Ensuring consistency in spatially-stratified stock assessment models: An analytical solution for equilibrium population structure with connectivity for age-and size-structured models - Matthew LH. Cheng; Timothy J. Miller; Daniel R. Goethel; Curry J. Cunningham (Fisheries Research, 2026)

Diversity of convolutid acoels (Convolutidae, Acoela) in Hokkaido, Japan, including a description of the symbiont-bearing Amphiscolops ranshimensis n. sp. - Siratee Riewluang; Regine C. Manglicmot; Shaun Cunningham; Matthew D. Hooge; Rintaro Ono; Hiroshi Kajihara; Brian S. Leander; Kevin C. Wakeman (Zoologischer Anzeiger, 2026)

Beyond the Surface: Non-Invasive Low-Field NMR Analysis of Microbially-Induced Calcium Carbonate Precipitation in Shale Fractures - Matthew R. Willett; Kayla Bedey; Dustin Crandall; Joseph D. Seymour; Jonny Rutqvist; Alfred B. Cunningham; Adrienne J. Phillips; Catherine M. Kirkland (Rock Mechanics and Rock Engineering, 2026)
Microbially-induced calcium carbonate precipitation (MICP) is a biological process in which microbially-produced urease enzymes convert urea and calcium into solid calcium carbonate (CaCO 3 ) deposits. MICP has been demonstrated to reduce permeability in shale fractures under elevated pressures, raising the possibility of applying this technology to enhance shale reservoir storage safety. For this and other applications to become a reality, non-invasive tools are needed to determine how effectively MICP seals shale fractures at subsurface temperatures. In this study, two different MICP strategies were tested on 2.54 cm diameter and 5.08 cm long shale cores with a single fracture at 60 ℃. Flow-through, pulsed-flow MICP-treatment was repeatedly applied to Marcellus shale fractures with and without sand (“proppant”) until reaching approximately four orders of magnitude reduction in apparent permeability, while a single application of polymer-based “immersion” MICP-treatment was applied to an Eagle Ford shale fracture with proppant. Low-field nuclear magnetic resonance (LF-NMR) and X-Ray computed microtomography (micro-CT) techniques were used to assess the degree of biomineralization. With the flow-through approach, these tools revealed that while CaCO 3 precipitation occurred throughout the fracture, there was preferential precipitation around proppant. Without proppant, the same approach led to premature sealing at the inlet side of the core. In contrast, immersion MICP-treatment sealed off the fracture edges and showed less mineral precipitation overall. This study highlights the use of LF-NMR relaxometry in characterizing fracture sealing and can help guide NMR logging tools in subsurface remediation efforts.

The SPoRC Stock Assessment Package: A Generalized Next‐Generation Platform to Assess Spatial, Age and Sex‐Structured Populations - Matthew LH. Cheng; Daniel R. Goethel; Curry J. Cunningham; Peter‐John F. Hulson; James N. Ianelli; Kristen L. Omori (Fish and Fisheries, 2026)
Fisheries managers increasingly rely on stock assessment models to provide sustainable management advice, which must balance complex and competing objectives. Although assessment models necessitate simplifying assumptions, there is increasing recognition to improve the integration of realistic biological and fishery dynamics. While ongoing and future development of increasingly complex stock assessments requires increased capacity (i.e., time, training, and personnel), there are concerns that the growing demand for assessment advice cannot be adequately fulfilled under current resources. To address these needs, we present the Stochastic Population over Regional Components (SPoRC) model, a modern integrated analysis platform that is generalized, modular and developed in a user‐friendly programming language (R with Template Model Builder, RTMB). Development of SPoRC emphasized consideration of age, sex, and spatial dynamics at the outset, while ensuring the ability to integrate diverse data sources (e.g., catch, abundance indices, age/length compositions and tagging). Moreover, state‐space specification of time‐varying processes through random effects and robust simulation capabilities were primary design features. Here, we highlight SPoRC's utility in cohesively implementing single‐and multi‐region applications, its ability to estimate time‐varying processes as random effects, and the potential to conduct closed‐loop simulations for evaluating the robustness of management procedures. By developing a generalized assessment platform in a user‐friendly R package, we suggest that SPoRC reduces barriers to implementation of next‐generation stock assessment models and facilitates team‐based model development, which will ultimately help improve the capacity to implement stock assessments globally.

