Movement reveals reproductive tactics in male elephants.

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.

Radiocarbon dating of seized ivory confirms rapid decline in African elephant populations and provides insight into illegal trade.

Carbon-14 measurements on 231 elephant ivory specimens from 14 large ivory seizures (≥0.5 ton) made between 2002 and 2014 show that most ivory (ca 90%) was derived from animals that had died less than 3 y before ivory was confiscated. This indicates that the assumption of recent elephant death for mortality estimates of African elephants is correct: Very little "old" ivory is included in large ivory shipments from Africa. We found only one specimen of the 231 analyzed to have a lag time longer than 6 y. Patterns of trade differ by regions: East African ivory, based on genetic assignments of geographic origin, has a much higher fraction of "rapid" transit than ivory originating in the Tridom region of Cameroon-Gabon-Congo. Carbon-14 is an important tool in understanding patterns of movement of illegal wildlife products.

Inter-generational change in African elephant range use is associated with poaching risk, primary productivity and adult mortality.

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.

Applying network theory to animal movements to identify properties of landscape space use.

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.

Beehive fences as a multidimensional conflict-mitigation tool for farmers coexisting with elephants.

Increasing habitat fragmentation and human population growth in Africa has resulted in an escalation in human-elephant conflict between small-scale farmers and free-ranging African elephants (Loxodonta Africana). In 2012 Kenya Wildlife Service (KWS) implemented the national 10-year Conservation and Management Strategy for the Elephant in Kenya, which includes an action aimed at testing whether beehive fences can be used to mitigate human-elephant conflict. From 2012 to 2015, we field-tested the efficacy of beehive fences to protect 10 0.4-ha farms next to Tsavo East National Park from elephants. We hung a series of beehives every 10 m around the boundary of each farm plot. The hives were linked with strong wire. After an initial pilot test with 2 farms, the remaining 8 of 10 beehive fences also contained 2-dimensional dummy hives between real beehives to help reduce the cost of the fence. Each trial plot had a neighboring control plot of the same size within the same farm. Of the 131 beehives deployed 88% were occupied at least once during the 3.5-year trial. Two hundred and fifty-three elephants, predominantly 20-45 years old entered the community farming area, typically during the crop- ripening season. Eighty percent of the elephants that approached the trial farms were kept out of the areas protected by the beehive fences, and elephants that broke a fence were in smaller than average groups. Beehive fences not only kept large groups of elephants from invading the farmland plots but the farmers also benefited socially and financially from the sale of 228 kg of elephant-friendly honey. As news of the success of the trial spread, a further 12 farmers requested to join the project, bringing the number of beehive fence protected farms to 22 and beehives to 297. This demonstrates positive adoption of beehive fences as a community mitigation tool. Understanding the response of elephants to the beehive fences, the seasonality of crop raiding and fence breaking, and the willingness of the community to engage with the mitigation method will help contribute to future management strategies for this high human-elephant conflict hotspot and other similar areas in Kenya.

Illegal killing for ivory drives global decline in African elephants.

Illegal wildlife trade has reached alarming levels globally, extirpating populations of commercially valuable species. As a driver of biodiversity loss, quantifying illegal harvest is essential for conservation and sociopolitical affairs but notoriously difficult. Here we combine field-based carcass monitoring with fine-scale demographic data from an intensively studied wild African elephant population in Samburu, Kenya, to partition mortality into natural and illegal causes. We then expand our analytical framework to model illegal killing rates and population trends of elephants at regional and continental scales using carcass data collected by a Convention on International Trade in Endangered Species program. At the intensively monitored site, illegal killing increased markedly after 2008 and was correlated strongly with the local black market ivory price and increased seizures of ivory destined for China. More broadly, results from application to continental data indicated illegal killing levels were unsustainable for the species between 2010 and 2012, peaking to ∼ 8% in 2011 which extrapolates to ∼ 40,000 elephants illegally killed and a probable species reduction of ∼ 3% that year. Preliminary data from 2013 indicate overharvesting continued. In contrast to the rest of Africa, our analysis corroborates that Central African forest elephants experienced decline throughout the last decade. These results provide the most comprehensive assessment of illegal ivory harvest to date and confirm that current ivory consumption is not sustainable. Further, our approach provides a powerful basis to determine cryptic mortality and gain understanding of the demography of at-risk species.

