Movement Ecology最新文献

American lobster inhabit the unique, brackish Bras d'Or Lake system, although densities are low compared to areas with similar habitats in the Atlantic Ocean. Nevertheless, lobsters are an important part of local First Nation (Mi'kmaq) food and culture. We used acoustic telemetry and habitat mapping, combined with local Mi'kmaw knowledge, to document the movements and habitat use of adult lobsters within a section of the Lake. Movement patterns of acoustically tagged individual lobsters were analyzed with both resource selection functions and integrated step selection functions using data obtained from a high-resolution VEMCO Positioning System within a restricted bay in the Bras d'Or Lake. The resource selection function suggested stronger selections of substrates that contained a combination of soft and hard sediments. While the integrated step selection functions found substantial individual variability in habitat selections, there was a trend for lobsters to exhibit more resident behaviour on the combined soft/hard substrates despite the fact these sediments provided little in the way of obvious shelters for the animals. Adult lobsters at this site have very little risk of predation, which presumably allows them to freely exhibit exploratory behaviours and reduce their association with substrates that provide shelters.

Background: Understanding how landscape characteristics affect animal movement is essential for conservation in human-dominated habitats. A fundamental question is how monoculture agroforests, including rubber and tea plantations, affect wildlife and its movement. Experimental translocations represent an important technique to assess animals' habitat selection while moving through agricultural matrices, especially when complemented with observations of birds' natural movements, and with "control" translocations, in which birds are moved within their natural habitat such as forest. Yet, experimental translocations have been little used for birds outside the Western Hemisphere.

Methods: We conducted experimental translocations and home-range measurements on an understory forest specialist, Brown-capped Babbler (BCBA, Pellorneum fuscocapillus), and a forest generalist, Tickell's Blue Flycatcher (TBFL, Cyornis tickelliae). These species were studied in three rubber plantations, which also included some open areas mostly planted with tea, and in three forest reserves of Sri Lanka.

Results: Four of the five BCBAs translocated within disturbed habitats (rubber plantations) could not return to their capture locations. However, all four individuals within undisturbed habitats (forest reserves) successfully returned to their point of origin within 10.5 daytime hours. In contrast, all TBFLs returned to their capture locations in both disturbed (n = 7) and undisturbed habitats (n = 3) within 11.3 daytime hours. A Cox-proportional survival model demonstrated that the percentage of rubber cover decreased return time, similar to the effect of open-area cover. The home range surveys (n = 13 for BCBA, n = 10 for TBFL) revealed that very little of the birds' natural home-ranges was covered by rubber (0.2% for BCBA, 13.1% for TBFL at 50% Kernel Density Estimates KDE). Home range size for BCBA was approximately half the size in disturbed habitats compared to undisturbed ones, although there was no significant difference between habitats for TBFL.

Conclusions: We conclude that rubber plantations can be impermeable to understory habitat specialist birds, and even generalist species may avoid them long-term. Our findings highlight the potential utility of strips of native vegetation, particularly those featuring understory layers, as corridors to facilitate the movement of forest specialists in landscapes dominated by rubber plantations and other types of disturbed habitats.

Background: Fidelity to a given foraging location or route may be beneficial when environmental conditions are predictable but costly if conditions deteriorate or become unpredictable. Understanding the magnitude of fidelity displayed by different species and the processes that drive or erode it is therefore vital for understanding how fidelity may shape the demographic consequences of anthropogenic change. In particular, understanding the information that individuals may use to adjust their fidelity will facilitate improved predictions of how fidelity may change as environments change and the extent to which it will buffer individuals against such changes.

Methods: We used movement data collected during the breeding season across eight years for common guillemots, Atlantic puffins, razorbills, and black-legged kittiwakes breeding on the Isle of May, Scotland to understand: (1) whether foraging site/route fidelity occurred within and between years, (2) whether the degree of fidelity between trips was predicted by personal foraging effort, and (3) whether different individuals made more similar trips when they overlapped in time at the colony prior to departure and/or when out at sea suggesting the use of the same local environmental cues or information on the decisions made by con- and heterospecifics.

