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Frequency histogram of one-way migratory modelled net displacements for the 31 classified migrations.

Frequency histogram of one-way migratory modelled net displacements for the 31 classified migrations.

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Migration is an important, but threatened ecological process. Conserving migration requires the maintenance of functional connectivity across sufficiently large areas. Therefore, we need to know if, where and why species migrate. Elephants are highly mobile and can travel long distances but we do not know if they migrate. Here, we analysed the move...

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... characteristics varied between individuals (Figs 4, 5, Supplementary Information Table S1). One-way migration distances ranged from 20 to 249 km ( Fig. 5) with no clear pattern between sex or cluster. The longest migration took place in Etosha (migration ID 22) while the shortest migration took place in Chobe ( Fig. 3: migration ID 16). In total, 77% of all departures took place during November and January (Fig. 4). This pattern correlated with the onset of the wet season and the subsequent greening up of vegetation (Fig. 4). The duration of time elephants spent in their away migratory ranges also corresponded with the wet season for most migrations, except in six (migration ID 12, 20, 22, 23, 25, 28; Fig. 4). While departure dates were consistent, the dates elephants migrated back to their dry season ranges varied greatly but most returned before the end of the dry season (Fig. ...

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... Some results from the consultation with community game guards are not surprising, such as their observation that elephants move after rains to find fresh vegetation, and that they eat most types of vegetation in the dry season when food sources are scarce. For example, there has been much previous research in different countries on these aspects of elephant movements and behaviour (Viljoen, 1989;Loarie et al., 2009;Young et al., 2009;Owen-Smith and Chafota, 2012;Garstang et al., 2014;Purdon et al., 2018;Tsalyuk et al., 2019;Birkett et al., 2012). The responses from the game guards provide confidence in their local ecological knowledge, which, for these general points, supports the conclusions from wider research. ...
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The Northern Highlands of northwest Namibia are a particularly remote and arid landscape, where wildlife, habitats and local communities are increasingly at risk from future climate change events. There has previously been minimal research on the population of African savanna elephants (Loxodonta africana) in these Highlands. The Highlands are located just to the west of Etosha National Park. One potential factor influencing the movement of elephants from the Park into the Highlands is their food preferences. The aim of this study was to determine the preferred forage species for elephants in the Highlands. The study benefited from local ecological knowledge of community game guards, and extensive field patrols to assess the most preferred trees of elephants. Our findings indicate clear selection preference for African star chestnut (Sterculia africana), and Commiphora species such as blue-leaved corkwood (Commiphora glaucescens). These species grow on steep mountain slopes and elephants are climbing slopes to browse those trees. Our results indicate that some tree species are much less preferred, most of which tend to be located in valleys or lower slopes. This suggests that a major factor in the increase in elephant population in the Northern Highlands is the preferred vegetation available on the mountain slopes compared to the vegetation on the flat landscape of Etosha.
... Known drivers of elephant motility include internal factors like reproductive state, and anthropogenic factors like poaching and competition at man-made permanent watering holes, as well as environmental factors including rainfall and greening [1][2][3][4][5][6][7][8][9][10][11]. Seasonal trends in spatial behaviour of Loxodonta africana have been researched extensively throughout Africa [2][3][4][5][6][7][8][9][10][11] and some movement trends are shared by elephants across ranges. ...
... Known drivers of elephant motility include internal factors like reproductive state, and anthropogenic factors like poaching and competition at man-made permanent watering holes, as well as environmental factors including rainfall and greening [1][2][3][4][5][6][7][8][9][10][11]. Seasonal trends in spatial behaviour of Loxodonta africana have been researched extensively throughout Africa [2][3][4][5][6][7][8][9][10][11] and some movement trends are shared by elephants across ranges. For example, elephants generally have larger wet season ranges than dry season ranges [2][3][4][5][6][7][8][9][11][12][13][14]. ...
