Prior to this study, it was not know which species of decay fungi caused decay in New Zealand leaky buildings. Use of molecular biology methodology, polymerase chain reaction (PCR), and subsequent DNA sequencing, as well as classical mycological techniques based on morphology, has enabled identification of decay fungi and has provided insight into their relative importance based on isolation frequency. Fungi colonising Pinus radiata D. Don framing timber of leaky New Zealand buildings were isolated to produce pure cultures. Mycelia from these cultures on agar media were collected to extract DNA. To identify the fungi to the species level, PCR with primer pairs NSI1 + NLB4 and ITS1-F + ITS4 were performed followed by sequencing of the internal transcribed spacer (ITS) region. Identification was by BLAST (Basic Local Alignment Search Tool) search on sequences in GenBank. In total, 421 samples from leaky buildings were processed, mainly decayed timber, but also fibre cement boards and building paper. Sixty-eight fungal identifications were achieved of which 4 species are very common as follows: • Gloeophyllum sepiarium (Wulf.: Fr.) Karst. 13x • Oligoporus placenta (Fries 1865) Gilb. In Ryv.1985 11x • Antrodia sinuosa (Fr.) Karst. 8x • Gloeophyllum trabeum (Fr.) Murr 4x An aerial spore study of internal air, wall cavity air and exterior air of leaky buildings was carried out using a Merck MAS-100 instrument which collects spores directly onto various selective media plates. Also, decayed wood samples from the same leaky buildings enabled identification of G. sepiarium and A. sinuosa at the same test site. Viable fungal aerial spores were detected at every sampling location, with a highest mean of 3714 colony-forming units (CFU) per square meter found in water-damaged walls. The use of Carboxymethylcellulose medium further demonstrated the presence of cellulose degrading fungi within and around the location. Overall, the combination of these two approaches proved useful for detection of fungal species variation at a multi-unit building complex and it was possible to identify the brown rot decay fungal genus Antrodia with both methods.

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