Movement Ecology最新文献

Avian navigation has fascinated researchers for many years. Yet, despite a vast amount of literature on the topic it remains a mystery how birds are able to find their way across long distances while relying only on cues available locally and reacting to those cues on the fly. Navigation is multi-modal, in that birds may use different cues at different times as a response to environmental conditions they find themselves in. It also operates at different spatial and temporal scales, where different strategies may be used at different parts of the journey. This multi-modal and multi-scale nature of navigation has however been challenging to study, since it would require long-term tracking data along with contemporaneous and co-located information on environmental cues. In this paper we propose a new alternative data-driven paradigm to the study of avian navigation. That is, instead of taking a traditional theory-based approach based on posing a research question and then collecting data to study navigation, we propose a data-driven approach, where large amounts of data, not purposedly collected for a specific question, are analysed to identify as-yet-unknown patterns in behaviour. Current technological developments have led to large data collections of both animal tracking data and environmental data, which are openly available to scientists. These open data, combined with a data-driven exploratory approach using data mining, machine learning and artificial intelligence methods, can support identification of unexpected patterns during migration, and lead to a better understanding of multi-modal navigational decision-making across different spatial and temporal scales.

Background: Freshwater megafishes are among some of the most commercially and ecologically important aquatic organisms yet are disproportionately threatened with range and population reduction. Anthropogenic alterations of rivers influencing migrations are among the most significant causes for these declines. However, migratory fishes do not always respond similarly to movement barriers and thus it is necessary to develop models to predict movements of freshwater migratory fishes in the face of anthropogenic alteration. Predicting movement of freshwater fishes is often investigated using statistical packages. However, empirical studies assessing these packages have led to mixed results, questioning its applicability to all taxa. We argue that spatial, temporal, and environmental attributes are more influential for movement of a migratory megafish, the Alligator Gar (Atractosteus spatula), than the current parameters explored in a globally relevant fish movement model.

Methods: This study explored two independent mobile telemetry datasets investigating Alligator Gar movement on the Brazos and Trinity rivers. Environmental associations were investigated to predict Alligator Gar displacement and dispersal using generalized additive models, generalized linear models, and model selection. Leptokurtosis of Alligator Gar populations was also assessed. Predictability of the movement model was tested by comparing observed to model derived stationary and mobile components making up a leptokurtic movement distribution.

Results: Our study suggests that current and antecedent measures of discharge and water temperature are positively correlated with Alligator Gar displacement and dispersal. However, these patterns are only detectable when monthly relocation intervals are explored rather than seasonal scales. Leptokurtosis was observed in both Alligator Gar populations. However, movement was normally distributed (i.e., mesokurtic) under tracking events following high flood pulses. Additionally, predicted Alligator Gar movement was significantly farther under modeled values compared to observed values, in part because the species undergoes cyclical migrations for reproduction that are sensitive to water temperature and discharge.

Discussion: In conclusion, this study provides an alternative framework to assess the movement patterns of migratory fishes, which could be tested on additional freshwater fishes, and suggests that assessing spatial, environmental, and temporal processes simultaneously are necessary to capture the complexities of fish movement which currently are unavailable for the movement model we investigated.

Background: Annual-cycle movements of wildlife are driven by a combination of intrinsic and extrinsic factors. In urban systems, management strategies to reduce human-wildlife interactions could also alter wildlife movement and distribution, with potential effects on key ecological processes such as pathogen spread.

Methods: To better understand how management actions interact with existing spatial dynamics to mediate wildlife movement patterns, we experimentally subjected urban-nesting yellow-legged gulls to induced breeding failure via egg-oiling. We then followed their movements using bird-borne GPS transmitters throughout the treatment season as well as the following annual cycle and compared them to the movements of tracked gulls whose nests were not oiled, while also accounting for individual and temporal factors known to influence movement patterns including sex, body size, and breeding stage.

Results: Gulls with oiled nests had smaller breeding-season home ranges, spent more time at breeding sites, made fewer foraging trips, and traveled shorter distances than gulls with non-oiled nests during the treatment season but not during the following breeding season. Gulls were partially migratory, with individuals showing a variety of migratory strategies from year-round residency to long-distance migration to inland urban centers. Although egg-oiling delayed the onset of post-breeding migration, individual migration strategies remaining consistent between years regardless of treatment. Antibody titres against three common pathogens varied among pathogens but not by migration distances or individual characteristics.

