The impact of land use on ecosystems has reached critical levels, jeopardizing biosphere integrity. A key indicator that quantifies, monitors, and analyses such impacts is the Human Appropriation of Net Primary Production (HANPP). Assessing HANPP requires integrating data from sources such as remote sensing and census statistics, as well as modelled data like potential Net Primary Production (NPP), which reflects NPP without land use. Although the availability of global land cover data at high spatial detail from remote sensing has improved, with resolutions reaching 30 arcseconds (about 1 km) and higher, global NPP results from Dynamic Global Vegetation Models (DGVMs) are still unavailable at this resolution. This spatial mismatch causes uncertainties, as simple interpolation methods fail to capture fine-scaled productivity patterns. We here present a parsimonious method to downscale NPP, using the Miami NPP model with temperature and precipitation data as readily available auxiliary information at high spatial resolution. Our method uses a moving window approach with Gaussian convolution to minimize downscaling artefacts. We demonstrate this Smooth Auxiliary Data (SAD) downscaling approach by downscaling potential NPP results from the LPJ-GUESS-DGVM model for the year 2010 from 30arcmin to 30arcsec resolution. This approach, requiring low computational cost, generates fine-scaled productivity patterns and aligns with alternative models for smaller geographic units, offering a solution until high-resolution DGVM results become feasible.

Wildfires and land use play a central role in the long-term carbon (C) dynamics of forested ecosystems of the United States. Important processes include fire suppression during the 20th century and a recent increase in fire activity, partly due to climatic extreme events. Although the historical fire narrative in the U.S. is well understood, its links to changes in forest biomass, resource use and consumption remain understudied. We reconstruct long-term trends in biomass burned, and biomass use by humans, integrating various data sources at different scales (national scale 1926-2017, regional level 1941-2017). We investigate the linear correlation of wildfires and forest biomass C stocks in comparison to forest uses, i.e., the extraction of woody biomass and forest grazing, and potential net primary production (NPPpot). During the 20th century, the reduction in burned biomass and increase in NPPpot coincide with forest regrowth in the Eastern U.S., allowing for increased wood harvest. Only in the Western U.S. these dynamics are less pronounced, indicating that forest fires and biomass harvest were less decisive factors for forest C stock developments in this section. In recent decades, linkages between forest change and wildfires are less straight-forward in all regions, indicating that past fire suppression levels are less efficient in present-day forests. Instead, the reduction of harvest in 3 of 4 regions was correlated to stock increase. We conclude that under changing climate, present-day fire and forest management practices might be unsuitable for ensuring both additional forest C sink potential and expanded wood use.