Model for detection and assessment of abiotic stress caused by uranium mining in European Black Pine landscapes

The article presents the results obtained from a study for detection and assessment of abiotic stress through pollution with heavy metals, metalloids, and natural radionuclides in European Black Pine (Pinus nigra L.) forests caused by uranium mining using ground-based biogeochemical, biophysical, and field spectrometry data. The forests are located on a territory subject to underground and open uranium mining. An operational model of the study is proposed. The areas subject to technogeochemical load are outlined based on the aggregate pollution index Zc. Laboratory and field spectrometry data were used to detect the signals of abiotic stress at pixel level. The methods used for determination of stressed and unstressed black pine forests are: four vegetation indices (TCARI, MCARI, MTVI 2, and PRI 1) for stress detection, and the position, depth, asymmetry, and shift of the red-edge. Based on the "blue shift" and the depth and position of the red-edge, registered by the laboratory analysis and field spectral reflectance, it is established that coniferous forests subject to abiotic stress show an increase in total chlorophyll content and carotene. It has been found that the vegetation indices MTVI 2 and PRI 1, as well as the combination of vegetation indices and pigments may be used as a direct indicator of abiotic stress in coniferous forests caused by uranium mining.