Environmental drivers of autumn migration departure decisions in midcontinental mallards

The efficiency of detecting seabird behaviour from movement patterns: the effect of sampling frequency on inferring movement metrics in Procellariiformes

BACKGROUND

Recent technological advances have resulted in low-cost GPS loggers that are small enough to be used on a range of seabirds, producing accurate location estimates (± 5 m) at sampling intervals as low as 1 s. However, tradeoffs between battery life and sampling frequency result in studies using GPS loggers on flying seabirds yielding locational data at a wide range of sampling intervals. Metrics derived from these data are known to be scale-sensitive, but quantification of these errors is rarely available. Very frequent sampling, coupled with limited movement, can result in measurement error, overestimating movement, but a much more pervasive problem results from sampling at long intervals, which grossly underestimates path lengths.

METHODS

We use fine-scale (1 Hz) GPS data from a range of albatrosses and petrels to study the effect of sampling interval on metrics derived from the data. The GPS paths were sub-sampled at increasing intervals to show the effect on path length (i.e. ground speed), turning angles, total distance travelled, as well as inferred behavioural states.

RESULTS

We show that distances (and per implication ground speeds) are overestimated (4% on average, but up to 20%) at the shortest sampling intervals (1-5 s) and underestimated at longer intervals. The latter bias is greater for more sinuous flights (underestimated by on average 40% when sampling > 1-min intervals) as opposed to straight flight (11%). Although sample sizes were modest, the effect of the bias seemingly varied with species, where species with more sinuous flight modes had larger bias. Sampling intervals also played a large role when inferring behavioural states from path length and turning angles.

CONCLUSIONS

Location estimates from low-cost GPS loggers are appropriate to study the large-scale movements of seabirds when using coarse sampling intervals, but actual flight distances are underestimated. When inferring behavioural states from path lengths and turning angles, moderate sampling intervals (10-30 min) may provide more stable models, but the accuracy of the inferred behavioural states will depend on the time period associated with specific behaviours. Sampling rates have to be considered when comparing behaviours derived using varying sampling intervals and the use of bias-informed analyses are encouraged.

Long-term changes in autumn-winter harvest distributions vary among duck species, months, and subpopulations

Our aim was to describe shifts in autumn and winter harvest distributions of three species of dabbling ducks (blue-winged teal [Spatula discors], mallard [Anas platyrhynchos], and northern pintail [Anas acuta]) in the Central and Mississippi flyways of North America during 1960-2019. We measured shifts in band recovery distributions corrected for changes in hunting season dates and zones by using kernel density estimators to calculate 10 distributional metrics. We then assessed interannual and intraspecific variation by comparing species-specific changes in distributional metrics for 4 months (October-January) and three geographically based subpopulations. During 1960-2019, band recovery distributions shifted west- and southwards (blue-winged teal) or east- and northwards (mallard and northern pintail) by one hundred to several hundred kilometers. For all three species, the broad (95% isopleth) and core distributions (50% isopleth) showed widespread decreases in overlap and increases in relative area compared to a 1960-1979 baseline period. Shifts in band recovery distributions varied by month, with southward shifts for blue-winged teal most pronounced in October and northward shifts for mallard and northern pintail greatest during December and January. Finally, distributional metric response varied considerably among mallard subpopulations, including 2-4-fold differences in longitude, latitude, and overlap, whereas differences among subpopulations were minimal for blue-winged teal and northern pintail. Our findings support the popular notion that winter (December-January) distributions of duck species have shifted north; however, the extent and direction of distributional changes vary among species and subpopulations. Long-term distributional changes are therefore complex and summarizing shifts across species, months, or subpopulations could mask underlying finer-scale patterns that are important to habitat conservation and population management. A detailed understanding of how species distributions have changed over time will help quantify important drivers of species occurrence, identify habitat management options, and could inform decisions on where to focus conservation or restoration efforts.

