Data from: Factors influencing wintering turfgrass field use in Atlantic Brant
Data files
Jul 30, 2026 version files 28.52 KB
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brant_grass_final_data.csv
25.27 KB
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README.md
3.24 KB
Abstract
Atlantic Brant (Branta bernicla hrota) increasingly use turfgrass fields, such as baseball fields and golf courses, throughout their wintering range. Most studies have focused on their primary food source, submerged aquatic vegetation, while studies of other goose species worldwide have examined field use in different contexts, including agricultural fields and use during staging and migration. These studies have generally supported the importance of extrinsic factors, such as field size and distance to the roost, as well as variable effects of intrinsic factors, including forage quality and quantity, in determining field use. However, no studies have examined the system of turfgrass fields used by Atlantic Brant in the United States. We sampled turfgrass fields during the winters of 2021–22 and 2022–23 in New Jersey and New York, USA, and used Bayesian hierarchical modeling to explore the importance of field and grass characteristics in predicting both field use and the intensity of use by Brant in this urban ecosystem. We found that extrinsic characteristics—field area, distance to water, and distance to the roost—had the strongest effects on field use. The biomass of live grass and dead grass were also important predictors in both models. In contrast, grass height, weed biomass, clover biomass, carbon–nitrogen ratio, and energy density had weak effects that varied in strength and importance among models. These results are consistent with previous studies of geese in other systems, despite differences between urban turfgrass ecosystems and natural or agricultural habitats. Our findings indicate that, within urban turfgrass systems, landscape-level characteristics may outweigh traditional forage-quality metrics in driving habitat use, and they may help inform future management of Brant if submerged aquatic vegetation declines or population dynamics change.
Dataset DOI: 10.5061/dryad.sn02v6xn3
Description of the data and file structure
These data were collected to identify the intrinsic (forage quality and quantity) and extrinsic (landscape and spatial) factors influencing winter turfgrass field use by Atlantic Brant (Branta bernicla hrota) in New Jersey and New York, USA. During the winters of 2021–2023, GPS telemetry data from marked Brant were used to identify paired used and unused turfgrass fields within individual home ranges. Field sampling quantified vegetation characteristics (e.g., grass height, biomass, clover and weed biomass, dead vegetation, carbon–nitrogen ratio, and energy density), while spatial analyses quantified landscape characteristics including field area, distance to open water, and distance to nightly roosts. These data were used in Bayesian hierarchical models to evaluate predictors of field use and field use intensity.
Files and variables
File: brant_grass_final_data.csv
Description:
Variables
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SID: sample identification number
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Month: month (1-12) sample was collected
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Year: year sample was collected
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State: state where sample was collection
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FID: identification number for the specific field where the sample was collected
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Use: was the field used by Brant (1) or not (0)
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Lat: latitude in decimal degrees
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Lon: longitude in decimal degrees
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Avg_height: the height of the grass in the sample, averaged across three subsamples in mm
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Bird_ID: individual identification numbers for GPS marked Brant
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total_points: total number of GPS points in two weeks prior to sampling on the sampled field among all individual birds
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average_points: average number of GPS points in two weeks prior to sampling on the sampled field among all individual birds
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missing_points_daily: the number of GPS points missing each day from the expected number based on the set fix rate for the GPS units. Indicates GPS and communication errors.
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Roost_Distance_m: the distance in meters from the edge of the field to the centroid of the nighttime roost of birds associated with that sample
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Field_area_m2: the area of the field in square meters
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Water_Distance_m: distance from the edge of the field to the nearest water
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Total: total weight of the dried sample in grams
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Grass: total weight in grams of grass in the sample
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Clover: total weight in grams of clover in the sample
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Other: total weight in grams of other plants (i.e. weeds) in the sample
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Dead: total weight in grams of dead plants in the sample
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Live_Dead: the ratio of live plants to dead plants (by weight) in the sample
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Total_Carbon_per: total percent of carbon in a subsample of the sample
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Total_Nitrogen_per: total percent of nitrogen in a subsample of the sample
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CN_Ratio: ratio of carbon to nitrogen in the subsample of the sample
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Energy: the amount of energy released in kilojules per gram after combustion of a subsample of the sample
Code/software
Microsoft Excel
Access information
Other publicly accessible locations of the data:
- N/A
Data was derived from the following sources:
- Field collected
