Literature DB >> 31654045

Longest terrestrial migrations and movements around the world.

Kyle Joly1, Eliezer Gurarie2, Mathew S Sorum3, Petra Kaczensky4,5, Matthew D Cameron6, Andrew F Jakes7, Bridget L Borg8, Dejid Nandintsetseg9,10, J Grant C Hopcraft11, Bayarbaatar Buuveibaatar12, Paul F Jones13, Thomas Mueller9,10, Chris Walzer5,14, Kirk A Olson12, John C Payne5,12,14, Adiya Yadamsuren15,16, Mark Hebblewhite17.   

Abstract

Long-distance terrestrial migrations are imperiled globally. We determined both round-trip migration distances (straight-line measurements between migratory end points) and total annual movement (sum of the distances between successive relocations over a year) for a suite of large mammals that had potential for long-distance movements to test which species displayed the longest of both. We found that caribou likely do exhibit the longest terrestrial migrations on the planet, but, over the course of a year, gray wolves move the most. Our results were consistent with the trophic-level based hypothesis that predators would move more than their prey. Herbivores in low productivity environments moved more than herbivores in more productive habitats. We also found that larger members of the same guild moved less than smaller members, supporting the 'gastro-centric' hypothesis. A better understanding of migration and movements of large mammals should aid in their conservation by helping delineate conservation area boundaries and determine priority corridors for protection to preserve connectivity. The magnitude of the migrations and movements we documented should also provide guidance on the scale of conservation efforts required and assist conservation planning across agency and even national boundaries.

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Year:  2019        PMID: 31654045      PMCID: PMC6814704          DOI: 10.1038/s41598-019-51884-5

