Movement Ecology最新文献

Background: Migratory birds generally have tightly scheduled annual cycles, in which delays can have carry-over effects on the timing of later events, ultimately impacting reproductive output. Whether temporal carry-over effects are more pronounced among migrations over larger distances, with tighter schedules, is a largely unexplored question.

Methods: We tracked individual Arctic Skuas Stercorarius parasiticus, a long-distance migratory seabird, from eight breeding populations between Greenland and Siberia using light-level geolocators. We tested whether migration schedules among breeding populations differ as a function of their use of seven widely divergent wintering areas across the Atlantic Ocean, Mediterranean Sea and Indian Ocean.

Results: Breeding at higher latitudes led not only to later reproduction and migration, but also faster spring migration and shorter time between return to the breeding area and clutch initiation. Wintering area was consistent within individuals among years; and more distant areas were associated with more time spent on migration and less time in the wintering areas. Skuas adjusted the period spent in the wintering area, regardless of migration distance, which buffered the variation in timing of autumn migration. Choice of wintering area had only minor effects on timing of return at the breeding area and timing of breeding and these effects were not consistent between breeding populations.

Conclusion: The lack of a consistent effect of wintering area on timing of return between breeding areas indicates that individuals synchronize their arrival with others in their population despite extensive individual differences in migration strategies.

Background: Ecological and physical conditions vary with depth in aquatic ecosystems, resulting in gradients of habitat suitability. Although variation in vertical distributions among individuals provides evidence of habitat selection, it has been challenging to disentangle how processes at multiple spatio-temporal scales shape behaviour.

Methods: We collected thousands of observations of depth from $>300$ acoustically tagged adult Chinook salmon Oncorhynchus tshawytscha, spanning multiple seasons and years. We used these data to parameterize a machine-learning model to disentangle the influence of spatial, temporal, and dynamic oceanographic variables while accounting for differences in individual condition and maturation stage.

Results: The top performing machine learning model used bathymetric depth ratio (i.e., individual depth relative to seafloor depth) as a response. We found that bathymetry, season, maturation stage, and spatial location most strongly influenced Chinook salmon depth. Chinook salmon bathymetric depth ratios were deepest in shallow water, during winter, and for immature individuals. We also identified non-linear interactions among covariates, resulting in spatially-varying effects of zooplankton concentration, lunar cycle, temperature and oxygen concentration.

Conclusions: Our results suggest Chinook salmon vertical habitat use is a function of ecological interactions, not physiological constraints. Temporal and spatial variation in depth distributions could be used to guide management decisions intended to reduce fishery impacts on Chinook salmon. More generally, our findings demonstrate how complex interactions among bathymetry, seasonality, location, and life history stage regulate vertical habitat selection.

Background: Interaction analysis via movement in space and time contributes to understanding social relationships among individuals and their dynamics in ecological systems. While there is an exciting growth in research in computational methods for interaction analysis using movement data, there remain challenges regarding reproducibility and replicability of the existing approaches. The current movement interaction analysis tools are often less accessible or tested for broader use in ecological research.

Results: To address these challenges, this paper presents ORTEGA, an Object-oRiented TimE-Geographic Analytical tool, as an open-source Python package for analyzing potential interactions between pairs of moving entities based on the observation of their movement. ORTEGA is developed based on one of the newly emerged time-geographic approaches for quantifying space-time interaction patterns among animals. A case study is presented to demonstrate and evaluate the functionalities of ORTEGA in tracing dynamic interaction patterns in animal movement data. Besides making the analytical code and data freely available to the community, the developed package also offers an extension of the existing theoretical development of ORTEGA for incorporating a context-aware ability to inform interaction analysis.

Conclusions: ORTEGA contributes two significant capabilities: (1) the functions to identify potential interactions (e.g., encounters, concurrent interactions, delayed interactions) from movement data of two or more entities using a time-geographic-based approach; and (2) the capacity to compute attributes of potential interaction events including start time, end time, interaction duration, and difference in movement parameters such as speed and moving direction, and also contextualize the identified potential interaction events.

Background: Understanding how to connect habitat remnants to facilitate the movement of species is a critical task in an increasingly fragmented world impacted by human activities. The identification of dispersal routes and corridors through connectivity analysis requires measures of landscape resistance but there has been no consensus on how to calculate resistance from habitat characteristics, potentially leading to very different connectivity outcomes.

Methods: We propose a new model, called the Time-Explicit Habitat Selection (TEHS) model, that can be directly used for connectivity analysis. The TEHS model decomposes the movement process in a principled approach into a time and a selection component, providing complementary information regarding space use by separately assessing the drivers of time to traverse the landscape and the drivers of habitat selection. These models are illustrated using GPS-tracking data from giant anteaters (Myrmecophaga tridactyla) in the Pantanal wetlands of Brazil.

Results: The time model revealed that the fastest movements tended to occur between 8 p.m. and 5 a.m., suggesting a crepuscular/nocturnal behavior. Giant anteaters moved faster over wetlands while moving much slower over forests and savannas, in comparison to grasslands. We also found that wetlands were consistently avoided whereas forest and savannas tended to be selected. Importantly, this model revealed that selection for forest increased with temperature, suggesting that forests may act as important thermal shelters when temperatures are high. Finally, using the spatial absorbing Markov chain framework, we show that the TEHS model results can be used to simulate movement and connectivity within a fragmented landscape, revealing that giant anteaters will often not use the shortest-distance path to the destination patch due to avoidance of certain habitats.