Bomb-curve radiocarbon measurement of recent biologic tissues and applications to wildlife forensics and stable isotope (paleo)ecology.

Above-ground thermonuclear weapons testing from 1952 through 1962 nearly doubled the concentration of radiocarbon ((14)C) in the atmosphere. As a result, organic material formed during or after this period may be radiocarbon-dated using the abrupt rise and steady fall of the atmospheric (14)C concentration known as the bomb-curve. We test the accuracy of accelerator mass spectrometry radiocarbon dating of 29 herbivore and plant tissues collected on known dates between 1905 and 2008 in East Africa. Herbivore samples include teeth, tusks, soft tissue, hair, and horn. Tissues formed after 1955 are dated to within 0.3-1.3 y of formation, depending on the tissue type, whereas tissues older than ca. 1955 have high age uncertainties (>17 y) due to the Suess effect. (14)C dating of tissues has applications to stable isotope (paleo)ecology and wildlife forensics. We use data from 41 additional samples to determine growth rates of tusks, molars, and hair, which improve interpretations of serial stable isotope data for (paleo)ecological studies. (14)C dating can also be used to calculate the time interval represented in periodic histological structures in dental tissues (i.e., perikymata), which in turn may be used as chronometers in fossil teeth. Bomb-curve (14)C dating of confiscated animal tissues (e.g., ivory statues) can be used to determine whether trade of the item is legal, because many Convention of International Trade of Endangered Species restrictions are based on the age of the tissue, and thus can serve as a powerful forensic tool to combat illegal trade in animal parts.

Novel opportunities for wildlife conservation and research with real-time monitoring.

The expansion of global communication networks and advances in animal-tracking technology make possible the real-time telemetry of positional data as recorded by animal-attached tracking units. When combined with continuous, algorithm-based analytical capability, unique opportunities emerge for applied ecological monitoring and wildlife conservation. We present here four broad approaches for algorithmic wildlife monitoring in real time--proximity, geofencing, movement rate, and immobility--designed to examine aspects of wildlife spatial activity and behavior not possible with conventional tracking systems. Application of these four routines to the real-time monitoring of 94 African elephants was made. We also provide details of our cloud-based monitoring system including infrastructure, data collection, and customized software for continuous tracking data analysis. We also highlight future directions of real-time collection and analysis of biological, physiological, and environmental information from wildlife to encourage further development of needed algorithms and monitoring technology. Real-time processing of remotely collected, animal biospatial data promises to open novel directions in ecological research, applied species monitoring, conservation programs, and public outreach and education.

Female African elephant rumbles differ between populations and sympatric social groups.

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.

African elephants address one another with individually specific name-like calls.

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.

Land use drives differential resource selection by African elephants in the Greater Mara Ecosystem, Kenya.

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.

Elephants and algorithms: a review of the current and future role of AI in elephant monitoring.

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.

Behavioral responses of terrestrial mammals to COVID-19 lockdowns.

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.

History of Animals using Isotope Records (HAIR): a 6-year dietary history of one family of African elephants.

The dietary and movement history of individual animals can be studied using stable isotope records in animal tissues, providing insight into long-term ecological dynamics and a species niche. We provide a 6-year history of elephant diet by examining tail hair collected from 4 elephants in the same social family unit in northern Kenya. Sequential measurements of carbon, nitrogen, and hydrogen isotope rations in hair provide a weekly record of diet and water resources. Carbon isotope ratios were well correlated with satellite-based measurements of the normalized difference vegetation index (NDVI) of the region occupied by the elephants as recorded by the global positioning system (GPS) movement record; the absolute amount of C(4) grass consumption is well correlated with the maximum value of NDVI during individual wet seasons. Changes in hydrogen isotope ratios coincided very closely in time with seasonal fluctuations in rainfall and NDVI whereas diet shifts to relatively high proportions of grass lagged seasonal increases in NDVI by approximately 2 weeks. The peak probability of conception in the population occurred approximately 3 weeks after peak grazing. Spatial and temporal patterns of resource use show that the only period of pure browsing by the focal elephants was located in an over-grazed, communally managed region outside the protected area. The ability to extract time-specific longitudinal records on animal diets, and therefore the ecological history of an organism and its environment, provides an avenue for understanding the impact of climate dynamics and land-use change on animal foraging behavior and habitat relations.

Inferring ecological and behavioral drivers of African elephant movement using a linear filtering approach.