... Seasonal trends in spatial behaviour of Loxodonta africana have been researched extensively throughout Africa [2][3][4][5][6][7][8][9][10][11] and some movement trends are shared by elephants across ranges. For example, elephants generally have larger wet season ranges than dry season ranges [2][3][4][5][6][7][8][9][11][12][13][14]. Motility variations within and between populations have various suitable ecological explanations: a period without rainfall can (i) constrain movements to minimise energy expended and water lost [2], (ii)"tether" elephants to water sources [8], or conversely (iii) force elephants to cover greater areas to find sustenance [15]. ...
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Previous research indicates that African savanna elephants change their movements preceding or coincident with local rainfall and it has been suggested that they respond to thunder in remote storms–perhaps reading seismic cues. We therefore aimed to test if elephants in Northern Kenya adhere to distinct daytime movement states between the wet and dry periods, and whether their abrupt movement changes precede local wet periods in response to lightning strikes from a specific compass heading. In our study site, lightning to the North and East often preceded local rainfall and could possibly be used to anticipate local wet periods, but local rainfall appears a more likely trigger of behavioural change. While some abrupt movement changes occurred ahead of local wet periods, they were only particularly frequent shortly following the onset of wet periods. These findings do not concur with reports of Namibian elephants that generally changed their movement behaviour preceding local rainfall, and the additional exploration of individual behaviours in the present study likewise did not provide compelling evidence of a generic reliance on remote thunder cues by Northern-Kenyan elephants. Nonetheless, the GPS tracks of elephants indicated that daytime movement velocities differed between wet and dry periods. Specifically, elephants were generally in a slow-moving state during the day through wet periods, and in a fast-moving state during the day through dry periods. There is a further indication that some elephants compensated for slow daytime speeds by moving faster at night. This shift towards increased nocturnal activity may become more common with climate change and may slightly reduce elephant foraging efficiency. We conclude that climate change makes a strong case for studying elephant behaviours in response to environmental cues during the day and night, especially in dry-land study sites like Northern Kenya.
... The social network of male elephants is therefore occurring on a "landscape scale," encompassing extended interactions over long periods and large areas. This characteristic helps in evaluating a sociophysical model of movement, which is easiest when the spatial resolutions of movement data, environmental data, and social interactions are broadly similar (Birkett et al. 2012;Purdon et al. 2018). ...
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Despite extensive research into the behavioral ecology of free-ranging animal groups, questions remain about how group members integrate information about their physical and social surroundings. This is because a) tracking of multiple group members is limited to a few easily manageable species; and b) the tools to simultaneously quantify physical and social influences on an individual’s movement remain challenging, especially across large geographic scales. A relevant example of a widely ranging species with complex social structure and of conservation concern is the African savanna elephant. We evaluate highly synchronized GPS tracks from five male elephants in Etosha National Park in Namibia by incorporating their dynamic social landscape into an established resource selection model. The fitted model predicts movement patterns based simultaneously on the physical landscape (e.g., repeated visitation of waterholes) and the social landscape (e.g., avoidance of a dominant male). Combining the fitted models for multiple focal individuals produces landscape-dependent social networks that vary over space (e.g., with distance from a waterhole) and time (e.g., as the seasons change). The networks, especially around waterholes, are consistent with dominance patterns determined from previous behavioral studies. Models that combine physical landscape and social effects, based on remote tracking, can augment traditional methods for determining social structure from intensive behavioral observations. More broadly, these models will be essential to effective, in-situ conservation and management of wide-ranging social species in the face of anthropogenic disruptions to their physical surroundings and social connections.
... This study provides insights into the complex spatial dynamics of elephants within the CKGR and highlights its critical connectivity with the KAZA, one of the world's largest and most significant transboundary conservation landscapes (Kaszta et al., 2021;Osipova et al., 2018;Purdon et al., 2018;Zacarias and Loyola, 2018). The establishment of artificial water points within the CKGR has significantly altered traditional elephant movement patterns, prompting a shift toward more sedentary behaviour among male elephants in areas that were historically occupied only seasonally. ...
