Pink-footed Geese Anser Brachyrhynchus Research Articles

Effects of capture and GPS-tagging in spring on migration timing and reproduction in Pink-footed geese Anser brachyrhynchus

BackgroundGPS-transmitters enable detailed study of animal behaviour but may impact the animals. Impacts vary from short-term stress and habituation to longer-term effects on e.g., migration and reproduction. To study impacts, ideally, true controls (i.e., uncaptured or untagged animals) are used, but unbiased assessments of their migration timing and breeding performance are challenging, especially in remote areas. Alternatively, quasi-controls can be used: individuals tagged longer ago, or the same tagged individuals but in later years. Quasi-controls reveal tagging effects that differ between the first and following years.ResultsWe captured Pink-footed geese (Anser brachyrhynchus) in spring and summer and deployed GPS-transmitter neckbands. In spring, geese were caught with cannon or clap nets on stopovers in Norway and Finland, 2 weeks before departure to breeding areas in Svalbard and Novaya Zemlya. In summer, geese were rounded up during wing moult in Svalbard. First, we compared geese tagged recently in spring with geese tagged in spring or summer 1–4 years prior. Newly tagged geese migrated significantly later, by 2 days, than previously tagged geese, both at departure from the spring stopover and arrival to the breeding grounds, while migration duration did not differ. Breeding propensity and laying date did not differ, but nesting success tended to be lowered, resulting in a significantly lower annual probability to produce hatchlings in recently tagged geese than in previously tagged geese. Second, within individuals tagged in spring, spring migration advanced in their next year, suggesting delay in their first spring. This was likely not an ageing effect, as geese tagged in summer showed no advancing spring migration timing over the years. Third, in Svalbard, observed brood sizes of geese tagged in summer and untagged geese did not differ 1 year after tagging.ConclusionsThe capture and GPS-tagging of geese 2 weeks before spring departure delayed their spring migration and lowered their probability to produce hatchlings in that year. These effects lasted longer than previously reported week-long effects of GPS-tagging on time budgets in summer and of neck-banding on spring body condition. Additional study is needed to evaluate longer-term or permanent effects which remain undetected with quasi-controls.

Low spatial habitat overlap of herbivores in the High Arctic tundra

Herbivores play a crucial role in shaping tundra ecosystems through their effects on vegetation, nutrient cycling, and soil abiotic factors. Understanding their habitat use, co-occurrence, and overlap is therefore essential for informing ecosystem-based management and conservation. In the High Arctic, only a marginal proportion of the land area is vegetated, and climate change is impacting herbivore population sizes and their habitats. In this study, we assessed the spatial habitat overlap of a vertebrate herbivore community based on: 1) regional predictive summer habitat suitability models for the resident Svalbard reindeer (Rangifer tarandus platyrhynchus), resident Svalbard rock ptarmigan (Lagopus muta hyperborea), and the migratory pink-footed goose (Anser brachyrhynchus), and 2) presence of fecal pellets, reflecting the annual habitat use of reindeer, ptarmigan, and geese, including the pink-footed goose and barnacle goose (Branta leucopsis). Our findings revealed that only small proportions of the available land cover (∼ 12,516 km2; all land area excluding glaciers and freshwater) are suitable for each of the species (habitat suitability [HS] > 0.5): reindeer (22 %), ptarmigan (11 %), and pink-footed goose (4 %). Overlapping suitable habitat [HS > 0.5] for reindeer and goose accounted for only 3 % of the total vegetated area (∼ 8848 km2) and was primarily found in heath and moist habitats dominated by mosses, graminoids, and herbaceous plants. The overlapping suitable habitat for reindeer and ptarmigan covered 8 % of the vegetated area, in higher elevation ridges with vegetation on drier substrates. The shared habitat for ptarmigan and goose, and all three species of herbivores, was less than 1 % of the vegetated area. Additionally, an assessment of fecal pellets suggested that the highest overlap in habitat use among reindeer and goose occurred in bird cliff moss tundra, followed by moss tundra and heath habitats. The small proportion of the vegetated area suitable for all three herbivores indicates a high degree of habitat differentiation. Therefore, different habitats need to be considered for the management and conservation of resident and migratory herbivore species in this High Arctic Archipelago. Moreover, our results underscore the importance of the small but productive parts of the landscape that were used by all herbivores.

