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108 results for “geese”
Detecting edge effects of geese grazing at the boundary of woodland and grassland
<p>The presence of geese on different areas of lawn was estimated by the length of droppings on the lawn. Geese defecate frequently and seemingly indiscriminately. Counting dropping is a well-known method for estimating their density on areas of land (Owen, 1971). However, we found it difficult to distinguish individual defecation events as the dropping tend to break apart as they are released. Therefore, we measured the total length of dropping in an area. Geese dropping are more or less cylindrical and we consider a measure related to the volume of droppings is more reliable than a count of their number.</p> <p>Observations were conducted in July 2014 and March and April 2015 at Meise Botanic Garden, Meise, Belgium. Rectangular plots were laid out perpendicular to a woodland-lawn boundary on sections of a Botanic Garden frequently used by geese. These plots are detailed in file DroppingsPlots.csv. The sites for these plots were chosen because they were well separated from each other; were away from other trees and faced different directions. The plots were marked out using bamboo canes and a tape measure. Then either 20 or 30 randomly chosen 1 m<sup>2</sup> square quadrats were surveyed within the rectangular plot. The cumulative length of dropping in a quadrat was measured to the nearest centimeter with a ruler.</p> <p>The results are found in file DroppingsMeasurements.csv.</p> <p>The columns of this file are as follows</p> <p>Plot - The identifying number given to the plot</p> <p>X - The distance parallel to the woodland-lawn boundary</p> <p>Y - The distance from the woodland-lawn boundary</p> <p>Length - The total length in centimeters of the dropping found in a 1m<sup>2</sup> quadrat</p> <p>Prunella - coverage of <em>Prunella vulgaris</em> L. in the 1m<sup>2</sup> quadrat on the DAFOR Scale (dominant 5, abundant 4, frequent 3, occasional 2, rare 1, absent 0)</p> <p>Renoncule - coverage of <em>Ranunculus</em> sp. in the 1m<sup>2</sup> quadrat on the DAFOR Scale (dominant 5, abundant 4, frequent 3, occasional 2, rare 1, absent 0)</p> <p>Bellis - coverage of <em>Bellis perennis</em> L. in the 1m<sup>2</sup> quadrat on the DAFOR Scale (dominant 5, abundant 4, frequent 3, occasional 2, rare 1, absent 0)</p> <p>Lotus - coverage of <em>Lotus</em> sp. in the 1m<sup>2</sup> quadrat on the DAFOR Scale (dominant 5, abundant 4, frequent 3, occasional 2, rare 1, absent 0)</p> <p>Glechoma - coverage of <em>Glechoma hederacea</em> L. in the 1m<sup>2</sup> quadrat on the DAFOR Scale (dominant 5, abundant 4, frequent 3, occasional 2, rare 1, absent 0)</p> <p>Four species of geese are present in the Botanic Garden and may have contributed droppings to the observations. These species are <em>Alopochen aegyptiaca</em> (L. 1766) (Egyptian geese), <em>Branta canadensis</em> (L. 1758) (Canada geese), <em>Anser anser</em> (L. 1758) (greylag geese) and <em>Branta leucopsis</em> (Bechstein, 1803) (barnacle geese).</p>
Fig. 2 in Flock Size Measures Of Migrating Lesser White-Fronted Geese Anser Erythropus
Fig. 2. The distribution of Lesser White-fronted Geese flocks (above) and individuals (below) among flock size categories in the autumn at Hortobágy, 1994–2006
Effects of severe anthropogenic disturbance on the heart rate and body temperature in free-living greylag geese (Anser anser)
<p>Anthropogenic disturbances are a major concern for the welfare and conservation of wildlife. We recorded heart rate and body temperature of 20 free-living greylag geese in response to a major regularly re-occurring anthropogenic disturbance, New Year’s Eve fireworks. Heart rate and body temperature were significantly higher in the first and second hour of the new year, compared to the same hour on the 31<sup>st</sup> of December, the average during December and the average during January. Heart rate and body temperature was not significantly affected by sex or age. From 0200-0300 onwards, 1<sup>st</sup> of January heart rates did not significantly differ from the other periods, however body temperatures were significantly increased until 0300-0400. From 0400-0500, heart rate was not affected by any of the investigated factors, whereas body temperature was significantly increased on the 1<sup>st</sup> of January compared 31<sup>st</sup> of December and the December average but not compared to the January average. To conclude, our results show that New Year’s Eve fireworks cause a substantial physiological response, indicative of a stress response in greylag geese, which is costly in terms of energy expenditure.</p>
Fig. 1 in Toxoplasma gondii exposure in arctic-nesting geese: A multi-state occupancy framework and comparison of serological assays
Fig. 1. Comparison of seroprevalence estimates for Ross's Geese and Lesser Snow Geese generated by naïve and multi-state occupancy estimators (seroprevalence = Ψ1 × Ψ2).