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


Introduction

Long-distance animal migrations (repeated seasonal movement from 1 discrete area to another) are a widespread and highly conspicuous phenomenon in the natural world[1]. The evolutionary mechanisms behind migratory behavior are ecological and biogeographic, and reflect the fitness advantage of seasonally tracking habitats that vary in their distribution of resources, environmental conditions, intra- and inter-specific competition, predation, gene flow, and parasites[2-5]. Resources include high quality forage or surface water, with greater seasonality and variability in vegetative productivity providing impetus for herbivore migration and concomitant benefits of reduced exposure to predation[2,6,7]. Long-distance, terrestrial migrations are globally imperiled, especially for large mammals, and many have already been extinguished or are under threat[6,8,9]. Loss of migration is cited as a threat to declines of large herbivores worldwide[10] and once migratory patterns are lost, they may never resume or take decades for populations to relearn[11]. Habitat loss, fences, roads, and other types of human infrastructure and disturbance can act as semi-permeable or impermeable barriers to migration[6,8,12]. Major losses of roadless areas continue[13] and there are only about 42,000 patches of roadless areas > 100 km2 globally[14]. Further, climate change could alter species distributions and migration patterns[15]. Migratory herbivores affect forage biomass, patterns of nutrient diffusion across regions, ecosystem functioning, and predators, which in turn influence decomposers and primary producers[16-18]. Impairment of large herbivore migration can also reduce population sizes[19], with economic and societal impacts on the people and businesses that benefit from their persistence through harvest or tourism[6,20]. Two of the most well-known terrestrial migrations are undertaken by caribou (Rangifer tarandus) traveling between their winter ranges and calving grounds in the Arctic[21] and blue wildebeest (Connochaetes taurinus) moving between wet and dry seasonal ranges in the Serengeti ecosystem[22]. Caribou are often credited with exhibiting the longest terrestrial migrations on the planet without documentation, or by referencing Fancy et al.’s[21] 5055 km figure (e.g.[8,23]). However, this value was not a migration distance per se, but rather the total cumulative distance traveled in a year. Moreover, it was based on currently outdated technology with high positional error, making direct comparisons to current (e.g. GPS) technology problematic. This begs the interesting conservation and management questions: how is migration best measured and which migrations are the longest? Net squared displacement (NSD) could be used to determine migration distance (e.g.[24]), although it was designed to be a tool to parse behavioral states and the location of greatest displacement may not be a migratory end point (i.e., calving ground or winter range). For example, some Porcupine Herd caribou migrate along non-linear routes that wrap around the east edge of the Brooks Range mountains before turning northwest during their north-bound, spring migration[21]. Thus, maximum NSD does not necessarily occur at the calving grounds. Selection of the start (and end) location(s) have also been shown to greatly impact the results of the NSD-based method (e.g.[25-27]). A different metric, total cumulative annual distance (TCAD) traveled, which we define as the sum of the distances between successive positional locations over the course of a year, could also be used to assess total migration. Many have misinterpreted Fancy et al.’s[21] results in this manner. While TCAD is a simple, repeatable metric, it is an estimate of movement distance: all movements, not just migratory ones. Thus, it is meaningful and computable for any mobile animal - whether migratory or not. In fact, the TCAD of migratory and non-migratory individuals within the same population can be similar (e.g.[28]). We suggest that the straight-line, round-trip distance (RTD) between migratory end points is perhaps the most repeatable, versatile, and straight-forward means to measure migration distance. Furthermore, RTD can also be directly compared with historic studies that identify, for example, wintering and calving grounds without recourse to collar-based data. Much like TCAD, RTD varies among individuals within years, among years for the same individual, with changes in population size and density, with differences in seasonal range fidelity, and with new barriers to migration over time[21,29,30]. Reported and historical migration distances are, however, typically reported as a static measurement at the population level. The utility of RTD is constrained to species that display clear migratory patterns but is not applicable to nomadic and resident species[31]. Obviously, the importance of movement is not just limited to migration. Animals move to acquire food, resources and mates, mark and defend territories, evade predation and parasites, disperse to avoid strife or competition, or increase mating potential[32]. All of these behaviors lie largely outside the migration rubric[1]. How much a particular animal moves depends on its size, trophic level, forage/prey availability, own population density and that of its competition, and on the amount of variability in seasonality, among other factors. We hypothesize that TCAD will be greater for cursorial predators than their prey, as only a limited amount of energy is transferred between trophic levels[33] and thus these predators must range more widely to track and successfully secure their prey. In areas with greater seasonal variability, as once-abundant resources become scarce in 1 area, animals must move to another area[3]. Similarly, areas with low primary productivity and/or unpredictable resource availability may force animals to roam more or become nomadic[34]. Thus, we posit that TCAD for larger animals will be less than it will be for smaller animals of the same guild (e.g., grazers), as they can use more ubiquitous, lower-quality forage[35-37] and may be more resilient to environmental stochasticity due to larger body stores. However, like migration, movement in general has also been adversely affected by human activity and development. For example, Tucker et al.[38] documented that, in large animals, movements were reduced by 50–67% in areas of high human activity. Thus, we predict that TCAD will be greater in more remote, less impacted regions. However, in some cases anthropogenic barriers could force wide-ranging species to move further to find suitable crossing opportunities even in remote areas[39,40]. Our goals for this paper were to: 1) provide methods to consistently measure migration and movements so that direct comparisons can be made, 2) document the length of RTD migrations for a wide array of species that encompass different regions and ecosystems so that we could determine which species exhibit the longest terrestrial migrations, and 3) determine the TCAD traveled in a year for a suite of animals that varied in movement patterns (migratory, territorial, and nomadic), trophic level, and body size which also had potential to be among the most cursorial large mammals in the world. Lastly, we discuss our results in relation to our hypotheses about trophic levels, vegetative productivity, body size, and human population density in order to explore some of the underlying factors that influence migration and movements.

Material and Methods

Study area and literature review

The study area included terrestrial ecosystems worldwide (Fig. 1). We focused our efforts on areas with known long-distance (~300 km) large mammal migrations, a high degree of seasonality, low primary productivity, and/or little human footprint (e.g., the Arctic, central Asia, central and southern Africa, and the inter-mountain and northern great plains regions of North America). We began with existing studies (e.g.[6,8,34]) and then conducted Google Scholar searches using different species name and the term ‘migration’ or ‘movement’. The remaining datasets we collected ourselves.
Figure 1

Locations of the study areas of some of the longest, terrestrial migrations and movements in the world. Migration distances are shown as lines of a length equaling half the round-trip distance (RTD), roughly oriented in the direction of the migration for that species. Total annual movement distances (TCAD) are depicted as circles with circumferences equaling how far that species moves in a year. Both RTDs and TCADs are color-coded to match species icons and are scaled to be directly comparable to each other and to all species. They may not match the world backdrop in some locations due to projection issues. Areas with greater human density are shaded darker.

Locations of the study areas of some of the longest, terrestrial migrations and movements in the world. Migration distances are shown as lines of a length equaling half the round-trip distance (RTD), roughly oriented in the direction of the migration for that species. Total annual movement distances (TCAD) are depicted as circles with circumferences equaling how far that species moves in a year. Both RTDs and TCADs are color-coded to match species icons and are scaled to be directly comparable to each other and to all species. They may not match the world backdrop in some locations due to projection issues. Areas with greater human density are shaded darker.

