB3 0ET, UK
| | - Rachael A Orben
- Department of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Hatfield Marine Science Center, 2030 SE Marine Science Dr., Newport, OR 97365, USA
| | - Chen Cui
- Department of Electrical and Computer Engineering, Stony Brook University, NY 11794-5000, USA
| | - Petar M Djurić
- Department of Electrical and Computer Engineering, Stony Brook University, NY 11794-5000, USA
| | - Eleanor Heywood
- School of Marine and Atmospheric Sciences, Stony Brook University, NY 11794-5000, USA
| | - Alexei L Vyssotski
- Institute of Neuroinformatics, University of Zurich and Swiss Federal Institute of Technology (ETH), Zurich 8057, Switzerland
| | - Lesley H Thorne
- School of Marine and Atmospheric Sciences, Stony Brook University, NY 11794-5000, USA
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2
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Zhao Y, Kirschenhofer T, Harvey M, Rainer G. Mediodorsal thalamus and ventral pallidum contribute to subcortical regulation of the default mode network. Commun Biol 2024; 7:891. [PMID: 39039239 PMCID: PMC11263694 DOI: 10.1038/s42003-024-06531-9] [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: 01/30/2024] [Accepted: 07/02/2024] [Indexed: 07/24/2024] Open
Abstract
Humans and other animals readily transition from externally to internally focused attention, and these transitions are accompanied by activation of the default mode network (DMN). The DMN was considered a cortical network, yet recent evidence suggests subcortical structures are also involved. We investigated the role of ventral pallidum (VP) and mediodorsal thalamus (MD) in DMN regulation in tree shrew, a close relative of primates. Electrophysiology and deep learning-based classification of behavioral states revealed gamma oscillations in VP and MD coordinated with gamma in anterior cingulate (AC) cortex during DMN states. Cross-frequency coupling between gamma and delta oscillations was higher during DMN than other behaviors, underscoring the engagement of MD, VP and AC. Our findings highlight the importance of VP and MD in DMN regulation, extend homologies in DMN regulation among mammals, and underline the importance of thalamus and basal forebrain to the regulation of DMN.
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Affiliation(s)
- Yilei Zhao
- Section of Medicine, Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland
| | - Tobias Kirschenhofer
- Section of Medicine, Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland
| | - Michael Harvey
- Section of Medicine, Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland
| | - Gregor Rainer
- Section of Medicine, Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland.
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3
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Ross TR, Thiemann GW, Kirschhoffer BJ, Kirschhoffer J, York G, Derocher AE, Johnson AC, Lunn NJ, McGeachy D, Trim V, Northrup JM. Telemetry without collars: performance of fur- and ear-mounted satellite tags for evaluating the movement and behaviour of polar bears. ANIMAL BIOTELEMETRY 2024; 12:18. [PMID: 39022453 PMCID: PMC11249465 DOI: 10.1186/s40317-024-00373-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 05/29/2024] [Indexed: 07/20/2024]
Abstract
The study of animal movement provides insights into underlying ecological processes and informs analyses of behaviour and resource use, which have implications for species management and conservation. The tools used to study animal movement have evolved over the past decades, allowing for data collection from a variety of species, including those living in remote environments. Satellite-linked radio and GPS collars have been used to study polar bear (Ursus maritimus) ecology and movements throughout the circumpolar Arctic for over 50 years. However, due to morphology and growth constraints, only adult female polar bears can be reliably collared. Collars have proven to be safe, but there has been opposition to their use, resulting in a deficiency in data across much of the species' range. To bolster knowledge of movement characteristics and behaviours for polar bears other than adult females, while also providing an alternative to collars, we tested the use of fur- and ear-mounted telemetry tags that can be affixed to polar bears of any sex and age. We tested three fur tag designs (SeaTrkr, tribrush and pentagon tags), which we affixed to 15 adult and 1 subadult male polar bears along the coast of Hudson Bay during August-September 2021-2022. Fur tags were compared with ear tags deployed on 42 subadult and adult male polar bears captured on the coast or the sea ice between 2016 and 2022. We used data from the tags to quantify the amount of time subadult and adult males spent resting versus traveling while on land. Our results show the three fur tag designs remained functional for shorter mean durations (SeaTrkr = 58 days; tribrush = 47 days; pentagon = 22 days) than ear tags (121 days), but positional error estimates were comparable among the Argos-equipped tags. The GPS/Iridium-equipped SeaTrkr fur tags provided higher resolution and more frequent location data. Combined, the tags provided sufficient data to model different behavioural states. Furthermore, as hypothesized, subadult and adult male polar bears spent the majority of their time resting while on land, increasing time spent traveling as temperatures cooled. Fur tags show promise as a short-term means of collecting movement data from free-ranging polar bears. Supplementary Information The online version contains supplementary material available at 10.1186/s40317-024-00373-2.