Remote-sensing methods for mapping eucalypt dieback: A systematic review - Weerach Charerntantanakul; John T. Burley; Marta Yebra; Adrienne Beth Nicotra; Saul Alan Cunningham; Matthew Theodore Brookhouse (Remote Sensing Applications: Society and Environment, 2026)

NextGen In A Box (NGIAB): Open-Source containerization of the NextGen framework to enable community-driven hydrology modeling - Arpita Patel; James Halgren; Zach Wills; Nels Frazier; Benjamin Lee; Joshua Cunningham; Jordan Laser; Mohammadsepehr Karimiziarani; Trupesh Patel; Giovanni Romero; Matthew Denno; Sam Lamont; et al. (Environmental Modelling & Software, 2025)

Panmictic Panacea? Demonstrating Good Practices for Developing Spatial Stock Assessments Through Application to Alaska Sablefish ( Anoplopoma fimbria ) - Matthew L. H. Cheng; Craig A. Marsh; Daniel R. Goethel; Peter‐John F. Hulson; Katy Echave; Benjamin C. Williams; Aaron M. Berger; Curry J. Cunningham (Fish and Fisheries, 2025)
Marine species and associated fisheries demonstrate complex spatial dynamics driven by biological, ecosystem and socioeconomic factors and integrating these spatial dynamics into stock assessment models can improve fishery management advice. While preliminary good practices for developing spatial stock assessment models have been proposed, comprehensive demonstrations applying these practices remain limited. Drawing on these good practices, we provide an end‐to‐end demonstration of developing a spatial stock assessment using Alaska sablefish ( Anoplopoma fimbria ). Our demonstration emphasises the utility of high‐resolution data analysis and conceptual models for informing key model structure decisions, the joint development of spatial and spatially‐aggregated models to enhance understanding of population dynamics, and the need for further guidance on integrating tagging data and diagnostic tools in spatial assessments. Spatial models highlighted regional differences in sablefish biomass, recruitment and age structure, but total population estimates generally aligned with outputs from spatially aggregated models. Moreover, the spatial model identified ontogenetic movement patterns for this highly mobile species. Overall, the spatially aggregated model for Alaska sablefish is likely adequate for management advice, but periodic spatial model updates could offer insights into spatial dynamics and regional depletion levels. Thus, we recommend concomitant use of both models: spatially aggregated models for informing population‐wide status, and spatial models for informing spatial fishery dynamics and local depletion. The sablefish application represents one of the first implementations of a spatial stock assessment using recently proposed good practices, serving as a valuable guide for future practitioners by underscoring critical decision points and analyses to address them when developing spatial stock assessments.

What a load of rubbish: The impact of anthropogenic litter on urban freshwater diversity - Victoria S. Milner; Matthew J. Hill; Kieran J. Gething; Summer B. Cunningham (Environmental Pollution, 2025)

