Real world data for real world problems: Importance of appropriate spatial resolution modelling to inform decision makers in marine management.

Description

The effective management of Blue Carbon ecosystems such as mangroves, seagrasses, and salt marshes require decision-making grounded in high-quality, precise data. A key challenge lies in the spatial resolution of datasets used in predictive modelling. By examining the influence of spatial resolution on the understanding and management of Blue Carbon habitats, we analyse how varying levels of detail in data affect our ability to accurately model ecosystems and the consequences when overlaid with anthropogenic pressures. This analysis is particularly crucial considering limitations in data availability. Higher spatial resolution data can reveal intricate patterns of habitat distribution and health, enabling more precise management strategies that are appropriate for local decision-making. Conversely, relying on coarse-resolution data may lead to gaps in understanding, potentially underestimating the ecological value and carbon sequestration potential of these habitats.
Using the example of maerl beds within the Fetlar-Haroldswick Marine Protected Area in the Shetland Islands, Scotland, we investigate how different spatial resolutions (50m, 100m, 200m, and 500m) affect the modelling of this Blue Carbon habitat. By comparing model outputs across these resolutions, we reveal significant variations in habitat coverage, distribution, and the potential implications for management strategies aimed at enhancing carbon sequestration and mitigating climate change.
Furthermore, we simulate real-world marine activities to assess the overlap of human impacts on these habitats, highlighting how different spatial resolutions can lead to under- or overestimation of pressures. The findings emphasise that while coarse resolution data may suffice for broader strategic decisions, fine resolution local data is essential for effective management and conservation efforts that directly affect Blue Carbon ecosystems.
This analysis aims to highlight the necessity of integrating high-resolution and local spatial data in Blue Carbon initiatives, thereby improving both conservation efforts and policy development. By addressing the complexities and limitations of existing datasets, this research enhances the understanding of Blue Carbon's role in climate change mitigation and contributes to the development of sustainable management practices. The implications also extend beyond marine environments, offering insights applicable to terrestrial ecosystems and broader environmental governance.

Period	7 Nov 2024
Event title	MASTS - Annual Science Meeting 2024
Event type	Conference
Degree of Recognition	National