Figure 5 in The effect of grazing by geese, goats, and fallow deer on soil mites (Acari)
Figure 5. Percentage ratio of adult and juvenile oribatids at goose pasture and corresponding meadow. Oribatida: A_ col – Achipteria coleoptrata, E_occ – Eupelops occultus, L_sim – Liebstadia similis, M_pul – Metabelba pulverosa, P_pel – Platynothrus peltifer, P_pun – Punctoribates punctum, S_lae – Scheloribates laevigatus, S_imm – Sellnickochthonius immaculatus, T_vel – Tectocepheus velatus, T_nov – Trichoribates novus.
Figure 3 in The effect of grazing by geese, goats, and fallow deer on soil mites (Acari)
Figure 3. Canonical correspondence analysis (CCA) for most abundant oribatid species with A> 0.5. Soil components and plant community, eigenvalues for axis 1 ʎ = 0.53 (72.0%), for axis 2 ʎ = 0.14 (19.2%), permutation test of first axis F = 0.7, p = 0.376. GM – goose meadow, GP – goose pasture, GoM – goat meadow, GoP – goat pasture, FM – fallow deer meadow, FP – fallow deer pasture, A_col – Achipteria coleoptrata, E_occ – Eupelops occultus, L_sim – Liebstadia similis, M_pul – Metabelba pulverosa, P_pel – Platynothrus peltifer, P_pun – Punctoribates punctum, S_lae – Scheloribates laevigatus, S_imm – Sellnickochthonius immaculatus, T_vel – Tectocepheus velatus, T_nov – Trichoribates novus.
Figure 1 in The effect of grazing by geese, goats, and fallow deer on soil mites (Acari)
Figure 1. Location of the study plots. Go – goat pasture and meadow, G – goose pasture and meadow, F – fallow deer pasture and meadow.
Figure 7 in The effect of grazing by geese, goats, and fallow deer on soil mites (Acari)
Figure 7. Percentage ratio of adult and juvenile oribatids at fallow deer pasture and corresponding meadow. Oribatida: A_col – Achipteria coleoptrata, E_occ – Eupelops occultus, L_sim – Liebstadia similis, M_pul – Metabelba pulverosa, P_pel – Platynothrus peltifer, P_pun – Punctoribates punctum, S_lae – Scheloribates laevigatus, S_imm – Sellnickochthonius immaculatus, T_vel – Tectocepheus velatus, T_nov – Trichoribates novus.