Determining migration distances

We used the Euclidean (straight-line), round-trip distance (RTD) between end points to determine length (km) of migrations. The 2 most common sets of migratory end points were winter range and calving area (e.g., caribou) and wet and dry seasonal ranges (e.g., wildebeest). We used information found in studies identified during our literature review and with our own datasets. Mostly, the distances were taken exactly as reported in the literature or as double the estimated distances from the far extent of 1 end point (e.g., winter range) to the center of the other end point (e.g., calving area) based on provided range maps. For studies at the population rather than individual level, we measured from the distal portion of the winter (or dry season) range to the center of the calving (or wet season) range.

Determining total cumulative annual distances

We used GPS datasets that we collected, colleagues made available, or were generally available (e.g., publicly housed in Movebank; www.movebank.org) to estimate total annual distance moved (not as a precise measurement of absolute distance traveled). We defined this distance as the cumulative distance between successive GPS locations over the span of 365 days. Movement rate estimates, like TCAD, are strongly correlated with sample interval[7,41]. Therefore, where possible, we used relocations that were on 8-hour intervals to standardize according to this bias. For datasets collected at shorter intervals (e.g., 1, 2 or 4 hours), we subsampled the data to achieve an 8-hour interval when possible. When we could not obtain an 8-hour interval (e.g., 5- or 12-hour intervals), we determined the total annual distance moved and adjusted it by the negative relationship between movement rates and sampling interval determined for caribou by Joly[41] (see that study’s Fig. 3). For example, if a wildebeest collar collected data every 12 hours, its calculated total annual movement would be increased by 10%, whereas if it collected data every 5 hours, it would be decreased by 6% (instances noted in the tables). While the relationship between movement rate and sample interval likely varied by species and study area, our method provided an approximate method to standardize movements for direct comparisons. We also assess correlation between TCAD and primary productivity (http://silvis.forest.wisc.edu/data/dhis/)[42] and human population density (http://sedac.ciesin.columbia.edu/data/collection/gpw-v4/sets/browse) at the center of the range of each species.
Figure 3

Total cumulative annual distance (TCAD) traveled by herbivores in relation to their (a) mass (from Teitelbaum et al.[34] and the authors’ unpublished data; species listed from smallest to largest) and (b) primary productivity[42].

Compliance with guidelines and regulations

All capture, handling, and collaring of study species was in accordance with applicable guidelines and regulations. This includes permitting and institutional animal care and use committee review and approvals from: Alberta Sustainable Resource Development, Fish and Wildlife Research 11861, 16707, 20394, 059-08MHECS-120908, 059-09MHWB-12209; Mongolian Ministry of Nature, Environment and Tourism 5/4275, 5/5656, 6/4136, 6/5621; Montana Fish, Wildlife and Parks 11-2007; National Park Service 2010-1, AKR_GAAR_Gustine_GrizzlyBear_2014, AKR_DENA_Borg_GrayWolf_2016.A3, AKR_YUCH_Sorum_GrayWolf_2016.A3; Saskatchewan Ministry of Environment 09FW040; State of Alaska 07-11, 253217-3, 2012-031R; University of Veterinary Medicine Vienna ETK-15/03/2016; U. S. Geological Survey 2014-01.

Results

Migration distances

Caribou and reindeer (also Rangifer tarandus) dominated terrestrial migrations in terms of longest RTD (Table 1). They were the only species exceeding 1000 km, with the exception of a population of gray wolves (Canis lupus; 1016 km) in the Northwest Territories, Canada that were thought to track caribou and be migratory rather than territorial[43]. There were some outliers of note. First, Alerstam et al.[44] reported a 1200 km, one-way migration for Canadian caribou based on a personal communication. Based on our findings of the same species in the same region and geography of the area, we believe this is probably the round-trip distance. Second, Bekenov et al.[45] reported a 2400 km round-trip migration for 1 population of saiga antelope (Saiga tatarica) and 600–1200 km for 2 others.
Table 1

Maximum Euclidean (straight-line), round-trip distance (RTD, in km) for different long-distance, terrestrial mammalian migrations.

SpeciesLocationDistanceYear(s)References
CaribouBathurst Herd13501993–2012[50]
CaribouPorcupine Herd13501985–1987[21]
CaribouLeaf River Herd13001990–2010[59]
CaribouWestern Arctic Herd12502009–2017this study
CaribouQamanirjuaq Herd12501993–2012[50]
ReindeerTaymyr Peninsula1200<2003[60] in[6]
Gray wolfNorthwest Territories10161997–1999[43]
CaribouSouth Baffin Island8001984–1992[61]
Mule deerWyoming/Idaho7722017[62]
CaribouNelchina Herd7501999–2003[63]
Tibetan antelopeTibet700<2005[64]
Blue wildebeestSerengeti6501999–2000[22,65]
Mongolian gazelleMongolia6002002–2003[66]
Burchell’s zebraBotswana5882007–2013[67,68]
BisonAlberta483<1940[69]
PronghornAlberta/Saskatchewan4352003–2010[27]
White-eared kobSouth Sudan4001980–1982[3]
MooseNortheast Alaska3921995–1996[70]
PronghornMontana/Saskatchewan3152003–2010this study;[27]
PronghornWyoming300<2005[71]
Maximum Euclidean (straight-line), round-trip distance (RTD, in km) for different long-distance, terrestrial mammalian migrations.