Conclusions: Our results show that induced breeding failure via egg-oiling may have unintended short-term consequences including smaller home range areas, altered habitat use, delayed migration, and longer breeding-site residency, suggesting that management actions aimed to reduce breeding success could increase opportunities for human-wildlife conflict and spread of spatially heterogeneous pathogens at local scales. At the landscape scale, the migration patterns and wintering distribution of yellow-legged gulls are unlikely to be affected by egg-oiling. However, long-distance inland migrations of a portion of the population present a novel pathway for pathogen transmission between and among marine habitats and terrestrial human, livestock, and wildlife populations.

Background: In highly constrained ecosystems such as in the Arctic, animals must constantly adjust their movements to cope with the highly versatile environmental conditions. However, to date most studies have focused on interseasonal differences in spatial behaviour, while intraseasonal dynamics are less described.

Methods: To fill this knowledge gap, we studied the movement patterns of an Arctic predator, the arctic fox (Vulpes lagopus) at the intraseasonal scale. To unravel temporal patterns in space use and movement metrics, we used GPS data collected on 20 individual foxes between 2017 and 2023 in North-East Greenland.

Results: We showed that weekly full and core home range sizes (estimated by means of Autocorrelated Kernel Density Estimates), and daily mean relative turning angles stayed constant throughout the summer. Conversely, daily distance travelled, mean daily speed and daily proportion of 'active' time showed intraseasonal variations. These fine-scale metrics had a hump-shaped distribution, peaking in mid-July, with males and non-breeding foxes travelling longer distances and being faster. Site-specific patterns were also identified, with foxes having smaller territories in the two most productive sites but moving shorter distances and at lower speeds at the poorest site.

Conclusion: Our study provides novel insights into how predators adjust their space use and behaviour to intraseasonal variations in environmental conditions. Specifically, we show that different movement metrics show different intraseasonal patterns. We also underline the importance of considering small spatiotemporal scales to fully understand predators' spatial behaviour.

Background: Models of utilization distribution in the form of partial differential equations have long contributed to our understanding of organismal space use patterns. In studies of infectious diseases, they are also being increasingly adopted in support of epidemic forecasting and scenario planning. However, as movement research shifts its focus towards large data collection and statistical modeling of movement trajectories, the development of such models has notably slowed.

Methods: Here, we demonstrate the continued importance of modeling utilization distribution to predict variation in space-use patterns over time. We highlight the considerable, yet largely untapped, potential of such models, which have historically been limited by the steady-state assumption due to longstanding technical constraints. Now, by adapting existing computational tools primarily developed for material science and engineering, we can probe beyond the steady states and unlock from them a broad spectrum of complex, transient space-use dynamics. Our approach requires little experience in numerical analysis and is readily accessible to model practitioners in ecology and epidemiology across diverse systems where movement is a critical feature.

Results: We illustrated our approach using a mix of canonical and novel case studies, covering topics from wildlife translocation to vaccine deployment. First, we revisited a classical model of canid territorial formation driven by scent-mediated conspecific avoidance. Transient space-use analysis uncovered previously hidden spatial dynamics that are ecologically informative. Next, we applied our approach to long-distance movement on realistic landscapes. Habitat and land-use heterogeneities markedly affected the transient space-use dynamics and short-term forecasts, even when the steady state remained unchanged, with direct implications for conservation management. Finally, we modeled transient space-use dynamics as both a response to and a driver of transient population dynamics. The importance of this interdependence was shown in the context of epidemiology, in a scenario where the movement of healthcare personnel is influenced by local outbreak conditions that are stochastically evolving.

Conclusions: By facilitating transient space-use analysis, our approach could lead to reevaluations of foundational ecological concepts such as home range and territory, replacing static with dynamic definitions that more accurately reflect biological realities. Furthermore, we contend that a growing interest in transient space-use dynamics, spurred by this work, could have transformative effects, stimulating new research avenues in ecology and epidemiology.

Background: Despite decades of epidemiological theory making relatively simple assumptions about host movements, it is increasingly clear that non-random movements drastically affect disease transmission. To better predict transmission risk, theory is needed that quantifies the contributions of both fine-scale host space use and non-independent, correlated host movements to epidemiological dynamics.