EDNA Metabarcoding- and Microscopic Analysis for Diet Determination in Waterfowl, a Comparative Study in Vejlerne, Denmark.

Understanding diets and structural food webs are keys to the apprehension of ecological communities, upon which conservation and management biology are based. The understanding of grazing and habitat choice for waterfowl is one of the most important topics for avian ecologists today and can, to some degree, be answered by dietary analysis. Droppings collected from four waterfowl, the Eurasian wigeon (Anas penelope), Greylag goose (Anser anser), pink-footed goose (Anser brachyrhynchus) and Barnacle goose (Branta leucopsis) in Vejlerne (Denmark), were analysed microscopically and through eDNA metabarcoding with the use of next generation sequencing (NGS) to accumulate knowledge about the diet of these waterfowl. In total, 120 dropping samples were microscopically analysed, of which the eDNA metabarcoding analysis was done on 79 samples. The prey items were identified according to the taxonomic level of species, and a qualitative method, frequency of occurrence (FO) and FO calculated as a percentage, was used in order to compare the results from the two methods. As neither of the methods was able to encompass all species discovered when combining the two methods, it was concluded in this study that the two methods can support each other in a dietary analysis of waterfowl, but not replace one another.

Spatiotemporal distribution of Arctic herbivores in spring: Potential for competition?

Biotic interactions are important to the structure and dynamics of food webs and may affect the spatial and temporal distribution of species. In the Arctic, spring snow-cover limits food availability at a critical time for herbivores, potentially leading to resource competition. This study investigates the potential for competition over forage resources during spring in a high-Arctic herbivore community comprising the resident, endemic Svalbard reindeer (Rangifer tarandus platyrhynchus) and Svalbard rock ptarmigan (Lagopus muta hyperborea), and the migratory pink-footed goose (Anser brachyrhynchus) and barnacle goose (Branta leucopsis). First, we investigated herbivore behaviour that could indicate the potential for competition by conducting a field study, and second, we quantified the effects of snow-cover extent, vegetation type and presence of potential herbivore competitors on the spatiotemporal distributions of herbivores using camera-traps in one early and one late snow melt year. Only reindeer and geese appeared with sufficient sample sizes for analysis. The field study revealed that reindeer and geese foraged in the same areas, particularly moss tundra habitats. Although geese were regularly alerted by reindeer, no direct aggressive interactions were observed. The camera-trap study showed that neither of the herbivores significantly affected the spatiotemporal distribution of its potential competitor, but reindeer and goose distribution was instead driven by snow-cover extent and vegetation type. However, the shared space use by these species may lead to different types of interactions, such as facilitation or exploitative competition, which require further assessment, including dietary overlap studies, particularly in the context of climate change-induced shifts in snow melt timing and herbivore abundances.