Misspecifying Sex‐Structured Dynamics in Stock Assessment Models - Matthew L. H. Cheng; Daniel R. Goethel; Peter‐John F. Hulson; Michael J. Wilberg; Craig Marsh; Curry J. Cunningham (Fish and Fisheries, 2025)
Sex‐specific variation in population demography and life‐history traits (e.g., growth, natural mortality) is common in many fish populations. Differences in these processes by sex can dictate population dynamics and influence how harvesters interact with the resource. Across various fisheries management systems, stock assessment models (SAMs), which mathematically represent population age and/or size structure, are widely utilised to estimate fish population status and provide sustainable harvest recommendations. However, few studies have examined the implications of alternative modelling assumptions when incorporating sex‐specific dynamics in SAMs. For instance, the impacts of simultaneously ignoring sex‐specific variations in growth, selectivity, and natural mortality on SAM performance have not been explored. In this study, a simulation‐estimation framework was developed for a sexually dimorphic fish population to: (1) assess the consequences of ignoring sexual dimorphism (i.e., growth, natural mortality, and selectivity) and the benefits of using sex‐specific catch data to inform the estimation of these processes, (2) evaluate the implications of incorrect modelling assumptions regarding sex ratio at birth, and (3) develop advice for parameterising observation likelihoods to describe sex‐specific composition data. Correctly parameterising sex‐specific variation in life‐history traits led to more robust population estimates and catch advice. Conversely, SAMs ignoring these variations yielded biased estimates of biomass and harvest recommendations. Collectively, our results underscore that oversimplified assumptions about sex‐specific variations in SAMs can lead to poor management advice. Moreover, results emphasise the need for routine collection of sex‐specific data to support the development of biologically realistic models.

Ranavirus in native amphibians from the Pyrenees National Park, France: a case study - Alexandra Peñafiel-Ricaurte; Stephen J. Price; Matthew C. Fisher; Jaime Bosch; Andrew A. Cunningham; Claudio Azat (European Journal of Wildlife Research, 2025)

Test of Rapamycin in Aging Dogs (TRIAD): study design and rationale for a prospective, parallel-group, double-masked, randomized, placebo-controlled, multicenter trial of rapamycin in healthy middle-aged dogs from the Dog Aging Project - Amanda E. Coleman; Kate E. Creevy; Rozalyn Anderson; May J. Reed; Virginia R. Fajt; Kathleen M. Aicher; Genna Atiee; Brian G. Barnett; Ryan D. Baumwart; Beth Boudreau; Suzanne M. Cunningham; Matthew D. Dunbar; et al. (GeroScience, 2025)

A mathematical proof comparing the statistical properties between two common approaches for parameterizing sex-composition likelihoods in fishery stock assessments - Matthew LH. Cheng; Peter-John F. Hulson; Daniel R. Goethel; Curry J. Cunningham (Fisheries Research, 2025)

Predicting energy consumption of zero emission buses using route feature selection methods - L.A.W. Blades; T. Matthews; T.E. McGrath; J. Early; G. Cunningham; A. Harris (Transportation Research Part D: Transport and Environment, 2024)

Addressing complex fleet structure in fishery stock assessment models: Accounting for a rapidly developing pot fishery for Alaska sablefish (Anoplopoma fimbria) - Matthew L.H. Cheng; Daniel R. Goethel; Curry J. Cunningham (Fisheries Research, 2024)

Unlocking the triad of age, year, and cohort effects for stock assessment: Demonstration of a computationally efficient and reproducible framework using weight-at-age - Matthew LH. Cheng; James T. Thorson; James N. Ianelli; Curry J. Cunningham (Fisheries Research, 2023)

Drinking dependency shapes behavioural thermoregulatory trade-offs in four arid-zone larks - Matthew Orolowitz; Eleanor Shadwell; Susan J. Cunningham (Journal of Arid Environments, 2023)

Prediction of disability-free survival in healthy older people - Johannes Tobias Neumann; Le T. P. Thao; Anne M. Murray; Emily Callander; Prudence R. Carr; Mark R. Nelson; Rory Wolfe; Robyn L. Woods; Christopher M. Reid; Raj C. Shah; Anne B. Newman; Jeff D. Williamson; et al. (GeroScience, 2022)
Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583)