... Migration, defined as the repeated seasonal movement between two non-overlapping regions (Dingle & Drake, 2007), allows elephants to escape severe seasonal decline in resources. Elephants may employ an extensive continuum of movement behaviors that includes migration, highly variable home ranges, or resident behavior (Bartlam-Brooks et al., 2011;Purdon et al., 2018). Seasonal range fidelity occurs when an individual changes the size of its range while maintaining the core area of habitat use, consequently presenting relatively high range fidelity but with a change in the degree of range overlap (Damuth, 1981;Lindstedt et al., 1986). ...
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African savanna elephants are a highly mobile species that ranges widely across the diversity of ecosystems they inhabit. In xeric environments, elephant movement patterns are largely dictated by the availability of water and suitable forage resources, which can drive strong seasonal changes in their movement behavior. In this study, we analyzed a unique movement dataset from 43 collared elephants, collected over a period of 10 years, to assess the degree to which seasonal changes influences home range size of elephants in the semi‐arid, Laikipia‐Samburu ecosystem of northern Kenya. Auto‐correlated Kernel Density Estimation (AKDE) was used to estimate elephants' seasonal home range size. For each individual elephant, we also calculated seasonal home range shifts, as the distance between wet season home range centroids and dry season home range centroids. Core areas (50% AKDE isopleths) of all individual elephants ranged from 3 to 1743 km² whereas total home range sizes (the 95% AKDE isopleths) ranged between 15 and 10,677 km². Core areas and home range sizes were 67% and 61% larger, respectively, during the wet season than during the dry season. On average, the core area centroids for all elephants were 17 km away from the nearest river (range 0.2–150.3 km). Females had their core areas closer to the river than males (13.5 vs. 27.5 km). Females differed from males in their response to seasonal variation. Specifically, females tended to occupy areas farther from the river during the wet season, while males occupied areas further from the river during the dry season. Our study highlights how elephants adjust their space use seasonally, which can be incorporated into conservation area planning in the face of increased uncertainty in rainfall patterns due to climate change.
... Connectivity across our landscape was associated with different environmental determinants, e.g., primary productivity (B) and "ambient human population" distribution (C) In addition to scale and resolution, seasonality and sex are crucial drivers of elephant dispersal and land use patterns (Young et al. 2009b). Future studies could consider seasonal and sex-specific differences when predicting gene flow across the landscape by generating individually modeled landscape connections maps for males and females, and for wet and dry seasons (Young et al. 2009a;Purdon et al. 2018). Sex-and season-based landscape connections maps may be especially important for elephant connectivity mapping since dispersal is predominantly male-mediated (Nyakaana and Arctander 1999;Roca et al. 2005), and males typically have larger home ranges and disperse farther than females with young calves (Mole et al. 2016). ...
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Across Africa, space for conservation is sometimes limited to formally protected areas that have become progressively more isolated. There is a need for targeted conservation initiatives such as the demarcation of landscape connections, defined as areas that encompass environmental variables that promote the natural movement of individuals between populations, which can facilitate gene flow. Landscape connections can mitigate genetic isolation, genetic drift, and inbreeding, which can occur in isolated populations in protected areas. Promoting gene flow can reduce the risk of extirpation often associated with isolated populations. Here we develop and test models for identifying landscape connections among African savannah elephant (Loxodonta africana) populations by combining habitat suitability modeling with gene flow estimates across a large region including seven countries. We find a pronounced non-linear response to unsuitable habitat, consistent with previous studies showing that non-transformed habitat models are poor predictors of gene flow. We generated a landscape connections map that considers both suitable habitats based on telemetry occurrence data and gene flow estimated as the inverse of individual genetic distance, delineating areas that are important for maintaining elephant population connectivity. Our approach represents a novel framework for developing spatially and genetically informed conservation strategies for elephants and many other taxa distributed across heterogeneous and fragmented landscapes. Graphical abstract
... Giraffe 62 and elephant 63 do not typically move as far and as predictably as wildebeest and zebra, yet both species have large annual home ranges that exceed the boundaries of protected areas 45,62 . Savanna elephants are mixed feeders (grazing and browsing) and considered a facultative partially migratory species 64 whereas Masai giraffes are primarily browsers and are considered a resident species with seasonal movements 65 . Both species occur year-round in all of our study sites. ...
