The use of seagrass (Zostera muelleri) habitat by Canada geese (Branta canadensis) in Waikato estuaries.
Bibliographic record
Abstract
Seagrass beds are highly biodiverse habitats delivering key ecosystem functions and services to mankind. Zostera muelleri is New Zealand’s single seagrass species, and occurs intertidally within several estuaries and sheltered harbours. However, these habitats are globally in decline due to the impacts of multiple stressors including eutrophication, turbidity, coastal urbanisation, sedimentation, and sea level rise. Herbivory by waterfowl is a relatively unknown biotic disturbance that may cause additional stress to these vulnerable seagrass habitats. Canada geese (Branta canadensis) were introduced to New Zealand in 1905, and have since been increasing in numbers since a change in species management. In response to increase in Canada geese populations and use of estuaries along the West coast, the Waikato Regional Council commissioned this MSc (Research) study to investigate the consumption of Zostera by Canada geese in Kawhia and Whāingaroa (Raglan) harbours, West coast of the North Island, New Zealand. \n \nIn order to better understand the grazing pressure placed on seagrass habitats, a three part investigation was conducted. Behaviours of Canada geese on Zostera beds were observed in January and February (2019), at two sites in Whāingaroa Harbour, with geese numbers varying between 8 to 200 at any one time. Observations indicated that foraging incorporated a large proportion of their behavioural budget (> 85%), and birds utilised several destructive methods to forage on both above and below-ground Zostera biomass. Foraging was significantly reduced by disturbance events less than 30 m away and was also influenced by group size. Repeat observations in June and July 2019, were not possible as geese were no longer present on the Zostera beds. \n \nCanada geese samples were collected to investigate bird diet across a temporal scale; from Kawhia between July to November 2019 (n = 33), and from Raglan between August to September 2020 (n = 26). Gut contents analysis showed that more than 70% of specimens consumed solely pasture in the two hours prior to sampling. Bayesian mixing models in MixSIAR were used for δ¹⁵N and δ¹³C stable isotope analysis to evaluate the assimilated diet three to four days (plasma), three to four weeks (red blood cells) and several months (primary feathers) prior to sampling. Pasture was the dominant food source (75 to 93%) contributing to all three tissue types. \n \nThis study aimed to provide insight into the consumption of seagrass (Zostera muelleri) by Canada geese, and determine the proportion of their diet that came from Zostera relative to pasture grass. Although Canada geese were observed feeding on Zostera during the dry summer months, gut and isotope samples could not support this, as they were collected during the winter/spring months. This difference indicates that the period where Canada geese exploit seagrass was not captured in the isotope study. Post-moult gut and tissue sampling (from late January) would confirm if these birds use the more digestible Zostera to meet their nutritional demands during the dry summer season as pasture grass becomes less nutritious or digestible.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".