Agricultural pastures challenge the attractiveness of natural saltmarsh for a migratory goose

Earlier springs increase goose breeding propensity and nesting success at Arctic but not at temperate latitudes

Intermittent breeding is an important tactic in long-lived species that trade off survival and reproduction to maximize lifetime reproductive success. When breeding conditions are unfavourable, individuals are expected to skip reproduction to ensure their own survival. Breeding propensity (i.e. the probability for a mature female to breed in a given year) is an essential parameter in determining reproductive output and population dynamics, but is not often studied in birds because it is difficult to obtain unbiased estimates. Breeding conditions are especially variable at high latitudes, potentially resulting in a large effect on breeding propensity of Arctic-breeding migratory birds, such as geese. With a novel approach, we used GPS-tracking data to determine nest locations, breeding propensity and nesting success of barnacle geese, and studied how these varied with breeding latitude and timing of arrival on the breeding grounds relative to local onset of spring. Onset of spring at the breeding grounds was a better predictor of breeding propensity and nesting success than relative timing of arrival. At Arctic latitudes (>66° N), breeding propensity decreased from 0.89 (95% CI: 0.65-0.97) in early springs to 0.22 (95% CI: 0.06-0.55) in late springs, while at temperate latitudes, it varied between 0.75 (95% CI: 0.38-0.93) and 0.89 (95% CI: 0.41-0.99) regardless of spring phenology. Nesting success followed a similar pattern and was lower in later springs at Arctic latitudes, but not at temperate latitudes. In early springs, a larger proportion of geese started breeding despite arriving late relative to the onset of spring, possibly because the early spring enabled them to use local resources to fuel egg laying and incubation. While earlier springs due to climate warming are considered to have mostly negative repercussions on reproductive success through phenological mismatches, our results suggest that these effects may partly be offset by higher breeding propensity and nesting success.

Year-round activity levels reveal diurnal foraging constraints in the annual cycle of migratory and non-migratory barnacle geese

Performing migratory journeys comes with energetic costs, which have to be compensated within the annual cycle. An assessment of how and when such compensation occurs is ideally done by comparing full annual cycles of migratory and non-migratory individuals of the same species, which is rarely achieved. We studied free-living migratory and resident barnacle geese belonging to the same flyway (metapopulation), and investigated when differences in foraging activity occur, and when foraging extends beyond available daylight, indicating a diurnal foraging constraint in these usually diurnal animals. We compared foraging activity of migratory (N = 94) and resident (N = 30) geese throughout the annual cycle using GPS-transmitters and 3D-accelerometers, and corroborated this with data on seasonal variation in body condition. Migratory geese were more active than residents during most of the year, amounting to a difference of over 370 h over an entire annual cycle. Activity differences were largest during the periods that comprised preparation for spring and autumn migration. Lengthening days during spring facilitated increased activity, which coincided with an increase in body condition. Both migratory and resident geese were active at night during winter, but migratory geese were also active at night before autumn migration, resulting in a period of night-time activity that was 6 weeks longer than in resident geese. Our results indicate that, at least in geese, seasonal migration requires longer daily activity not only during migration but throughout most of the annual cycle, with migrants being more frequently forced to extend foraging activity into the night.

Nocturnal foraging lifts time constraints in winter for migratory geese but hardly speeds up fueling

Climate warming advances the optimal timing of breeding for many animals. For migrants to start breeding earlier, a concurrent advancement of migration is required, including premigratory fueling of energy reserves. We investigate whether barnacle geese are time constrained during premigratory fueling and whether there is potential to advance or shorten the fueling period to allow an earlier migratory departure. We equipped barnacle geese with GPS trackers and accelerometers to remotely record birds’ behavior, from which we calculated time budgets. We examined how time spent foraging was affected by the available time (during daylight and moonlit nights) and thermoregulation costs. We used an energetic model to assess onset and rates of fueling and whether geese can further advance fueling by extending foraging time. We show that, during winter, when facing higher thermoregulation costs, geese consistently foraged at night, especially during moonlit nights, in order to balance their energy budgets. In spring, birds made use of the increasing day length and gained body stores by foraging longer during the day, but birds stopped foraging extensively during the night. Our model indicates that, by continuing nighttime foraging throughout spring, geese may have some leeway to advance and increase fueling rate, potentially reaching departure body mass 4 days earlier. In light of rapid climatic changes on the breeding grounds, whether this advancement can be realized and whether it will be sufficient to prevent phenological mismatches remains to be determined.

An evaluation of machine learning classifiers for next-generation, continuous-ethogram smart trackers

BACKGROUND

Our understanding of movement patterns and behaviours of wildlife has advanced greatly through the use of improved tracking technologies, including application of accelerometry (ACC) across a wide range of taxa. However, most ACC studies either use intermittent sampling that hinders continuity or continuous data logging relying on tracker retrieval for data downloading which is not applicable for long term study. To allow long-term, fine-scale behavioural research, we evaluated a range of machine learning methods for their suitability for continuous on-board classification of ACC data into behaviour categories prior to data transmission.

