Scale dependency of biocapacity and the fallacy of unsustainable development

Area-based information obtained from remote sensing and aerial photography is often used in studies on ecological footprint and sustainability, especially in calculating biocapacity. Given the importance of the modifiable areal unit problem (MAUP; i.e. the scale dependency of area-based information), a comprehensive understanding of how the changes of biocapacity across scales (i.e. the resolution of data) is pivotal for regional sustainable development. Here, we present case studies on the effect of spatial scales on the biocapacity estimated for two typical river basin and watershed in Northwest China. The analysis demonstrated that the area sizes of major land covers and subsequently biocapacity showed strong signals of scale dependency, with minor land covers in the region shrinking while major land covers expanding when using large-grain (low resolution) data. The relationship between land cover sizes and their change ratio across scales was shown to follow a logarithm function. The biocapacity estimated at 10 × 10 km resolution is 10% lower than the one estimated at 1 × 1 km resolution, casting doubts on many regional and global studies which often rely on coarse scale datasets. Our results not only suggest that fine-scale biocapacity estimates can be extrapolated from coarse-scale ones according to the specific scale-dependent patterns of land covers, but also serve as a reminder that conclusions of regional and global un-sustainability derived from low-resolution datasets could be a fallacy due to the MAUP.