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Accelerometers can be used to monitor animal behavior remotely, but validation is required for each species. Previously, we showed that accelerometer data in collars could be used to identify specific behaviors in African elephants Loxodonta africana, using complex analytical methods. Here, we show that simple methods can also be used to identify elephant activity levels and body orientation. Subjects were 6 African elephants: 3 at Disneyís Animal KingdomÆ, Florida, USA, and 3 in Samburu-Laikipia, Kenya. Each elephant wore a collar containing a tri-axial accelerometer positioned on top of the neck. Simultaneous video recordings allowed validation of accelerometer data against observed behavior. The standard deviation of the total acceleration was shown to be a valid measure of dynamic acceleration, differentiating activity levels associated with resting, feeding, bathing, walking, and rapid walking. The mean of the total acceleration was shown to be a valid measure of static acceleration, and indicated upright and recumbent orientations. Simulations showed how accuracy was affected by sample rate, number of axes examined, and analysis window lengths. Based on 34 continuous 24 h acceleration streams, the 6 elephants exhibited an average of 2.5 h of overnight recumbence associated with minimal movement, indicating sleep. Daily activity budgets exhibited periods of minimal activity (e.g. resting, 17%), low activity (e.g. feeding, 68%), medium activity (e.g. walking, 13%), and high activity (e.g. rapid walking, 2%). Kenyan elephants were slightly more active and exhibited less restful recumbence compared to zoo elephants. Accelerometers in elephant collars can detect activity levels that are associated with specific behaviors, and can detect body orientation as a proxy for sleep.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.anbehav.2004.08.018 Byline: G. Wittemyer, I. Douglas-Hamilton, W.M. Getz Abstract: In this paper, we investigate the formation and function of the multilevelled, fission-fusion social structure in a free-ranging African elephant, Loxodonta africana, population. We quantitatively identified the existence of four social tiers by using cluster analysis on individual association data. We assessed the effects of season and study period on social structuring and levels of cohesion within and among social units. We found that second-tier units, potentially the equivalent of the 'family', were stable across seasonal periods but the number of units increased as the study progressed and the population grew. It appears that these units were sufficiently small not to be influenced by ecologically related factors, such as resource competition, that might otherwise lead to them splitting. On the other hand, third- and fourth-tier units were significantly affected by season in a way that suggests a trade-off between ecological costs (e.g. from resource competition) and different social and ecological benefits (e.g. from predator defence, territoriality, knowledge sharing and rearing of young). Age structure also appeared to influence this multitiered social organization. The size of second-tier social units was significantly affected by the age of matriarchs: units lead by matriarchs likely to be grandmothers (i.e. females 35 years and older) were significantly larger than those lead by younger matriarchs. We present a conceptual framework for understanding the emergence of multiple-tier social structure from interactions driven by socioecological processes. This study is the first to use rigorous quantitative methods to statistically show the existence of four hierarchical tiers of social organization in a nonhuman animal. Additionally, our results elucidate the role that ecological processes play in producing complex social structures. Author Affiliation: (*) Department of Environmental Science, Policy and Management, University of California, Berkeley, U.S.A. (a ) Save the Elephants, Kenya (a ) Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, South Africa Article History: Received 17 June 2004; Revised 23 July 2004; Accepted 18 August 2004 Article Note: (miscellaneous) MS. number: A9821

Monitoring anthropogenic impacts on wildlife can be challenging, particularly when human activities affecting wildlife are cryptic. Using anti-predator behaviors as proxies for perceived pressure is appealing because of the relative ease with which they can be recorded and the presumed relationship between the threat of interest and a predator stimulus. However, behaviors are plastic and affected by factors unrelated to human activity. Consequently, it is critical to assess the relationship between behavioral indicators and their context before interpretation. In this study we used a combination of behavior, movement and demography from a threatened population of African elephants in northern Kenya to determine whether reaction to research vehicles was indicative of poaching pressure. We used mixed-effects models predicting reaction of elephants to observer vehicle approaches in which we treated individuals as random effects and included ecological, anthropogenic, spatial, social and demographic predictor variables. Contrary to our hypothesis, recorded levels of reactive behavior did not increase with poaching levels in either a population-level dataset or a data subset of individuals whose spatial behavior was precisely known via radio-tracking. Rather, primary productivity positively predicted reactive behavior in both datasets. This relationship was heightened by the presence of musth males in the radio-collar dataset. Reactivity was not related to the time since entering the protected areas, but increased among groups that spent less time in the protected areas. Inter-individual differences were apparent, suggesting the importance of inherent differences (e.g. personality) across groups. In our study, elephants plagued by a severe human threat did not react defensively to humans in another context, suggesting nuanced discrimination of threats. Our study demonstrates the caution that should be taken in designing studies that use behavioral indices to represent threat and contributes to a growing body of literature employing behavioral indicators to monitor wildlife populations of conservation concern. [ABSTRACT FROM AUTHOR]

