Climate change causes spatial shifts in the productivity of agricultural long-term field experiments

Abstract

Long-term field experiments (LTE) are highly valuable infrastructures in agricultural- and soil sciences for understanding the long-term impacts of climate and management practices. While they are designed to run under constant conditions, climate change is expected to affect site conditions considerably. This needs to be quantified when interpreting experimental results and when redesigning the experimental setup. One way to achieve this is by utilizing vegetation growth and carbon dynamics, specifically the Net Primary Productivity (NPP), as a spatially explicit indicator. NPP facilitates the assessment and interpretation of yield performance in LTEs under future climatic conditions. Our study estimated the changes in NPP for 271 LTE sites in Germany, comparing a baseline (2000–2020) with two scenarios (2081–2100) that were based on the Shared Socioeconomic Pathways (SSPs) (SSP245) and SSP585) by the Intergovernmental Panel on Climate Change (IPCC). We used the NASA-CASA biogeochemical model to calculate NPP in baseline and IPCC scenarios using Germany as a test case. LTEs were grouped by land use (crop types) and soil information (soil type, texture), drawing on the geodata infrastructure “BonaRes Repository”. The total annual terrestrial NPP for the baseline was calculated as 202.4 Mt C (sum of forests, grasslands, and arable lands) in Germany, while total NPP was up to 56.0 Mt C for different land use types. For both scenarios, NPP was projected to increase in LTEs located in southern Germany, indicating increased crop productivity, while a decrease was projected for the central Germany. The decrease in NPP of numerous LTEs in central Germany was estimated to extend to the LTEs in the eastern part corresponding to the worst-case scenario SSP585. Explicitly, the use of the multi-model ensemble mean as the climate driver in modelling may overestimate projected NPP by reducing inter-annual variability, highlighting the importance of methodological choices for accurate future projections. Besides, the results indicated that poor soils are projected to experience a further decline in productivity, primarily attributed to escalating water scarcity. Conversely, soils with high quality are likely to witness enhanced productivity, largely driven by the extension of the growing seasons. The outcomes of this study provide a basis for considering the future conditions of German LTEs and facilitate distinguishing between the effects of climate change and the impact of agricultural management on productivity at the regional level. These outputs enable planning and developing research strategies for selecting future LTE sites and redesigning existing or newly planned experiments. Moreover, the integrated modelling framework presented here highlights the potential of LTE data for large-scale modelling studies of ecosystem functions.