Tracking the occurrence and fate of human bocavirus 2 in municipal wastewater from a small city - Sharon C. Kosgei; Olivia N. Birch; Roberto A. Rodriguez; Monica Kpabar; Kendall L. Ratliff; Justin C. Greaves (Molecular Biology Reports, 2026)
Background Human Bocavirus 2 (HBoV2) is an emerging enteric virus frequently detected in wastewater, yet its environmental fate, persistence, and treatment remain poorly understood. Improved characterization of HBoV2 is important for advancing wastewater-based epidemiology and understanding viral transmission dynamics. Methods and Results A year-long wastewater surveillance study was conducted from December 2023 to December 2024 in a small urban wastewater treatment system. Viral concentrations were quantified using digital PCR (dPCR), decay kinetics were assessed using controlled mesocosm experiments, and phylogenetic relationships were evaluated through NP1 gene sequencing. HBoV2 was detected in 93.8% of influent samples (average 4.76 log₁₀ genome copies per liter (GC/L) ) with seasonal peaks in summer and fall. Phylogenetic analysis revealed clustering with globally circulating HBoV2 lineages. Decay experiments indicated slow viral degradation (k = 0.10 d⁻¹), comparable to other non-enveloped DNA viruses including Adeno-Associated Virus type 2 (AAV-2), Adenovirus 41 (AdV41), and Human Polyomavirus (HPyV). Additionally, HBoV2 persisted through secondary treatment, with no significant reduction observed between influent and secondary effluent samples. Conclusion Our findings indicate HBoV2 as highly prevalent and environmentally stable in a small urban city’s wastewater and that it is resistant to conventional treatment. These findings highlight HBoV2’s potential role in gastrointestinal infections worldwide and the need for further monitoring of this environmental contaminant.

A hybrid physics-machine learning framework for improving simulations of urban air-conditioning electricity consumption - Xiangwen Deng; Jed J. Cohen; Justin Rodriguez; Bohumil M. Svoma; Chris Gonzales; Matei Georgescu (Energy and Buildings, 2026)

Per- and polyfluoroalkyl substances and pesticides in black bears (Ursus americanus) and grizzly bears (Ursus arctos horribilis) from Montana's Cabinet-Yaak ecosystem: A baseline assessment of emerging and legacy contaminants - Brian C. Balmer; Marina D. Rodriguez; Justin E. Teisberg; Michelle L. Hladik; Wayne F. Kasworm; Amber Kornak; Thomas G. Radandt; Landon M. Keele; Erin L. Pulster (Environmental Pollution, 2026)

Revealing the hidden burden: wastewater-based epidemiology for underreported and emerging infectious diseases in communities - Justin C. Greaves; Roberto A. Rodriguez (Environmental Monitoring and Assessment, 2026)
Wastewater-based epidemiology (WBE) has become a transformative tool for infectious disease surveillance, providing population-level insights that complement and extend traditional case-based reporting. This review examines the expanding role of WBE in identifying and characterizing underreported, novel, and emerging human pathogens. Evidence reveals that wastewater analysis consistently detects enteric, respiratory, and neglected pathogens that are often missed by clinical systems, thereby revealing the hidden burden of infection within communities. Sequencing-based studies have identified numerous novel and divergent human viruses, highlighting the extensive diversity of the human virome. The frequent co-detection of multiple viral taxa also suggests that interactions and co-infections may influence viral evolution, disease manifestation, and transmission. Despite methodological challenges in quantification and biological validation, WBE has proven capable of detecting both known and novel pathogens before they are clinically recognized. Future developments in long-read sequencing, bioinformatics, and global data integration will enhance the precision and scope of wastewater genomics, positioning it as a central element of early-warning and One Health surveillance frameworks. By illuminating the unseen spectrum of infectious agents, WBE bridges environmental and clinical domains, offering a scalable and equitable strategy for global pathogen discovery and public health preparedness.

Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration - Nikhil N. Chaudhari; Owen M. Vega; Phoebe Imms; Jaron M. Kawamura; Nahian F. Chowdhury; Tamara Jafar; Andrei Irimia; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2026)
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can find aging-related structural alterations above and beyond cortical thickness and atrophy. Using a novel approach to DNN interpretability, we mapped brain aging progression in 25,539 cognitively normal UK Biobank adults aged 45–83 years. Cortical aging is found to involve anatomic features becoming prominent during the 50s within frontolateral, mesolimbic, cuneal, and occipitotemporal regions. From these foci, aging-related features propagate to adjacent areas at rates peaking in the 60s. Cortical thinning and atrophy do not trend closely with neurodegeneration, but important DNN-identifiable anatomic features have spatiotemporal dynamics that match those of amyloid or tau. Our results challenge the assumption that MRI cannot map anatomic features trending with neurodegeneration. Interpretable DNNs can empower MRI to quantify anatomic aging as a process of spatial feature expansion from focal regions into nearby structures in the sequence of neurodegenerative pathology. Traditional morphometrics explain only ∼1% of variance in DNN-identifiable features, which clarifies why the former are insensitive to anatomic changes involving neurodegeneration. Our results conceptualize brain aging in the context of spatial and temporal parallels between anatomic senescence and neuropathology. These findings may help to map cognitively normal adults’ neurodegenerative anatomy even without PET measurements. Graphical Abstract

Sex and APOE genotype specific brain regional vulnerability to Alzheimer's Disease - Qi Zeng; Minghui Wang; Erming Wang; Xianxiao Zhou; Peng Xu; Vahram Haroutunian; Dongming Cai; Bin Zhang; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2026)
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), and regional vulnerability was assessed with a composite vulnerability score (CVS) derived from associations between diffusion features and AD severity across clinical traits in each of the four sex-APOE groups (female or male, with or without APOE4). Brain parcellation with the Eve atlas revealed regions consistently affected across sex-APOE groups (e.g., parahippocampal and superior temporal gyri) and regions specific to individual groups (e.g., the cingulum in females with APOE4 and the middle frontal gyrus in males without APOE4). Gene co-expression network analysis of the matched blood expression data identified gene subnetworks linked to group-specific regional vulnerability, including a muscle tissue morphogenesis module regulated by NEURL1B and HIST1H2BN associated with middle frontal gyrus vulnerability. These findings demonstrate that sex and APOE genotype jointly shape region-specific WM vulnerability and its molecular signatures in AD. Understanding these interactions provides novel mechanistic insights and may inform precision approaches to drug development, biomarker discovery, and clinical trial design for AD.

Integrated Population Pharmacokinetic-pharmacodynamic Modeling of HIV Virus-host Infection Dynamics in Patients Undergoing Antiretroviral Monotherapy - Alberto Vegas Rodriguez; Nieves Velez de Mendizábal; Yanan Zheng; Jason T. Hindman; Ramesh Palaparthy; John Ling; Iñaki F. Trocóniz; Ana Ruíz-Garcia; Justin S. Feigelman (The AAPS Journal, 2025)
Chronic human immunodeficiency virus (HIV) infection continues to pose a major global health challenge, with an estimated 39.9 M cases and 1.3 M new infections per year. Up to 75%, of people with HIV (PWH) are currently being treated with antiretroviral therapy. The development of effective treatments for HIV requires a detailed understanding of the virus-host interaction. Often, mathematical models are used to inform this understanding as well as to characterize therapeutic response. This work aims to develop a single and fully identifiable population semi-mechanistic pharmacokinetic/pharmacodynamic (popPKPD) model integrating data (drug levels, CD4 + T cells and viral RNA) of five different antiretroviral (ARV) drugs administered in monotherapy: lenacapavir, bictegravir, tenofovir alafenamide, emtricitabine and elvitegravir. Data were obtained from six phase 1 clinical studies and model development was performed using NONMEM 7.5.1. The viral dynamics were best described by expanding the “basic” viral dynamics model with two more populations of infected cells: chronically and latently infected. Obtained death rates values of infected cells & virus were consistent with literature values. Population baseline HIV-RNA was estimated to be 43,460 copies/mL, with an IIV of 141%, the estimated baseline concentrations of CD4 + cells varied largely across the different cell types in the model: 410, 20, 7 and 7 cells/mL for uninfected, infected, chronic and latently infected cells, respectively. The popPKPD model was able to capture key aspects of viral dynamics, drug behaviour, and treatment response. The models developed will serve as a useful tool for further development and optimization of these HIV therapies, especially when evaluating multiple ARVs to be administered in a novel combination setting. Graphical Abstract

Replication of human enteric viruses from wastewater in saliva cell lines - Sharon C. Kosgei; Olivia N. Birch; Roberto A. Rodriguez; Sang C. Par; Justin C. Greaves (Science of The Total Environment, 2025)