Fig. 6 in Negligible evidence for detrimental effects of Leucocytozoon infections among Emperor Geese (Anser canagicus) breeding on the Yukon-Kuskokwim Delta, Alaska
Fig. 6. Comparison of mass measures for incubating adult female Emperor Geese infected with Leucocytozoon parasites genetically characterized in this study L. simondi clade A (blue), L. simondi clade B (red), or other/mixed Leucocytozoon (grey; see Materials and methods) using boxplots (Panel A) and plotted by incubation day (Panel B). The trendline in panel B is depicts predicted mass given the day of incubation and positive Leucocytozoon infection status from our top-ranking regression model (see Results). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 5. Phylogenetic tree depicting inferred genetic relationships among Leucocytozoon mitochondrial DNA cytochrome b in Negligible evidence for detrimental effects of Leucocytozoon infections among Emperor Geese (Anser canagicus) breeding on the Yukon-Kuskokwim Delta, Alaska
Fig. 5. Phylogenetic tree depicting inferred genetic relationships among Leucocytozoon mitochondrial DNA cytochrome b haplotypes identified from blood samples collected from Emperor Geese inhabiting the Yukon-Kuskokwim Delta, Alaska during 2006–2016 and those previously reported for closely related haemosporidian morphospecies on the National Center for Biotechnology Information GenBank and Malavi databases (accession IDs in parentheses). Bars to the right of tree represent the assignment of sequences to L. simondi clade A (teal), L. simondi clade B (orange), or other Leucocytozoon. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 4. Phylogenetic tree depicting inferred genetic relationships among Haemoproteus mitochondrial DNA cytochrome b in Negligible evidence for detrimental effects of Leucocytozoon infections among Emperor Geese (Anser canagicus) breeding on the Yukon-Kuskokwim Delta, Alaska
Fig. 4. Phylogenetic tree depicting inferred genetic relationships among Haemoproteus mitochondrial DNA cytochrome b haplotypes identified from blood samples collected from Emperor Geese inhabiting the Yukon-Kuskokwim Delta, Alaska during 2006–2016 and those previously reported for closely related haemosporidian morphospecies on the National Center for Biotechnology Information GenBank and Malavi databases (accession IDs in parentheses).
Fig. 1 in Negligible evidence for detrimental effects of Leucocytozoon infections among Emperor Geese (Anser canagicus) breeding on the Yukon-Kuskokwim Delta, Alaska
Fig. 1. Mass of adult female nesting Emperor Geese per day of incubation for birds infected (red) and uninfected (black/white) with Leucocytozoon parasites using samples collected on the Yukon-Kuskokwim Delta, Alaska during 2006–2016. Trend lines indicate the predicted mass for an individual goose throughout the incubation period from day 11 based upon on the top supported model (Mass ~ Inc + Leu). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2. Minimum spanning network for haemosporidian mitochondrial DNA cytochrome b haplotypes identified from blood samples collected from Emperor Geese inhabiting the YukonKuskokwim Delta, Alaska during 2006–2016 in Negligible evidence for detrimental effects of Leucocytozoon infections among Emperor Geese (Anser canagicus) breeding on the Yukon-Kuskokwim Delta, Alaska
Fig. 2. Minimum spanning network for haemosporidian mitochondrial DNA cytochrome b haplotypes identified from blood samples collected from Emperor Geese inhabiting the YukonKuskokwim Delta, Alaska during 2006–2016. Circles are drawn proportional to the frequency at which haplotypes were detected. Shading represented the assignment of representative sequences for haplotypes to L. simondi clade A (teal), L. simondi clade B (orange), or other Leucocytozoon (grey) in phylogenetic analyses (see Results and Fig. 5). Lines are drawn proportional to genetic distance and are labeled per the number of mutations represented (except single nucleotide polymorphisms which are unlabeled). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 11 in Developmental Abnormalities in Wild Populations of Birds: Examples from Lesser Snow Geese (Chen caerulescens caerulescens)
Fig. 11. Asymmetrical reduction in lower mandible of specimen LPB009 that also displays misshapen anterior frontal bones.
Fig. 3. Specimen LPB002 in Developmental Abnormalities in Wild Populations of Birds: Examples from Lesser Snow Geese (Chen caerulescens caerulescens)
Fig. 3. Specimen LPB002 displaying duplication of mandibles and fusion of medial eye socket. Entire specimen (left) and details of head region (right).