Multi-taxa spatial conservation planning reveals similar priorities between taxa and improved protected area representation with climate change - Rob Critchlow; Charles A. Cunningham; Humphrey Q. P. Crick; Nicholas A. Macgregor; Michael D. Morecroft; James W. Pearce-Higgins; Tom H. Oliver; Matthew J. Carroll; Colin M. Beale (Biodiversity and Conservation, 2022)
Protected area (PA) networks have in the past been constructed to include all major habitats, but have often been developed through consideration of only a few indicator taxa or across restricted areas, and rarely account for global climate change. Systematic conservation planning (SCP) aims to improve the efficiency of biodiversity conservation, particularly when addressing internationally agreed protection targets. We apply SCP in Great Britain (GB) using the widest taxonomic coverage to date (4,447 species), compare spatial prioritisation results across 18 taxa and use projected future (2080) distributions to assess the potential impact of climate change on PA network effectiveness. Priority conservation areas were similar among multiple taxa, despite considerable differences in spatial species richness patterns; thus systematic prioritisations based on indicator taxa for which data are widely available are still useful for conservation planning. We found that increasing the number of protected hectads by 2% (to reach the 2020 17% Aichi target) could have a disproportionate positive effect on species protected, with an increase of up to 17% for some taxa. The PA network in GB currently under-represents priority species but, if the potential future distributions under climate change are realised, the proportion of species distributions protected by the current PA network may increase, because many PAs are in northern and higher altitude areas. Optimal locations for new PAs are particularly concentrated in southern and upland areas of GB. This application of SCP shows how a small addition to an existing PA network could have disproportionate benefits for species conservation.

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Testing a global standard for quantifying species recovery and assessing conservation impact - Molly K. Grace; H. Resit Akçakaya; Elizabeth L. Bennett; Thomas M. Brooks; Anna Heath; Simon Hedges; Craig Hilton‐Taylor; Michael Hoffmann; Axel Hochkirch; Richard Jenkins; David A. Keith; Barney Long; et al. (Conservation Biology, 2021)
Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a “Green List of Species” (now the IUCN Green Status of Species). A draft Green Status framework for assessing species’ progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species’ viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score ) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics ( conservation legacy, conservation dependence , conservation gain , and recovery potential ). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species’ recovery scores, we propose the following species recovery categories : fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty‐nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics , indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard.

A novel knockout mouse for the small EDRK-rich factor 2 (Serf2) showing developmental and other deficits - Karen Cleverley; Weaverly Colleen Lee; Paige Mumford; Toby Collins; Matthew Rickman; Thomas J. Cunningham; James Cleak; Joffrey Mianne; Zsombor Szoke-Kovacs; Michelle Stewart; Lydia Teboul; Cheryl Maduro; et al. (Mammalian Genome, 2021)
The small EDRK-rich factor 2 (SERF2) is a highly conserved protein that modifies amyloid fibre assembly in vitro and promotes protein misfolding. However, the role of SERF2 in regulating age-related proteotoxicity remains largely unexplored due to a lack of in vivo models. Here, we report the generation of Serf2 knockout mice using an ES cell targeting approach, with Serf2 knockout alleles being bred onto different defined genetic backgrounds. We highlight phenotyping data from heterozygous Serf2 +/− mice, including unexpected male-specific phenotypes in startle response and pre-pulse inhibition. We report embryonic lethality in Serf2 −/− null animals when bred onto a C57BL/6 N background. However, homozygous null animals were viable on a mixed genetic background and, remarkably, developed without obvious abnormalities. The Serf2 knockout mice provide a powerful tool to further investigate the role of SERF2 protein in previously unexplored pathophysiological pathways in the context of a whole organism.

Projected changes in Brook Trout and Brown Trout distribution in Wisconsin streams in the mid-twenty-first century in response to climate change - Matthew G. Mitro; John D. Lyons; Jana S. Stewart; Paul K. Cunningham; Joanna D. T. Griffin (Hydrobiologia, 2019)

Real-Time Monitoring with a Tablet App Improves Implementation of Treatments to Enhance Forest Structural Diversity - Colin T Maher; Emily Oja; Abigail Marshall; Matthew Cunningham; Lucas Townsend; Graham Worley-Hood; Luke Ruffner Robinson; Taylor Margot; Drew Lyons; Stuart Fety; Eryn E Schneider; Sean M A Jeronimo; et al. (Journal of Forestry, 2019)

