Charlotte Lorand

• Rozier-Delgado, Pablo; Vonderscher, Mylène; Blervaque, Léo; Brivio, Francesca; Buuveibaatar, Bayarbaatar & Chamaillé-Jammes, Simon [Show all 28 contributors for this article] (2026). Evaluation of mammalian endurance using accelerometry in natura: bridging exercise physiology and ecology. Journal of Experimental Biology. ISSN 0022-0949. 229(7). doi: 10.1242/jeb.251129. Full text in Research Archive
• Lorand, Charlotte Muguette Renée; Mihoub, Jean Baptiste; Duriez, Olivier; Giraud, Léa; Lécuyer, Philippe & Descaves, Bruno [Show all 8 contributors for this article] (2025). Survival Remains High in Griffon Vultures 40 Years After Reintroduction. Animal Conservation. ISSN 1367-9430. doi: 10.1111/acv.70044. Full text in Research Archive Show summary

  The long-term success of conservation translocations not only relies on the survival and reproductive success of released individuals, but also on addressing challenges related to population expansion up to natural regulation, whether exceeding expected numbers, or hindered by environmental or anthropogenic changes over time. Using the 40-year dataset of intensive griffon vulture (Gyps fulvus ) monitoring since its reintroduction in French Grands Causses in 1981, we performed a multi-strata (multi-states and multi-events) mark-recapture analysis to estimate survival probabilities. We (1) integrated mark-loss and remarking events, (2) explored a variety of anthropic and environmental factors that may affect survival in this population, such as wind turbines, feeding stations or density dependence. Overall, the life histories of 1506 wild-born individuals were computed, yielding juvenile survival probabilities of 0.66 (95% CI = 0.605–0.707), immature survival probabilities of 0.91 (95% CI = 0.872–0.937) and adult probabilities of 0.94 (95% CI = 0.917–0.952). Even though founder individuals were released four decades ago, and the population has grown continuously ever since, no effect of density dependence or of potential anthropic threats was detected on survival. Beyond bringing another piece of evidence supporting the relevance of this translocation program, as well as the benefit of regular monitoring efforts over several decades, our findings illustrate the importance of considering the maximum carrying capacity once wildlife populations are restored. Questioning the number of individuals to be expected may indeed allow anticipating both adaptive monitoring and management strategies, and ultimately, ensure the long-term viability of restored populations.

• Lorand, Charlotte Muguette Renée; Bouet, Lea Charlotte Marie; Devineau, Olivier; Chimienti, Marianna; Evans, Alina & Callahan, Peggy [Show all 9 contributors for this article] (2025). A supervised model to identify wolf behavior from tri-axial acceleration. Animal Biotelemetry. 13. doi: 10.1186/s40317-025-00400-w. Full text in Research Archive Show summary

  Background In wildlife studies, animal behavior serves as a key indicator of the impact of environmental changes and anthropogenic disturbances. However, wild animals are elusive and traditional GPS studies only provide limited insight into their daily activities. To address this issue, behavior classification models have increasingly been used to detect specific behaviors in wildlife equipped with tri-axial accelerometers. Such models typically need to be trained on data from the target species. The present study focuses on developing a behavioral classification model tailored to the grey wolf (Canis lupus) and encompassing a variety of ecologically relevant behaviors. Methods We collected data from nine captive wolves equipped with collar-mounted tri-axial accelerometers recording continuous acceleration at 32 Hz (“fine-scale”) and averaged acceleration over 5-min intervals (“activity”). Using simultaneous video observations, we trained Random Forest models to classify wolf acceleration data into specific behaviors. We investigated the potential limits to the generalizability of these models to unlabeled data through individual-based cross-validation. Results We present: (1) a model classifying fine-scale acceleration data (32 Hz) into 12 distinct behaviors (lying, trotting, stationary, galloping, walking, chewing, sniffing, climbing, howling, shaking, digging and jumping) with a class recall of 0.77–0.99 (0.01–0.91 in cross-validation), (2) a model classifying activity data (5-min averages) into 3 behavior categories (static, locomotion and miscellaneous) with a class recall of 0.43–0.91 (0.39–0.92 in cross-validation). Although classification performance decreased following cross-validation, recall scores for lying, trotting, stationary, galloping, walking and chewing individual behaviors (as well as static and locomotion categories) remained above 0.6. Classification performance was consistently poorer for rare behaviors, which constituted less than 1.1% of the training dataset. Conclusions We demonstrate the use of collar-mounted accelerometer to distinguish between 12 behaviors and 3 behavior categories in captive wolves, at fine-scale (32 Hz) and averaged 5-min resolutions, respectively. We also discuss the generalizability of the two models to free-ranging settings. These models can be employed to support future behavioral studies examining questions such as conflict mitigation, wolf responses to human disturbances, or specific activity budgets.

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• Eriksen, Ane; Rozier-Delgado, Pablo; Lorand, Charlotte Muguette Renée; Devineau, Olivier; Nordli, Kristoffer & Loison, Anne [Show all 7 contributors for this article] (2025). Uncovering the triggers of wolf fatigue: From sports science to wolf energetics. Full text in Research Archive
• Lorand, Charlotte Muguette Renée; Eriksen, Ane; Devineau, Olivier; Chimienti, Marianna; Wikenros, Camilla & Sand, Håkan [Show all 8 contributors for this article] (2025). Close encounters with wolves: who's tiptoeing around whom? Full text in Research Archive
• Eriksen, Ane; Lorand, Charlotte Muguette Renée; Versluijs, Erik; Chimienti, Marianna; Devineau, Olivier & Bouet, Lea [Show all 10 contributors for this article] (2024). Studying wolf flight responses during experimental approaches using fine-scale GPS and accelerometer data. Full text in Research Archive
• Eriksen, Ane; Lorand, Charlotte Muguette Renée; Versluijs, Erik; Chimienti, Marianna; Devineau, Olivier & Bouet, Lea [Show all 10 contributors for this article] (2024). Eksperimentelle nærmøter med ulv – oppdatering og framtidige planer. Full text in Research Archive
• Lorand, Charlotte Muguette Renée; Eriksen, Ane; Devineau, Olivier; Bouet, Lea; Chimienti, Marianna & Wikenros, Camilla [Show all 9 contributors for this article] (2024). The secret lives of wolves: Predicting behaviors in wild wolves approached by humans, using collar-mounted accelerometers and a model calibrated in captivity. Full text in Research Archive
• Lorand, Charlotte Muguette Renée & Eriksen, Ane (2024). Short-term controlled disturbances - How to make them work for wolf-human coexistence. Full text in Research Archive

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