@article {9919,
	title = {A benchmark for computational analysis of animal behavior, using animal-borne tags},
	journal = {Movement Ecology},
	volume = {12},
	year = {2024},
	month = {18/12/2024},
	pages = {1-22},
	keywords = {Accelerometers, animal behavior, Bio-loggers, Machine Learning, Self-supervised Learning, Time series},
	doi = {10.1186/s40462-024-00511-8},
	url = {https://doi.org/10.1186/s40462-024-00511-8},
	author = {Hoffman, Benjamin and Cusimano, Maddie and Baglione, Vittorio and Canestrari, Daniela and Chevallier, Damien and DeSantis, Dominic L. and Jeantet, Lor{\`e}ne and Ladds, Monique A. and Maekawa, Takuya and Mata-Silva, Vicente and Moreno-Gonz{\'a}lez, V{\'\i}ctor and Pagano, Anthony M. and Trapote, Eva and Vainio, Outi and Vehkaoja, Antti and Yoda, Ken and Zacarian, Katherine and Friedlaender, Ari}
}
@article {9524,
	title = {A benchmark for computational analysis of animal behavior, using animal-borne tags},
	journal = {arXiv},
	year = {2023},
	month = {05/2023},
	abstract = {Animal-borne sensors ({\textquoteleft}bio-loggers{\textquoteright}) can record a suite of kinematic and environmental data, which can elucidate animal ecophysiology and improve conservation efforts. Machine learning techniques are useful for interpreting the large amounts of data recorded by bio-loggers, but there exists no standard for comparing the different machine learning techniques in this domain. To address this, we present the Bio-logger Ethogram Benchmark (BEBE), a collection of datasets with behavioral annotations, standardized modeling tasks, and evaluation metrics. BEBE is to date the largest, most taxonomically diverse, publicly available benchmark of this type, and includes 1654 hours of data collected from 149 individuals across nine taxa. We evaluate the performance of ten different machine learning methods on BEBE, and identify key challenges to be addressed in future work. Datasets, models, and evaluation code are made publicly available at https://github.com/earthspecies/ BEBE, to enable community use of BEBE as a point of comparison in methods development.},
	keywords = {Accelerometers, animal behavior, Bio-loggers, Clustering, Machine Learning, Time series},
	author = {Benjamin Hoffman and Maddie Cusimano and Vittorio Baglione and Daniela Canestrari and Chevallier, Damien and Dominic L. DeSantis and Lor{\`e}ne Jeantet and Monique A. Ladds and Takuya Maekawa and Vicente Mata-Silva and V{\'\i}ctor Moreno-Gonz{\'a}lez and Eva Trapote and Outi Vainio and Antti Vehkaoja and Ken Yoda and Katherine Zacarian and Ari Friedlaender and Christian Rutz}
}
@article {6667,
	title = {Dynamics of particulate organic matter composition in coastal systems: A spatio-temporal study at multi-systems scale},
	journal = {Progress in Oceanography},
	volume = {156},
	year = {2017},
	pages = {221-239},
	abstract = {In coastal systems, the multiplicity of sources fueling the pool of particulate organic matter (POM) leads to divergent estimations of POM composition. Eleven systems (two littoral systems, eight embayments and semi-enclosed systems and one estuary) distributed along the three maritime fa{\c c}ades of France were studied for two to eight years in order to quantify the relative contribution of organic matter sources to the surface-water POM pool in coastal systems. This study was based on carbon and nitrogen elemental and isotopic ratios, used for running mixing models. The POM of the estuary is dominated by terrestrial material (93\% on average), whereas the POM of the other systems is dominated by phytoplankton (84\% on average). Nevertheless, for the latter systems, the POM composition varies in space, with (1) systems where POM is highly composed of phytoplankton (>=93\%), (2) systems characterized by a non-negligible contribution of benthic (8{\textendash}19\%) and/or river (7{\textendash}19\%) POM sources, and (3) the Mediterranean systems characterized by the contribution of diazotroph organisms (ca. 14\%). A continent-to-ocean gradient of river and/or benthic POM contribution is observed. Finally, time series reveal (1) seasonal variations of POM composition, (2) differences in seasonality between systems, and (3) an inshore-offshore gradient of seasonality within each system that were sampled at several stations. Spatial and seasonal patterns of POM composition are mainly due to local to regional processes such as hydrodynamics and sedimentary hydrodynamic (e.g. resuspension processes, changes in river flows, wind patterns influencing along-shore currents) but also due to the geomorphology of the systems (depth of the water column, distance to the shore). Future studies investigating the link between these forcings and POM composition would help to better understand the dynamics of POM composition in coastal systems. {\textcopyright} 2017 Elsevier Ltd},
