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Implementations &  
Methods

Spatial Framework

PatchBird Surveys use a simple spatial framework in which the globe is divided into 1 × 1 kilometre grid squares. Each survey is linked to a fixed grid location, allowing observations to be repeated at the same place over time and compared consistently across regions and habitats.

This grid-based approach ensures that bird observations are spatially structured without requiring participants to work with complex coordinate systems. Surveyors only need to visit the assigned location and follow the standardised survey protocol.

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Choosing Your Survey Spot

When you decide to participate, you are asked to indicate the general area where you plan to conduct surveys — for example, your local neighbourhood, a favourite birding site, or another accessible landscape.

Based on this information, the project team will provide one or more designated UTM grid locations for your surveys. Because these points are not public eBird Hotspots, they must be activated in your eBird account through a shared checklist process:

  1. The coordinator will share a blank eBird checklist tied to your assigned UTM grid location.

  2. Once you accept the shared checklist, the location appears in your eBird account.

  3. After your first completed survey, the original blank checklist will be deleted automatically.

Please do not create your own eBird location for PatchBird surveys — using the provided point ensures that data remain consistent and comparable across contributors.

Because survey locations are linked to a fixed 1 × 1 km grid, the assigned point may not fall exactly on the spot you originally had in mind. A deviation of up to 50–100 metres is acceptable when selecting a practical counting position.

What matters most is consistency. Once you have chosen your final counting spot, all subsequent surveys should be conducted from the same position. Repeated surveys from a consistent location are far more valuable than small differences in exact placement between visits.

Regular surveys at the same location are more valuable than occasional visits to many different sites.

Survey Protocol

PatchBird uses standardised eBird protocols to define survey efforts clearly, including duration, method, and location. Following a consistent protocol improves the reliability and comparability of observations across places and participants.

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Checklist sharing

To ensure your data are included in the PatchBird Surveys dataset:

  • Add the PatchBird project’s eBird username (PatchBirdSurveys) to your contacts in the eBird app or website.

  • Add the project username as a friend in eBird; this prevents the account from appearing unfamiliar when you share checklists.

  • Shared checklists will then be included in the project’s analytical dataset.
     

Detailed information on eBird’s checklist-sharing process is available from the official eBird support resources.

Data Analysis and Outputs

Collected survey data are submitted directly to eBird, where they become part of a globally accessible biodiversity dataset. Within PatchBird Surveys, submitted checklists are processed using established statistical and analytical methods to estimate relative abundance patterns and generate outputs such as:

  • Spatial maps illustrating bird occurrence and relative abundance

  • Seasonal summaries showing changes in species activity

  • Trend indicators highlighting emerging increase or decline signals

 

These analyses help translate individual checklists into broader ecological insights that can inform conservation planning and research.

Quality Assurance

Data quality in citizen science initiatives depends on consistent methods and transparent protocols. The PatchBird Survey Protocol contributes to quality assurance by:

  • Fixing survey duration and method to reduce effort variation

  • Using a structured spatial system (UTM grid) to ensure location consistency

  • Encouraging repeated visits to the same site to strengthen temporal inference

  • Leveraging eBird’s existing review and validation systems to flag unusual records

 

Additional quality control may be applied during analysis as the dataset accumulates, such as checking for observer bias and variability in detectability.

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