A vadlúd monitoring eredményei a 2020/2021-es idényben Magyarországon

Results of Geese Monitoring in Hungary in the season 2020/2021. The author presents the results of the HUNGARIAN GEESE MONITORING (Table 1.) for 2020/2021 in the form of a data base. After reviewing the basic data recorded at each site of observation (Table 3-21.) he analyse the obtained data separately for each species, i.e. Brent Goose (Branta bernicla) (Table 22., Map 1., Figure 1-2.), Barnacle Goose (Branta leucopsis) (Table 23., Map 2., Figure 3-4.), Red-breasted Goose (Branta ruficollis) (Table 24, Map 3., Figure 5-6.), Bar-headed Goose (Anser indicus) (Table 25, Map 4, Figure 7.), Greylag Goose (Anser anser) (Table 26., Map 5., Figure 8-10.), Tundra Bean Goose (Anser serrirostris rossicus) (Table 27., Map 6., Figure 11-13.), Taiga Bean Goose (Anser fabalis) (Table 28, Map 7, Figure 14.), Pink-footed Goose (Anser brachyrhynchus) (Table 29., Map 8., Figure 15.), White-fronted Goose (Anser albifrons) (Table 30., Map 9., Figure 16-18.), Lesser White-fronted Goose (Anser erythropus) (Table 31., Map 10., Figure 19-20.), as well as for the total of observed geese (Table 32., Figure 21-24.). In respect of dominance – when data recorded monthly in each of the observed sites (Table 3-21., Figure 25.) or those referring to the total of geese present in Hungary (Table 33., Figure 25.) are analysed, it is found that in conformity with the numbers of individuals, also in the season 2020/2021 White-fronted Goose was the most common goose species in Hungary (max. 265 010 birds, max. 96%), followed by Greylag Goose (max. 39 261 birds, max. 100%), Tundra Bean Goose (max. 711 birds, max. 0-1%) ranking third. Dominance of Red-breasted Goose and Lesser White-fronted Goose – both are globally threatened species – ranged both from 0% to <1% (max. 147 and 10 birds). If the data obtained for the season 2020/2021 are fitted into the data series of long-term monitoring, the following conclusions can be drawn from the actual changes in population numbers of the geese species in the Pannon region. In the season 2020/2021, we observed max. 2 Brent Geese, max. 1 Barnacle Goose, max. 1 Bar-headed Goose, max. 1 Pink-footed Goose and max. 6 Taiga Bean Goose. For the globally threatened Red-breasted Goose may be considered higher (+40% – 147 birds) to the maximum counted in the season 2019/2020 (105 birds), but much lower to the record number counted in the season 2014/2015 (1258 birds). Greylag Goose continued to be present with high numbers in Hungary. However, in the new season its peaks (39 261 birds) were found to be higher (+4%) those counted in the previous 2019/2020 season (37 707 birds). Peak number of Tundra Bean Goose (711 birds) was lower (–8%) as the maximum counted in the season 2019/2020 (769 birds). The dramatic decline in the dynamics of the Tundra Bean Goose population continued and stabilized in the Pannon Region. Peak number of White-fronted Goose (265 010 birds) was 5% higher as the maximum counted in 2019/2020 (250 888 birds). For the globally threatened Lesser White-fronted Goose may be considered higher (10 birds) to the maximum counted in the season 2019/2020 (9 birds). The maximum numbers of total geese in the season 2020/2021 registered simultaneously (306 526 birds) was 11% higher to the maximum number of the season 2019/2020 (275 164 birds).

The metabolome of pink-footed goose: Heavy metals and lipid metabolism

Wildlife is exposed to mixtures of environmental contaminants that affect health and population dynamics. Exposure to toxic heavy metals originating from anthropogenic sources may exert metabolic effects at even low exposure concentrations. Here we investigated the relationships between heavy metal exposure and metabolic changes in the migratory bird pink-footed goose (Anser brachyrhynchus). We used blood pellet and blood plasma samples from 27 free-ranging pink-footed geese to study heavy metal (Cd, Cr, Hg, and Pb) exposure in relation to the metabolome. The results relate blood concentrations of Cd (range: 0.218–1.09 ng/g), Cr (range: 0.299–5.60 ng/g), and Hg (range: 2.63–6.00 ng/g) to signal areas of fatty acids and other lipids, while no correlations were identified for Pb level (range: 21.0–64.2 ng/g) exposure. Lipid signal areas were negatively associated with concentrations of Cr and positively associated with Hg exposure (both p < 0.05). α-Linolenic acid and 9-oxononanoic acid were negatively correlated to Cr exposure (both p < 0.05) and were related in the α-linolenic acid metabolism pathway. Compared to known thresholds for aviary species, the heavy metal concentrations are below levels of toxicity, which may explain the low number of metabolites that significantly change. Nevertheless, the heavy metal exposure is still correlated to changes in the lipid metabolism that may reduce migrating birds’ breeding success and increase mortality for an exposed part of the population.