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Affiliation(s)
- Tyler R. Ross
- Department of Biology, York University, Toronto, ON Canada
| | - Gregory W. Thiemann
- Faculty of Environmental and Urban Change, York University, Toronto, ON Canada
| | | | | | - Geoff York
- Polar Bears International, Bozeman, MT USA
| | - Andrew E. Derocher
- Department of Biological Sciences, University of Alberta, Edmonton, AB Canada
| | - Amy C. Johnson
- Department of Biological Sciences, University of Alberta, Edmonton, AB Canada
- Ecofish Research Ltd., Courtenay, BC Canada
| | | | - David McGeachy
- Environment and Climate Change Canada, Edmonton, AB Canada
| | - Vicki Trim
- Department of Agriculture and Resource Development, Manitoba Sustainable Development, Thompson, MB Canada
| | - Joseph M. Northrup
- Ontario Ministry of Natural Resources and Forestry, Peterborough, ON Canada
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4
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Akeresola RA, Butler A, Jones EL, King R, Elvira V, Black J, Robertson G. Validating hidden Markov models for seabird behavioural inference. Ecol Evol 2024; 14:e11116. [PMID: 38440082 PMCID: PMC10911961 DOI: 10.1002/ece3.11116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 02/06/2024] [Accepted: 02/22/2024] [Indexed: 03/06/2024] Open
Abstract
Understanding animal movement and behaviour can aid spatial planning and inform conservation management. However, it is difficult to directly observe behaviours in remote and hostile terrain such as the marine environment. Different underlying states can be identified from telemetry data using hidden Markov models (HMMs). The inferred states are subsequently associated with different behaviours, using ecological knowledge of the species. However, the inferred behaviours are not typically validated due to difficulty obtaining 'ground truth' behavioural information. We investigate the accuracy of inferred behaviours by considering a unique data set provided by Joint Nature Conservation Committee. The data consist of simultaneous proxy movement tracks of the boat (defined as visual tracks as birds are followed by eye) and seabird behaviour obtained by observers on the boat. We demonstrate that visual tracking data is suitable for our study. Accuracy of HMMs ranging from 71% to 87% during chick-rearing and 54% to 70% during incubation was generally insensitive to model choice, even when AIC values varied substantially across different models. Finally, we show that for foraging, a state of primary interest for conservation purposes, identified missed foraging bouts lasted for only a few seconds. We conclude that HMMs fitted to tracking data have the potential to accurately identify important conservation-relevant behaviours, demonstrated by a comparison in which visual tracking data provide a 'gold standard' of manually classified behaviours to validate against. Confidence in using HMMs for behavioural inference should increase as a result of these findings, but future work is needed to assess the generalisability of the results, and we recommend that, wherever feasible, validation data be collected alongside GPS tracking data to validate model performance. This work has important implications for animal conservation, where the size and location of protected areas are often informed by behaviours identified using HMMs fitted to movement data.
