Integrating Species Distribution Models, GeoAI, and Citizen Science: Predictive Tools for Bird Habitat Assessment and Conservation Decision-Making

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About this Research Topic

Submission deadlines

  1. Manuscript Submission Deadline 12 January 2027

  2. This Research Topic is currently accepting articles

Background

Bird populations are facing unprecedented global pressures from climate change, habitat fragmentation, land use transformation, and intensifying human activity. These threats are compounding rapidly, demanding tools that can process large, heterogeneous spatiotemporal datasets and translate scientific insight into effective conservation outcomes. Species distribution models (SDMs), geospatial artificial intelligence (GeoAI), remote sensing, and citizen science platforms such as eBird and iNaturalist have each advanced significantly in recent years, creating an opportunity to integrate these approaches into a coherent framework for bird habitat assessment and conservation planning.



Despite this progress, the gap between predictive modelling and on-the-ground management decisions remains wide. Habitat suitability maps are rarely paired with quality assessments or connectivity analyses. Migration route predictions seldom account for real-time environmental dynamics or collision risk in human-modified landscapes. Conservation planning and reserve design still depend heavily on static data, even as the spatiotemporal dynamics and drivers of climate and land use change reshape ecosystems at pace.



This Research Topic invites original contributions that advance the theory and practical application of predictive and spatial tools across the full spectrum of avian habitat science and conservation management. We are particularly interested in research that bridges the methodological and applied dimensions, from data-intensive modelling to actionable strategies for threatened and migratory species.



We especially welcome submissions on the following topics:



1. Species distribution and habitat suitability modelling

2. GeoAI and machine learning for avian spatial analysis

3. Remote sensing, LiDAR, and GIS for bird habitat mapping

4. Citizen science data integration for predictive modelling

5. Acoustic monitoring and computer vision with geospatial data

6. Migration dynamics, flyway modelling, and collision risk assessment

7. Spatiotemporal dynamics and drivers of climate and land use change impacts

8. Landscape connectivity and habitat quality assessment

9. Conservation prioritization, reserve design, and ecological restoration

10. Adaptive management strategies for threatened and migratory species

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Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

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  • Clinical Trial
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Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Keywords: species distribution models, GeoAI, citizen science, bird habitat assessment, conservation decision-making, remote sensing, landscape connectivity, migration dynamics, spatiotemporal dynamics, avian conservation

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Manuscripts can be submitted to this Research Topic via the main journal or any other participating journal.

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