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.

From magma to macrophage: the grand challenges of volcanic environments - Catherine A. Mériaux; Edward Ntim Gasu; Guillaume Nyagatare; Vicky Ruganzu; Philbert Ntivuguruzwa; Mwumvaneza Mutagoma; Atalay Ayele; Julyan H. E. Cartwright; Valérie Cayol; Laurent Charlet; Claudia Corradino; Antonio Costa; et al. (Bulletin of Volcanology, 2026)
The interdisciplinary study of volcanic processes, which extend across all timescales and lengths, requires a multitude of approaches, ranging from analogue and numerical modelling to observations and fieldwork and extending to mathematics. A conference was held at the East African Institute for Fundamental Research, affiliated with the University of Rwanda, a country which, along with the Democratic Republic of Congo, presents a unique geodynamic context. Located along the East African Rift, an active seismic region, Rwanda is close to two of Africa's most active volcanoes, including Nyiragongo, which overlooks Lake Kivu, a deep volcanic lake rich in dissolved carbon dioxide and methane, the latter of which is used for electricity generation. In this context, the conference addressed many “classic” volcanological topics and their modern advances, such as multiphase lava flows, subsurface magma propagation, seismic and deformation signals from a volcano, modelling of volcanic emission dispersion, and volcanic lakes. Yet, it broadened the discussion to the volcanic particle-water interface and its impact on soils, volcanoes and climate change, and volcanoes and health. This article aims to highlight and share the richness of the integration and interconnectedness of the various questions related to a volcanic environment, as well as their impact on society. Ultimately, this conference also demonstrated the importance of promoting science in Africa and developing countries so that the next generation of African researchers is equipped to address the challenges facing their nations.

AIS underrepresents vessel traffic in Scotland's Marine Protected Areas - Emily L. Hague; Alice Walters; Anna Moscrop; Emma Steel; Katie Dyke; Lauren Hartny-Mills; Alison Lomax; Juliane Lehmann; Sebastian Olias; Carsten Hilgenfeld; Debbie Cole; Sarah MacDonald-Taylor; et al. (Ocean & Coastal Management, 2026)

Network of networks: Time series clustering of AmeriFlux sites - David E Reed; Housen Chu; Brad G. Peter; Jiquan Chen; Michael Abraha; Brian Amiro; Ray G. Anderson; M. Altaf Arain; Paulo Arruda; Greg A. Barron-Gafford; Carl Bernacchi; Daniel P. Beverly; et al. (Agricultural and Forest Meteorology, 2025)

AIS data underrepresents vessel traffic around coastal Scotland - Emily Hague; Alice Walters; Anna Moscrop; Emma Steel; Katie Dyke; Lauren Hartny-Mills; Alison Lomax; Rebecca Dudley; Pippa Garrard; Jenny Hampson; Sadie Gorvett; Hannah Lightley; et al. (Marine Policy, 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.

Germline copy number variants and endometrial cancer risk - Cassie E. Stylianou; George A. R. Wiggins; Vanessa L. Lau; Joe Dennis; Andrew N. Shelling; Michelle Wilson; Peter Sykes; Frederic Amant; Daniela Annibali; Wout De Wispelaere; Douglas F. Easton; Peter A. Fasching; et al. (Human Genetics, 2024)
Known risk loci for endometrial cancer explain approximately one third of familial endometrial cancer. However, the association of germline copy number variants (CNVs) with endometrial cancer risk remains relatively unknown. We conducted a genome-wide analysis of rare CNVs overlapping gene regions in 4115 endometrial cancer cases and 17,818 controls to identify functionally relevant variants associated with disease. We identified a 1.22-fold greater number of CNVs in DNA samples from cases compared to DNA samples from controls ( p = 4.4 × 10 –63 ). Under three models of putative CNV impact (deletion, duplication, and loss of function), genome-wide association studies identified 141 candidate gene loci associated ( p < 0.01) with endometrial cancer risk. Pathway analysis of the candidate loci revealed an enrichment of genes involved in the 16p11.2 proximal deletion syndrome, driven by a large recurrent deletion (chr16:29,595,483-30,159,693) identified in 0.15% of endometrial cancer cases and 0.02% of control participants. Together, these data provide evidence that rare copy number variants have a role in endometrial cancer susceptibility and that the proximal 16p11.2 BP4-BP5 region contains 25 candidate risk gene(s) that warrant further analysis to better understand their role in human disease.