Methods: We developed and applied new theory that quantifies relative contributions of fine-scale space use and non-independent host movements to spatio-temporal transmission risk. Our theory decomposes pairwise spatio-temporal transmission risk into two components: (i) spatial overlap of hosts-a classic metric of spatial transmission risk - and (ii) pairwise correlations in space use - a component of transmission risk that is almost universally ignored. Using analytical results, simulations, and empirical movement data, we ask: under what ecological and epidemiological conditions do non-independent movements substantially alter spatio-temporal transmission risk compared to spatial overlap?

Results: Using theory and simulation, we found that for directly transmitted pathogens even weak pairwise correlations in space use among hosts can increase contact and transmission risk by orders of magnitude compared to independent host movements. In contrast, non-independent movements had reduced importance for transmission risk for indirectly transmitted pathogens. Furthermore, we found that if the scale of pathogen transmission is smaller than the scale where host social decisions occur, host movements can be highly correlated but this correlation matters little for transmission. We applied our theory to GPS movement data from white-tailed deer (Odocoileus virginianus). Our approach predicted highly seasonally varying contributions of the spatial and social drivers of transmission risk - with social interactions augmenting transmission risk between hosts by greater than a factor of 10 in some cases, despite similar degrees of spatial overlap. Moreover, social interactions could lead to a distinct shift in the predicted locations of transmission hotspots, compared to joint space use.

Conclusions: Our theory provides clear expectations for when non-independent movements alter spatio-temporal transmission risk, showing that correlated movements can reshape epidemiological landscapes, creating transmission hotspots whose magnitude and location are not necessarily predictable from spatial overlap.

Background: Seasonal migration is a behavioral strategy that animals evolved to exploit seasonally changing resources. Ungulates in northern temperate landscapes often seasonally migrate between low-elevation winter ranges and higher-elevation summer ranges, allowing individuals to exploit a diversity of forage resources during summer while avoiding extreme conditions during winter. In autumn, the timing of this behavior often overlaps with hunting seasons for managed ungulate populations. Migration presents challenges for managing ungulates when the timing of autumn migrations varies across years and migrations cross management jurisdictions.

Methods: We evaluated the spatial and temporal patterns of autumn migration using GPS collar data collected during 2017-2019 from 68 female mule deer (Odocoileus hemionus) that migrated seasonally within three study areas in northwest Montana. We related the timing of autumn migration to environmental variables including precipitation, snow depth and density, temperature, plant phenology, migration distance, and estimates of relative hunting intensity. We summarized variables across multiple temporal scales (2-day, and 1 week) to identify possible lagged or cumulative effects of conditions on mule deer behavior. We incorporated these variables into a time-to-event modeling framework to estimate their relative impacts on the timing of initiation of autumn migration.

Results: The collective annual space use of deer in each study area spanned up to 9 hunting districts, and individual deer used an average of 2.1, 2.8, and 2.0 hunting districts per year (range 1-4) in the Cabinet-Fisher, Rocky Mountain Front, and Whitefish study areas, respectively. Furthermore, the return of deer to winter ranges occurred over a 3-month timeframe spanning archery, rifle, and closed hunting periods. While some deer returned to winter range relatively early during archery season in September, others remained in summer range into December, after the general rifle season concluded. Declines in daily minimum temperatures and increased weekly precipitation provided the strongest cues for mule deer to begin their autumn migration. Mule deer with longer migration distances were more likely to initiate their migration sooner, and declining forage conditions also showed a modest effect on timing. Mule deer migrations occurred during times of lower hunting activity prior to its peak during rifle season.

Conclusions: Our study demonstrates changing weather conditions were the primary driver of the initiation of autumn migration for mule deer. Given most migrations spanned more than one hunting district, the boundaries of management units were mismatched with the scale of ecological processes, implying that management actions in certain districts may have unintended consequences for populations in nearby districts.

Background: Access to critical resources, including food, water, or shelter, significantly determines individual fitness. As these resources are limited in most habitats, animals may employ strategies of landscape partitioning to mitigate the impact of direct resource competition. Territoriality may be regarded as an aggressive form of landscape partitioning, but other forms of landscape partitioning exist in non-territorial species. Animals living in groups with greater flexibility in their association patterns, such as multilevel societies with fission-fusion dynamics, may adjust their grouping and space use patterns to short-term variations in ecological conditions such as food availability, predation pressure, or the presence of conspecific groups. This flexibility may allow them to balance the costs of competition while reaping the benefits of better predator detection and defence.