METHODS

We tested six supervised machine learning methods, including linear discriminant analysis (LDA), decision tree (DT), support vector machine (SVM), artificial neural network (ANN), random forest (RF) and extreme gradient boosting (XGBoost) to classify behaviour using ACC data from three bird species (white stork Ciconia ciconia, griffon vulture Gyps fulvus and common crane Grus grus) and two mammals (dairy cow Bos taurus and roe deer Capreolus capreolus).

RESULTS

Using a range of quality criteria, SVM, ANN, RF and XGBoost performed well in determining behaviour from ACC data and their good performance appeared little affected when greatly reducing the number of input features for model training. On-board runtime and storage-requirement tests showed that notably ANN, RF and XGBoost would make suitable on-board classifiers.

CONCLUSIONS

Our identification of using feature reduction in combination with ANN, RF and XGBoost as suitable methods for on-board behavioural classification of continuous ACC data has considerable potential to benefit movement ecology and behavioural research, wildlife conservation and livestock husbandry.

COVID19-induced reduction in human disturbance enhances fattening of an overabundant goose species

Overabundant species can have major impacts on their habitat and induce trophic cascades within ecosystems. In North America, the overabundant greater snow goose (Anser caerulescens atlanticus) has been successfully controlled through special spring hunting regulations since 1999. Hunting is a source of mortality but also of disturbance, which affects the behavior and nutrient storage dynamics of staging snow geese. In 2020, the lockdown imposed by the COVID19 pandemic reduced hunting activity during their migratory stopover in Québec by at least 31%. This provided a unique opportunity to assess the effects of a sudden reduction in hunting disturbance on geese. We used long-term data on body mass combined with movement data from GPS-tracked birds in 2019 and 2020 to assess the effects of the 2020 lockdown on the spring body condition and behavior of greater snow geese. Body condition was higher in 2020 than in all years since the inception of spring hunting in 1999, except for 2019. However, in 2020 geese reached maximal body condition earlier during the staging period than in any other year and reduced by half time spent feeding in highly profitable but risky agricultural habitat in late spring compared to 2019. Although our study was not designed to evaluate the effects of the lockdown, the associated reduction in disturbance in 2020 supports the hypothesis that hunting-related disturbance negatively affects foraging efficiency and body condition in geese. Since spring body condition is related to subsequent breeding success, the lockdown could increase productivity in this overabundant population.

Less is more: On-board lossy compression of accelerometer data increases biologging capacity

GPS‐tracking devices have been used in combination with a wide range of additional sensors to study animal behaviour, physiology and interaction with their environment. Tri‐axial accelerometers allow researchers to remotely infer the behaviour of individuals, at all places and times. Collection of accelerometer data is relatively cheap in terms of energy usage, but the amount of raw data collected generally requires much storage space and is particularly demanding in terms of energy needed for data transmission.

Here, we propose compressing the raw accelerometer (ACC) data into summary statistics within the tracking device (before transmission) to reduce data size, as a means to overcome limitations in storage and energy capacity.

We explored this type of lossy data compression in the accelerometer data of tagged Bewick's swans Cygnus columbianus bewickii collected in spring 2017. Using software settings in which bouts of 2 s of both raw ACC data and summary statistics were collected in parallel but with different bout intervals to keep total data size comparable, we created the opportunity for a direct comparison of time budgets derived by the two data collection methods.

We found that the data compression in our case yielded a six times reduction in data size per bout, and concurrent, similar decreases in storage and energy use of the device. We show that with the same accuracy of the behavioural classification, the freed memory and energy of the device can be used to increase the monitoring effort, resulting in a more detailed representation of the individuals’ time budget. Rare and/or short behaviours, such as daily roost flights, were picked up significantly more when collecting summary statistics instead of raw ACC data (but note differences in sampling rate). Such level of detail can be of essential importance, for instance to make a reliable estimate of the energy budgets of individuals.

In conclusion, we argue that this type of lossy data compression can be a well‐considered choice in study situations where limitations in energy and storage space of the device pose a problem. Ultimately, these developments can allow for long‐term and nearly continuous remote monitoring of the behaviour of free‐ranging animals.

Ontogenetic niche shifts as a driver of seasonal migration

Ontogenetic niche shifts have helped to understand population dynamics. Here we show that ontogenetic niche shifts also offer an explanation, complementary to traditional concepts, as to why certain species show seasonal migration. We describe how demographic processes (survival, reproduction and migration) and associated ecological requirements of species may change with ontogenetic stage (juvenile, adult) and across the migratory range (breeding, non-breeding). We apply this concept to widely different species (dark-bellied brent geese (Branta b. bernicla), humpback whales (Megaptera novaeangliae) and migratory Pacific salmon (Oncorhynchus gorbuscha) to check the generality of this hypothesis. Consistent with the idea that ontogenetic niche shifts are an important driver of seasonal migration, we find that growth and survival of juvenile life stages profit most from ecological conditions that are specific to breeding areas. We suggest that matrix population modelling techniques are promising to detect the importance of the ontogenetic niche shifts in maintaining migratory strategies. As a proof of concept, we applied a first analysis to resident, partial migratory and fully migratory populations of barnacle geese (Branta leucopsis). We argue that recognition of the costs and benefits of migration, and how these vary with life stages, is important to understand and conserve migration under global environmental change.