Conclusions: The proposed approach can be used to characterize how landscape features are perceived by individuals through the decomposition of movement patterns into a time and a habitat selection component. Additionally, this framework can help bridge the gap between movement-based models and connectivity analysis, enabling the generation of time-explicit connectivity results.

Many baleen whales are renowned for their acoustic communication. Under pristine conditions, this communication can plausibly occur across hundreds of kilometres. Frequent vocalisations may allow a dispersed migrating group to maintain contact, and therefore benefit from improved navigation via the "wisdom of the crowd". Human activities have considerably inflated ocean noise levels. Here we develop a data-driven mathematical model to investigate how ambient noise levels may inhibit whale migration. Mathematical models allow us to simultaneously simulate collective whale migration behaviour, auditory cue detection, and noise propagation. Rising ambient noise levels are hypothesised to influence navigation through three mechanisms: (i) diminished communication space; (ii) reduced ability to hear external sound cues and; (iii) triggering noise avoidance behaviour. Comparing pristine and current soundscapes, we observe navigation impairment that ranges from mild (increased journey time) to extreme (failed navigation). Notably, the three mechanisms induce qualitatively different impacts on migration behaviour. We demonstrate the model's potential predictive power, exploring the extent to which migration may be altered under future shipping and construction scenarios.

Diadromous fish such as the European eel (Anguilla anguilla L.) are hampered by a high density of barriers in estuaries and freshwater systems. Modified and fragmented waterbodies lack tidal flows, and habitat may be less accessible and underutilized compared to free-flowing rivers and estuaries. With rising sea levels and increased occurrence of droughts, the number of barriers may further increase, implying that the need to study migration in such areas may even become more urgent worldwide. To study glass eel migration and behaviour in such highly modified water systems, a mark-recapture study was carried out in the North Sea Canal (NSC) basin, which drains into the North Sea via a large sluice complex. In total, eight uniquely tagged groups (3,797 glass eels) were released near the sluice complex, and 11 groups (2,663 glass eels) were released at inland barriers upstream over a 28 km long stretch in the NSC in spring 2018. The sluice complex attracted 10.3 million glass eel and did not block or delay their immigration. The large and diurnally intensively used coastal ship locks and allowings some saltwater intrusion, efficiently facilitated glass eel migration. Once in the NSC, water outlets from adjacent polders attracted glass eels relative proportional to the discharge of pumping stations. In the NSC, average migration speeds of 0.7 km/day (max. 1.8 km/day) were measured, and this increased with higher temperatures. Redistribution of glass eel from accumulations at inland barriers to other outlet locations was observed in both upstream and downstream directions in the NSC. Passage success and residence time ('delays' of 4.1-13.7 days) varied between the different inland barriers. Most of the glass eel, however, appears to settle in the easily accessible habitats within the brackish NSC catchment. This study combined an integral assessment of successive bottlenecks in a modified inland water system.

Background: Natal dispersal, the distance between site of birth and site of first breeding, has a fundamental role in population dynamics and species' responses to environmental changes. Population density is considered a key driver of natal dispersal. However, few studies have been able to examine densities at both the natal and the settlement site, which is critical for understanding the role of density in dispersal. Additionally, the role of density on natal dispersal remains poorly understood in long-lived and slowly reproducing species, due to their prolonged dispersal periods and often elusive nature. We studied the natal dispersal of the white-tailed eagle (Haliaeetus albicilla) in response to local breeder densities. We investigated the effects of the number of active territories around the natal site on (a) natal dispersal distance and (b) the difference between natal and settlement site breeder density. We were interested in whether eagles showed tendencies of conspecific attraction (positive density-dependence) or intraspecific competition (negative density-dependence) and how this related to settlement site breeder density.

Methods: We used a combination of long-term visual and genotypic identification to match individuals from their breeding site to their natal nest. We identified natal dispersal events for 355 individuals hatched between 1984 and 2015 in the Baltic Sea coast and Arctic areas of Finland. Of those, 251 were identified by their genotype.

Results: Individuals born in high-density areas dispersed shorter distances than those born in low-density areas, but settled at lower density breeding sites in comparison to their natal site. Eagles born in low natal area densities dispersed farther but settled in higher density breeding sites compared to their natal site.

Conclusions: We show that eagles might be attracted by conspecifics (positive density-dependence) to identify high-quality habitats or find mates, but do not settle in the most densely populated areas. This indicates that natal dispersal is affected by an interplay of conspecific attraction and intraspecific competition, which has implications for population dynamics of white-tailed eagles, but also other top predators. Furthermore, our study demonstrates the value of long-term collection of both nestling and (non-invasive) adult DNA samples, and thereafter using genotype matching to identify individuals in long-lived and elusive species.

Background: The process known as ecological diffusion emerges from a first principles view of animal movement, but ecological diffusion and other partial differential equation models can be difficult to fit to data. Step-selection functions (SSFs), on the other hand, have emerged as powerful practical tools for ecologists studying the movement and habitat selection of animals.

Methods: SSFs typically involve comparing resources between a set of used and available points at each step in a sequence of observed positions. We use change of variables to show that ecological diffusion implies certain distributions for available steps that are more flexible than others commonly used. We then demonstrate advantages of these distributions with SSF models fit to data collected for a mountain lion in Colorado, USA.

Results: We show that connections between ecological diffusion and SSFs imply a Rayleigh step-length distribution and uniform turning angle distribution, which can accommodate data collected at irregular time intervals. The results of fitting an SSF model with these distributions compared to a set of commonly used distributions revealed how precision and inference can vary between the two approaches.

Conclusions: Our new continuous-time step-length distribution can be integrated into various forms of SSFs, making them applicable to data sets with irregular time intervals between successive animal locations.