Marginal value analysis reveals shifting importance of migration habitat for waterfowl under a changing climate

Migratory waterfowl are an important resource for consumptive and non-consumptive users alike and provide tremendous economic value in North America. These birds rely on a complex matrix of public and private land for forage and roosting during migration and wintering periods, and substantial conservation effort focuses on increasing the amount and quality of target habitat. Yet, the value of habitat is a function not only of a site's resources but also of its geographic position and weather. To quantify this value, we used a continental-scale energetics-based model of daily dabbling duck movement to assess the marginal value of lands across the contiguous United States during the non-breeding period (September to May). We examined effects of eliminating each habitat node (32 × 32 km) in both a particularly cold and a particularly warm winter, asking which nodes had the largest effect on survival. The marginal value of habitat nodes for migrating dabbling ducks was a function of forage and roosting habitat but, more importantly, of geography (especially latitude and region). Irrespective of weather, nodes in the Southeast, central East Coast, and California made the largest positive contributions to survival. Conversely, nodes in the Midwest, Northeast, Florida, and the Pacific Northwest had consistent negative effects. Effects (positive and negative) of more northerly nodes occurred in late fall or early spring when climate was often severe and was most variable. Importance and effects of many nodes varied considerably between a cold and a warm winter. Much of the Midwest and central Great Plains benefited duck survival in a warm winter, and projected future warming may improve the value of lands in these regions, including many National Wildlife Refuges, for migrating dabbling ducks. Our results highlight the geographic variability in habitat value, as well as shifts that may occur in these values due to climate change.

Factors influencing autumn-winter movements of midcontinent Mallards and consequences for harvest and habitat management

Annual phenology and distributions of migratory wildlife have been noticeably influenced by climate change, leading to concerns about sustainable populations. Recent studies exploring conditions influencing autumn migration departure have provided conflicting insights regarding factors influencing the movements of Mallards (Anas platyrhynchos), a popular game species. We determined factors affecting timing and magnitude of long-distance movements of 97 juvenile Mallards during autumn-winter across the midcontinent of North America marked with implanted transmitters in North and South Dakota, 2018-2019. Factors influencing variation in movement timing, along with direction and magnitudes, depended on type of movement (i.e., regional [25-310 km], initial migration, or subsequent migration movements [>310 km]). Photoperiod influenced probability of initiating all movements, although the effect was most influential for regional movements. Minimum temperature most influenced initial migration events (probability of movement increased 29% for each 1°C decrease); favorable winds also increased likelihood of initial migration events. Probability of subsequent migration events increased 80% for each 1 cm increase in depth of snow. Subsequent migration movements also were 2.0 times more likely to occur on weekend days, indicating disturbance from humans may influence movements. Migration distances increased 166 km for each 1°C reduction in minimum temperature. We also observed markedly different autumn-winter distributions of marked birds between years. Median locations during autumn-winter 2018-2019 were ~250 km farther north and ~300 km farther west during mid-December-January compared to the same time in 2019-2020. Concurrently, harvest rates for marked females and males were 10% and 26% during autumn-winter 2018-2019 and 26% and 31% during autumn-winter 2019-2020. Climate-related changes may result in increasingly variable autumn-winter distributions, with implications for wildlife recreationalists, conservation planners, and harvest managers.

Genomic evidence indicates small island-resident populations and sex-biased behaviors of Hawaiian reef Manta Rays

BACKGROUND

Reef manta rays (Mobula alfredi) are globally distributed in tropical and subtropical seas. Their life history traits (slow growth, late maturity, low reproductive output) make them vulnerable to perturbations and therefore require informed management strategies. Previous studies have reported wide-spread genetic connectivity along continental shelves suggesting high gene flow along continuous habitats spanning hundreds of kilometers. However, in the Hawaiian Islands, tagging and photo-identification evidence suggest island populations are isolated despite proximity, a hypothesis that has not yet been evaluated with genetic data.

RESULTS

This island-resident hypothesis was tested by analyzing whole mitogenome haplotypes and 2048 nuclear single nucleotide polymorphisms (SNPs) between M. alfredi (n = 38) on Hawai'i Island and Maui Nui (the 4-island complex of Maui, Moloka'i, Lāna'i and Kaho'olawe). Strong divergence in the mitogenome (ΦST = 0.488) relative to nuclear genome-wide SNPs (neutral FST = 0.003; outlier FST = 0.186), and clustering of mitochondrial haplotypes among islands provides robust evidence that female reef manta rays are strongly philopatric and do not migrate between these two island groups. Combined with restricted male-mediated migration, equivalent to a single male moving between islands every 2.2 generations (~ 64 years), we provide evidence these populations are significantly demographically isolated. Estimates of contemporary effective population size (Ne) are 104 (95% CI: 99-110) in Hawai'i Island and 129 (95% CI: 122-136) in Maui Nui.

CONCLUSIONS

Concordant with evidence from photo identification and tagging studies, these genetic results indicate reef manta rays in Hawai'i have small, genetically-isolated resident island populations. We hypothesize that due to the Island Mass Effect, large islands provide sufficient resources to support resident populations, thereby making crossing deep channels separating island groups unnecessary. Small effective population size, low genetic diversity, and k-selected life history traits make these isolated populations vulnerable to region-specific anthropogenic threats, which include entanglement, boat strikes, and habitat degradation. The long-term persistence of reef manta rays in the Hawaiian Islands will require island-specific management strategies.

