Movement Ecology最新文献

Background: Large carnivores in human-dominated landscapes face significant risks from increased anthropogenic pressure, making it crucial to understand their movement behaviour for conservation strategies.

Methods: We used conventional and generalised hidden Markov models (HMMs) to analyse GPS telemetry data collected from 2016 to 2022 on 15 subadult tigers to classify behavioural states across three life stages (pre-dispersal, dispersal, post-dispersal) in the Eastern Vidarbha Landscape, India. We further examined how intrinsic and extrinsic factors influenced transitions between these behavioural states.

Results: Three distinct behavioural states were identified: resting (stationary movement with very short step lengths), area-restricted movement (tortuous movement with short to intermediate step lengths), and travelling (highly directional movement with long step lengths). During the pre-dispersal phase, tigers displayed exploratory movement within their natal range, with significant emphasis on area-restricted movement (42.10%), followed by travelling (30.47%), and resting (27.42%). Travelling peaked at dusk and showed the highest probability of occurrence throughout the night until dawn and exhibited faster movement in areas with high human density. Area-restricted movement was most frequent during the day and peaked between 09:00-11:00 h, while resting showed the highest probability between 22:00-23:00 h. Dispersing tigers allocated their activity budget equally among resting (32.09%), area-restricted movement (35.77%), and travelling (32.14%), as they navigated fragmented landscapes comprising of forests, wildlife corridors, agricultural fields, and human settlements. They exhibited faster, directed movements in low-cover areas and increased step lengths in fragmented, non-forest habitats, with a greater likelihood of travelling at dusk and night. Tigers in the post-dispersal phase had stable home ranges and maintained well-defined territorial boundaries. During area-restricted movement, they exhibited longer step lengths in forest habitats and faster travel speeds in a human‒agricultural matrix. Moreover, they tended to rest at high temperatures and travelled more when the temperatures were between 20 and 30 °C.

Conclusions: Our study provides crucial insights on tiger movements in human-dominated landscapes across different life stages and habitats. Understanding their behavioural patterns and implementing effective conservation efforts can ensure the long-term survival of tigers and their coexistence with humans.

Background: Understanding collective behaviours and interactions in sharks is still in its infancy. Although recent studies have revealed some social structures in several shark species, little is known about complex interactions and social processes such as leader-follower dynamics. Recognising the dynamics in shark populations can help to further understand population structure and the influence of specific individuals.

Methods: We developed a methodological approach to detect and analyse leader-follower behavioural patterns using acoustic telemetry data. By utilising lag-time distributions from acoustic telemetry detections for pairs of individuals we infer directed relationships based on temporal patterns. We applied this method to existing datasets from grey reef sharks (Carcharhinus amblyrhynchos), blacktip reef sharks (Carcharhinus melanopterus), and tiger sharks (Galeocerdo cuvier).

Results: We found evidence of leader-follower behaviour in both reef-associated species, with half of the tagged grey reef sharks forming leader-follower networks at eight locations. Size was a significant influence on female grey reef sharks leading-following behaviour. We found similar behaviours at three locations for blacktip reef sharks, with one-third of the tagged individuals forming separate and non-overlapping networks. Size was a significant influence on male blacktip reef sharks leading-following behaviour. No species showed a significant effect of sex alone on leader-follower behaviours. Aggregating networks did not show an overall hierarchy for either species but showed that grey reef shark coordinated in smaller networks than expected with strong influences from more dominant individuals. We found no leader-follower networks for tiger sharks.

Conclusions: Our methodology reveals leader-follower behaviours in blacktip reef sharks and grey reef sharks and corroborates findings from the literature which have previously either been described using visual observation or using a different analytical approach. We demonstrate how existing acoustic telemetry datasets are a valuable source which can be used to detect social interactions associated with leader-follower behaviours in sharks, especially when visual observations are not feasible. Our approach provides new insights into understanding the social dynamics in sharks and offers a way to be applied to many more species already acoustically tagged.