Understanding the environmental factors influencing animal movements is fundamental to theoretical and applied research in the field of movement ecology. Studies relating fine-scale movement paths to spatiotemporally structured landscape data, such as vegetation productivity or human activity, are particularly lacking despite the obvious importance of such information to understanding drivers of animal movement. In part, this may be because few approaches provide the sophistication to characterize the complexity of movement behavior and relate it to diverse, varying environmental stimuli. We overcame this hurdle by applying, for the first time to an ecological question, a finite impulse-response signal-filtering approach to identify human and natural environmental drivers of movements of 13 free-ranging African elephants (Loxodonta africana) from distinct social groups collected over seven years. A minimum mean-square error (MMSE) estimation criterion allowed comparison of the predictive power of landscape and ecological model inputs. We showed that a filter combining vegetation dynamics, human and physical landscape features, and previous movement outperformed simpler filter structures, indicating the importance of both dynamic and static landscape features, as well as habit, on movement decisions taken by elephants. Elephant responses to vegetation productivity indices were not uniform in time or space, indicating that elephant foraging strategies are more complex than simply gravitation toward areas of high productivity. Predictions were most frequently inaccurate outside protected area boundaries near human settlements, suggesting that human activity disrupts typical elephant movement behavior. Successful management strategies at the human-elephant interface, therefore, are likely to be context specific and dynamic. Signal processing provides a promising approach for elucidating environmental factors that drive animal movements over large time and spatial scales.

Disentangling the effects of forage, social rank, and risk on movement autocorrelation of elephants using Fourier and wavelet analyses.

The internal state of an individual-as it relates to thirst, hunger, fear, or reproductive drive-can be inferred by referencing points on its movement path to external environmental and sociological variables. Using time-series approaches to characterize autocorrelative properties of step-length movements collated every 3 h for seven free-ranging African elephants, we examined the influence of social rank, predation risk, and seasonal variation in resource abundance on periodic properties of movement. The frequency domain methods of Fourier and wavelet analyses provide compact summaries of temporal autocorrelation and show both strong diurnal and seasonal based periodicities in the step-length time series. This autocorrelation is weaker during the wet season, indicating random movements are more common when ecological conditions are good. Periodograms of socially dominant individuals are consistent across seasons, whereas subordinate individuals show distinct differences diverging from that of dominants during the dry season. We link temporally localized statistical properties of movement to landscape features and find that diurnal movement correlation is more common within protected wildlife areas, and multiday movement correlations found among lower ranked individuals are typically outside of protected areas where predation risks are greatest. A frequency-related spatial analysis of movement-step lengths reveal that rest cycles related to the spatial distribution of critical resources (i.e., forage and water) are responsible for creating the observed patterns. Our approach generates unique information regarding the spatial-temporal interplay between environmental and individual characteristics, providing an original approach for understanding the movement ecology of individual animals and the spatial organization of animal populations.

Human footprint and protected areas shape elephant range across Africa.

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 ranges8 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 km2 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.

Poaching of African elephants indirectly decreases population growth through lowered orphan survival.

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.

Where sociality and relatedness diverge: the genetic basis for hierarchical social organization in African elephants.

Hierarchical properties characterize elephant fission-fusion social organization whereby stable groups of individuals coalesce into higher order groups or split in a predictable manner. This hierarchical complexity is rare among animals and, as such, an examination of the factors driving its emergence offers unique insight into the evolution of social behaviour. Investigation of the genetic basis for such social affiliation demonstrates that while the majority of core social groups (second-tier affiliates) are significantly related, this is not exclusively the case. As such, direct benefits received through membership of these groups appear to be salient to their formation and maintenance. Further analysis revealed that the majority of groups in the two higher social echelons (third and fourth tiers) are typically not significantly related. The majority of third-tier members are matrilocal, carrying the same mtDNA control region haplotype, while matrilocality among fourth-tier groups was slightly less than expected at random. Comparison of results to those from a less disturbed population suggests that human depredation, leading to social disruption, altered the genetic underpinning of social relations in the study population. These results suggest that inclusive fitness benefits may crystallize elephant hierarchical social structuring along genetic lines when populations are undisturbed. However, indirect benefits are not critical to the formation and maintenance of second-, third- or fourth-tier level bonds, indicating the importance of direct benefits in the emergence of complex, hierarchical social relations among elephants. Future directions and conservation implications are discussed.