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Affiliation(s)
- Rebecca A. Akeresola
- School of Mathematics and Maxwell Institute for Mathematical SciencesUniversity of EdinburghEdinburghUK
- Biomathematics & Statistics ScotlandEdinburghUK
| | - Adam Butler
- Biomathematics & Statistics ScotlandEdinburghUK
| | | | - Ruth King
- School of Mathematics and Maxwell Institute for Mathematical SciencesUniversity of EdinburghEdinburghUK
| | - Víctor Elvira
- School of Mathematics and Maxwell Institute for Mathematical SciencesUniversity of EdinburghEdinburghUK
| | - Julie Black
- Joint Nature Conservation CommitteeAberdeenUK
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Barbour N, Shillinger GL, Gurarie E, Hoover AL, Gaspar P, Temple-Boyer J, Candela T, Fagan WF, Bailey H. Incorporating multidimensional behavior into a risk management tool for a critically endangered and migratory species. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2023; 37:e14114. [PMID: 37204012 DOI: 10.1111/cobi.14114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 05/12/2023] [Accepted: 05/16/2023] [Indexed: 05/20/2023]
Abstract
Conservation of migratory species exhibiting wide-ranging and multidimensional behaviors is challenged by management efforts that only utilize horizontal movements or produce static spatial-temporal products. For the deep-diving, critically endangered eastern Pacific leatherback turtle, tools that predict where turtles have high risks of fisheries interactions are urgently needed to prevent further population decline. We incorporated horizontal-vertical movement model results with spatial-temporal kernel density estimates and threat data (gear-specific fishing) to develop monthly maps of spatial risk. Specifically, we applied multistate hidden Markov models to a biotelemetry data set (n = 28 leatherback tracks, 2004-2007). Tracks with dive information were used to characterize turtle behavior as belonging to 1 of 3 states (transiting, residential with mixed diving, and residential with deep diving). Recent fishing effort data from Global Fishing Watch were integrated with predicted behaviors and monthly space-use estimates to create maps of relative risk of turtle-fisheries interactions. Drifting (pelagic) longline fishing gear had the highest average monthly fishing effort in the study region, and risk indices showed this gear to also have the greatest potential for high-risk interactions with turtles in a residential, deep-diving behavioral state. Monthly relative risk surfaces for all gears and behaviors were added to South Pacific TurtleWatch (SPTW) (https://www.upwell.org/sptw), a dynamic management tool for this leatherback population. These modifications will refine SPTW's capability to provide important predictions of potential high-risk bycatch areas for turtles undertaking specific behaviors. Our results demonstrate how multidimensional movement data, spatial-temporal density estimates, and threat data can be used to create a unique conservation tool. These methods serve as a framework for incorporating behavior into similar tools for other aquatic, aerial, and terrestrial taxa with multidimensional movement behaviors.
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Affiliation(s)
- Nicole Barbour
- Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science, Solomons, Maryland, USA
- Department of Biology, University of Maryland, College Park, Maryland, USA
- Upwell, Monterey, California, USA
- Department of Environmental Biology, SUNY College of Environmental and Forest Sciences, Syracuse, New York, USA
| | - George L Shillinger
- Upwell, Monterey, California, USA
- Hopkins Marine Station, Stanford University, Pacific Grove, California, USA
- MigraMar, Bodega Bay, California, USA
| | - Eliezer Gurarie
- Department of Biology, University of Maryland, College Park, Maryland, USA
- Department of Environmental Biology, SUNY College of Environmental and Forest Sciences, Syracuse, New York, USA
| | | | | | | | - Tony Candela
- Upwell, Monterey, California, USA
- Mercator Ocean International, Toulouse, France
| | - William F Fagan
- Department of Biology, University of Maryland, College Park, Maryland, USA
| | - Helen Bailey
- Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science, Solomons, Maryland, USA
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6
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Angelakis N, Goldsworthy SD, Connell SD, Durante LM. A novel method for identifying fine-scale bottom-use in a benthic-foraging pinniped. MOVEMENT ECOLOGY 2023; 11:34. [PMID: 37296462 PMCID: PMC10257308 DOI: 10.1186/s40462-023-00386-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 04/16/2023] [Indexed: 06/12/2023]
Abstract
BACKGROUND For diving, marine predators, accelerometer and magnetometer data provides critical information on sub-surface foraging behaviours that cannot be identified from location or time-depth data. By measuring head movement and body orientation, accelerometers and magnetometers can help identify broad shifts in foraging movements, fine-scale habitat use and energy expenditure of terrestrial and marine species. Here, we use accelerometer and magnetometer data from tagged Australian sea lions and provide a new method to identify key benthic foraging areas. As Australian sea lions are listed as endangered by the IUCN and Australian legislation, identifying key areas for the species is vital to support targeted management of populations. METHODS Firstly, tri-axial magnetometer and accelerometer data from adult female Australian sea lions is used in conjunction with GPS and dive data to dead-reckon their three-dimensional foraging paths. We then isolate all benthic phases from their foraging trips and calculate a range of dive metrics to characterise their bottom usage. Finally, k-means cluster analysis is used to identify core benthic areas utilised by sea lions. Backwards stepwise regressions are then iteratively performed to identify the most parsimonious model for describing bottom usage and its included predictor variables. RESULTS Our results show distinct spatial partitioning in benthic habitat-use by Australian sea lions. This method has also identified individual differences in benthic habitat-use. Here, the application of high-resolution magnetometer/accelerometer data has helped reveal the tortuous foraging movements Australian sea lions use to exploit key benthic marine habitats and features. CONCLUSIONS This study has illustrated how magnetometer and accelerometer data can provide a fine-scale description of the underwater movement of diving species, beyond GPS and depth data alone, For endangered species like Australian sea lions, management of populations must be spatially targeted. Here, this method demonstrates a fine-scale analysis of benthic habitat-use which can help identify key areas for both marine and terrestrial species. Future integration of this method with concurrent habitat and prey data would further augment its power as a tool for understanding the foraging behaviours of species.
