Geographical network: legacy of the Soviet era long-term field experiments in Russian agriculture

Abstract To ensure the most efficient use of data from long-term field experiments for comparative assessments of crop response to the application of fertilizers, soil reclamation measures, crop rotation systems, and tillage technologies under different soil and climatic conditions over the years and decades, it is reasonable to organize a unified experimental research network. Large-scale foundation of long-term experiments (LTEs) in Russia, according to a unified experimental plan, was realized in 1926–1930. An official foundation of the geographic network of experiments with fertilizers dates back to the governmental decision in January 1941. The network of experiments with the same or comparable treatments was intended for generalization and data averaging over extensive geographical units. During the first two decades, this network was mainly used for the scientific planning of the development of fertilizer industry. In the 1960s–1970s, with the development of zonal fertilizer systems, the main geographical patterns of fertilizer efficiency were determined on the basis of LTEs with due account for the soil pools of nutrients and their mobilization capacity, the influence of climatic conditions, and the duration of soil use and fertilizer application. During 1960s–1980s, more than 500 LTEs were conducted in the former Soviet Union. At present, the network integrates 130 LTEs performed by 65 scientific institutions in Russia. Ten of them have a history of more than 70 years. Computer processing of agronomic data accumulated in the LTEs database is used for substantiation of the integrated agrochemical field improvement technologies. With the development of global research networks in the 1990s, information from LTEs of various countries was integrated in the EuroSOMNET and LTSE Global Inventory systems and used in international and European projects for verification of dynamic models and predictive modeling, including better understanding and management of C cycles based on the dynamic modeling of soil C and crop growth for adaptation of agriculture to the expected climate change. Current promising research areas include data generalization for assessing nutrient use efficiency, soil fertility, crop yield, quality sustainability, and the effective management of bioclimatic yield potential and climatic risks under optimal nutrition and soil fertility levels. It is a challenge to expand the results of LTEs to a landscape level with the use of GIS tools and information technologies; in particular, it is important to delineate the most promising areas for agricultural intensification without damage to the environment.