Global assessment of landscape pattern changes from 1992 to 2020
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Context
Changes in landscape patterns, which refer to the composition and spatial configuration of land use and land cover (LULC) classes in a landscape, can have negative impacts on biodiversity and environmental processes such as carbon cycles. Such impacts are both dependent on the spatial extent of changes and which LULC classes are affected, but previous global-scale landscape pattern assessments have focused on single LULC classes or landscape-level measurements only. A comprehensive, multiscale analysis across multiple LULC types is therefore key for understanding the full impact of landscape pattern change on the environment.
Objectives
We assessed global-scale change in landscape patterns for six LULC classes from the HILDA+ dataset (urban, cropland, pasture/rangeland, forest, unmanaged grass/shrubland, and sparse/no vegetation) between 1992 and 2020.
Methods
Six class-level landscape metrics with predictable scaling behaviour across landscape extents were calculated at global scale for each LULC class and year. Landscape metrics were quantified for five landscape extents (100, 400, 1600, 6400 and 25,600 km 2 ). Trends in landscape metrics were evaluated and linked to changes in LULC composition (area) and configuration over time.
Results
Unmanaged grass/shrubland LULC expanded in area and showed increased number of patches, edge length, and complexity in shapes, while pasture/rangeland and forest LULC tended to decline in area, number of patches, and edge length. Even though there was high spatial heterogeneity in landscape pattern change for all LULC classes, neighbouring 100 km 2 landscapes often showed the same directional change in area and fragmentation.
Conclusions
Global landscape pattern change was highly variable for all LULC classes between 1992 and 2020, suggesting that drivers of LULC change act on local to regional scales. We expect that the multiscale global dataset of landscape metrics generated here will have future applications in understanding the drivers of landscape pattern change and its environmental impacts.