Arnthor Gardarsson 1938–2022

Professor Arnthor Gardarsson (1938–2022) was an Icelandic ornithologist who made a major contribution to the studies of the bird fauna of Iceland and to the ecology of waterfowl and wetland conservation. After finishing a BSc in Zoology from the University of Bristol in 1962 he went to the University of California, Berkeley, for a PhD project under the supervision of Professor Frank A. Pitelka. His project, finished in 1971, was about the population and feeding ecology of the Icelandic Ptarmigan Lagopus muta islandorum. In 1971–73, working with the Icelandic Museum of Natural History, he conducted a research programme on the ecology of the Thjorsarver area. This tundra oasis in the otherwise desert-like Icelandic highlands harboured the world's largest breeding colony of the Pink-footed Goose Anser brachyrhynchus and was under serious threat by hydropower development. A part of this ecosystem-oriented study involved aerial surveys of birds, a method that was to become one of Arnthor's signature research tools. Waterfowl held a special place in Arnthor's heart. The opportunity to study them in detail came in 1974 when Lake Myvatn, the world-renowned waterfowl site in Iceland, was defined as a nature reserve. This was in the wake of a heated debate over a hydropower project that would have fundamentally altered the lake's ecology. In 1974, Arnthor became professor in zoology at the new biology department of the University of Iceland and he promptly focused his academic research effort on Lake Myvatn. The idea was to monitor the ecological situation of the lake by studying its many duck populations. Despite the newly acquired protection status, there was concern about ongoing industrial sediment extraction from the lake (continuing till 2004). Arnthor's efforts, with students and collaborators, soon developed into a full-scale ecological study of the lake's foodweb, benefiting from his deep insight into ecological processes. His research revealed immense fluctuations in the Lake Myvatn ecosystem, that still occur and continue to attract scientific interest. The studies resulted in a series of classic papers, demonstrating how the variable abundance of aquatic insects and crustaceans in a lake determined duckling production and subsequent changes in breeding populations. It was Arnthor's ambition to obtain a comprehensive picture of the bird populations of Iceland, their distribution, size, production, resources, and trends. It was a gargantuan task, considering the size, remoteness and ruggedness of the landscape and the sheer number of birds. But Arnthor was a daredevil who was quick to apply aerial surveys to the mapping and photographing of all the important bird areas, both coastal and inland, and he kept seeking new techniques to this effect. Estimating bird densities in the immense, towering seabird colonies of northwest Iceland was his biggest challenge. His final solution was to fly low over and then off the cliff edge, taking a rapid succession of photographs with a large-format camera aimed slightly backwards – a rather risky undertaking with the myriad of fast-flying birds around. His aerial endeavours, backed up by field studies, resulted in comprehensive population estimates of alcids, Black-legged Kittiwakes Rissa tridactyla, Northern Fulmars Fulmarus glacialis, Northern Gannets Morus bassanus, European Shags Gulosus aristotelis, Great Cormorants Phalacrocorax carbo, Common Eiders Somateria mollissima and other ducks, swans, geese and even passing migratory waders such as Red Knots Calidris canutus, Ruddy Turnstones Arenaria interpres and Sanderlings Calidris alba. Later he extended the surveying to cover all the Atlantic Puffin Fratercula arctica colonies of Iceland and developed methods to monitor seabird trends via ground-based observations. Arnthor also used his skills to reveal the details of the population dynamics of European Shags and Great Cormorants in the Breidafjördur archipelago, their central stronghold in Iceland. Spring field trips with his students to the impressive seabird colonies in the northwest of Iceland made an enduring impact on many, who are now continuing and expanding the monitoring work on birds in marine, freshwater and terrestrial habitats all over Iceland. Arnthor served as a chairman of the Nature Conservation Council in 1990–96, a government advisory body that also managed protected areas. Through this he became a leading figure in the protection of many of the ecosystems he had studied, in particular Thjorsarver and Myvatn, the crown jewels of inland wetland sites in Iceland. In addition to his extensive ornithological skills, Arnthor had a fascination for terrestrial and marine invertebrates, polychaetes in particular, and he was proficient in botany. He was also artistic and made a name for himself at a young age when illustrating papers on bird life. Arnthor's character may be described as an attractive mix of generousity, ambition and shyness, as well as being humble, friendly and joyful. In 1959 Arnthor married Gudrun Sveinbjarnardóttir (1937–2016), an economist from Reykjavik. They had two children, Soffia and Thrandur.