Total annual movement distances

The animal that had the greatest TCAD (7247 km) was a male gray wolf from southwest Mongolia (Table 2). A territorial female wolf with pups from the same area traveled 5429 km in a year. An adult female gray wolf (without pups) from central Alaska moved 5630 km in a year and hunted caribou. An adult male whose pack hunted moose (Alces alces) moved 5554 km in a year. Gray wolves from east-central Alaska traveled similar, yet slightly less, distances: a young female gray wolf (without pups) traveled 5116 km in a year, was territorial, and hunted caribou during the winter months. A wolf from this same area dispersed shortly after capture and ended up in the Yukon Territory, Canada. Including the long-distance dispersal, this wolf moved 4686 km in a year. Wolves that primarily hunted moose from this region moved less (maximum = 3131 km/year) than wolves that primarily hunted caribou.
Table 2

Maximum total cumulative annual distance (TCAD, in km) traveled by different terrestrial mammals, at or adjusted (denoted with*) to an 8-hr GPS fix rate. Samples sizes (n) for both the number of individuals and animal-years of data, respectively, are also reported.

SpeciesLocationTCADnYear(s)References
Gray wolfSouthwest Mongolia72472, 32003–2005this study;[72]
KhulanSoutheast Mongolia61459, 182013–2015this study;[51]
Arctic fox*Northern Canada590312, 242008–2009[56]
Gray wolfCentral Alaska563016, 312012–2018this study
Gray wolfEast-central Alaska51167, 72017–2018this study
KhulanSouthwest Mongolia50677, 72007–2010this study;[52]
CaribouSouth Slave Beverly/Ahiak486862, 1422006–2014this study
CaribouWestern Arctic Herd4488103, 2502009–2017this study
CaribouSahtu Bluenose East380747, 912005–2014this study
Mongolian gazelleEastern Mongolia34645, 92014–2017this study
Burchell’s zebraBotswana34561, 12007–2008[73,74]
CaribouNorth Slave Bathurst Herd334128, 381996–2014this study
Bactrian camel*Southwest Mongolia28211, 12007–2008this study;[75]
Blue wildebeest*Serengeti28199, 132013–2015this study;[76]
Plains zebra*Serengeti23566, 62007–2008this study;[76]
Gray wolfAlberta21552, 22002–2004this study;[77]
Mongolian gazelle*Southern Mongolia20804, 42002–2003[66]
PronghornAlberta/Saskatchewan194138, 382006–2007this study
PronghornMontana/Saskatchewan179758, 582009–2010this study
Brown bearNorth-central Alaska132530, 562014–2016this study
ElkAlberta12004, 42003–2004this study;[78]
CaribouLittle Smoky Herd113136, 491999–2016this study;[79]
MooseAlberta/British Columbia7702, 22009–2010this study;[80]
MooseNorth-central Alaska75428, 282008–2012this study;[28]
Maximum total cumulative annual distance (TCAD, in km) traveled by different terrestrial mammals, at or adjusted (denoted with*) to an 8-hr GPS fix rate. Samples sizes (n) for both the number of individuals and animal-years of data, respectively, are also reported. Aside from gray wolves, nomadic khulan (Equus hemionus; also known as the Mongolian wild ass) exhibited greater TCAD than any other species we analyzed (Table 2). In southeast Mongolia, khulan moved as much as 6145 km/year and as much as 5067 km/year in southwest Mongolia. Caribou in northern North America moved as much as 4868 km/year. No other species besides wolves, khulan, arctic fox (Vulpes lagopus) and caribou had total annual movements >3500 km (Table 2). Mongolian gazelle (Procapra gutturosa) and Burchell’s zebra (Equus quagga) were just below this threshold. Some barren-ground caribou traveled more than 4 times the distance boreal caribou (e.g., Little Smoky Herd) did in a year (1131 km; Table 2). In southwest Mongolia, gray wolves moved more than khulan or wild Bactrian camels (Camelus bactrianus; Table 2; Fig. 2), which are among their prey species. In Alaska, gray wolves moved more than their primary prey of caribou or moose. Similarly, in Alberta, gray wolves moved more than elk (Cervus canadensis) or boreal caribou. In north-central Alaska, brown bear (Ursus arctos) also moved more than moose from the same region. Khulan moved more than camels in southwest Mongolia. This was true for sympatric (unfortunately these data had too many missed GPS fixes for us to report TCAD) and allopatric populations (Table 2, Fig. 3a). In Alberta, pronghorn (Antilocapra americana) moved more than elk and caribou, and, in Alaska, caribou moved more than moose. Caribou in northern Canada moved more than those in southern Canada, and pronghorn in Alberta/Saskatchewan moved more than those in Montana/Saskatchewan 400 km to the south. However, moose in northern Alaska had similar annual movement distances as those in southern Canada. TCAD of herbivores was significantly and negatively correlated with primary productivity (Fig. 3b; P < 0.01, F = 10.35, df = 17, R2 = 0.393). TCAD was not significantly correlated with human population density.
Figure 2