The importance of tropical tree-ring chronologies for global change research - Peter Groenendijk; Flurin Babst; Valerie Trouet; Ze-Xin Fan; Daniela Granato-Souza; Giuliano Maselli Locosselli; Mulugeta Mokria; Shankar Panthi; Nathsuda Pumijumnong; Abrham Abiyu; Rodolfo Acuña-Soto; Eduardo Adenesky-Filho; et al. (Quaternary Science Reviews, 2025)

Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning - Marthe Mieling; Mushfa Yousuf; Nico Bunzeck; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; Susan Landau; Monica Rivera-Mindt; Leslie M. Shaw; Edward B. Lee; et al. (GeroScience, 2025)
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70–77% accuracy and 61–83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

Temperature Drives Seagrass Recovery Across the Western North Atlantic - Fee O. H. Smulders; Justin E. Campbell; Andrew H. Altieri; Anna R. Armitage; Elisabeth S. Bakker; Savanna C. Barry; S. Tatiana Becker; Enrique Bethel; James G. Douglass; Hannah J. van Duijnhoven; Jimmy de Fouw; Thomas K. Frazer; et al. (Global Change Biology, 2025)
Climate‐driven shifts in herbivores, temperature, and nutrient runoff threaten coastal ecosystem resilience. However, ecological resilience, particularly for foundation species, remains poorly understood due to the scarcity of field experiments conducted across appropriate spatial and temporal scales that investigate multiple stressors. This study evaluates the resilience of a widespread tropical marine plant (turtlegrass) to disturbances across its geographic range and examines how environmental gradients in (a)biotic factors influence recovery. We assessed turtlegrass resilience by following recovery rates for a year after a simulated pulse disturbance (complete above‐ and belowground biomass removal). Contrary to studies in temperate areas, higher temperature generally enhanced seagrass recovery. While nutrients had minimal individual effects, they reduced aboveground recovery when combined with high levels of herbivore grazing (meso and megaherbivore). Belowground recovery was also affected by combined high levels of nutrients and grazing (megaherbivores only). Light availability had minimal effects. Our results suggest that the resilience of some tropical species, particularly in cooler subtropical waters, may initially benefit from warming. However, continuing shifts in nutrient supply and changes in grazing pressure may ultimately serve to compromise seagrass recovery.

A review of the venom microbiome and its utility in ecology and evolution including future directions for emerging research - Marina E. De León; Eduardo G. P. Fox; Sara Dunaj; Ronald A. Jenner; Carl N. Keiser; Jason Macrander; Samantha A. Nixon; Clarissa J. Nobile; Daniel Petras; Eduardo Rodriguez-Roman; Anthony J. Saviola; Steven A. Trim; et al. (Symbiosis, 2025)

Non-Catalytic direct partial oxidation of methane to methanol in a Wall-Coated microreactor - Kelly Cohen; Justin Blanchard; Paul Rodriguez; Kevin Kelly; James A. Dorman; Kerry M. Dooley (Chemical Engineering Journal, 2024)

Seagrass Abundance Predicts Surficial Soil Organic Carbon Stocks Across the Range of Thalassia testudinum in the Western North Atlantic - James W. Fourqurean; Justin E. Campbell; O. Kennedy Rhoades; Calvin J. Munson; Johannes R. Krause; Andrew H. Altieri; James G. Douglass; Kenneth L. Heck; Valerie J. Paul; Anna R. Armitage; Savanna C. Barry; Enrique Bethel; et al. (Estuaries and Coasts, 2023)

