Long-term landscape – land use interactions as explaining factor for soil organic matter variability in Dutch agricultural landscapes

Abstract

The present-day land use pattern is often used for estimating soil organic matter pools. Although the effect of historical land use on soil organic matter (SOM) pools is often recognized, this factor is never accounted for in large-scale SOM inventories. We assessed if an inventory of long-term landscape management can be used to improve estimates of landscape-scale SOM variability for a 60 km 2 case study in the northern Dutch sand area. We hypothesize that soil, present-day and historical land use and their interactions can explain the bulk of SOM variability at multiple scales. Actual SOM data from a 1:10.000 soil inventory of the study area were used to test this hypothesis. Land use history (1780-2000) was reconstructed using topographic maps and land use databases. Potential explaining factors for SOM contents were analysed. Linear models were used to characterize SOM variability at 50 m, 200 m and 500 m resolutions. Soil characteristics like loam content (R 2 = 0.25), median sand grain size (R 2 = 0.20) or soil classification (R 2 = 0.23) can partly explain total SOM variability. Present-day land use only explains 2% of SOM variability. Historical land use patterns explain a much larger part of the total SOM variability (R 2 = 0.14 for land use patterns in 1780 and R 2 = 0.20 for land use patterns in 1850). At 50 m resolution, SOM contents can be best explained with soil and land use history factors (R 2 = 0.28). At 200 m resolution, soil and groundwater factors yileld the best model (R 2 = 0.42) while at 500 m resolution a model including soil, groundwater and historical land use performs best (R 2 = 0.75). We conclude that land use history data can significantly improve SOM inventories at multiple scales. Especially at detailed scales it can improve insight in both SOM pool size and origin of SOM variability. As land use history of the Netherlands is relatively well documented, we expect that an improvement of national SOM pool estimates is feasible.