Vocalizations often vary in structure within a species, from the individual to population level. Vocal differences among social groups and populations can provide insight into biological processes such as vocal learning and evolutionary divergence, with important conservation implications. As vocal learners of conservation concern, intraspecific vocal variation is of particular interest in elephants. We recorded calls from individuals in multiple, wild elephant social groups in two distinct Kenyan populations. We used machine learning to investigate vocal differentiation among individual callers, core groups, bond groups (collections of core groups) and populations. We found clear evidence for vocal distinctiveness at the individual and population level, and evidence for much subtler vocal differences among social groups. Social group membership was a better predictor of call similarity than genetic relatedness, suggesting that subtle vocal differences among social groups may be learned. Vocal divergence among populations and social groups has conservation implications for the effects of social disruption and translocation of elephants., Competing Interests: We declare we have no competing interests., (© 2024 The Author(s).)

Personal names are a universal feature of human language, yet few analogues exist in other species. While dolphins and parrots address conspecifics by imitating the calls of the addressee, human names are not imitations of the sounds typically made by the named individual. Labelling objects or individuals without relying on imitation of the sounds made by the referent radically expands the expressive power of language. Thus, if non-imitative name analogues were found in other species, this could have important implications for our understanding of language evolution. Here we present evidence that wild African elephants address one another with individually specific calls, probably without relying on imitation of the receiver. We used machine learning to demonstrate that the receiver of a call could be predicted from the call's acoustic structure, regardless of how similar the call was to the receiver's vocalizations. Moreover, elephants differentially responded to playbacks of calls originally addressed to them relative to calls addressed to a different individual. Our findings offer evidence for individual addressing of conspecifics in elephants. They further suggest that, unlike other non-human animals, elephants probably do not rely on imitation of the receiver's calls to address one another., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Understanding drivers of space use by African elephants is critical to their conservation and management, particularly given their large home-ranges, extensive resource requirements, ecological role as ecosystem engineers, involvement in human-elephant conflict and as a target species for ivory poaching. In this study we investigated resource selection by elephants inhabiting the Greater Mara Ecosystem in Southwestern Kenya in relation to three distinct but spatially contiguous management zones: (i) the government protected Maasai Mara National Reserve (ii) community-owned wildlife conservancies, and (iii) elephant range outside any formal wildlife protected area. We combined GPS tracking data from 49 elephants with spatial covariate information to compare elephant selection across these management zones using a hierarchical Bayesian framework, providing insight regarding how human activities structure elephant spatial behavior. We also contrasted differences in selection by zone across several data strata: sex, season and time-of-day. Our results showed that the strongest selection by elephants was for closed-canopy forest and the strongest avoidance was for open-cover, but that selection behavior varied significantly by management zone and selection for cover was accentuated in human-dominated areas. When contrasting selection parameters according to strata, variability in selection parameter values reduced along a protection gradient whereby elephants tended to behave more similarly (limited plasticity) in the human dominated, unprotected zone and more variably (greater plasticity) in the protected reserve. However, avoidance of slope was consistent across all zones. Differences in selection behavior was greatest between sexes, followed by time-of-day, then management zone and finally season (where seasonal selection showed the least differentiation of the contrasts assessed). By contrasting selection coefficients across strata, our analysis quantifies behavioural switching related to human presence and impact displayed by a cognitively advanced megaherbivore. Our study broadens the knowledge base about the movement ecology of African elephants and builds our capacity for both management and conservation., (© 2024. The Author(s).)