Effects of varying types and amounts of herbivory and nutrient enrichment on a tropicalizing seagrass meadow - Alexandra R. Rodriguez; Candela Marco-Méndez; Justin Campbell; Kenneth L. Heck (Frontiers in Marine Science, 2022)
Climate change is impacting marine ecosystem community dynamics on a global scale. While many have assessed direct effects of climate change, indirect effects on marine ecosystems produced by biotic interactions remain poorly understood. For example, warming-induced range expansions and increased consumption rates of herbivores can lead to significant and unexpected changes in seagrass-dominated ecosystems. To better understand the threats tropicalization presents for the functioning of turtlegrass ( Thalassia testudinum ) meadows, we focused on the extensive turtlegrass beds of St. Joseph Bay, Florida in the northern Gulf of Mexico, a location with increasing numbers of tropically-associated green turtles. Our goals were to investigate experimentally how different grazing rates (natural and simulated),including high levels reflective of green turtle herbivory, coupled with nutrient supply, might alter turtlegrass structure and functioning in a higher latitude, subtropical turtlegrass meadow. We found that 4 months of varying levels of herbivory did not affect turtlegrass productivity, while 7 months of herbivory reduced percent cover, and 10 months reduced shoot density. Nutrient additions had few important effects. Ten months into the study, a massive recruitment of the herbivorous sea urchin ( Lytechinus variegatus ), whose densities reached 19 urchins/m 2 completely overgrazed our study area and a large portion of the lush turtlegrass meadows of St. Joseph Bay. While local turtlegrass overgrazing had been previously noted at these urchin densities, a total loss of seagrass in such a large area has rarely ever been recorded. Overgrazing of the kind we observed, likely a result of both urchin and increasing green turtle grazing, can result in the loss of many key ecosystem services. As tropicalization continues, understanding how changes in biotic interactions, such as increased herbivory, affect higher latitude seagrass meadows will be necessary for their proper management and conservation.

Natural Intertidal Oyster Reef Growth Across Two Landscape Settings and Tidal Ranges - Molly C. Bost; Antonio B. Rodriguez; Justin T. Ridge; Carson B. Miller; Stephen R. Fegley (Estuaries and Coasts, 2021)

Automated detection of frog calls and choruses by pulse repetition rate - Sam Lapp; Tianhao Wu; Corinne Richards‐Zawacki; Jamie Voyles; Keely Michelle Rodriguez; Hila Shamon; Justin Kitzes (Conservation Biology, 2021)
Anurans (frogs and toads) are among the most globally threatened taxonomic groups. Successful conservation of anurans will rely on improved data on the status and changes in local populations, particularly for rare and threatened species. Automated sensors, such as acoustic recorders, have the potential to provide such data by massively increasing the spatial and temporal scale of population sampling efforts. Analyzing such data sets will require robust and efficient tools that can automatically identify the presence of a species in audio recordings. Like bats and birds, many anuran species produce distinct vocalizations that can be captured by autonomous acoustic recorders and represent excellent candidates for automated recognition. However, in contrast to birds and bats, effective automated acoustic recognition tools for anurans are not yet widely available. An effective automated call‐recognition method for anurans must be robust to the challenges of real‐world field data and should not require extensive labeled data sets. We devised a vocalization identification tool that classifies anuran vocalizations in audio recordings based on their periodic structure: the repeat interval‐based bioacoustic identification tool (RIBBIT). We applied RIBBIT to field recordings to study the boreal chorus frog ( Pseudacris maculata ) of temperate North American grasslands and the critically endangered variable harlequin frog ( Atelopus varius ) of tropical Central American rainforests. The tool accurately identified boreal chorus frogs, even when they vocalized in heavily overlapping choruses and identified variable harlequin frog vocalizations at a field site where it had been very rarely encountered in visual surveys. Using a few simple parameters, RIBBIT can detect any vocalization with a periodic structure, including those of many anurans, insects, birds, and mammals. We provide open‐source implementations of RIBBIT in Python and R to support its use for other taxa and communities.

The global abundance of tree palms - Robert Muscarella; Thaise Emilio; Oliver L. Phillips; Simon L. Lewis; Ferry Slik; William J. Baker; Thomas L. P. Couvreur; Wolf L. Eiserhardt; Jens‐Christian Svenning; Kofi Affum‐Baffoe; Shin‐Ichiro Aiba; Everton C. de Almeida; et al. (Global Ecology and Biogeography, 2020)
Aim Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location Tropical and subtropical moist forests. Time period Current. Major taxa studied Palms (Arecaceae). Methods We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co‐occurring non‐palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long‐term climate stability. Life‐form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non‐tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above‐ground biomass, but the magnitude and direction of the effect require additional work. Conclusions Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests.