Total cumulative annual distance (TCAD) traveled by predators (red bars) versus their prey (blue bars) from southwestern Mongolia, Alaska and interior Canada.

Total cumulative annual distance (TCAD) traveled by predators (red bars) versus their prey (blue bars) from southwestern Mongolia, Alaska and interior Canada. Total cumulative annual distance (TCAD) traveled by herbivores in relation to their (a) mass (from Teitelbaum et al.[34] and the authors’ unpublished data; species listed from smallest to largest) and (b) primary productivity[42].

Discussion

Caribou have long been thought to exhibit the longest, terrestrial migrations on the planet, albeit often without robust validation. Our study of comparable migratory distances provides substantially more robust support for this claim. With multiple populations with > 1200 km straight-line, round-trip migration distance, caribou are indeed world-class migrators. While we believe caribou likely exhibit the longest extant terrestrial migrations, it is possible that another species may claim that recognition. In particular, the 2400 km RTD migration reported for saiga antelope in Kazakhstan is by far the longest to our knowledge. However, this distance was estimated without the assistance of tracking technology that allowed known individuals to be relocated[45] and thus there remains the possibility that Saiga antelope seen on 1 winter range were from different sub-populations than others found on the calving grounds used to determine this distance. Moreover, there have been dramatic declines in saiga antelope populations[46,47] and populations are currently becoming increasingly constrained by human developments[48]. Thus, saiga antelope migrations have likely been diminished and the species may not exhibit the longest, extant, terrestrial migrations (E.J. Milner-Gulland, pers. comm.[6]). We encourage the support and publication of GPS-collar research to help identify, quantify and conserve long-distance migrations in this species. Future work quantifying migration distances should focus on movements at the scale of the individual rather than populations for repeatability and comparability. Migration distance is thought to be positively correlated with population size and density[21,29,30]. We offer 2 more examples that support this hypothesis. First, the Bathurst Caribou Herd, in central Canada, used to migrate up to 1500 km (see[49]), but as the herd has declined, it now migrates about 1350 km[50]. Second, the round-trip migration distance covered by Western Arctic Herd caribou was about 1500 km at its peak population of nearly 500,000 animals (circa 2003), but is now about 1250 km with a population of about half of its peak (this study). Recently, however, the Porcupine Herd has shown the opposite trend. While RTD is a recognizable and valuable metric, it has numerous limitations. Start and end points can be difficult to objectively and quantifiably define and population-level analyses might over-estimated migration distances. Greater standardization and explicit definitions would aid in future comparisons. Additionally, facultative winter migrations, nomadism, dispersal events, territorial and other movements fall outside the domain of RTD. TCAD provides a much more straight-forward, repeatable and quantifiable method to directly compare movements across individuals, populations and species. Our TCAD results are intriguing, yet preliminary. Predator species consistently moved more than their prey, in line with our hypothesis (Fig. 2). We could not rigorously test our hypotheses due to small samples sizes and biased geography, however, gray wolves from southwest Mongolia moved more than sympatric khulan or wild camels from near the same region. In Alaska, the gray wolf moved more than its primary prey species, caribou or moose, and similarly, in Alberta, the gray wolf moved more than elk or boreal caribou. Also, brown bears moved more than moose in north-central Alaska. While brown bears are omnivores, they prey upon moose and their calves in this region. We suspect this pattern of predators moving more than their prey may be widespread among cursorial predators. We also hypothesize that the TCAD of cursorial predators will increase with more vagile prey or with prey at lower densities and be greater than those for ambush predators. Our findings also suggest that complex social structure, territoriality, and extended periods of relative immobility of young, rather than metabolic and/or anatomical inefficiencies, could prevent wolves and similar cursorial predators from tracking their prey year-round (see[2,5]): not only can they keep up, they can go farther. In agreement with another of our hypotheses, but also hampered by small sample sizes, smaller members of the same guild appeared to move more than larger members found in the same region (Fig. 3a). For example, in southwest Mongolia, khulan (~230 kg) moved more than wild camels (~690 kg), in