Working on solid ground: how AI bird monitoring supports onshore wind development

Biodiversity monitoring on onshore wind farm

Published
September 9, 2025
Reading time
5 minutes
Categories
Bird monitoring, Biodiversity conservation

There are clear evidences that onshore wind’s biodiversity impacts extend far beyond collisions, affecting displacement, habitat use, breeding success and long-term behavior. For developers, the message is clear: occasional surveys no longer suffice, and continuous, high-resolution monitoring is fast becoming the baseline expectation of regulators, financiers and stakeholders.

Rising expectations from regulators and policy

Impacts such as habitat disruption, migration disturbance and reduced breeding success play out across the entire wind farm lifecycle, from site preparation to decommissioning, and are particularly acute where projects intersect with flyways, raptor hunting grounds or breeding sites. Regulators are responding by raising the bar:

The 2025 NatureScot guidelines require quantitative estimates of collision risk for all relevant species, contextualized at population level. This demands richer datasets than many legacy approaches provide.
NatureScot has also updated its avoidance rate assumptions, emphasizing the importance of empirical site-based data.
The EU-funded Wind4Bio project codifies best practices across the wind farm lifecycle, placing continuous monitoring and adaptive management at the centre.

Together, these developments point towards a future where adaptive, high-resolution data becomes the baseline standard, not the exception.

What modern onshore monitoring needs to deliver

For monitoring to add real value, it must provide:

Continuity – data streams that extend beyond short-term surveys, capturing seasonal and year-to-year variability.
Resolution – detailed trajectory and altitude data to refine collision risk models.
Context – insights into activity patterns that inform both permitting and operational strategies.
Integration – compatibility with mitigation tools such as shutdown-on-demand (SDOD) systems, which pause turbines only when sensitive species are detected.

This is the shift from reactive to adaptive monitoring: from static reports submitted for permits, to dynamic systems that actively support biodiversity governance throughout the project lifecycle.

Applying continuous monitoring systems in onshore wind

Vision-based AI monitoring systems, when deployed on turbines, masts, or nearby infrastructure, can now provide detailed, site-specific insights into bird activity. Cameras capture high-resolution video, which is processed in real time to track flight paths, altitude, and activity hotspots.

When combined with expert validation by ornithologists, such systems generate defensible datasets for:

Improving avoidance rate parameters in collision risk models.
Detecting changes in bird activity across seasons and years.
Triggering curtailment events only when necessary, reducing energy loss while protecting species.
Meeting the data transparency demands of regulators and lenders.

Spoor currently supports several European onshore wind projects with this type of adaptive monitoring. Its AI platform feeds into shutdown-on-demand protocols while generating data aligned with IFC and EBRD biodiversity safeguards.

Transparency and limits in context

No monitoring technology is perfect, and credible practice requires acknowledging limitations. For vision-based systems, weather and visibility conditions, vegetation density, or extreme light levels can affect detection quality. Species-level identification often still benefits from collaboration with ecological experts.

These constraints are not shortcomings of one tool but realities consistent with the 2025 biodiversity review, which stresses that outcomes depend heavily on local ecological context. The key is transparency: using monitoring systems within their validated ranges, and complementing them with expert input where needed.

Building resilient projects

As more countries reinforce biodiversity protections and strengthen permitting conditions, wind developers who adopt robust monitoring strategies will be better positioned to secure approvals, maintain compliance, and demonstrate ecological responsibility.

AI-driven monitoring platforms like Spoor’s provide one pathway towards this goal — scalable, transparent, and adaptable to the realities of modern onshore wind. More importantly, they exemplify a broader shift in the sector: from viewing monitoring as a compliance burden to recognizing it as a cornerstone of long-term project resilience.

📩 Interested in exploring how adaptive monitoring could be applied to your onshore projects? Contact us to discuss our deployments solutions.