Background: The efficient acquisition of two critical but spatially separated resources -food and oxygen- governs the daily movements and diving patterns of air-breathing aquatic animals. Unlike pinnipeds, turtles and seabirds, fully marine ('true') sea snakes spend their entire lifecycle at sea and have evolved specialised movement behaviours. However, fine-scale data on the diving behaviour of free-ranging sea snakes remain scarce, limiting our understanding of their ecology and vulnerability to anthropogenic threats.

Methods: We used acoustic telemetry to track five individuals of two benthic-foraging sea snake species (Hydrophis stokesii, H. major) in Exmouth Gulf, Western Australia, and Baie des Citrons, New Caledonia. Each snake was continuously tracked using a directional hydrophone for up to 18 h, generating high-resolution, three-dimensional dive paths. After filtering, we analysed 106 dives from 46 h of tracking.

Results: Sea snakes primarily conducted U- and S-shaped dives and spent on average 97.2% of their time submerged. Most U-shaped dives were characterised by limited vertical and horizontal movement. S-shaped dives were more complex, with variable time on the seafloor and occasionally interrupted gradual ascents. Dive duration was positively correlated with post-dive surface interval, while depth and duration of the gradual ascent phase were influenced by environmental depth. We also identified distinctive, repetitive undulations ('wiggles') in the depth profiles of several dives completed by all three tracked H. stokesii.

Conclusions: These high-resolution data provide the first insights into the fine-scale diving patterns of benthic-foraging sea snakes. Like surface-foraging species, they appear to regulate air intake based on environmental depth and may be neutrally buoyant in the gradual ascent phase of S-shaped dives. We hypothesise that this phase facilitates efficient horizontal travel, despite potential increases in predation risk. The 'wiggles' observed in H. stokesii may have a functional role in buoyancy control, energy conservation, or foraging. Our study contributes to a deeper understanding of sea snake diving strategies, with implications for their ecology, physiology, and conservation.

Background: Migratory phenology affects fitness and therefore plays a crucial role in the annual life cycle of migrants. Various indicators in relation to the migration patterns of Arctic nesting birds have been well studied (e.g. vegetation production), but we still lack knowledge from lower latitudes, e.g. the Mongolian Plateau, which is one of the top-priority regions for avian research and conservation.

Methods: We used 208 spring and 248 autumn migration tracks from individually tagged Swan Geese Anser cygnoides (SG) and Greylag Geese A. anser (GG) from four geographically discrete breeding groups across the Mongolian Plateau. We analyzed the difference in their migratory timing, how they responded to nine environmental metrics as indicators of environmental change, and the probability of spring arrival and autumn departure.

Results: We found significant differences in spring and autumn departure times between species, yet their arrival times were similar, although the migration phenology of eastern nesting birds differed significantly from those in central and western Mongolia. Their spring migration followed the onset of daily temperature reaching 0 °C, but was not correlated with indices of plant green-up, which occurred behind them along their migration routes. The autumn departure phenology of SG exhibited stronger responses to 0 °C nighttime temperatures, while the GG responded more to 0 °C cumulative temperatures.

Conclusions: Two goose species follow behind the daily 0 °C and before the green-up of plants in spring, allowing the time of hatching of goslings to coincide with the plant growth peak, ensuring a predictable food supply for the nidifugous juveniles. Vegetation and snow metrics were not appropriate indicators to predict the migration process of either species, due to the lack of strong latitudinal gradients in plant growth and long-term snow cover.

Background: Prey species can display antipredator movement behaviours to reduce predation risk, including proactive responses to chronic or predictable risk, and reactive responses to acute or unpredictable risk. Thus, at any given time, prey movement choice may reflect a trade-off between proaction and reaction. In previous studies, proaction and reaction have generally been considered separately, which neglects their potentially simultaneous influence on animal movement decisions and overall space use.

Methods: In this study, we analysed how proaction and reaction interact to shape the movements of GPS-collared red deer (Cervus elaphus) in response to hunting by humans. Using an exhaustive inventory of red deer hunting events and very high-resolution canopy cover density (LiDAR), we combined movement metric (displacement and path length) models and integrated step selection functions to investigate antipredator movement responses to lethal risk on various spatiotemporal scales, considering a dynamic landscape of risk.