Alaska, barren-ground caribou (~90 kg) moved more than moose (~480 kg), in the Serengeti, wildebeest (~140 kg) moved more than zebras (~320 kg), and in Alberta, pronghorn (~55 kg) moved more than elk (~235 kg) and boreal caribou (~180 kg). Again, we suspect this pattern is widespread and related to allometry and the ability of larger species to use lower quality forage than smaller species[35-37]. Our results did, however, document elk moving more than boreal caribou in Alberta. These 2 studies did not overlap spatially and primary productivity was lower in the region where the elk occurred. We confirmed our prediction that species dwelling in areas with dramatic seasonal variability or low primary productivity (e.g., the Arctic and central Asia) would have greater TCAD (Fig. 3). We expect that low vegetative productivity and high degree of seasonality in southern Mongolia contributed to this region having the greatest TCAD we found[34]. Khulan in southeast Mongolia, where resource availability is more variable, moved more than khulan in southwest Mongolia[51,52]. Zebra in Botswana, where primary productivity is lower, moved more than zebra in the Serengeti. Furthermore, we found wolves in Alaska moved more than wolves found 3000 km south in Alberta, caribou in northern Canada moved more than those in southern Canada, and pronghorn in Alberta/Saskatchewan moved more than those 400 km to the south in Montana/Saskatchewan. We did not find a significant correlation between human population density and TCAD, but that may be related to our focus on species with high TCAD. Indeed, all TCADs > 3500 km were found in areas with densities of < 0.2 people/km2. Large patch sizes, associated with low human population density, may also facilitate greater movements. In our study, gray wolves were the most cursorial species, with individuals from southwest Mongolia exhibiting the longest annual movements. However, like other species (e.g., caribou), wolves displayed a high degree of plasticity. Territorial wolves had greater total annual movements than even long-distance (>450 km) dispersing conspecifics. This may be due to territory maintenance[53] or hunting behavior. Wolves in packs that hunted caribou moved more than packs that focused on less cursorial moose. Frame et al.[54] reported 1 denning female wolf traveled 341 km in 14 days, to a maximum distance of 103 km from her active den, in pursuit of caribou. Wolves from central Alaska, where caribou density was lower, moved more than wolves from east-central Alaska, where caribou density was greater. While wolves were the most mobile species that we studied, they modulate movements in relation to their primary prey[55]. Meso-carnivores inhabiting low productivity regions, such as the arctic fox, warrant more attention as they can travel very long distances (>4400 km) in 4 or 5 months[56,57] as well as annually (>4900 km based on daily or every other day PTT relocations[56], also see Table 2). While caribou exhibited the longest migration distances, these did not translate into the greatest annual distances traveled. Caribou were outpaced annually by nomadic khulan, but also by their primary predator, the gray wolf and the arctic fox. Caribou, from various study areas, were the next most cursorial species. We posit that extreme movements, in caribou and other species that travel great distances, are driven by extreme seasonal variability, patchy distribution of key resources, low primary productivity, predator avoidance, territoriality of conspecifics, and/or access to parturition location.

Conclusion

Our work documents and compares some of the longest, extant terrestrial migrations and movements in the world in a standardized way. Such long-distance movements are increasingly challenged by infrastructure development that hinders mobility[38], thus data on long-distance migrations will help future efforts to identify key areas and species of conservation concern, as well as a better understanding of the mechanisms that structure overall movement of large terrestrial mammals. Furthermore, the spatial and temporal scale of these movements should be accounted for when conservation, corridor, and mitigation planning is undertaken. Territorial, migratory, and nomadic species populations may require different conservation planning strategies[58]. Conservation of long-distance terrestrial movements should also have ancillary benefits to a wide array of other species and ecosystem services.
  24 in total

1.  A model-driven approach to quantify migration patterns: individual, regional and yearly differences.

Authors:  Nils Bunnefeld; Luca Börger; Bram van Moorter; Christer M Rolandsen; Holger Dettki; Erling Johan Solberg; Göran Ericsson
Journal:  J Anim Ecol       Date:  2010-11-25       Impact factor: 5.091

2.  Causes and consequences of migration by large herbivores.

Authors:  J M Fryxell; A R Sinclair
Journal:  Trends Ecol Evol       Date:  1988-09       Impact factor: 17.712