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In East Africa, community-based conservation models (CBCMs) have been established to support the conservation of wildlife in fragmented landscapes like the Tarangire Ecosystem, Tanzania. To assess how different management approaches maintained large herbivore populations, we conducted line distance surveys and estimated seasonal densities of elephant, giraffe, zebra, and wildebeest in six management units, including three CBCMs, two national parks (positive controls), and one area with little conservation interventions (negative control). Using a Monte-Carlo approach to propagate uncertainties from the density estimates and trend analysis, we analyzed the resulting time series (2011–2019). Densities of the target species were consistently low in the site with little conservation interventions. In contrast, densities of zebra and wildebeest in CBCMs were similar to national parks, providing evidence that CBCMs contributed to the stabilization of these migratory populations in the central part of the ecosystem. CBCMs also supported giraffe and elephant densities similar to those found in national parks. In contrast, the functional connectivity of Lake Manyara National Park has not been augmented by CBCMs. Our analysis suggests that CBCMs can effectively conserve large herbivores, and that maintaining connectivity through CBCMs should be prioritized.
... Partial migratory populations are composed of individuals that remain local throughout the year and individuals that migrate over long distances. Partial migration is ubiquitous in various taxa, including insects (Menz et al. 2019), amphibians (Grayson et al. 2011), fish (Espinoza et al. 2016), birds (Arnekleiv et al. 2022), and mammals (Purdon et al. 2018). Individuals of partially migratory populations respond with different migration strategies to the same environmental cues. ...
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Migration is a life-history trait that shapes individual-by-environment interactions, affecting fitness. Currently, many species are changing their migration strategies, stressing the need to identify and better understand the behavioral correlates of migration. As a partial migrant, the noctule bat, Nyctalus noctula, allows for rare intra-specific investigations of the potential behavioral causes (or consequences) of variation in migration. Here, we combined in-situ behavioral assays with stable isotope analyses to investigate whether spatial and acoustic responses to a roost-like novel environment correlate with migration strategy (local or distant). Given a migrant’s more frequent exposure to novel environments, we predicted migrants would enter a novel environment more quickly and show stronger spatial and acoustic exploration activity. However, individuals of local and distant origin did not differ in acoustic exploration (call activity per unit space), nor, contrasting to several bird studies, in spatial activity (number of chambers visited). Surprisingly, local individuals were more likely than migrants to enter the novel environment. Our findings suggest that small-scale exploration does not vary with migration, potentially because of similar selection pressures across migration strategies on small-scale exploration (e.g., exploration of roosts) as opposed to large-scale. Yet, our findings on the likelihood of entering a novel environment suggest that locals may be more risk-taking. Repeated measures would be necessary to determine if personality differences are underlying these responses. Our unique approach, combining behavioral assays with isotopic geolocation, gave us novel insight into an elusive taxon, highlighting the importance of studying behavioral correlates of migration across various taxa.
... These bioclimatic variables indicate that mastodons, like modern elephants, likely require large amounts of water. African Savanna Elephants (Loxodonta africana), which live in semi-arid savannas, will restrict their ranges to no more than a day's travel from a permanent water source during the dry season when drinking water becomes far more restricted (Blake, 2002;Purdon et al., 2018). African Savanna Elephants are known to migrate based on seasonal rainfall, and migration seems to be influenced by seasonality and precipitation as elephants search for new grazing areas and require large amounts of water to sustain themselves (Purdon et al., 2018). ...
... African Savanna Elephants (Loxodonta africana), which live in semi-arid savannas, will restrict their ranges to no more than a day's travel from a permanent water source during the dry season when drinking water becomes far more restricted (Blake, 2002;Purdon et al., 2018). African Savanna Elephants are known to migrate based on seasonal rainfall, and migration seems to be influenced by seasonality and precipitation as elephants search for new grazing areas and require large amounts of water to sustain themselves (Purdon et al., 2018). African Forest Elephants (Loxodonta cyclotis) live in the equatorial forests of the Congo Basin, which has abundant permanent drinking water sources even during the dry seasons (Blake, 2002). ...