Results: Our results show that red deer either proactively avoided areas of chronic risk, or they selected canopy cover where and when risk was predictably high. However, when risk was encountered anyway, canopy cover was no longer selected, but only modulated a reactive response along a remain-to-leave continuum. This reaction was even more evident when the environment was unfamiliar, underlining the importance of memory in such reaction patterns.

Conclusions: We describe how proaction and reaction fuse in an antipredator sequence of interconnected movement decisions in a large herbivore, and discuss how this result may help disentangle the ecological consequences of behavioural responses to predation. Finally, we lay the foundations for further investigations into the origins of similarities and differences between proactive and reactive movement responses.

Background: Abundant evidence exists that mobile animals exhibit different movement behavior during different seasons, especially in landscapes with strong seasonal variation in climate and resource availability. Quantifying seasonal movement dynamics is critical for making accurate inferences and appropriate recommendations for species conservation and landscape management. Using empirical approaches to characterize seasonal variation in animal movement minimizes assumptions about the timing of seasonal transitions, environmental proxies, and effects of spatiotemporal variation.

Methods: We calculated 57,255 mean daytime hourly movement rates for 104 scimitar-horned oryx (Oryx dammah) released into a large protected area in central Chad from 2016 to 2022. We used these movement data to build generalized additive mixed models of movement rates over a generic calendar year to detect potential seasonal variation in oryx movement behavior.

Results: Our final model indicated that reintroduced oryx experience three seasons per year, exhibiting dramatically lower daytime movement rates during the hot, dry season and higher movement rates during the rainy and cool, dry seasons. Reproductive status also affected oryx movement rates, notably females 1-4 months into pregnancy.

Conclusions: Captive-born oryx exhibited transitions in movement behavior aligned with regionally characteristic seasonal variation, a promising indicator for an ongoing reintroduction effort. Females 1-4 months pregnant, particularly those accompanied by neonates, exhibited consistently elevated daytime movement rates, suggesting substantial energy allocation to foraging in early pregnancy. The three seasons delineated by this study will be used to manage the reintroduced oryx population, for example to identify priority areas and time periods for enhanced monitoring and enforcement actions, as well as to investigate the potential re-emergence of historical seasonal migrations.

Background: Many animals disperse to find their own territory, mates to reproduce or suitable environments to live. Dispersal can be described as a three-phase process consisting of two stationary phases (S₁ and S₂) at the beginning and the end of a dispersal event. These stationary phases are temporally separated by a transient phase (T), where the animal moves from S₁ to a new area S₂ in space. The net squared displacement (NSD) is a frequently used metric to identify these phases from animal tracking data.

Methods: We tested whether early warning signals (EWSs) on time series of the NSD, can be used to predict dispersal events. To identify EWSs we conducted a rolling window approach and evaluated the dispersal events by performing a spatial cluster analysis with the mechanistic range shift analysis (MRSA). We used data from 22 GPS-collared red foxes (Vulpes vulpes) as an example of a mammal species in which the juvenile (sub-) adult transition usually involves dispersal.

Results: Applying EWSs resulted in the identification of both transitions from S₁ to T and from T to S₂. For 10 individuals we detected EWSs. For 8 out of these 10 individuals (80%) we identified a spatial shift between S₁ and S₂ via a MRSA. Accordingly, for 8 out of 22 individuals (36%) we observed a transient phase (T) which led to a major and persistent transformation of red fox locations.

Conclusion: Even though the identification of dispersal events based on movement data is challenging using well known techniques such as state space models or the MRSA, our results suggested that EWS in combination with MRSA is appropriate to detect and identify dispersal events in radio-collared mammals. Thus, in the context of identifying dispersal events using EWSs we recommend to evaluate the existence of stationary and transient phases using the MSRA. The benefit of using EWSs is the calculation of the NSD and simple statistics (standard deviation, autocorrelation) and no requirement of high resolution tracking data. Additionally, transitions to the stationary or transient phase might be detected where home range calculations are not possible.