3.  How far to go? Determinants of migration distance in land mammals.

Authors:  Claire S Teitelbaum; William F Fagan; Chris H Fleming; Gunnar Dressler; Justin M Calabrese; Peter Leimgruber; Thomas Mueller
Journal:  Ecol Lett       Date:  2015-04-12       Impact factor: 9.492

4.  A framework for modelling range shifts and migrations: asking when, whither, whether and will it return.

Authors:  Eliezer Gurarie; Francesca Cagnacci; Wibke Peters; Christen H Fleming; Justin M Calabrese; Thomas Mueller; William F Fagan
Journal:  J Anim Ecol       Date:  2017-05-25       Impact factor: 5.091

5.  Is ungulate migration culturally transmitted? Evidence of social learning from translocated animals.

Authors:  Brett R Jesmer; Jerod A Merkle; Jacob R Goheen; Ellen O Aikens; Jeffrey L Beck; Alyson B Courtemanch; Mark A Hurley; Douglas E McWhirter; Hollie M Miyasaki; Kevin L Monteith; Matthew J Kauffman
Journal:  Science       Date:  2018-09-07       Impact factor: 47.728

6.  Connecting the dots: an invariant migration corridor links the Holocene to the present.

Authors:  Joel Berger; Steven L Cain; Kim Murray Berger
Journal:  Biol Lett       Date:  2006-12-22       Impact factor: 3.703

7.  Moving in the Anthropocene: Global reductions in terrestrial mammalian movements.

Authors:  Marlee A Tucker; Katrin Böhning-Gaese; William F Fagan; John M Fryxell; Bram Van Moorter; Susan C Alberts; Abdullahi H Ali; Andrew M Allen; Nina Attias; Tal Avgar; Hattie Bartlam-Brooks; Buuveibaatar Bayarbaatar; Jerrold L Belant; Alessandra Bertassoni; Dean Beyer; Laura Bidner; Floris M van Beest; Stephen Blake; Niels Blaum; Chloe Bracis; Danielle Brown; P J Nico de Bruyn; Francesca Cagnacci; Justin M Calabrese; Constança Camilo-Alves; Simon Chamaillé-Jammes; Andre Chiaradia; Sarah C Davidson; Todd Dennis; Stephen DeStefano; Duane Diefenbach; Iain Douglas-Hamilton; Julian Fennessy; Claudia Fichtel; Wolfgang Fiedler; Christina Fischer; Ilya Fischhoff; Christen H Fleming; Adam T Ford; Susanne A Fritz; Benedikt Gehr; Jacob R Goheen; Eliezer Gurarie; Mark Hebblewhite; Marco Heurich; A J Mark Hewison; Christian Hof; Edward Hurme; Lynne A Isbell; René Janssen; Florian Jeltsch; Petra Kaczensky; Adam Kane; Peter M Kappeler; Matthew Kauffman; Roland Kays; Duncan Kimuyu; Flavia Koch; Bart Kranstauber; Scott LaPoint; Peter Leimgruber; John D C Linnell; Pascual López-López; A Catherine Markham; Jenny Mattisson; Emilia Patricia Medici; Ugo Mellone; Evelyn Merrill; Guilherme de Miranda Mourão; Ronaldo G Morato; Nicolas Morellet; Thomas A Morrison; Samuel L Díaz-Muñoz; Atle Mysterud; Dejid Nandintsetseg; Ran Nathan; Aidin Niamir; John Odden; Robert B O'Hara; Luiz Gustavo R Oliveira-Santos; Kirk A Olson; Bruce D Patterson; Rogerio Cunha de Paula; Luca Pedrotti; Björn Reineking; Martin Rimmler; Tracey L Rogers; Christer Moe Rolandsen; Christopher S Rosenberry; Daniel I Rubenstein; Kamran Safi; Sonia Saïd; Nir Sapir; Hall Sawyer; Niels Martin Schmidt; Nuria Selva; Agnieszka Sergiel; Enkhtuvshin Shiilegdamba; João Paulo Silva; Navinder Singh; Erling J Solberg; Orr Spiegel; Olav Strand; Siva Sundaresan; Wiebke Ullmann; Ulrich Voigt; Jake Wall; David Wattles; Martin Wikelski; Christopher C Wilmers; John W Wilson; George Wittemyer; Filip Zięba; Tomasz Zwijacz-Kozica; Thomas Mueller
Journal:  Science       Date:  2018-01-26       Impact factor: 47.728

8.  Going, going, gone: is animal migration disappearing.

Authors:  David S Wilcove; Martin Wikelski
Journal:  PLoS Biol       Date:  2008-07-29       Impact factor: 8.029

9.  Space and habitat use by wild Bactrian camels in the Transaltai Gobi of southern Mongolia.

Authors:  Petra Kaczensky; Yadamsuren Adiya; Henrik von Wehrden; Batmunkh Mijiddorj; Chris Walzer; Denise Güthlin; Dulamtseren Enkhbileg; Richard P Reading
Journal:  Biol Conserv       Date:  2014-01       Impact factor: 5.990

Review 10.  Collapse of the world's largest herbivores.

