Tax team leader: Matteo Garbelotto (UC Berkeley)
Full team

Background:

Current Status and Background: To enable confidence in any overall estimate of fungal diversity, more detailed studies, especially on particular hosts in the tropics, are critical for improving estimates of overall diversity. The fungal endophyte (fungi occupying host tissues which cause no symptomatic disease) community represents the `pinnacle´ of fungal species diversity in the tropics, but are `cryptic´ and consequently, poorly documented. The Moorea Fungi biocode project objectives are to stratify the sampling according to trophic guilds (wood, leaves) for direct comparison of fungal diversity of soil (soil saprobes, root endophytes and mutualists) and to capture the astounding `cryptic´ diversity of tropical ecosystems. Second, we plan to collect macrofungal specimens for cataloguing and identification from expert tropical mycologists. Both approaches add significant strengths to the MBP by recognizing that fungi are macro-components of Moorea as well as cryptic microscopic components that are critical for ecosystem function. To accomplish these goals, we propose a two year inventory of fungi occupying diverse trophic guilds that utilizes our expertise with handling difficult substrates, exposing cryptic diversity, and handling large datasets. The benchmarks of this study are: (a) creating better biodiversity estimates of fungi by universalizing surveys across stratified trophic guilds making them robust and comparable; (b) provide a benchmark, not only for future studies on fungal tropical diversity, but also for surveys of other habitats, or areas worldwide and; (c) provide the first robust estimates of alpha diversity from stratified fungal guilds in tropical ecosystems by targeting the `cryptic´ diversity in plant and soil substrates. In a preliminary study conducted in June, 2006, Matteo Garbelotto sampled soils from an out-planted Caribbean pine (Pinus caribea) plantation in Moorea. Our goals were to characterize phyletic diversity of bulked soil pools from two geographically distant sites from: a) soil underneath pine (pine); and b) pine and other tropical plants (pine + understory). This sampling effort was not intended as an exhaustive approach, but rather to estimate the fungal diversity and dominant guilds from a simplified plant ecosystem (i.e., single plant species = pine) introduced as a timber commodity, and to compare alpha diversity across soil environments (i.e., pine + other tropical plants). We found that the overall phyletic species diversity (based on the number of unique sequence types) did not differ between pine or pine + understory. Only two dominant phyletic species were encountered in all four sample locales, and only 15% of the species were sampled more than once. Significantly, slightly less than half of all clones sequenced were unique species. We intend to sample ~60 sites, chosen in collaboration with other terrestrial teams, and sequence between 15-20,000 clones from those samples. Based on the Pinus relative abundance results, we expect to encounter 7-10,000 unique phyletic species. Stratifying sampling effort (multiple reps/site) across spatial scales and hosts will increase our chances of characterizing fungal diversity. We also recognize that the sampling efforts may be insufficient for estimating true alpha diversity, but our efforts will provide the critical means to estimate species richness by capturing the `cryptic´ diversity.

Significance:

This fungal portion of the MBP mixes both vouchered and non-vouchered documentation of biodiversity. Thus, it fills a pivotal role between collections based research and a community metagenomic approach that better captures the phyletic diversity of fungi in ecosystems. The fungal survey will provide a necessary test data set for extending the functionality of the IT infrastructure, particularly in capturing alternative loci and analytical methods involving cloning. While the metadata associated with the fungal survey is essentially the same (event data, PCR, trace files, etc.), the data flow is different; specimen IDs are assigned after PCR and cloning, not before entering the laboratory analytic chain.

First results