Results: All species exhibited site and route fidelity both within- and between-years, and fidelity between trips in guillemots and razorbills was related to metrics of foraging effort, suggesting they adjust fidelity to their personal foraging experience. We also found evidence that individuals used local environmental cues of prey location or availability and/or information gained by observing conspecifics when choosing foraging routes, particularly in puffins, where trips of individuals that overlapped temporally at the colony or out at sea were more similar.

Conclusions: The fidelity shown by these seabird species has the potential to put them at greater risk in the face of environmental change by driving individuals to continue using areas being degraded by anthropogenic pressures. However, our results suggest that individuals show some flexibility in their fidelity, which may promote resilience under environmental change. The benefits of this flexibility are likely to depend on numerous factors, including the rapidity and spatial scale of environmental change and the reliability of the information individuals use to choose foraging sites or routes, thus highlighting the need to better understand how organisms combine cues, prior experience, and other sources of information to make movement decisions.

The movements and behaviour of mature European sea bass (Dicentrarchus labrax L.) in UK waters have not been studied extensively since a series of mark-recapture experiments during the 1970s, 80s and 90s. To better understand the timing and extent of seasonal migrations, 171 mature sea bass > 42 cm were internally tagged with floated electronic tags programmed to record temperature and depth, and released in the English Channel, in the southern North Sea and in the Irish Sea. Among the 48 tags returned to date, sea bass were at liberty for 370 ± 337 days and were recovered 172 ± 200 km from their respective release locations. Most tags were recovered from beaches (54%), or via the fishery (44%). A comparison of the reconstructed tracks from returned electronic tags with the recapture locations of 237 mark-recapture returns (6.5%) from 3615 sea bass released between 1970 and 2020 showed strong overlap. Seasonal movements between shallow areas (Q2-Q3) and deeper spawning areas (Q4-Q1) were accompanied by elevated vertical swimming speeds and average water temperatures of 8.5 °C in the English Channel and Irish Sea, but lower temperatures in the North Sea. Movements between the Celtic Sea/Irish Sea and the North Sea and vice versa demonstrate high levels of connectivity in UK waters. We demonstrate that a proportion of sea bass remained resident within the North Sea throughout the year, with a strong suggestion that spawning might be occurring. These data have significant implications for the future sustainable management of sea bass stocks in UK and surrounding waters.

The application of supervised machine learning methods to identify behavioural modes from inertial measurements of bio-loggers has become a standard tool in behavioural ecology. Several design choices can affect the accuracy of identifying the behavioural modes. One such choice is the inclusion or exclusion of segments consisting of more than a single behaviour (mixed segments) in the machine learning model training data. Currently, the common practice is to ignore such segments during model training. In this paper we tested the hypothesis that including mixed segments in model training will improve accuracy, as the model would perform better in identifying them in the test data. We test this hypothesis using a series of data simulations on four datasets of accelerometer data coupled with behaviour observations, obtained from four study species (Damaraland mole-rats, meerkats, olive baboons, polar bears). Results show that when a substantial proportion of the test data are mixed behaviour segments (above ~ 10%), including mixed segments in machine learning model training improves the accuracy of classification. These results were consistent across the four study species, and robust to changes in segment length, sample size, and degree of mixture within the mixed segments. However, we also find that in some cases (particularly in baboons) models trained with mixed segments show reduced accuracy in classifying test data containing only single behaviour (pure) segments, compared to models trained without mixed segments. Based on these results, we recommend that when the classification model is expected to deal with a substantial proportion of mixed behaviour segments (> 10%), it is beneficial to include them in model training, otherwise, it is unnecessary but also not harmful. The exception is when there is a basis to assume that the training data contains a higher rate of mixed segments than the actual (unobserved) data to be classified-such a situation may occur particularly when training data are collected in captivity and used to classify data from the wild. In this case, excess inclusion of mixed segments in training data should probably be avoided.