Methods: We explored patterns of landscape partitioning among neighbouring Guinea baboon (Papio papio) parties in the Niokolo-Koba National Park, Senegal. Guinea baboons live in a multilevel society in which parties predictably form higher-level associations ("gangs"). We used four years of locational data from individuals equipped with GPS collars to estimate annual home ranges, home range overlap, and average minimum distances between parties. We examined whether food availability and predator presence levels affected the cohesion between parties in 2022.

Results: We found substantial overlap in home range and core area among parties (33 to 100%). Food availability or predator presence did not affect the distance to the closest neighbouring party; the average minimum distance between parties was less than 100 m.

Conclusions: Our results suggest a low level of feeding competition between our study parties. Whether this is a general feature of Guinea baboons or particular to the situation in the Niokolo-Koba National Park remains to be investigated.

Background: The degree to which avian migrants revisit the same sites to replicate routes from previous years has received more and more attention as the possibilities of tracking small to medium-size birds over multiple annual cycles have improved. Repeated measurements of individuals with an appropriate sampling resolution can potentially inform about their navigation and migration strategies and to what extent observed variation within and between individuals may reflect the selective potential in the population.

Methods: We analysed the annual space-use of European nightjars Caprimulgus europaeus tracked with GPS-loggers in multiple years between northern Europe and southern Africa. We quantified spatial consistency of stationary sites and variation, repeatability, and latitudinal correlations in route choice and also investigated barrier-associated changes of within- and between-individual longitudinal variation in flight routes.

Results: We found that the nightjars consistently used the same breeding and wintering sites. In contrast, the birds generally varied their migration routes between years, and we could only rarely confirm site fidelity to stopover sites. Nevertheless, route variation within individuals remained low for most of both autumn and spring migration, while the between individual variation generally was larger, resulting in a high repeatability in flight routes. Although we found extensive spatial autocorrelation in both seasons across latitudes, we detected significant changes in longitudinal variation associated with the passage of ecological barriers enroute. Potential intermediate goal areas were visited prior to the crossing of the Mediterranean Sea and the Sahara Desert in both seasons. In spring, within-individual route variability dropped to a few tens of kilometres at the initiation of the Sahara crossing but increased to maximum over the barrier.

Conclusions: The nightjars incorporate individual-specific space use within their annual cycle that allows for a degree of flexibility during migration, possibly driven by the energetic benefits of allowing adaptive wind drift while airborne. Our data demonstrate how topography and spatial autocorrelation of positions influence flight path variability that may diminish or reinforce individuality in route choice. Hence, this study highlights that identifying and quantifying past and present external influences on emergence of realised routes can be critical for distinguishing the genetic basis and environmental variation in migration.

Background: Species ranges are shaped by a variety of ecological and environmental factors that are inherently dynamic, fluctuating in response to climatic, biotic, and anthropogenic influences. Dispersal plays a key role in range shifts, allowing species to adapt to changing habitats and exploit new regions. In this study, we examined the dispersal processes of four thrush species (Turdus amaurochalinus, T. chiguanco, T. falcklandii and T. rufiventris) that have expanded their ranges in recent decades, with a focus on the interaction between spread and seasonal movements.

Methods: We collected eBird records from 2003 to 2023 to create heat maps that illustrate changes in densities of reported occurrences between seasons and over the years. We also evaluated how bioclimatic and land cover variables influenced the observed variations.

Results: The four thrush species have shown significant range expansions, with initially distinct seasonal distributions, which became increasingly similar over time, leading to significant overlap in their breeding and non-breeding habitats. Temperature and precipitation associated with the presence of the four species varied over time and between seasons. Additionally, all four species exhibited shifts in habitat selection, both seasonally and across years.

Conclusion: The changes of range are likely driven by a combination of climate and land-use change, and resource availability, which also influence seasonal dispersal patterns. At the same time, thrushes perform very well in urban environments, which offer stable resources and may contribute to their reduction in seasonal movements. Overall, these findings highlight the dynamic nature of thrush species' range shifts and their adaptation to environmental changes.