Integral soil quality assessment based on arbuscular mycorrhizal fungi and related microbiological indicators (AMF-RI)

Abstract

ABSTRACT : Currently, soil quality assessments are based on scoring functions that assign scores to each indicator and combine them to generate an overall soil quality value. Whitin this type of soil quality assessment, microbiological indicators are highly necessary in conjunction with physical, chemical, and other biological indicators since the microbiological component drives a large part of soil functionality in terms of soil nutrient cycling, decomposition, nitrogen fixation, nutrient uptake to plant growth and water retention. However, soil quality assessments face two challenges that scoring functions and the subsequent use of microbiological indicators alone cannot adequately address. First, microbiological indicators are dependent on soil properties and other biological variables, making their interpretation context-dependent. Second, since scoring functions losses transparency during assignation of scores, other methods are necessary to analyze the effects of soil perturbations in response variables, considering local referents to identify the more affected variables. To address these challenges, this research focused on characterizing the responses to soil variations of communities of arbuscular mycorrhizal fungi and related microbiological indicators (AMF-RI). AMF-RI have been considered as generalist and relevant indicators of soil functionality but their implementation in soil quality assessments must be supported by an integral understanding of the relationship between them and the abiotic soil component. This thesis establishes, through a cross-biome meta-analysis, the Total Influence Degree (TID) of soil abiotic changes on AMF-RI. Results suggested a trend of large dependencies between AMF-RI with soil properties such as Pb concentrations, soil structural features, and nutrients stocks, which are explained by the effects of partial correlations among AMF-RI and microbial diversity, microbial biomass carbon and soil microbial respiration. Besides, the responses of AMR-RI facing soil abiotic changes derived from agricultural (AGA) and mining activities (MEA) were described in andosols of the southeast region of Antioquia (Colombia). A confident ANOVA approach was used to determine that populations of culturable mesophilic bacteria and fungi, catalase activity, microbial basal respiration, AMF diversity, AMF spore abundance, and total glomalin related soil proteins, as well as soil abiotic properties like NH4-N, SOC, S, and soil water contents, all suffered significant detriments depending on the degree of pressure exerted by land use. On the contrary, as the deterioration gradient progresses, Ca concentrations, soil temperature, and bulk density rise. Then, we tested a novel approach to integrate a set of soil quality indicators and AMF-RI into a soil quality measure based on a geometrical analysis of proportions of change. Using Log responses ratios (LRR) in a soil quality assessment to overcome the problems of referent target values and lack of transparency, the perimeter of 2D polygons projected from radius vectors whose length represented a proportion of change in an indicator (LRR) was tested as a soil quality index (SQILRR). This method allows showing that mining and agricultural activities have a negative but varying degree of impact on abiotic soil features such as soil organic content and water contents, as well as microbiological features such as populations of culturable mesophilic bacteria and fungi, microbial basal respiration and spore density of arbuscular mycorrhizal fungi (AMF), AMF diversity, and the contents total glomalin related soil proteins. The geometrical analysis of proportions of change in soil quality indicators offered a different soil quality measure that, even with little data, accurately distinguishes the effects of various land uses (AGA SQILRR= 0.163; MEA SQILRR= 0.296) while also identifying the variables that are more affected. To assess the effect of land use on the fungal community diversity with the LRR, the complete fungal component of the andosols in the research region was examined using meta-barcoding. There were significant correlations (r=0.94) between Shannon and Fisher indices with variations in microbial communities. Thus, fungal diversity enabled the classification of soil samples based on the land use and revealed that the abundances of important orders (Wallemiales and Trichosporonales) changed in the andosols because of variations in temperature and organic matter contents.