Understanding fungal functional biodiversity during the mitigation of environmentally dispersed pentachlorophenol in cork oak forest soils

Pentachlorophenol (PCP) is globally dispersed and contamination of soil with this biocide adversely affects its functional biodiversity, particularly of fungi - key colonizers. Their functional role as a community is poorly understood, although a few pathways have been already elucidated in pure cultures. This constitutes here our main challenge - elucidate how fungi influence the pollutant mitigation processes in forest soils. Circumstantial evidence exists that cork oak forests in N. W. Tunisia - economically critical managed forests are likely to be contaminated with PCP, but the scientific evidence has previously been lacking. Our data illustrate significant forest contamination through the detection of undefined active sources of PCP. By solving the taxonomic diversity and the PCP-derived metabolomes of both the cultivable fungi and the fungal community, we demonstrate here that most strains (predominantly penicillia) participate in the pollutant biotic degradation. They form an array of degradation intermediates and by-products, including several hydroquinone, resorcinol and catechol derivatives, either chlorinated or not. The degradation pathway of the fungal community includes uncharacterized derivatives, e.g. tetrachloroguaiacol isomers. Our study highlights fungi key role in the mineralization and short lifetime of PCP in forest soils and provide novel tools to monitor its degradation in other fungi dominated food webs. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd

Parameter Estimation in Linear Models with Heteroscedastic Variances Subject to Order Restrictions

Estimation of parameters in linear fixed and mixed effects models, under order restrictions on the error variances, is considered in this article. For simplicity of exposition, we shall assume that the error variances are subject to simple order restriction. Similar methodology can be developed for other forms of order restrictions as well.fixed effects heteroscedastic errors isotonic regression maximum likelihood estimation mixed effects simple order restriction