Data from: Modelling harvest of Greenland barnacle geese and its implications in mitigating human-wildlife conflict
<p>Arctic-breeding goose populations have increased in recent decades and their expansion into agricultural areas has caused increasing conflict with farmers due to the damage they cause. Lethal control and scaring are common management strategies of conflict mitigation. Management typically focuses on local/national scales, making addressing the impact of localised control on the wider population challenging, particularly when populations move over large areas and cross international borders.</p> <p>We construct an integrated population model (IPM) to assess the cumulative impact of all shooting harvest (hunting and derogation shooting) on the Greenland barnacle goose, <em>Branta leucopsis</em>. We use data from monitoring schemes throughout the migratory flyway and use population projections to evaluate the impact of potential future shooting strategies on abundance.</p> <p>Our model suggests flyway abundance has declined since its 2012 peak, consistent with an increase in harvest rate and low productivity. Harvest rate increase was most pronounced on Islay (rising from 2% to 7% from 2011 to 2017), suggesting this was a probable cause of flyway abundance decline. </p> <p>Islay abundance has declined since derogation shooting began in 2000, whilst abundance at other wintering sites has increased. This may indicate that declines in Islay abundance may be due to both shooting mortality and emigration from Islay.</p> <p>Should future flyway-level harvest rates increase, further declines in abundance could be expected, and are likely to be more pronounced if harvests are extended to the entire winter range. Conversely, should harvest rates decline, an increase in abundance is predicted. Projections can therefore be used to allocate flyway-level harvest rates to alleviate local pressure without hindering flyway-level management objectives.</p> <p>Synthesis and applications. Our findings demonstrate the impact of local harvests on global abundance, emphasising the importance of internationally coordinated monitoring and management strategies of migratory species. IPMs provide a framework for adaptation to incorporate additional data when they become available and enable comparisons of future harvest scenarios to inform management strategies throughout the flyway. </p>
Data from: Culling-induced perturbation of social networks of wild geese reinforces rather than disrupts associations among survivors
<p>Wildlife populations may be the subject of management interventions for disease control that can have unintended, counterproductive effects. Social structure exerts a strong influence over infectious disease transmission in addition to other characteristics of populations such as size and density that are the primary target for disease control. Social network approaches have been widely used to understand disease transmission in wildlife but rarely in the context of perturbations, such as culling, despite the likely impacts of such disturbance on social structure and disease dynamics. Here we present a 'removal' study of a free-living population of resident Canada geese <em>Branta canadensis</em>, a highly social species that is frequently managed by culling and can carry pathogens relevant to human and domestic animal health. We quantified social network structure and spatial behaviour before and after controlled culling of individuals during the summer moult. Culling did not substantially increase individual social connectivity. Individuals that moulted at cull sites or were formerly strongly associated with removed birds were more likely to strengthen and maintain any surviving existing associations while also forming new associations. However, the establishment of new associations was largely compensatory (with only small increases in the number and strength of connections) and occurred locally. Synthesis & applications: geese that survived the cull responded by strengthening existing social relationships and forming new, compensatory relationships with birds local to them in the network. In the short-term such compensatory adjustments to patterns of association in response to culling could facilitate pathogen transmission. But in the longer term, controlled culling of geese is unlikely to strongly influence pathogen spread and may even slow transmission into new social clusters by reducing wider mixing. When managing wildlife for disease control, in addition to changes in social network structure the prevalence of infection at the time of the cull and the mode of transmission (e.g., direct versus environmental) will also be critical determinants of disease transmission risk in perturbed populations of geese and other wild animals.</p>
Data from: Modelling harvest of Greenland barnacle geese and its implications in mitigating human-wildlife conflict
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Data from: Culling-induced perturbation of social networks of wild geese reinforces rather than disrupts associations among survivors
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Data from: Flight initiation distance is repeatable and geographically flexible in greylag geese (Anser anser)
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