... Despite their differences in habitats, all three species of elephants follow similar migration/foraging patterns due to rainfall and seasonality. During the dry season, elephants will remain near permanent sources of drinking water, but when rainfall increased elephants were able to expand into new areas (Sukumar, 1989;Blake, 2002;Purdon et al., 2018). Interglacial Period. ...
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The Ziegler Reservoir fossil site (ZRFS) in Colorado contains over 4000 mastodon bones that date from 140,000 to 100,000 years ago. At an elevation of ~2705 meters above sea level, ZRFS represents an alpine ecosystem dated to Marine Isotope Stage (MIS) 5. Formal descriptions of cheek teeth, mandibles, crania, and femora were completed. Statistical analyses of the upper and lower third molars, including a novel measurement of interloph(id) distances, indicate significant differences between ZRFS mastodons and Mammut pacificus, while falling within the ranges for Mammut americanum. This study agrees with the taxonomic assignment of ZRFS mastodons to Mammut americanum and not Mammut pacificus. Body mass estimates of ZRFS mastodons are between 3451 and 6244 kg, and a niche model indicates elevation and water availability influenced Mammut distribution during MIS 5. Incorporating ZRFS mastodons into large comparative datasets will contribute to ongoing research into Late Pleistocene Mammut.
... Two primary benefits of migration are increased forage opportunities and decreased seasonal predation risk [9,10]. Migrating to match available forage is common among mammals [9]; African elephants (Loxodonta Africana) [11], red deer (Cervus elaphus) [12], and bats (order Chiroptera) [13] demonstrate migratory behavior for foraging. Though more difficult to identify, migrating to reduce seasonal predation risk also occurs among mammals (e.g., baleen whales [parvorder Mysticeti] [14], and bighorn sheep [Ovis canadensis] [15]) [9]. ...
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Background Prey are more vulnerable during migration due to decreased familiarity with their surroundings and spatially concentrated movements. Predators may respond to increased prey vulnerability by shifting their ranges to match prey. Moose (Alces alces) and white-tailed deer (Odocoileus virginianus) are primary gray wolf (Canis lupus) prey and important subsistence species for Indigenous communities. We hypothesized wolves would increase use of ungulate migration corridors during migrations and predicted wolf distributions would overlap primary available prey. Methods We examined seasonal gray wolf, moose, and white-tailed deer movements on and near the Grand Portage Indian Reservation, Minnesota, USA. We analyzed GPS collar data during 2012–2021 using Brownian bridge movement models (BBMM) in Migration Mapper and mechanistic range shift analysis (MRSA) to estimate individual- and population-level occurrence distributions and determine the status and timing of range shifts. We estimated proportional overlap of wolf distributions with moose and deer distributions and tested for differences among seasons, prey populations, and wolf sex and pack affiliations. Results We identified a single migration corridor through which white-tailed deer synchronously departed in April and returned in October–November. Gray wolf distributions overlapped the deer migration corridor similarly year-round, but wolves altered within-range distributions seasonally corresponding to prey distributions. Seasonal wolf distributions had the greatest overlap with deer during fall migration (10 October–28 November) and greatest overlap with moose during summer (3 May–9 October). Conclusions Gray wolves did not increase their use of the white-tailed deer migration corridor but altered distributions within their territories in response to seasonal prey distributions. Greater overlap of wolves and white-tailed deer in fall may be due to greater predation success facilitated by asynchronous deer migration movements. Greater summer overlap between wolves and moose may be linked to moose calf vulnerability, American beaver (Castor canadensis) co-occurrence, and reduced deer abundance associated with migration. Our results suggest increases in predation pressure on deer in fall and moose in summer, which can inform Indigenous conservation efforts. We observed seasonal plasticity of wolf distributions suggestive of prey switching; that wolves did not exhibit migratory coupling was likely due to spatial constraints resulting from territoriality.