Experimental habitat fragmentation disrupts nematode infections in Australian skinks - Julian Resasco; Matthew E. Bitters; Saul A. Cunningham; Hugh I. Jones; Valerie J. McKenzie; Kendi F. Davies (Ecology, 2019)
Habitat conversion and fragmentation threaten biodiversity and disrupt species interactions. While parasites are recognized as ecologically important, the impacts of fragmentation on parasitism are poorly understood relative to other species interactions. This lack of understanding is in part due to confounding landscape factors that accompany fragmentation. Fragmentation experiments provide the opportunity to fill this knowledge gap by mechanistically testing how fragmentation affects parasitism while controlling landscape factors. In a large‐scale, long‐term experiment, we asked how fragmentation affects a host–parasite interaction between a skink and a parasitic nematode, which is trophically transmitted via a terrestrial amphipod intermediate host. We expected that previously observed amphipod declines resulting from fragmentation would result in decreased transmission of nematodes to skinks. In agreement, we found that nematodes were absent among skinks in the cleared matrix and that infections in fragments were about one quarter of those in continuous forest. Amphipods found in gut contents of skinks and collected from pitfall traps mirrored this pattern. A structural equation model supported the expectation that fragmentation disrupted this interaction by altering the abundance of amphipods and suggested that other variables are likely also important in mediating this effect. These findings advance understanding of how landscape change affects parasitism.

Silencing porcine genes significantly reduces human-anti-pig cytotoxicity profiles: an alternative to direct complement regulation - James R. Butler; Gregory R. Martens; Jose L. Estrada; Luz M. Reyes; Joseph M. Ladowski; Cesare Galli; Andrea Perota; Conor M. Cunningham; Matthew Tector; A. Joseph Tector (Transgenic Research, 2016)

Grassland area determines beetle assemblage dissimilarity from surrounding floodplain forest - Philip S. Barton; Matthew J. Colloff; Kimberi R. Pullen; Saul A. Cunningham (Journal of Insect Conservation, 2013)

Arthropod assemblages in a focal tree species (Eucalyptus microcarpa) depends on the species mix in restoration plantings - Philip S. Barton; Matthew J. Colloff; Kimberi R. Pullen; Saul A. Cunningham (Biodiversity and Conservation, 2013)

Pacific Rim Forestry / Silviculture and Forest Ecology - Vishal Singh Negi; Archana Pal; Ratnesh Singh; Dulal Borthakur; Archana Pala; Vishal Singh Negi; Dulal Borthakur; Isabel Rushanaedy; Tyler Jones; Nicklos Dudley; Dulal Borthakur; Jannai Yafuso; et al. (Journal of Forestry, 2011)
Leucaena leucocephala (leucaena) is an important agroforestry tree of tropics and subtropics due to its protein rich foliages, ability to grow on poor soils, and high level of tolerance to various stresses including drought and diseases. We hypothesized that leucaena have a unique set of genes which confer tolerance to various abiotic and biotic stresses and these genes are either absent or not expressed in other legumes that are susceptible to these stress conditions. Interspecies suppression subtractive hybridization (iSSH) was performed to identify some unique genes from leucaena using cDNAs from leucaena and Acacia confusa (acacia) as the tester and driver, respectively. We identified 100 leucaena genes showing homology to various plant genes with known functions, of which 23 genes had homology to various stress-related proteins including chitinase, PR-10 protein, wound-stress protein, type-2 metallothionein, thaumatin-like protein, disease resistance response protein, cysteine proteinase, and kunitz trypsin inhibitor. We also identified 50 leucaena genes which either had homology to hypothetical proteins (HyPs) or had no homology at all. Putative functions of 15 HyPs were predicted using conserved domain and PSI-BLAST analyses. Linear motif analyses identified 17 HyPs with MAPK recognition motif, which is involved in signaling pathways, including stress responses. This study identified 23 known and some putative unique stress-related genes from leucaena which may serve as a useful source of stress-tolerance genes for tree and crop improvement in the future.

