A qPCR Assay for the Detection of Phytophthora cinnamomi Including an mRNA Protocol Designed to Establish Propagule Viability in Environmental Samples.

Phytophthora cinnamomi causes root and collar rot in many plant species in natural ecosystems and horticulture. A species-specific primer and probe PCIN5 were designed based on a mitochondrial locus encoding subunit 2 of cytochrome c oxidase (cox2). Eight PCR primers, including three forward and five reverse, were designed and tested in all possible combinations. Annealing temperatures were optimized for each primer pair set to maximize both specificity and sensitivity. Each set was tested against P. cinnamomi and two closely related clade 7 species, P. parvispora and P. niederhauseri. From these tests, five primer pairs were selected based on specificity and, with a species-specific P. cinnamomi probe, used to develop quantitative real-time PCR (qPCR) assays. The specificity of the two most sensitive qPCR assays was confirmed using the genomic DNA of 29 Phytophthora isolates, including 17 isolates of 11 species from clade 7, and representative species from nine other clades (all except clade 3). The assay was able to detect as little as 150 ag of P. cinnamomi DNA and showed no cross-reaction with other Phytophthora species, except for P. parvispora, a very closely related species to P. cinnamomi, which showed late amplification at high DNA concentrations. The efficiency of the qPCR protocol was evaluated with environmental samples including roots and associated soil from plants artificially infected with P. cinnamomi. Different RNA isolation kits were tested and evaluated for their performance in the isolation of RNA from environmental samples, followed by cDNA synthesis, and qPCR assay. Finally, a protocol was recommended for determining the presence of P. cinnamomi in recalcitrant environmental samples.

Do state-and-transition models derived from vegetation succession also represent avian succession in restored mine pits?

State-and-transition models are increasingly used as a tool to inform management of post-disturbance succession and effective conservation of biodiversity in production landscapes. However, if they are to do this effectively, they need to represent faunal, as well as vegetation, succession. We assessed the congruence between vegetation and avian succession by sampling avian communities in each state of a state-and-transition model used to inform management of post-mining restoration in a production landscape in southwestern Australia. While avian communities differed significantly among states classified as on a desirable successional pathway, they did not differ between desirable and deviated states of the same post-mining age. Overall, we concluded there was poor congruence between vegetation and avian succession in this state-and-transition model. We identified four factors that likely contributed to this lack of congruence, which were that long-term monitoring of succession in restored mine pits was not used to update and improve models, states were not defined based on ecological processes and thresholds, states were not defined by criteria that were important in structuring the avian community, and states were not based on criteria that related to values in the reference community. We believe that consideration of these four factors in the development of state-and-transition models should improve their ability to accurately represent faunal, as well as vegetation, succession. Developing state-and-transition models that better incorporate patterns of faunal succession should improve the ability to manage post-disturbance succession across a range of ecosystems for biodiversity conservation.

Soil microbial community successional patterns during forest ecosystem restoration.

Soil microbial community characterization is increasingly being used to determine the responses of soils to stress and disturbances and to assess ecosystem sustainability. However, there is little experimental evidence to indicate that predictable patterns in microbial community structure or composition occur during secondary succession or ecosystem restoration. This study utilized a chronosequence of developing jarrah (Eucalyptus marginata) forest ecosystems, rehabilitated after bauxite mining (up to 18 years old), to examine changes in soil bacterial and fungal community structures (by automated ribosomal intergenic spacer analysis [ARISA]) and changes in specific soil bacterial phyla by 16S rRNA gene microarray analysis. This study demonstrated that mining in these ecosystems significantly altered soil bacterial and fungal community structures. The hypothesis that the soil microbial community structures would become more similar to those of the surrounding nonmined forest with rehabilitation age was broadly supported by shifts in the bacterial but not the fungal community. Microarray analysis enabled the identification of clear successional trends in the bacterial community at the phylum level and supported the finding of an increase in similarity to nonmined forest soil with rehabilitation age. Changes in soil microbial community structure were significantly related to the size of the microbial biomass as well as numerous edaphic variables (including pH and C, N, and P nutrient concentrations). These findings suggest that soil bacterial community dynamics follow a pattern in developing ecosystems that may be predictable and can be conceptualized as providing an integrated assessment of numerous edaphic variables.