Rapid formation of new migration route and breeding area by Arctic geese

Many Arctic-breeding animals are at risk from local extirpation associated with habitat constriction and alterations in phenology in their Arctic environment as a result of rapid global warming.1 Migratory species face additional increasing anthropogenic pressures along their migratory routes such as habitat destruction, droughts, creation of barriers, and overexploitation.2,3 Such species can only persist if they adjust their migration, timing of breeding, and range.4 Here, we document both the abrupt (∼10 years) formation of a new migration route and a disjunct breeding population of the pink-footed goose (Anser brachyrhynchus) on Novaya Zemlya, Russia, almost 1,000km away from the original breeding grounds in Svalbard. The population has grown to 3,000-4,000 birds, explained by intrinsic growth and continued immigration from the original route. The colonization was enabled by recent warming on Novaya Zemlya. We propose that social behavior of geese, resulting in cultural transmission of migration behavior among conspecifics as well as in mixed-species flocks, is key to this fast development and acts as a mechanism enabling ecological rescue in a rapidly changing world.

Highly differentiated loci resolve phylogenetic relationships in the Bean Goose complex

BackgroundReconstructing phylogenetic relationships with genomic data remains a challenging endeavor. Numerous phylogenomic studies have reported incongruent gene trees when analyzing different genomic regions, complicating the search for a ‘true’ species tree. Some authors have argued that genomic regions of increased divergence (i.e. differentiation islands) reflect the species tree, although other studies have shown that these regions might produce misleading topologies due to species-specific selective sweeps or ancient introgression events. In this study, we tested the extent to which highly differentiated loci can resolve phylogenetic relationships in the Bean Goose complex, a group of goose taxa that includes the Taiga Bean Goose (Anser fabalis), the Tundra Bean Goose (Anser serrirostris) and the Pink-footed Goose (Anser brachyrhynchus).ResultsFirst, we show that a random selection of genomic loci—which mainly samples the undifferentiated regions of the genome—results in an unresolved species complex with a monophyletic A. brachyrhynchus embedded within a paraphyletic cluster of A. fabalis and A. serrirostris. Next, phylogenetic analyses of differentiation islands converged upon a topology of three monophyletic clades in which A. brachyrhynchus is sister to A. fabalis, and A. serrirostris is sister to the clade uniting these two species. Close inspection of the locus trees within the differentiated regions revealed that this topology was consistently supported over other phylogenetic arrangements. As it seems unlikely that selection or introgression events have impacted all differentiation islands in the same way, we are convinced that this topology reflects the ‘true’ species tree. Additional analyses, based on D-statistics, revealed extensive introgression between A. fabalis and A. serrirostris, which partly explains the failure to resolve the species complex with a random selection of genomic loci. Recent introgression between these taxa has probably erased the phylogenetic branching pattern across a large section of the genome, whereas differentiation islands were unaffected by the homogenizing gene flow and maintained the phylogenetic patterns that reflect the species tree.ConclusionsThe evolution of the Bean Goose complex can be depicted as a simple bifurcating tree, but this would ignore the impact of introgressive hybridization. Hence, we advocate that the evolutionary relationships between these taxa are best represented as a phylogenetic network.

Monitoring Dropping Densities with Unmanned Aerial Vehicles (UAV): An Effective Tool to Assess Distribution Patterns in Field Utilization by Foraging Geese