Factors driving pathogenicity vs. prevalence of amphibian panzootic chytridiomycosis in Iberia - Susan F. Walker; Jaime Bosch; Virgilio Gomez; Trenton W. J. Garner; Andrew A. Cunningham; Dirk S. Schmeller; Miguel Ninyerola; Daniel A. Henk; Cedric Ginestet; Christian‐Philippe Arthur; Matthew C. Fisher (Ecology Letters, 2010)
Ecology Letters (2010) 13: 372–382 Abstract Amphibian chytridiomycosis is a disease caused by the fungus Batrachochytrium dendrobatidis ( Bd ). Whether Bd is a new emerging pathogen (the novel pathogen hypothesis; NPH) or whether environmental changes are exacerbating the host‐pathogen dynamic (the endemic pathogen hypothesis; EPH) is debated. To disentangle these hypotheses we map the distribution of Bd and chytridiomycosis across the Iberian Peninsula centred on the first European outbreak site. We find that the infection‐free state is the norm across both sample sites and individuals. To analyse this dataset, we use Bayesian zero‐inflated binomial models to test whether environmental variables can account for heterogeneity in both the presence and prevalence of Bd, and heterogeneity in the occurrence of the disease, chytridiomycosis. We also search for signatures of Bd ‐spread within Iberia using genotyping. We show (1) no evidence for any relationship between the presence of Bd and environmental variables, (2) a weak relationship between environmental variables and the conditional prevalence of infection, (3) stage‐dependent heterogeneity in the infection risk, (4) a strong association between altitude and chytridiomycosis, (5) multiple Iberian genotypes and (6) recent introduction and spread of a single genotype of Bd in the Pyrenees. We conclude that the NPH is consistent with the emergence of Bd in Iberia. However, epizootic forcing of infection is tied to location and shaped by both biotic and abiotic variables. Therefore, the population‐level consequences of disease introduction are explained by EPH‐like processes. This study demonstrates the power of combining surveillance and molecular data to ascertain the drivers of new emerging infections diseases.

Transcriptome Profiling of Selectively Bred Pacific Oyster Crassostrea gigas Families that Differ in Tolerance of Heat Shock - R. Paul Lang; Christopher J. Bayne; Mark D. Camara; Charles Cunningham; Matthew J. Jenny; Christopher J. Langdon (Marine Biotechnology, 2009)

Whole-tree sap flow is substantially diminished by leaf herbivory - Saul A. Cunningham; Kimberi R. Pullen; Matthew J. Colloff (Oecologia, 2009)

Effect of soil biota on growth and allocation by Eucalyptus microcarpa - Mark Bourne; Adrienne B. Nicotra; Matthew J. Colloff; Saul A. Cunningham (Plant and Soil, 2008)

A cDNA Microarray for Crassostrea virginica and C. gigas - Matthew J. Jenny; Robert W. Chapman; Annalaura Mancia; Yian A. Chen; David J. McKillen; Hal Trent; Paul Lang; Jean-Michel Escoubas; Evelyne Bachere; Viviane Boulo; Z. John Liu; Paul S. Gross; et al. (Marine Biotechnology, 2007)

New Resources for Marine Genomics: Bacterial Artificial Chromosome Libraries for the Eastern and Pacific Oysters (Crassostrea virginica and C. gigas) - Charles Cunningham; Jun-ichi Hikima; Matthew J. Jenny; Robert W. Chapman; Guang-Chen Fang; Chris Saski; Mats L. Lundqvist; Rod A. Wing; Pauline M. Cupit; Paul S. Gross; Greg W. Warr; Jeff P. Tomkins (Marine Biotechnology, 2006)

Development of an Advanced Hyperspectral Imaging (HSI) System with Applications for Cancer Detection - Matthew E. Martin; Musundi B. Wabuyele; Kui Chen; Paul Kasili; Masoud Panjehpour; Mary Phan; Bergein Overholt; Glenn Cunningham; Dale Wilson; Robert C. DeNovo; Tuan Vo-Dinh (Annals of Biomedical Engineering, 2006)