	keywords = {bacterium, benthos, biogeochemistry, Biological materials, C and n stable isotopes, C:N ratio, Carbon, carbon isotope, Coastal systems, coastal zone, Fluid dynamics, France, geomorphology, Hydrodynamics, Isotopes, isotopic ratio, Mediterranean sea, Meta analysis, meta-analysis, Mixing, Mixing models, nitrogen isotope, Organic compounds, particulate organic matter, Particulate organic matters, Phytoplankton, prokaryote, Rivers, seasonality, spatiotemporal analysis, stable isotope, Surface water, Surface waters, terrestrial deposit, Time series},
	issn = {00796611},
	doi = {10.1016/j.pocean.2017.03.001},
	url = {https://www.sciencedirect.com/science/article/abs/pii/S0079661116301914},
	author = {Li{\'e}nart, Camilla and Savoye, Nicolas and Bozec, Yann and Elsa Breton and Conan, Pascal and David, Val{\'e}rie and Eric Feunteun and Karine Granger{\'e} and Kerherv{\'e}, P. and Lebreton, B. and S{\'e}bastien Lefebvre and St{\'e}phane L{\textquoteright}Helguen and Mousseau, Laure and Raimbault, P and Richard, P. and Riera, P. and Sauriau, P.-G. and Gauthier Schaal and Aubert, F. and Aubin, S. and Bichon, S. and Boinet, C. and Bourasseau, L. and Br{\'e}ret, M. and Caparros, J. and Cariou, T. and Charlier, K. and Claquin, P. and Vincent Cornille and Corre, A.-M. and Costes, L. and Crispi, O. and Muriel Crouvoisier and Czamanski, M. and Del Amo, Y. and Derriennic, H. and Dindinaud, F. and Durozier, M. and Hanquiez, V. and Antoine Nowaczyk and Devesa, J. and Ferreira, S. and Fornier, M. and Garcia, F. and Garcia, N. and Geslin, S. and Emilie Grossteffan and Gueux, A. and Guillaudeau, J. and Guillou, G. and Joly, O. and Lachauss{\'e}e, N. and Lafont, M. and Lamoureux, J. and Lecuyer, E. and Lehodey, J.-P. and Lemeille, D. and Leroux, C. and Mac{\'e}, E. and Maria, E. and Pineau, P. and Petit, F. and Pujo-Pay, M. and Rimelin-Maury, P. and Sultan, E.}
}
@article {5813,
	title = {{Global impacts of the 1980s regime shift}},
	journal = {Global Change Biology},
	volume = {22},
	year = {2016},
	abstract = {<p>{\textcopyright} 2016 John Wiley {\&amp;} Sons Ltd. Despite evidence from a number of Earth systems that abrupt temporal changes known as regime shifts are important, their nature, scale and mechanisms remain poorly documented and understood. Applying principal component analysis, change-point analysis and a sequential t-test analysis of regime shifts to 72 time series, we confirm that the 1980s regime shift represented a major change in the Earth{\textquoteright}s biophysical systems from the upper atmosphere to the depths of the ocean and from the Arctic to the Antarctic, and occurred at slightly different times around the world. Using historical climate model simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and statistical modelling of historical temperatures, we then demonstrate that this event was triggered by rapid global warming from anthropogenic plus natural forcing, the latter associated with the recovery from the El Chich{\'o}n volcanic eruption. The shift in temperature that occurred at this time is hypothesized as the main forcing for a cascade of abrupt environmental changes. Within the context of the last century or more, the 1980s event was unique in terms of its global scope and scale; our observed consequences imply that if unavoidable natural events such as major volcanic eruptions interact with anthropogenic warming unforeseen multiplier effects may occur.</p>
},
	keywords = {Climate, Earth systems, Global change, Regime shift, Statistical analysis, Time series, Volcanic forcing},
	issn = {13652486},
	doi = {10.1111/gcb.13106},