Counting of droppings is often, with great effect, used as an indirect method to monitor the appearance and usage of an area by a population covering longer time spans. However, manual detecting and counting of droppings can be time-consuming and tedious, and with a risk of resulting in course estimations. In this context, we studied the use of imaging from unmanned aerial vehicles (UAVs) as a novel and enhanced tool to estimate the dropping densities and distributions of field foraging Arctic migratory geese, such as pink-footed goose Anser brachyrhynchus and barnacle goose Branta leucopsis. Aided by analysis in geographical information systems (GIS), we sought to detect and use fine-scale changes in the within-field dropping densities to evaluate avoidance distance to selected landscape elements. Data in the form of aerial photos from farmed grassland and pastures were collected in areas adjacent to Limfjorden, Northern Jutland, Denmark. The UAV proved usable for detecting droppings from field foraging geese, but with the applied UAV technology only at a low flying altitude (≤3 m), which rendered traditional methods for georeferencing inapplicable. A revised protocol for georeferencing of single aerial photos triggered from low altitudes was successfully developed, which was considered suitable for future use. Analyses based on the performed UAV data sampling allowed for an unprecedented fine-scale estimation of distribution patterns of the goose droppings and further for determination of optimal sampling frequencies (≤12 × 12 m spacing between photo samples) for calculation of density patterns, which reflected differences in foraging activity of geese across whole fields. Contagious dispersions in dropping densities were detected in the majority of fields indicating local, within-field displacements of the geese, which were illustrated by interpolated heatmaps. Additionally, avoidance distances were assessed for four landscape elements and detected with consistent results for windbreaks (100 m), roads (175 m) and wind turbines (1100 m) throughout the ten surveyed fields.

Genetic assessment reveals inbreeding, possible hybridization, and low levels of genetic structure in a declining goose population.

The population numbers of taiga bean goose (Anser fabalis fabalis) have halved during recent decades. Since this subspecies is hunted throughout most of its range, the decline is of management concern. Knowledge of the genetic population structure and diversity is important for guiding management and conservation efforts. Genetically unique subpopulations might be hunted to extinction if not managed separately, and any inbreeding depression or lack of genetic diversity may affect the ability to adapt to changing environments and increase extinction risk. We used microsatellite and mitochondrial DNA markers to study the genetic population structure and diversity among taiga bean geese breeding within the Central flyway management unit using non‐invasively collected feathers. We found some genetic structuring with the maternally inherited mitochondrial DNA between four geographic regions (ɸ ST = 0.11–0.20) but none with the nuclear microsatellite markers (all pairwise F ST‐values = 0.002–0.005). These results could be explained by female natal philopatry and male‐biased dispersal, which completely homogenizes the nuclear genome. Therefore, the population could be managed as a single unit. Genetic diversity was still at a moderate level (average H E = 0.69) and there were no signs of past population size reductions, although significantly positive inbreeding coefficients in all sampling sites (F IS = 0.05–0.10) and high relatedness values (r = 0.60–0.86) between some individuals could indicate inbreeding. In addition, there was evidence of either incomplete lineage sorting or introgression from the pink‐footed goose (Anser brachyrhynchus). The current population is not under threat by genetic impoverishment but monitoring in the future is desirable.

First detection of highly pathogenic avian influenza virus in Norway

BackgroundSeveral outbreaks of highly pathogenic avian influenza (HPAI) caused by influenza A virus of subtype H5N8 have been reported in wild birds and poultry in Europe during autumn 2020. Norway is one of the few countries in Europe that had not previously detected HPAI virus, despite widespread active monitoring of both domestic and wild birds since 2005.ResultsWe report detection of HPAI virus subtype H5N8 in a wild pink-footed goose (Anser brachyrhynchus), and several other geese, ducks and a gull, from south-western Norway in November and December 2020. Despite previous reports of low pathogenic avian influenza (LPAI), this constitutes the first detections of HPAI in Norway.ConclusionsThe mode of introduction is unclear, but a northward migration of infected geese or gulls from Denmark or the Netherlands during the autumn of 2020 is currently our main hypothesis for the introduction of HPAI to Norway. The presence of HPAI in wild birds constitutes a new, and ongoing, threat to the Norwegian poultry industry, and compliance with the improved biosecurity measures on poultry farms should therefore be ensured. [MK1]Finally, although HPAI of subtype H5N8 has been reported to have very low zoonotic potential, this is a reminder that HPAI with greater zoonotic potential in wild birds may pose a threat in the future. [MK1]Updated with a sentence emphasizing the risk HPAI pose to poultry farms, both in the and in the Conclusion-section in main text, as suggested by Reviewer 1 (#7).

Interspecific comparison of the fecal microbiota structure in three Arctic migratory bird species.