Predictive model of sperm whale prey capture attempts from time-depth data

BACKGROUND

High-resolution sound and movement recording tags offer unprecedented insights into the fine-scale foraging behaviour of cetaceans, especially echolocating odontocetes, enabling the estimation of a series of foraging metrics. However, these tags are expensive, making them inaccessible to most researchers. Time-Depth Recorders (TDRs), which have been widely used to study diving and foraging behaviour of marine mammals, offer a more affordable alternative. Unfortunately, data collected by TDRs are bi-dimensional (time and depth only), so quantifying foraging effort from those data is challenging.

METHODS

A predictive model of the foraging effort of sperm whales (Physeter macrocephalus) was developed to identify prey capture attempts (PCAs) from time-depth data. Data from high-resolution acoustic and movement recording tags deployed on 12 sperm whales were downsampled to 1 Hz to match the typical TDR sampling resolution and used to predict the number of buzzes (i.e., rapid series of echolocation clicks indicative of PCAs). Generalized linear mixed models were built for dive segments of different durations (30, 60, 180 and 300 s) using multiple dive metrics as potential predictors of PCAs.

RESULTS

Average depth, variance of depth and variance of vertical velocity were the best predictors of the number of buzzes. Sensitivity analysis showed that models with segments of 180 s had the best overall predictive performance, with a good area under the curve value (0.78 ± 0.05), high sensitivity (0.93 ± 0.06) and high specificity (0.64 ± 0.14). Models using 180 s segments had a small difference between observed and predicted number of buzzes per dive, with a median of 4 buzzes, representing a difference in predicted buzzes of 30%.

CONCLUSIONS

These results demonstrate that it is possible to obtain a fine-scale, accurate index of sperm whale PCAs from time-depth data alone. This work helps leveraging the potential of time-depth data for studying the foraging ecology of sperm whales and the possibility of applying this approach to a wide range of echolocating cetaceans. The development of accurate foraging indices from low-cost, easily accessible TDR data would contribute to democratize this type of research, promote long-term studies of various species in several locations, and enable analyses of historical datasets to investigate changes in cetacean foraging activity.

Movement predictability of individual barn owls facilitates estimation of home range size and survival

BACKGROUND

There is growing attention to individuality in movement, its causes and consequences. Similarly to other well-established personality traits (e.g., boldness or sociability), conspecifics also differ repeatedly in their spatial behaviors, forming behavioral types ("spatial-BTs"). These spatial-BTs are typically described as the difference in the mean-level among individuals, and the intra-individual variation (IIV, i.e., predictability) is only rarely considered. Furthermore, the factors determining predictability or its ecological consequences for broader space-use patterns are largely unknown, in part because predictability was mostly tested in captivity (e.g., with repeated boldness assays). Here we test if (i) individuals differ in their movement and specifically in their predictability. We then investigate (ii) the consequences of this variation for home-range size and survival estimates, and (iii) the factors that affect individual predictability.

METHODS

We tracked 92 barn owls (Tyto alba) with an ATLAS system and monitored their survival. From these high-resolution (every few seconds) and extensive trajectories (115.2 ± 112.1 nights; X̅ ± SD) we calculated movement and space-use indices (e.g., max-displacement and home-range size, respectively). We then used double-hierarchical and generalized linear mix-models to assess spatial-BTs, individual predictability in nightly max-displacement, and its consistency across time. Finally, we explored if predictability levels were associated with home-range size and survival, as well as the seasonal, geographical, and demographic factors affecting it (e.g., age, sex, and owls' density).

RESULTS

Our dataset (with 74 individuals after filtering) revealed clear patterns of individualism in owls' movement. Individuals differed consistently both in their mean movement (e.g., max-displacement) and their IIV around it (i.e., predictability). More predictable individuals had smaller home-ranges and lower survival rates, on top and beyond the expected effects of their spatial-BT (max-displacement), sex, age and ecological environments. Juveniles were less predictable than adults, but the sexes did not differ in their predictability.

CONCLUSION

These results demonstrate that individual predictability may act as an overlooked axis of spatial-BT with potential implications for relevant ecological processes at the population level and individual fitness. Considering how individuals differ in their IIV of movement beyond the mean-effect can facilitate understanding the intraspecific diversity, predicting their responses to changing ecological conditions and their population management.