	author = {Philip Chris Reid and Renata E. Hari and Gr{\'e}gory Beaugrand and David M. Livingstone and Christoph Marty and Dietmar Straile and Jonathan Barichivich and Goberville, Eric and Rita Adrian and Yasuyuki Aono and Ross Brown and James Foster and Pavel Groisman and Pierre H{\'e}laou{\"e}t and Huang-Hsiung Hsu and Richard R Kirby and Jeff Knight and Alexandra Kraberg and Jianping Li and Tzu-Ting Lo and Ranga B. Myneni and Ryan P. North and Alan J. Pounds and Tim Sparks and Ren{\'e} St{\"u}bi and Yongjun Tian and Karen H. Wiltshire and Dong Xiao and Zaichun Zhu}
}
@article {6824,
	title = {Behavioural study of two hydrothermal crustacean decapods: Mirocaris fortunata and Segonzacia mesatlantica, from the Lucky Strike vent field (Mid-Atlantic Ridge)},
	journal = {Deep Sea Research Part II: Topical Studies in Oceanography},
	volume = {121},
	year = {2015},
	pages = {146 - 158},
	abstract = {Identifying the factors driving community dynamics in hydrothermal vent communities, and in particular biological interactions, is challenged by our ability to make direct observations and the difficulty to conduct experiments in those remote ecosystems. As a result, we have very limited knowledge on species׳ behaviour and interactions in these communities and how they in turn influence community dynamics. Interactions such as competition or predation significantly affect community structure in vent communities, and video time-series have successfully been used to gain insights in biological interactions and species behaviour, including responses to short-term changes in temperature or feeding strategies. In this study, we combined in situ and ex situ approaches to characterise the behaviour and interactions among two key species encountered along the Mid-Atlantic Ridge (MAR): the shrimp Mirocaris fortunata and the crab Segonzacia mesatlantica. In situ, species small-scale distribution, interactions and behaviour were studied using the TEMPO observatory module deployed on the seafloor at the base of the active Eiffel Tower edifice in the Lucky Strike vent field as part of the EMSO-A{\c c}ores MoMAR observatory. TEMPO sampled 2min of video four times a day from July 2011 to April 2012. One week of observations per month was used for {\textquoteleft}long-term{\textquoteright} variations, and a full video data set was analysed for January 2012. In addition, observations of crab and shrimp individuals maintained for the first time under controlled conditions in atmospheric pressure (classic tank) and pressurised (AbyssBox) aquaria allowed better characterisation and description of the different types of behaviour and interactions observed in nature. While the identified in situ spatial distribution pattern was stable over the nine months, both species displayed a significant preference for mussel bed and anhydrite substrata, and preferentially occupied the area located directly in the fluid flow axis. The aggregation behaviour of M. fortunata resulted in the occurrence of numerous intraspecific interactions mainly involving the use of two pairs of sensory organs (antenna/antennule) and fleeing behaviours when in contact or close to individuals of S. mesatlantica. The higher level of passiveness observed in the ex situ artificial environment compared to the in situ environment was attributed to the lack of stimulation related to low densities of congeners and/or of sympatric species compared to the natural environment and the absence of continuous food supply, as both species displayed a significant higher level of activity during feeding time. This result emphasises the role of food supply as a driver of species distribution and behaviour. Direct in situ observations using cameras deployed on deep-sea observatories, combined with experimental set-up in pressurised aquaria, will help investigators understand the factors influencing community dynamics and species biology at vents as well as their underlying mechanisms.},
	keywords = {32{\textdegree}16.3'W, 37{\textdegree}17'N, AbyssBox, Biological interactions, Deep-sea observatory, Eiffel Tower edifice, Experimental research, Feeding behaviour, Lucky Strike, Mid-Atlantic Ridge, Time series, Video imagery},
	issn = {0967-0645},
	doi = {https://doi.org/10.1016/j.dsr2.2015.04.008},
	url = {http://www.sciencedirect.com/science/article/pii/S0967064515001113},
	author = {Matabos Marjolaine and Cuvelier Daphn{\'e} and Brouard Johan and Bruce Shillito and Juliette Ravaux and Magali Zbinden and Barthelemy Dominique and Sarradin, Pierre-Marie and Sarrazin, Jozee}
}