The gut microbiota of birds is known to be characterized for different species, although it may change with feeding items. In this study, we compared the gut microbiota of birds with different feeding behaviors in the same habitat. We collected fecal samples from three Arctic species, snow buntings Plectrophenax nivalis, sanderlings Calidris alba, and pink‐footed geese Anser brachyrhynchus that are phylogenetically quite distant in different families to evaluate effects of diet on gut microbiota. Also, we characterized the prevalence of fecal bacteria using the Illumina MiSeq platform to sequence bacterial 16S rRNA genes. Our NMDS results showed that fecal bacteria of snow buntings and sanderlings were significantly distant from those of pink‐footed geese. Although all three birds were occupied by three bacterial phyla, Proteobacteria, Firmicutes, and Bacteroidetes, dominant taxa still varied among the species. Our bacterial sequences showed that snow buntings and sanderlings were dominated by Firmicutes and Bacteroidetes, while pink‐footed geese were dominated by Proteobacteria. In addition, the bacterial diversity in snow buntings and sanderlings was significantly higher than that in pink‐footed geese. Our results suggest that insectivorous feeding diet of snow buntings and sanderlings could be responsible for the similar bacterial communities between the two species despite the distant phylogenetic relationship. The distinctive bacterial community in pink‐footed geese was discussed to be related with their herbivorous diet.

Using integrated population models for insights into monitoring programs: An application using pink-footed geese

Development of integrated population models (IPMs) assume the absence of systematic bias in monitoring programs, yet many potential sources of systematic bias in monitoring data exist (e.g., under-counts of abundance). By integrating multiple sources of data, we can assess whether various sources of monitoring data provide consistent inferences about changes in population size and, thus, whether monitoring programs appear unbiased. For the purposes of understanding how IPMs could provide insights for monitoring programs, we used the Svalbard breeding population of pink-footed goose (Anser brachyrhynchus) as a case study. The Svalbard pink-footed goose is a well-studied species, the focus of the first adaptive-harvest-management program in Europe, and the subject of a variety of long-term monitoring programs. We examined two formulations of an IPM, but ultimately relied on the one that provided a satisfactory fit to all the available data as based on Chi-squared goodness of fit tests. Our analyses suggest a negative bias in November counts (-20 %), a negative bias in capture-mark-recapture estimates of survival (-3 %), and a negative bias in indices of productivity (-23 %). We offer possible explanations for these biases, whether the degree of bias seems reasonable considering those explanations, and how bias might be investigated directly and ultimately avoided or corrected. Finally, we discuss implications of our work for developing IPMs and associated monitoring programs for managing pink-footed geese and other waterbird species.

From reference genomes to population genomics: comparing three reference-aligned reduced-representation sequencing pipelines in two wildlife species

BackgroundRecent advances in genomics have greatly increased research opportunities for non-model species. For wildlife, a growing availability of reference genomes means that population genetics is no longer restricted to a small set of anonymous loci. When used in conjunction with a reference genome, reduced-representation sequencing (RRS) provides a cost-effective method for obtaining reliable diversity information for population genetics. Many software tools have been developed to process RRS data, though few studies of non-model species incorporate genome alignment in calling loci. A commonly-used RRS analysis pipeline, Stacks, has this capacity and so it is timely to compare its utility with existing software originally designed for alignment and analysis of whole genome sequencing data. Here we examine population genetic inferences from two species for which reference-aligned reduced-representation data have been collected. Our two study species are a threatened Australian marsupial (Tasmanian devil Sarcophilus harrisii; declining population) and an Arctic-circle migrant bird (pink-footed goose Anser brachyrhynchus; expanding population). Analyses of these data are compared using Stacks versus two widely-used genomics packages, SAMtools and GATK. We also introduce a custom R script to improve the reliability of single nucleotide polymorphism (SNP) calls in all pipelines and conduct population genetic inferences for non-model species with reference genomes.ResultsAlthough we identified orders of magnitude fewer SNPs in our devil dataset than for goose, we found remarkable symmetry between the two species in our assessment of software performance. For both datasets, all three methods were able to delineate population structure, even with varying numbers of loci. For both species, population structure inferences were influenced by the percent of missing data.ConclusionsFor studies of non-model species with a reference genome, we recommend combining Stacks output with further filtering (as included in our R pipeline) for population genetic studies, paying particular attention to potential impact of missing data thresholds. We recognise SAMtools as a viable alternative for researchers more familiar with this software. We caution against the use of GATK in studies with limited computational resources or time.