Background: Successive stamen movement is a complex plant behavior involving successive uplift of stamens and pollen release, which plays a role in reducing sexual interference, increasing pollen deposition and promoting pollen export. Although reported from several taxa, studies on whether the movement can be influenced by abiotic and biotic factors are scarce.

Methods: In this study, we here for the first time described a pattern of successive stamen movement in Saxifraga candelabrum (Saxifragaceae). We then compared the rates of stamen movement in S. candelabrum under different weather and varying pollinator visits. Pollen packaging and presentation schedule of S. candelabrum were also investigated.

Results: The results showed that the number of stamens bent per day in sunny days was significantly higher than overcast and rain. Flowers that receive more pollinator visits (control treatment) had significantly higher number of stamen movement than those that received fewer (removal treatment) and none (bagging treatment). Throughout the staminate phase of a flower, there was a progressive increase in both pollen quantity of individual stamens and pollen presentation during each day.

Conclusion: Our research demonstrates that successive stamen movement in S. candelabrum was accelerated by favorable weather and increased pollinator visits, which may promote pollen export. Moreover, incremental pollen packaging is likely an adaptation to seasonal regularity in variations of sex ratio resulting from protandry.

Background: Accurate predictions of animal occurrence in time and space are crucial for informing and implementing science-based management strategies for threatened species.

Methods: We compiled known, available satellite tracking data for pygmy blue whales in the Eastern Indian Ocean (n = 38), applied movement models to define low (foraging and reproduction) and high (migratory) move persistence underlying location estimates and matched these with environmental data. We then used machine learning models to identify the relationship between whale occurrence and environment, and predict foraging and migration habitat suitability in Australia and Southeast Asia.

Results: Our model predictions were validated by producing spatially varying accuracy metrics. We identified the shelf off the Bonney Coast, Great Australian Bight, and southern Western Australia as well as the slope off the Western Australian coast as suitable habitat for migration, with predicted foraging/reproduction suitable habitat in Southeast Asia region occurring on slope and in deep ocean waters. Suitable foraging habitat occurred primarily on slope and shelf break throughout most of Australia, with use of the continental shelf also occurring, predominanly in South West and Southern Australia. Depth of the water column (bathymetry) was consistently a top predictor of suitable habitat for most regions, however, dynamic environmental variables (sea surface temperature, surface height anomaly) influenced the probability of whale occurrence.

Conclusions: Our results indicate suitable habitat is related to dynamic, localised oceanic processes that may occur at fine temporal scales or seasonally. An increase in the sample size of tagged whales is required to move towards developing more dynamic distribution models at seasonal and monthly temporal scales. Our validation metrics also indicated areas where further data collection is needed to improve model accuracy. This is of particular importance for pygmy blue whale management, since threats (e.g., shipping, underwater noise and artificial structures) from the offshore energy and shipping industries will persist or may increase with the onset of an offshore renewable energy sector in Australia.

Background: Migrating birds fly non-stop for hours or even for days. They rely mainly on fat as fuel complemented by a certain amount of protein. Studies on homing pigeons and birds flying in a wind-tunnel suggest that the shares of fat and protein on total energy expenditure vary with flight duration and body fat stores. Also, flight behaviour, such as descending flight, is expected to affect metabolism. However, studies on free flying migrant birds under natural conditions are lacking.

Methods: On a Swiss Alpine pass, we caught three species of nocturnal migrant passerines out of their natural migratory flight. Since most night migrants start soon after dusk, we used time since dusk as a measure of flight duration. We used plasma concentrations of metabolites of the fat, protein, and carbohydrate metabolism as indicators of relative fuel use. We used flight altitudes of birds tracked with radar and with atmospheric pressure loggers to characterize flight behaviour.

