Input data resolution affects the conservation prioritization outcome of spatially sparse biodiversity features

Area of Science:

• Ecology
• Conservation Science
• Remote Sensing

Background:

• Detailed spatial data are vital for land use planning and decision-making.
• The spatial resolution of datasets can limit their utility, particularly for detecting small-scale ecological phenomena.

Purpose of the Study:

• To investigate the impact of varying spatial resolutions on conservation prioritization outcomes using Zonation software.
• To assess how different spatial resolutions affect the accuracy of identifying important ecological features in a forest landscape.

Main Methods:

• Utilized high-resolution remote sensing data, object-based mapping, and forest site type data to create feature layers.
• Applied Zonation software to conduct a conservation prioritization analysis across different spatial resolutions.
• Evaluated the ecological outcome and identified conservation errors at various resolutions.

Main Results:

• Increasing spatial resolution beyond a 16m baseline introduced substantial errors in conservation prioritization.
• Rare features, such as European Aspen, exhibited the highest conservation errors with coarser resolutions.
• Common features, like dominant tree species, showed potential benefits from increased cell size at coarser resolutions.

Conclusions:

• Adequate spatial resolution is a fundamental requirement for effective conservation prioritization.
• The size and spatial distribution of ecological features significantly influence the necessary spatial resolution for accurate assessment.