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.

Barnacle geese Branta leucopsis breeding on Novaya Zemlya: current distribution and population size estimated from tracking data

The Russian breeding population of barnacle geese Branta leucopsis has shown a rapid increase in numbers since 1980, which has coincided with a southwest-wards breeding range expansion within the Russian Arctic. Here barnacle geese also started to occupy coastal and marsh land habitats, in which they were not know to nest on their traditional breeding grounds. While these changes have been well documented by studies and observations throughout the new breeding range of barnacle geese, observations are lacking from the traditional breeding grounds on Novaya Zemlya, as this area is remote and difficult to access. This is especially relevant given rapid climate warming in this area, which may impact local distribution and population size. We used GPS-tracking and behavioural biologging data from 46 individual barnacle geese captured on their wintering grounds to locate nest sites in the Russian Arctic and study nesting distribution in 2008–2010 and 2018–2020. Extrapolating from nest counts on Kolguev Island, we estimate the breeding population on Novaya Zemlya in 2018–2020 to range around 75,250 pairs although the confidence interval around this estimate was large. A comparison with the historical size of the barnacle goose population suggests an increase in the breeding population on Novaya Zemlya, corresponding with changes in other areas of the breeding range. Our results show that many barnacle geese on Novaya Zemlya currently nest on lowland tundra on Gusinaya Zemlya Peninsula. This region has been occupied by barnacle geese only since 1990 and appears to be mainly available for nesting in years with early spring. Tracking data are a valuable tool to increase our knowledge of remote locations, but counts of breeding individuals or nests are needed to further corroborate estimates of breeding populations based on tracking data.

Changes in Behaviour and Proxies of Physiology Suggest Individual Variation in the Building of Migratory Phenotypes in Preparation for Long-Distance Flights

Long-distance migration in birds is a complex syndrome that involves high energy costs and, in some species, substantial physiological re-organisation. Such flexible migratory phenotypes are commonly associated with bird species flying non-stop across vast ecological barriers, where there are few opportunities to stop and refuel en route. Prior to making migratory flights, some species have been found to atrophy organs that are not required (e.g., digestive organs) and grow those associated with powering flight (pectora muscles and heart), presumably to optimise costs. However, most studies of this flexibility have required sacrificing study animals and this has limited our capacity to measure individual variation and its potential consequences. Here we investigate the behavioural and, indirectly, physiological adaptation of an arctic breeding long-distance migrant the light-bellied brent goose Branta bernicla hrota, during spring staging in southwest Iceland. We use a sequential sampling approach to record behavioural observations and conduct stable isotope analysis of faecal samples from uniquely marked individuals to assess protein catabolism. Individuals showed a three-phase fuel deposition process, with initial slow intake rates followed by hyperphagia and then a period of inactivity immediately prior to migratory departure (despite multiple days with favourable wind conditions). The C:N ratio and δ15N values in faeces were significantly linked to fat deposition during the latter stages and suggests catabolism (reorganisation of proteins) occurring prior to departure. Our results suggest a strategic delay in migratory departure to enable reorganisation into a flying phenotype and that the extent of this varies among individuals.

Migration distance affects how closely Eurasian wigeons follow spring phenology during migration

BACKGROUND

The timing of migration for herbivorous migratory birds is thought to coincide with spring phenology as emerging vegetation supplies them with the resources to fuel migration, and, in species with a capital breeding strategy also provides individuals with energy for use on the breeding grounds. Individuals with very long migration distances might however have to trade off between utilising optimal conditions en route and reaching the breeding grounds early, potentially leading to them overtaking spring on the way. Here, we investigate whether migration distance affects how closely individually tracked Eurasian wigeons follow spring phenology during spring migration.

METHODS

We captured wigeons in the Netherlands and Lithuania and tracked them throughout spring migration to identify staging sites and timing of arrival. Using temperature-derived indicators of spring phenology, we investigated how maximum longitude reached and migration distance affected how closely wigeons followed spring. We further estimated the impact of tagging on wigeon migration by comparing spring migratory timing between tracked individuals and ring recovery data sets.

RESULTS

Wigeons migrated to locations between 300 and 4000 km from the capture site, and migrated up to 1000 km in a single day. We found that wigeons migrating to more north-easterly locations followed spring phenology more closely, and increasingly so the greater distance they had covered during migration. Yet we also found that despite tags equalling only around 2% of individual's body mass, individuals were on average 11-12 days slower than ring-marked individuals from the same general population.

DISCUSSION

Overall, our results suggest that migratory strategy can vary dependent on migration distance within species, and even within the same migratory corridor. Individual decisions thus depend not only on environmental cues, but potentially also trade-offs made during later life-history stages.

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.

Arctic Geese Tune Migration to a Warming Climate but Still Suffer from a Phenological Mismatch

Climate warming challenges animals to advance their timing of reproduction [1], but many animals appear to be unable to advance at the same rate as their food species [2, 3]. As a result, mismatches can arise between the moment of largest food requirements for their offspring and peak food availability [4-6], with important fitness consequences [7]. For long-distance migrants, adjustment of phenology to climate warming may be hampered by their inability to predict the optimal timing of arrival at the breeding grounds from their wintering grounds [8]. Arrival can be advanced if birds accelerate migration by reducing time on stopover sites [9, 10], but a recent study suggests that most long-distance migrants are on too tight a schedule to do so [11]. This may be different for capital-breeding migrants, which use stopovers not only to fuel migration but also to acquire body stores needed for reproduction [12-14]. By combining multiple years of tracking and reproduction data, we show that a long-distance migratory bird (the barnacle goose, Branta leucopsis) accelerates its 3,000 km spring migration to advance arrival on its rapidly warming Arctic breeding grounds. As egg laying has advanced much less than arrival, they still encounter a phenological mismatch that reduces offspring survival. A shift toward using more local resources for reproduction suggests that geese first need to refuel body stores at the breeding grounds after accelerated migration. Although flexibility in body store use allows migrants to accelerate migration, this cannot solve the time constraint they are facing under climate warming.