Contributions of Hydrology to Vesicular Stomatitis Virus Emergence in the Western USA - Emile Elias; D. Scott McVey; Debra Peters; Justin D. Derner; Angela Pelzel-McCluskey; T. Scott Schrader; Luis Rodriguez (Ecosystems, 2019)

Measuring currents, ice drift, and waves from space: the Sea surface KInematics Multiscale monitoring (SKIM) concept - Fabrice Ardhuin; Yevgueny Aksenov; Alvise Benetazzo; Laurent Bertino; Peter Brandt; Eric Caubet; Bertrand Chapron; Fabrice Collard; Sophie Cravatte; Jean-Marc Delouis; Frederic Dias; Gérald Dibarboure; et al. (Ocean Science, 2018)
We propose a satellite mission that uses a near-nadir Ka-band Doppler radar to measure surface currents, ice drift and ocean waves at spatial scales of 40 km and more, with snapshots at least every day for latitudes 75 to 82°, and every few days for other latitudes. The use of incidence angles of 6 and 12° allows for measurement of the directional wave spectrum, which yields accurate corrections of the wave-induced bias in the current measurements. The instrument's design, an algorithm for current vector retrieval and the expected mission performance are presented here. The instrument proposed can reveal features of tropical ocean and marginal ice zone (MIZ) dynamics that are inaccessible to other measurement systems, and providing global monitoring of the ocean mesoscale that surpasses the capability of today's nadir altimeters. Measuring ocean wave properties has many applications, including examining wave–current interactions, air–sea fluxes, the transport and convergence of marine plastic debris and assessment of marine and coastal hazards.

Salt Marsh and Fringing Oyster Reef Transgression in a Shallow Temperate Estuary: Implications for Restoration, Conservation and Blue Carbon - Justin T. Ridge; Antonio B. Rodriguez; F. Joel Fodrie (Estuaries and Coasts, 2017)

Tumor-associated Endo180 requires stromal-derived LOX to promote metastatic prostate cancer cell migration on human ECM surfaces - Matthew P. Caley; Helen King; Neel Shah; Kai Wang; Mercedes Rodriguez-Teja; Julian H. Gronau; Jonathan Waxman; Justin Sturge (Clinical & Experimental Metastasis, 2016)

Safety and Injury Characteristics of Youth Farmworkers in North Carolina: A Pilot Study - Thomas A. Arcury; Guadalupe Rodriguez; Gregory D. Kearney; Justin T. Arcury; Sara A. Quandt (Journal of Agromedicine, 2014)

Genetic variation within a dominant shrub structures green and brown community assemblages - Gregory M. Crutsinger; Mariano A. Rodriguez-Cabal; Adam B. Roddy; Kabir G. Peay; Justin L. Bastow; Allison G. Kidder; Todd E. Dawson; Paul V. A. Fine; Jennifer A. Rudgers (Ecology, 2014)
Two rising challenges in ecology are understanding the linkages between above‐ and belowground components of terrestrial ecosystems and connecting genes to their ecological consequences. Here, we blend these emerging perspectives using a long‐term common‐garden experiment in a coastal dune ecosystem, whose dominant shrub species, Baccharis pilularis , exists as erect or prostrate architectural morphotypes. We explored variation in green (foliage‐based) and brown (detritus‐based) community assemblages, local ecosystem processes, and understory microclimate between the two morphs. Prostrate morphs supported more individuals, species, and different compositions of foliage arthropods, litter microarthropods, and soil bacteria than erect morphs. The magnitude of community compositional differences was maintained from crown to litter to soil. Despite showing strikingly similar responses, green and brown assemblages were associated with different underlying mechanisms. Differences in estimated shrub biomass best explained variation in the green assemblage, while understory abiotic conditions accounted for variation in the brown assemblage. Prostrate morphs produced more biomass and litter, which corresponded with their strong lateral growth in a windy environment. Compared to erect morphs, the denser canopy and thicker litter layer of prostrate morphs helped create more humid understory conditions. As a result, decomposition rates were higher under prostrate shrubs, despite prostrate litter being of poorer quality. Together, our results support the hypothesis that intraspecific genetic variation in primary producers is a key mediator of above‐ and belowground linkages, and that integrating the two perspectives can lead to new insights into how terrestrial communities are linked with ecosystem pools and processes.

Quantifying the limits of HANPP and carbon emissions which prolong total species well-being - Justin D. K. Bishop; Gehan A. J. Amaratunga; Cuauhtemoc Rodriguez (Environment, Development and Sustainability, 2010)

Studies on the diversity of the distinct phylogenetic lineage encompassing Glomus claroideum and Glomus etunicatum - Alia Rodriguez; Justin P. Clapp; Louisa Robinson; John C. Dodd (Mycorrhiza, 2005)

Glomales rRNA gene diversity - all that glistens is not necessarily glomalean? - Justin Clapp; Alia Rodriguez; John Dodd (Mycorrhiza, 2002)