Determination of management-sensitive indicators in assessment and monitoring of soil quality in lower seyhan plain

The Lower Seyhan Plain is experiencing a risk of losing natural functions of soils due to long-term conventional agricultural practices. The main objectives of this thesis are to; 1.) Determine the minimum data sets (MDS) required to assess various functions and overall quality of 3 genetically different soil series, 2.) Compare the scoring and weighting methods and determine the soil quality indices (SQI) and 3.) Geostatistically model the variability of the SQI and indicators in the study area and create updatable digital maps. Arıklı, Çanakçı and Helvacı soil series were chosen as the sampling area in the thesis. Soil sampling was carried out at a depth of 0-20 cm in September 2018 according to the grid system. Physical, chemical and biological properties were selected as soil quality indicators. The indicators were scored using linear and non-linear scoring curves and weighted using simple additive, principal component analysis (PCA) and analytical hierarchy process (AHP) methods. A total of 12 SQIs were identified in the study, including functions. The scores of the linearly scored indicators were mostly high, which resulted in high values for function and SQI. In contrast, lower values were obtained in non-linear scoring. The average SQI in Arıklı, Çanakçı and Helvacı series were between 38.9-82.5%, 67.1-78.8% and 46.6-76.7% respectively, and the SQI values in Arıklı and Çanakçı series were higher compared to Helvacı series. The sensitivity of weighting by PCA and AHP compared to the simple additive method, the non-linear scoring method compared to linear, and the MDS compared to the total data set are higher. Bulk density, penetration resistance, pH, organic carbon, microbial biomass carbon and beta glycosidase enzyme activity were determined as the sensitive indicators to assess the effects of management on SQI. The results showed that poor soil quality requires a comprehensive assessment of current management practices, adaptation of practices to improve soil quality, and monitor the effects of management practices on soil quality. Key Words: Soil quality, Minimum data set, Weighting, Scoring, Geostatistics