Yield prediction models can be divided between data-driven and process-based models
(crop growth models). The first category contains many different types of models with …

Provisioning a sufficient stable source of food requires sound knowledge about current and
upcoming threats to agricultural production. To that end machine learning approaches were …

Climate change affects the spatial and temporal distribution of crop yields, which can
critically impair food security across scales. A number of previous studies have assessed the …

The daily air temperature and precipitation time series recorded between January 1, 1980
and December 31, 2010 in four European sites (Jokioinen, Dikopshof, Lleida and Lublin) …

Crop models are often used to project future crop yield under climate and global change and
typically show a broad range of outcomes. To understand differences in modeled responses …

Concerns about food security under climate change motivate efforts to better understand
future changes in crop yields. Process-based crop models, which represent plant …

Integrated assessment models (IAMs) hold great potential to assess how future agricultural
systems will be shaped by socioeconomic development, technological innovation, and …

Increasingly frequent and severe droughts pose a growing threat to food security in China.
However, our understanding of how different crops respond to multi-timescale drought under …

The results of the multifractal analysis performed for meteorological time series coming from
four stations in Poland and Bulgaria located in varying climatic zones are presented. To …

Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their
temporal variability as well as flux attribution to natural and anthropogenic processes is …