Many migratory herbivores seem to follow the flush of plant growth during migration in order to acquire the most nutrient-rich plants. This has also been hypothesized for arctic-breeding geese, but so far no test of this so-called green wave hypothesis has been performed at the individual level. During four years, a total of 30 greater white-fronted geese Anser albifrons albifrons was tracked using GPS transmitters, of which 13 yielded complete spring migration tracks. From those birds we defined stopover sites and related the date of arrival at each of these stopovers to temperature sum (growing degree days, GDD), snow cover, accumulated photoperiod and latitude. We found that geese arrived at spring stopovers close to the peak in GDD jerk; the 'jerk' is the third derivative, or the rate of change in acceleration, and GDD jerk maxima therefore represent the highest acceleration of daily temperature per site. Day of snow melt also correlated well with the observed arrival of the geese. Factors not closely related to onset of spring, i.e. accumulated photoperiod and latitude, yielded poorer fits. A comparison with published data revealed that the GDD jerk occurs 1-2 weeks earlier than the onset of spring derived from NDVI, and probably represents the very start of spring growth. Our data therefore suggest that white-fronted geese track the front of the green wave in spring.
Nine Dark‐bellied Brent Geese Branta bernicla bernicla were equipped with satellite transmitters during spring staging in the Dutch Wadden Sea in 1998 and 1999. The transmitters (in all cases less than 3% of body mass) were attached to the back by a flexible elastic harness. One juvenile female was tracked to the Yamal peninsula in 1998. Eight adult males were selected from a single catch of 75 to span the range of body mass observed on the date of capture (11 May 1999) and all but the lightest individual completed the first lap of the migratory flight to the White Sea, Russia, according to the time schedule normal for the species. Six birds were successfully tracked to Taymyr for a total distance averaging 5004 km (range 4577–5164) but judging from later movements none bred (although 1999 was a breeding year). Although the routes chosen during spring migration were closely similar, none of the tagged birds migrated together. On average the geese used 16 flights to reach their summer destinations on Taymyr. The longest uninterrupted flights during the first half of the journey (Wadden Sea to Kanin) covered 1056 km (mean of seven adult males, range 768–1331), while the corresponding value for the second half of the migration (Kanin–Taymyr) was only 555 km (mean of six adult males). Only 7% of total time during spring migration was spent in active flight, as contrasted to c. 80% at long‐term stopovers. Overall average travelling speed was 118 km/day (range 97–148). Including fattening prior to departure the rate of travel falls to 62 km/day (range 49–70), in keeping with theoretical predictions. Routes followed deviated from the great circle route, adding at least 700 km (16%) to the journey from Wadden Sea to Taymyr, and we conclude that the coastal route is chosen to facilitate feeding, drinking and resting en route instead of minimizing total flight distance.
Recent outbreaks of highly pathogenic avian influenza (HPAI) in poultry have raised interest in the interplay between avian influenza (AI) viruses and their wild hosts. Studies linking virus ecology to host ecology are still scarce, particularly for non-duck species. Here, we link capture-resighting data of greater white-fronted geese Anser albifrons albifrons with the AI virus infection data collected during capture in The Netherlands in four consecutive winters. We ask what factors are related to AI virus prevalence and whether there are ecological consequences associated with AI virus infection in staging white-fronted geese. Mean seasonal (low pathogenic) AI virus prevalence ranged between 2.5 and 10.7 per cent, among the highest reported values for non-duck species, and occurred in distinct peaks with near-zero prevalence before and after. Throat samples had a 2.4 times higher detection frequency than cloacal samples. AI virus infection was significantly related to age and body mass in some but not other winters. AI virus infection was not related to resighting probability, nor to maximum distance travelled, which was at least 191 km during the short infectious lifespan of an AI virus. Our results suggest that transmission via the respiratory route could be an important transmission route of AI virus in this species. Nearzero prevalence upon arrival on their wintering grounds, in combination with the epidemic nature of AI virus infections in white-fronted geese, suggests that white-fronted geese are not likely to disperse Asian AI viruses from their Siberian breeding grounds to their European wintering areas.
1. The huge changes in population sizes of Arctic-nesting geese offer a great opportunity to study population limitation in migratory animals. In geese, population limitation seems to have shifted from wintering to summering grounds. There, in the Arctic, climate is rapidly changing, and this may impact reproductive performance, and perhaps population size of geese, both directly (e.g. by changes in snow melt) or indirectly (e.g. by changes in trophic interactions).2. Dark-bellied brent geese (Branta bernicla bernicla L.) increased 20-fold since the 1950s. Its reproduction fluctuates strongly in concert with the 3-year lemming cycle. An earlier analysis, covering the growth period until 1988, did not find evidence for density dependence, but thereafter the population levelled off and even decreased. The question is whether this is caused by changes in lemming cycles, population density or other factors like carry-over effects.3. Breeding success was derived from proportions of juveniles. We used an information-theoretical approach to investigate which environmental factors best explained the variation in breeding success over nearly 50 years (1960–2008). We subsequently combined GLM predictions of breeding success with published survival estimates to project the population trajectory since 1991 (year of maximum population size). In this way, we separated the effects of lemming abundance and population density on population development.4. Breeding success was mainly dependent on lemming abundance, the onset of spring at the breeding grounds, and the population size of brent goose. No evidence was found for carry-over effects (i.e. effects of conditions at main spring staging site). Negative density dependence was operating at a population size above c. 200 000 individuals, but the levelling off of the population could be explained by faltering lemming cycles alone.5. Lemmings have long been known to affect population productivity of Arctic-nesting migratory birds and, more recently, possibly population dynamics of resident bird species, but this is the first evidence for effects of lemming abundance on population size of a migratory bird species. Why lemming cycles are faltering in the last two decades is unclear, but this may be associated with changes in winter climate at Taimyr Peninsula (Siberia).
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