Bird and Mammal Point Count Surveys with Acoustic Noise Data, 2019-2024

Emily K. Anderson's dataset contains 12,048 five-minute point counts from 746 locations recorded between 2019 and 2024. It models detection probability and relative abundance for eight bird species and one mammal using N-mixture models with acoustic covariates. The data includes observer-rated ambient noise and smartphone-measured soundscape volume from 2019.

Use Cases

• Modeling detection probability for wildlife based on ambient noise ratings and soundscape volume measurements.
• Estimating relative abundance and population trends for specific bird and mammal species.
• Correcting undercounting bias in point count surveys by incorporating acoustic covariates.
• Comparing the effects of different sound metrics (ambient noise vs. soundscape volume) on near and distant detections.

Strengths

• Contains 12,048 survey records from 746 locations, providing a substantial observational base.
• Covers a six-year time range from 2019 to 2024, allowing for trend analysis.
• Includes two distinct acoustic metrics: observer-rated ambient noise and smartphone-measured soundscape volume.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is small at 42.1 KB, indicating limited scope or aggregated summary data.

Provenance

Source

figshare, authored by Emily K. Anderson.

Collection Method

Data gathered from point count surveys where observers rated ambient noise and used a smartphone app to measure soundscape volume.

Time Range

2019 to 2024

Freshness

Last updated 2026-04-15 11:24:18.

Geography

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