Artificial intelligence (AI) and machine learning (ML) present revolutionary opportunities to enhance our understanding of animal behaviour and conservation strategies. Using elephants, a crucial species in Africa and Asia's protected areas, as our focal point, we delve into the role of AI and ML in their conservation. Given the increasing amounts of data gathered from a variety of sensors like cameras, microphones, geophones, drones and satellites, the challenge lies in managing and interpreting this vast data. New AI and ML techniques offer solutions to streamline this process, helping us extract vital information that might otherwise be overlooked. This paper focuses on the different AI-driven monitoring methods and their potential for improving elephant conservation. Collaborative efforts between AI experts and ecological researchers are essential in leveraging these innovative technologies for enhanced wildlife conservation, setting a precedent for numerous other species.

COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals' 1-hour 95th percentile displacements declined by 12% and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.

Prolonged maternal care is vital to the well-being of many long-lived mammals. 1 The premature loss of maternal care, i.e., orphaning, can reduce offspring survival even after weaning is complete. 2-5 However, ecologists have not explicitly assessed how orphaning impacts population growth. We examined the impact of orphaning on population growth in a free-ranging African elephant population, using 19 years of individual-based demographic monitoring data. We compared orphan and nonorphan survival, performed a sensitivity analysis to understand how population growth responds to the probability of being orphaned and orphan survival, and investigated how sensitivity to these orphan parameters changed with level of poaching. Orphans were found to have lower survival compared to nonorphaned age mates, and population growth rate was negatively correlated with orphaning probability and positively correlated with orphan survival. This demonstrates that, in addition to its direct effects, adult elephant death indirectly decreases population growth through orphaning. Population growth rate's sensitivity to orphan survival increased for the analysis parameterized using only data from years of more poaching, indicating orphan survival is more important for population growth as orphaning increases. We conclude that orphaning substantively decreases population growth for elephants and should not be overlooked when quantifying the impacts of poaching. Moreover, we conclude that population models characterizing systems with extensive parental care benefit from explicitly incorporating orphan stages and encourage research into quantifying effects of orphaning in other social mammals of conservation concern., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Over the last two millennia, and at an accelerating pace, the African elephant (Loxodonta spp. Lin.) has been threatened by human activities across its range. 1-7 We investigate the correlates of elephant home range sizes across diverse biomes. Annual and 16-day elliptical time density home ranges 8 were calculated by using GPS tracking data collected from 229 African savannah and forest elephants (L. africana and L. cyclotis, respectively) between 1998 and 2013 at 19 sites representing bushveld, savannah, Sahel, and forest biomes. Our analysis considered the relationship between home range area and sex, species, vegetation productivity, tree cover, surface temperature, rainfall, water, slope, aggregate human influence, and protected area use. Irrespective of these environmental conditions, long-term annual ranges were overwhelmingly affected by human influence and protected area use. Only over shorter, 16-day periods did environmental factors, particularly water availability and vegetation productivity, become important in explaining space use. Our work highlights the degree to which the human footprint and existing protected areas now constrain the distribution of the world's largest terrestrial mammal. 9 , 10 A habitat suitability model, created by evaluating every square kilometer of Africa, predicts that 18,169,219 km 2 would be suitable as elephant habitat-62% of the continent. The current elephant distribution covers just 17% of this potential range of which 57.4% falls outside protected areas. To stem the continued extirpation and to secure the elephants' future, effective and expanded protected areas and improved capacity for coexistence across unprotected range are essential., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Long-term bio-logging has the potential to reveal how movements, and hence life-history trade-offs, vary over a lifetime. Reproductive tactics in particular may vary as individuals' trade-off current investment versus lifetime fitness. Male African savanna elephants (Loxodona africana) provide a telling example of balancing body growth with reproductive fitness due to the combination of indeterminate growth and strongly delineated periods of sexual activity (musth), which results in reproductive tactics that alter with age. Our study aims to quantify the extent to which male elephants alter their movement patterns, and hence energetic allocation, in relation to (a) reproductive state and (b) age, and (c) to determine whether musth periods can be detected directly from GPS tracking data. We used a combination of GPS tracking data and visual observations of 25 male elephants ranging in age from 20 to 52 years to examine the influence of reproductive state and age on movement. We then used a three-state hidden Markov model (HMM) to detect musth behaviour in a subset of sequential tracking data. Our results demonstrate that male elephants increased their daily mean speed and range size with age and in musth. Furthermore, non-musth speed decreased with age, presumably reflecting a shift towards energy acquisition during non-musth. Thus, despite similar speeds and marginally larger ranges between reproductive states at age 20, by age 50, males were travelling 2.0 times faster in a 3.5 times larger area in musth relative to non-musth. The distinctiveness of musth periods over age 35 meant the three-state HMM could automatically detect musth movement with high sensitivity and specificity, but could not for the younger age class. We show that male elephants increased their energetic allocation into reproduction with age as the probability of reproductive success increases. Given that older male elephants tend to be both the target of legal trophy hunting and illegal poaching, man-made interference could drive fundamental changes in elephant reproductive tactics. Bio-logging, as our study reveals, has the potential both to quantify mature elephant reproductive tactics remotely and to be used to institute proactive management strategies around the reproductive behaviour of this charismatic keystone species., (© 2019 The Authors Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.)