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Affiliation(s)
- Nathan Angelakis
- University of Adelaide, North Terrace, Adelaide, SA, 5000, Australia.
| | - Simon D Goldsworthy
- University of Adelaide, North Terrace, Adelaide, SA, 5000, Australia
- South Australian Research and Development Institute (SARDI) (Aquatic Sciences), 2 Hamra Avenue, West Beach, SA, 5024, Australia
| | - Sean D Connell
- University of Adelaide, North Terrace, Adelaide, SA, 5000, Australia
| | - Leonardo M Durante
- South Australian Research and Development Institute (SARDI) (Aquatic Sciences), 2 Hamra Avenue, West Beach, SA, 5024, Australia
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7
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Ehlman SM, Scherer U, Bierbach D, Francisco FA, Laskowski KL, Krause J, Wolf M. Leveraging big data to uncover the eco-evolutionary factors shaping behavioural development. Proc Biol Sci 2023; 290:20222115. [PMID: 36722081 PMCID: PMC9890127 DOI: 10.1098/rspb.2022.2115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Mapping the eco-evolutionary factors shaping the development of animals' behavioural phenotypes remains a great challenge. Recent advances in 'big behavioural data' research-the high-resolution tracking of individuals and the harnessing of that data with powerful analytical tools-have vastly improved our ability to measure and model developing behavioural phenotypes. Applied to the study of behavioural ontogeny, the unfolding of whole behavioural repertoires can be mapped in unprecedented detail with relative ease. This overcomes long-standing experimental bottlenecks and heralds a surge of studies that more finely define and explore behavioural-experiential trajectories across development. In this review, we first provide a brief guide to state-of-the-art approaches that allow the collection and analysis of high-resolution behavioural data across development. We then outline how such approaches can be used to address key issues regarding the ecological and evolutionary factors shaping behavioural development: developmental feedbacks between behaviour and underlying states, early life effects and behavioural transitions, and information integration across development.