Hunter opinions on the management of migratory geese: a case of stakeholder involvement in adaptive harvest management

ABSTRACTKnowledge of hunter attitudes toward goose management is essential for the involvement of hunters in adaptive harvest management. Our study provides insight into processes of stakeholder involvement in adaptive harvest management, as demonstrated by the case of implementing the International Species Management Plan for the Svalbard-breeding pink-footed goose (Anser brachyrhynchus). We conducted an online survey among goose hunters in Norway in the main autumn staging area of this species, Nord-Trøndelag, which is also the area in which most geese are harvested nationally. Our results demonstrated that a majority of these hunters see themselves as active participants in management. These hunters expressed a willingness to support management objectives through the delivery of daily harvest reports and by complying with regulations, as defined by national wildlife authorities and the international management plan.

High goose abundance reduces nest predation risk in a simple rodent-free high-Arctic ecosystem

Breeding geese are the preferred prey of the Arctic fox Vulpes lagopus in the high-Arctic Svalbard archipelago. According to the apparent competition hypothesis (ACH), less-abundant prey species (e.g. ptarmigan, waders and small passerines) will experience higher predation rates when breeding in association with the more common prey (geese), due to spill-over predation by the shared predator. As many of these less-abundant species are endemic and/or red-listed, increased predation can have negative repercussions on their populations. We used a one-year baited artificial nest study to assess relative nest predation risk on Svalbard Rock Ptarmigan Lagopus muta hyperborea, small waders (Purple Sandpiper Calidris maritima, Dunlin Calidris alpina, plovers Charadrius spp., and phalaropes Phalaropus spp.) and Snow bunting Plectrophenax nivalis in two study locations contrasted by nesting density of Arctic breeding geese (Pink-footed Goose Anser brachyrhynchus and Barnacle Goose Branta leucopsis). We predicted higher predation risk for the less-abundant species in the study location with higher goose abundance. However, we found that relative nest predation risk was lower in the study location with higher goose abundance, thus being compatible with apparent mutualism and/or prey swamping mechanisms. Our results contrast with those from more structurally complex Arctic ecosystems and suggest that allochtonous subsidies from temperate ecosystems structure the predation pattern in this high-Arctic tundra ecosystem.

British Ornithologists’ Union Union Medal

British Ornithologists’ Union Union Medal

Goose management schemes to resolve conflicts with agriculture: Theory, practice and effects

In 2012, the four countries hosting the Svalbard population of pink-footed goose Anser brachyrhynchus along its flyway launched an International Species Management Plan for the population. One of the aims was to reduce conflicts between geese and agriculture to an acceptable level. Since 2006, Norway has offered subsidies to farmers that provide refuge areas for geese on their land. We evaluate the mid-Norwegian goose management subsidy scheme, with a view to its adjustment to prevailing ecological and socio-economic parameters. The analysis indicates that the legitimacy of the scheme is highly dependent on transparency of knowledge management and accountability of management scheme to the farming community. Among farmers, as well as front-line officials, outcomes of prioritisation processes within the scheme are judged unfair when there is an evident mismatch between payments and genuine damage. We suggest how the scheme can be made more fair and responsive to ecological changes, within a framework of adaptive management.

Combining modelling tools to evaluate a goose management scheme

Many goose species feed on agricultural land, and with growing goose numbers, conflicts with agriculture are increasing. One possible solution is to designate refuge areas where farmers are paid to leave geese undisturbed. Here, we present a generic modelling tool that can be used to designate the best locations for refuges and to gauge the area needed to accommodate the geese. With a species distribution model, locations are ranked according to goose suitability. The size of the area to be designated as refuge can be chosen by including more or less suitable locations. A resource depletion model is then used to estimate whether enough resources are available within the designated refuge to accommodate all geese, taking into account the dynamics of food resources, including depletion by geese. We illustrate this with the management scheme for pink-footed goose Anser brachyrhynchus implemented in Norway. Here, all geese can be accommodated, but damage levels appear to depend on weather, land use and refuge size.