Repeated use of the same areas may benefit animals as they exploit familiar sites, leading to consistent home ranges over time that can span generations. Changing risk landscapes may reduce benefits associated with home range fidelity, however, and philopatric animals may alter movement in response to new pressures. Despite the importance of range changes to ecological and evolutionary processes, little tracking data have been collected over the long-term nor has range change been recorded in response to human pressures across generations. Here, we investigate the relationships between ecological, demographic and human variables and elephant ranging behaviour across generations using 16 years of tracking data from nine distinct female social groups in a population of elephants in northern Kenya that was heavily affected by ivory poaching during the latter half of the study. Nearly all groups-including those that did not experience loss of mature adults-exhibited a shift north over time, apparently in response to increased poaching in the southern extent of the study area. However, loss of mature adults appeared to be the primary indicator of range shifts and expansions, as generational turnover was a significant predictor of range size increases and range centroid shifts. Range expansions and northward shifts were associated with higher primary productivity and lower poached carcass densities, while westward shifts exhibited a trend to areas with higher values of primary productivity and higher poached carcass densities relative to former ranges. Together these results suggest a trade-off between resource access, mobility and safety. We discuss the relevance of these results to elephant conservation efforts and directions meriting further exploration in this disrupted society of a keystone species., (© 2018 The Author(s).)

Network (graph) theory is a popular analytical framework to characterize the structure and dynamics among discrete objects and is particularly effective at identifying critical hubs and patterns of connectivity. The identification of such attributes is a fundamental objective of animal movement research, yet network theory has rarely been applied directly to animal relocation data. We develop an approach that allows the analysis of movement data using network theory by defining occupied pixels as nodes and connection among these pixels as edges. We first quantify node-level (local) metrics and graph-level (system) metrics on simulated movement trajectories to assess the ability of these metrics to pull out known properties in movement paths. We then apply our framework to empirical data from African elephants (Loxodonta africana), giant Galapagos tortoises (Chelonoidis spp.), and mule deer (Odocoileous hemionus). Our results indicate that certain node-level metrics, namely degree, weight, and betweenness, perform well in capturing local patterns of space use, such as the definition of core areas and paths used for inter-patch movement. These metrics were generally applicable across data sets, indicating their robustness to assumptions structuring analysis or strategies of movement. Other metrics capture local patterns effectively, but were sensitive to specified graph properties, indicating case specific applications. Our analysis indicates that graph-level metrics are unlikely to outperform other approaches for the categorization of general movement strategies (central place foraging, migration, nomadism). By identifying critical nodes, our approach provides a robust quantitative framework to identify local properties of space use that can be used to evaluate the effect of the loss of specific nodes on range wide connectivity. Our network approach is intuitive, and can be implemented across imperfectly sampled or large-scale data sets efficiently, providing a framework for conservationists to analyze movement data. Functions created for the analyses are available within the R package moveNT., (© 2018 by the Ecological Society of America.)

Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission., (Copyright © 2018, The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)