There is increasing evidence that the impact of climate change on the productivity of
grasslands will at least partly depend on their biodiversity. A high level of biodiversity may …

In the present study, multiple linear regression models were constructed to simulate the yield
of winter wheat, rapeseed, maize and sunflower in Hungary for the 2000–2016 time period …

Farmers and ranchers depend on annual forage production for grassland livestock
enterprises. Many regression and machine learning (ML) prediction models have been …

Conservation agriculture (CA) involves complex and interactive processes that ultimately
determine soil carbon (C) storage, making it difficult to identify clear patterns. To solve these …

Simulation models represent soil organic carbon (SOC) dynamics in global carbon (C) cycle
scenarios to support climate‐change studies. It is imperative to increase confidence in long …

Simulation models are extensively used to predict agricultural productivity and greenhouse
gas emissions. However, the uncertainties of (reduced) model ensemble simulations have …

Croplands and grasslands are agricultural systems that contribute to land–atmosphere
exchanges of carbon (C). We evaluated and compared gross primary production (GPP) …

In this introductory paper to the special issue on crop model prediction uncertainty, we
present and compare the methodological choices in the studies included in this issue, and …

Simulation models quantify the impacts on carbon (C) and nitrogen (N) cycling in grassland
systems caused by changes in management practices. To support agricultural policies, it is …

Crop production will likely face enormous challenges against the occurrences of extreme
climatic events projected under future climate change. Heat waves that occur at critical …