Biodiversity and Anthropogenic Change in Fungal Communities of the Santa Rita Mountains (Arizona, USA)
Bibliographic record
Abstract
Represented by extensive functional and phylogenetic diversity and encompassing mycorrhizae, saprotrophs, pathogens, lichens, animal associates, and endophytes, the fungal kingdom is an important component of global ecosystems. Macrofungi – the subset of fungi distinguished by having macroscopic sporocarps – play diverse ecological roles in wild ecosystems, including substrate decomposition, enhancement of soil fertility, and facilitation of rhizosphere dynamics as root symbionts. Recent observations facilitated by current sequencing methods reveal that some macrofungi may occur in an endophytic phase within plant tissues. Endophytes are those fungi that inhabit plant tissues asymptomatically, often exhibiting commensal and mutualistic lifestyles that influence phenotypes and functional traits of plant hosts. Thus, to characterize macrofungal diversity it is beneficial to combine traditional methods such as collections of sporocarps and reviews of fungal herbarium specimens with evaluation of plant tissues for evidence of endophytic macrofungi. This thesis explores macrofungal diversity in a biodiversity hotspot in southern Arizona: the Santa Rita Mountains and the adjacent grasslands and oak woodlands that comprise parts of the Santa Rita Experimental Range. This area in southern Arizona has a well recorded fire history and stark ecological and vegetation gradients traversing desert scrub typical of the Sonoran Desert to coniferous forests resembling those of Canada in only a few kilometers. The area has been subject to intensive study via the Santa Rita Experimental Range for many years, with extensive knowledge of grazing history and plant community and vegetation dynamics. The goal of my work was to provide a first inventory of macrofungi in the Santa Rita region. In this work I combine several data streams. First, I and my collaborators conducted field collections of macrofungal sporocarps in grasslands, oak forests in woodlands, and coniferous forests over three years. Second, I evaluated over 100 years of historical collections from the Santa Ritas, drawing from specimens housed at the University of Arizona’s Robert L. Gilbertson Mycological Herbarium and made publicly visible through the fungal biodiversity portal, MyCoPortal. Third, I reviewed a compendium of records from community scientists and enthusiasts in a collaborative iNaturalist project for the area. Finally, I used DNA sequencing to characterize culturable fungal endophytes from plant tissues at our selected sites, each having distinctive plant communities, abiotic conditions, and fire histories, to understand the contributions of endophytes to macrofungal biodiversity in this area. Records of sporocarp collection from over a century, coupled with new collections, new iNaturalist observations, and molecular analyses of endophyte communities, revealed at least 300 species of macrofungi in the Santa Rita Mountains and Santa Rita Experimental Range. New collections during the 2024 monsoon season coupled with iNaturalist records added over 40 species to the known records (>10%). We detected macrofungi as cryptic endophytes in both burned and unburned grasslands, oak woodlands and conifer forests, but the contribution to the macrofungal inventory of the region was limited relative to the inputs of community scientists/observers and Herbarium collections. My work contributed new accessions in the Gilbertson Herbarium, new digital records on MyCoPortal and iNaturalist, and new DNA sequences to be archived publicly in GenBank in the future. I also supported the training of an undergraduate student in curatorial activity, with all aspects of my work advancing the understanding of the fungal biodiversity of iconic landscapes of southern Arizona. To complement my research as a Master’s student, I gained a broad perspective on changing ecosystems and the -omics-based tools used to study them in a collaborative manner. My experiences included training through two programs funded by the National Science Foundation: EMERGE-BII (EMergent Ecosystem Response to ChanGE Biology Integration Institute) and the BRIDGES NRT (Building Resources for InterDisciplinary training in Genomic and Ecosystem Sciences). As a trainee in both programs and as a Fellow in the latter, I learned to contextualize my research within a comparative and convergent framework of scientific inquiry and multiple scales of biology. This approach facilitates the discovery of interactions among fungal biology, diversity, and genetics within dynamic ecosystems, spanning molecular to community scales. With these programs, my fundamental graduate training, and my research, my Masters work has begun to elucidate the relationships between the phenology, ecology, systematics, and taxonomy of fungi within Arizona and beyond.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".