A simple inhibition coefficient for quantifying potency of biocontrol agents against plant-pathogenic fungi

Microbial interactions depend on a range of biotic and environmental variables, and are both dynamic and unpredictable. For some purposes, and under defined conditions, it is nevertheless imperative to evaluate the inhibitory efficacy of microbes, such as those with potential as biocontrol agents. We selected six, phylogenetically diverse microbes to determine their ability to inhibit the ascomycete Fusarium
coeruleum, a soil-dwelling pathogen of potato tubers that causes the storage disease dry rot. Interaction assays, where colony development was quantified (for both fungal pathogen and potential control agents), were therefore carried out on solid media. The key parameters that contributed to, and were indicative of, inhibitory efficacy were identified as: fungal growth-rates (i) prior to contact with the biocontrol
agent and (ii) if/once contact with the biocontrol agent was established (i.e. in the zone of mixed
culture), and (iii) the ultimate distance traveled by the fungal mycelium. It was clear that there was no correlation between zones of fungal inhibition and the overall reduction in the extent of fungal colony development. An inhibition coefficient was devised which incorporated the potential contributions of distal inhibition of fungal growth-rate; prevention of mycelium development in the vicinity of the biocontrol
agent; and ability to inhibit plant-pathogen growth-rate in the zone of mixed culture (in a ratio of 2:2:1). The values derived were 84.2 for Bacillus subtilis (QST 713), 74.0 for Bacillus sp. (JC12GB42), 30.7 for Pichia anomala (J121), 19.3 for Pantoea agglomerans (JC12GB34), 13.9 for Pantoea sp. (S09:T:12), and
21.9 (indicating a promotion of fungal growth) for bacterial strain (JC12GB54). This inhibition coefficient, with a theoretical maximum of 100, was consistent with the extent of F. coeruleum-colony development (i.e. area, in cm2) and assays of these biocontrol agents carried out previously against Fusarium
spp., and other fungi. These findings are discussed in relation to the dynamics and inherent complexity of natural ecosystems, and the need to adapt models for use under specific sets of conditions.

A spatial approach to network generation for three properties:Degree distribution, clustering coefficient and degree assortativity

Social networks generally display a positively skewed degree distribution and higher values for clustering coefficient and degree assortativity than would be expected from the degree sequence. For some types of simulation studies, these properties need to be varied in the artificial networks over which simulations are to be conducted. Various algorithms to generate networks have been described in the literature but their ability to control all three of these network properties is limited. We introduce a spatially constructed algorithm that generates networks with constrained but arbitrary degree distribution, clustering coefficient and assortativity. Both a general approach and specific implementation are presented. The specific implementation is validated and used to generate networks with a constrained but broad range of property values. © Copyright JASSS.