Results: The indicators of fat catabolism (triglycerides, very low-density lipoproteins, glycerol) were positively correlated with body energy stores, supporting earlier findings that birds with high fat stores have a higher fat catabolism. As expected, plasma levels of triglycerides, very low-density lipoproteins, glycerol and ß-hydroxy-butyrate increased at the beginning of the night, indicating that nocturnal migrants increased their fat metabolism directly after take-off. Surprisingly, fat catabolism as well as glucose levels decreased in the second half of the night. Data from radar observations showed that the number of birds aloft, their mean height above ground and vertical flight speed decreased after midnight. Together with the findings from atmospheric pressure-loggers put on three species, this shows that nocturnal migrants migrating over continental Europe descend slowly during about 1.5 h before final landfall at night, which results in 11-30% energy savings according to current flight models.

Conclusions: We suggest that this slow descent reduces energy demands to an extent which is noticeable in the plasma concentration of lipid, protein, and carbohydrate metabolites. The slow descent may facilitate the search for a suitable resting habitat and serve to refill glycogen stores needed for foraging and predator escape when landed.

Background: Individual variation in movement strategies of foraging loggerhead turtles have been documented on the scale of tens to hundreds of kilometers within single ocean basins. Use of different strategies among individuals may reflect variations in resources, predation pressure or competition. It is less common for individual turtles to use different foraging strategies on the scale of kilometers within a single coastal bay. We used GPS tags capable of back-filling fine-scale locations to document movement patterns of loggerhead turtles in a coastal bay in Northwest Florida, U.S.A.

Methods: Iridium-linked GPS tags were deployed on loggerhead turtles at a neritic foraging site in Northwest Florida. After filtering telemetry data, point locations were transformed to movement lines and then merged with the original point file to define travel paths and assess travel speed. Home ranges were determined using kernel density function. Diurnal behavioral shifts were examined by examining turtle movements compared to solar time.

Results: Of the 11 turtles tagged, three tracked turtles remained in deep (~ 6 m) water for almost the entire tracking period, while all other turtles undertook movements from deep water locations, located along edges and channels, to shallow (~ 1-2 m) shoals at regular intervals and primarily at night. Three individuals made short-term movements into the Gulf of Mexico when water temperatures dropped, and movement speeds in the Gulf were greater than those in the bay. Turtles exhibited a novel behavior we termed drifting.

Conclusions: This study highlighted the value provided to fine-scale movement studies for species such as sea turtles that surface infrequently by the ability of these GPS tags to store and re-upload data. Future use of these tags at other loggerhead foraging sites, and concurrent with diving and foraging data, would provide a powerful tool to better understand fine-scale movement patterns of sea turtles.

The relationship between animal dispersal and conspecific density has been explored in various study systems but results in terms of both the magnitude and the direction of density dependence are inconsistent. We conducted a thorough review of the literature (2000-2023) and found k = 97 empirical studies of birds, fishes, herpetofauna (amphibians and reptiles), invertebrates, or mammals that had tested for a correlation between conspecific density and animal dispersal. We extracted categorical variables for taxonomic group, sex, age, migratory behavior, study design, dispersal metric, density metric and variable type, as well as temporal and spatial scale, to test each of their correlation with the effect of density on dispersal (Pearson's r) using linear regressions and multilevel mixed-effect modelling. We found certain biases in the published literature, highlighting that the impact of conspecific density on dispersal is not as widespread as it is thought to be. We also found no predominant trend for density-dependent dispersal across taxonomic groups. Instead, results show that the scale and metrics of empirical observations significantly affected analytical results, and heterogeneity measures were high within taxonomic groups. Therefore, the direction and magnitude of the interaction between density and dispersal in empirical studies could partially be attributed to the data collection method involved. We suggest that the contradictory observations for density-dependent dispersal could be explained by dispersal-dependent density, where density is driven by movement instead, and urge researchers to either test this interaction when applicable or consider this perspective when reporting results.