Authors:  William J Ripple; Thomas M Newsome; Christopher Wolf; Rodolfo Dirzo; Kristoffer T Everatt; Mauro Galetti; Matt W Hayward; Graham I H Kerley; Taal Levi; Peter A Lindsey; David W Macdonald; Yadvinder Malhi; Luke E Painter; Christopher J Sandom; John Terborgh; Blaire Van Valkenburgh
Journal:  Sci Adv       Date:  2015-05-01       Impact factor: 14.136

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  11 in total

1.  A pan-African spatial assessment of human conflicts with lions and elephants.

Authors:  Enrico Di Minin; Rob Slotow; Christoph Fink; Hans Bauer; Craig Packer
Journal:  Nat Commun       Date:  2021-05-20       Impact factor: 14.919

Review 2.  Behavioral, Physiological, Demographic and Ecological Impacts of Hematophagous and Endoparasitic Insects on an Arctic Ungulate.

Authors:  Kyle Joly; Ophélie Couriot; Matthew D Cameron; Eliezer Gurarie
Journal:  Toxins (Basel)       Date:  2020-05-20       Impact factor: 4.546

3.  Apex scavengers from different European populations converge at threatened savannah landscapes.

Authors:  A Delgado-González; A Cortés-Avizanda; D Serrano; E Arrondo; O Duriez; A Margalida; M Carrete; P Oliva-Vidal; E Sourp; Z Morales-Reyes; I García-Barón; M de la Riva; J A Sánchez-Zapata; J A Donázar
Journal:  Sci Rep       Date:  2022-02-15       Impact factor: 4.379

4.  Genomic legacy of migration in endangered caribou.

Authors:  Maria Cavedon; Bridgett vonHoldt; Mark Hebblewhite; Troy Hegel; Elizabeth Heppenheimer; Dave Hervieux; Stefano Mariani; Helen Schwantje; Robin Steenweg; Jessica Theoret; Megan Watters; Marco Musiani
Journal:  PLoS Genet       Date:  2022-02-10       Impact factor: 5.917

Review 5.  The role of context in elucidating drivers of animal movement.

Authors:  Nicolas Lubitz; Michael Bradley; Marcus Sheaves; Neil Hammerschlag; Ryan Daly; Adam Barnett
Journal:  Ecol Evol       Date:  2022-07-24       Impact factor: 3.167

6.  Seasonal patterns of spatial fidelity and temporal consistency in the distribution and movements of a migratory ungulate.

Authors:  Kyle Joly; Eliezer Gurarie; D Alexander Hansen; Matthew D Cameron
Journal:  Ecol Evol       Date:  2021-05-14       Impact factor: 2.912

7.  Mapping potential effects of proposed roads on migratory connectivity for a highly mobile herbivore using circuit theory.

Authors:  Timothy J Fullman; Ryan R Wilson; Kyle Joly; David D Gustine; Paul Leonard; Wendy M Loya
Journal:  Ecol Appl       Date:  2020-08-18       Impact factor: 6.105

8.  Evaluating the Impact of Anthropogenic Factors on the Dissemination of Contemporary Cosmopolitan, Arctic, and Arctic-like Rabies Viruses.

Authors:  Andrei A Deviatkin; Yulia A Vakulenko; Mariia A Dashian; Alexander N Lukashev
Journal:  Viruses       Date:  2021-12-30       Impact factor: 5.048

9.  Long-distance, synchronized and directional fall movements suggest migration in Arctic hares on Ellesmere Island (Canada).

Authors:  Jacob Caron-Carrier; Sandra Lai; François Vézina; Andrew Tam; Dominique Berteaux
Journal:  Sci Rep       Date:  2022-03-23       Impact factor: 4.379

10.  Seasonal movements in caribou ecotypes of Western Canada.

Authors:  Jessica Theoret; Maria Cavedon; Troy Hegel; Dave Hervieux; Helen Schwantje; Robin Steenweg; Megan Watters; Marco Musiani
Journal:  Mov Ecol       Date:  2022-03-10       Impact factor: 3.600

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