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Affiliation(s)
- Sean M. Ehlman
- SCIoI Excellence Cluster, 10587 Berlin, Germany,Faculty of Life Sciences, Humboldt University, 10117 Berlin, Germany,Department of Fish Biology, Fisheries, and Aquaculture, Leibniz Institute of Freshwater Ecology and Inland Fisheries, 12587 Berlin, Germany
| | - Ulrike Scherer
- SCIoI Excellence Cluster, 10587 Berlin, Germany,Faculty of Life Sciences, Humboldt University, 10117 Berlin, Germany,Department of Fish Biology, Fisheries, and Aquaculture, Leibniz Institute of Freshwater Ecology and Inland Fisheries, 12587 Berlin, Germany
| | - David Bierbach
- SCIoI Excellence Cluster, 10587 Berlin, Germany,Faculty of Life Sciences, Humboldt University, 10117 Berlin, Germany,Department of Fish Biology, Fisheries, and Aquaculture, Leibniz Institute of Freshwater Ecology and Inland Fisheries, 12587 Berlin, Germany
| | - Fritz A. Francisco
- SCIoI Excellence Cluster, 10587 Berlin, Germany,Faculty of Life Sciences, Humboldt University, 10117 Berlin, Germany
| | - Kate L. Laskowski
- Department of Evolution and Ecology, University of California – Davis, Davis, CA 95616, USA
| | - Jens Krause
- SCIoI Excellence Cluster, 10587 Berlin, Germany,Faculty of Life Sciences, Humboldt University, 10117 Berlin, Germany,Department of Fish Biology, Fisheries, and Aquaculture, Leibniz Institute of Freshwater Ecology and Inland Fisheries, 12587 Berlin, Germany
| | - Max Wolf
- SCIoI Excellence Cluster, 10587 Berlin, Germany,Department of Fish Biology, Fisheries, and Aquaculture, Leibniz Institute of Freshwater Ecology and Inland Fisheries, 12587 Berlin, Germany
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8
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Carneiro APB, Dias MP, Oppel S, Pearmain EJ, Clark BL, Wood AG, Clavelle T, Phillips RA. Integrating immersion with
GPS
data improves behavioural classification for wandering albatrosses and shows scavenging behind fishing vessels mirrors natural foraging. Anim Conserv 2022. [DOI: 10.1111/acv.12768] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
| | - M P Dias
- BirdLife International Cambridge UK
- Centre for Ecology, Evolution and Environmental Changes, cE3c & Department of Animal Biology, Faculdade de Ciências Universidade de Lisboa Lisbon Portugal
| | - S Oppel
- Royal Society for the Protection of Birds The David Attenborough Building Cambridge UK
| | | | | | - A G Wood
- British Antarctic Survey Natural Environment Research Council Cambridge UK
| | - T Clavelle
- Global Fishing Watch Washington District of Columbia USA
| | - R A Phillips
- British Antarctic Survey Natural Environment Research Council Cambridge UK
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9
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Zekoll T, Waldherr M, Tessmar-Raible K. Characterization of tmt-opsin2 in Medaka Fish Provides Insight Into the Interplay of Light and Temperature for Behavioral Regulation. Front Physiol 2021; 12:726941. [PMID: 34744767 PMCID: PMC8569850 DOI: 10.3389/fphys.2021.726941] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 09/17/2021] [Indexed: 12/02/2022] Open
Abstract
One of the big challenges in the study of animal behavior is to combine molecular-level questions of functional genetics with meaningful combinations of environmental stimuli. Light and temperature are important external cues, influencing the behaviors of organisms. Thus, understanding the combined effect of light and temperature changes on wild-type vs. genetically modified animals is a first step to understand the role of individual genes in the ability of animals to cope with changing environments. Many behavioral traits can be extrapolated from behavioral tests performed from automated motion tracking combined with machine learning. Acquired datasets, typically complex and large, can be challenging for subsequent quantitative analyses. In this study, we investigate medaka behavior of tmt-opsin2 mutants vs. corresponding wild-types under different light and temperature conditions using automated tracking combined with a convolutional neuronal network and a Hidden Markov model-based approach. The temperatures in this study can occur in summer vs. late spring/early autumn in the natural habitat of medaka fish. Under summer-like temperature, tmt-opsin2 mutants did not exhibit changes in overall locomotion, consistent with previous observations. However, detailed analyses of fish position revealed that the tmt-opsin2 mutants spent more time in central locations of the dish, possibly because of decreased anxiety. Furthermore, a clear difference in location and overall movement was obvious between the mutant and wild-types under colder conditions. These data indicate a role of tmt-opsin2 in behavioral adjustment, at least in part possibly depending on the season.
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Affiliation(s)
- Theresa Zekoll
- Max Perutz Labs, University of Vienna, Vienna Biocenter, Vienna, Austria
- Research Platform “Rhythms of Life, ” University of Vienna, Vienna BioCenter, Vienna, Austria
| | - Monika Waldherr
- Max Perutz Labs, University of Vienna, Vienna Biocenter, Vienna, Austria
- Research Platform “Rhythms of Life, ” University of Vienna, Vienna BioCenter, Vienna, Austria
| | - Kristin Tessmar-Raible
- Max Perutz Labs, University of Vienna, Vienna Biocenter, Vienna, Austria
- Research Platform “Rhythms of Life, ” University of Vienna, Vienna BioCenter, Vienna, Austria
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