Engaging stakeholders in the use of an interactive simulation tool to support decision-making about the implementation of colorectal cancer screening interventions - Meghan C. O’Leary; Kristen Hassmiller Lich; Maria E. Mayorga; Karen Hicklin; Melinda M. Davis; Alison T. Brenner; Daniel S. Reuland; Sarah A. Birken; Stephanie B. Wheeler (Cancer Causes & Control, 2023)
Purpose We aimed to understand how an interactive, web-based simulation tool can be optimized to support decision-making about the implementation of evidence-based interventions (EBIs) for improving colorectal cancer (CRC) screening. Methods Interviews were conducted with decision-makers, including health administrators, advocates, and researchers, with a strong foundation in CRC prevention. Following a demonstration of the microsimulation modeling tool, participants reflected on the tool’s potential impact for informing the selection and implementation of strategies for improving CRC screening and outcomes. The interviews assessed participants’ preferences regarding the tool’s design and content, comprehension of the model results, and recommendations for improving the tool. Results Seventeen decision-makers completed interviews. Themes regarding the tool’s utility included building a case for EBI implementation, selecting EBIs to adopt, setting implementation goals, and understanding the evidence base. Reported barriers to guiding EBI implementation included the tool being too research-focused, contextual differences between the simulated and local contexts, and lack of specificity regarding the design of simulated EBIs. Recommendations to address these challenges included making the data more actionable, allowing users to enter their own model inputs, and providing a how-to guide for implementing the simulated EBIs. Conclusion Diverse decision-makers found the simulation tool to be most useful for supporting early implementation phases, especially deciding which EBI(s) to implement. To increase the tool’s utility, providing detailed guidance on how to implement the selected EBIs, and the extent to which users can expect similar CRC screening gains in their contexts, should be prioritized.

Documenting Twenty Years of the Contracted Labor-Intensive Forestry Workforce on National Forest System Lands in the United States - Alison Deak; Heidi Huber-Stearns; Mindy Crandall; Kamana Poudel; Emily Jane Davis; Michael R Coughlan; Carl Wilmsen (Journal of Forestry, 2023)
This paper presents the first nationwide analysis detailing the scope and scale of labor-intensive forestry contracts performed on National Forest System lands and examines the businesses contracted, location and types of work performed, and distance traveled by businesses between 2001 and 2020. During the study period, 61,698 contracts were awarded to 7,896 businesses, totaling $12.9 billion, to perform labor-intensive forestry work, with most work being contracted for wildfire-related activities. Businesses were typically located in western states and non-minority owned businesses received the majority of contracts. Of minority-owned businesses, Hispanic American–owned businesses received the most contracts. The median distance that businesses traveled to accomplish work increased significantly through time but differed by business type. Understanding the scope and work of businesses awarded contracts provides insight into the workforce and its relationship to marginalized populations. Strategic investment in this workforce may have widespread impacts on federal, state, and local economies and the livelihoods of forest workers. Study Implications: Between 2001–2020, the USDA Forest Service spent billions of dollars on contracts with thousands of businesses to conduct labor-intensive forestry projects; however, project locations and awarded businesses were not evenly distributed through space and time. Emerging and minority businesses represented a small proportion of contracts awarded. Advancing understanding of the businesses conducting labor-intensive forestry work lays the foundation for inquiry into the working conditions forest workers experience as well as disparities in contract capture. Some regions may have benefitted more from contract capture than others. Understanding factors enabling places and businesses to capture these contract dollars may help identify others that may benefit from investment.

Opportunities for regional collaboration and prevention: Assessing the risk of the live bait trade as a pathway of invasive species - Hannah Mulligan; Benjamin J. Schall; Tanner Davis; Alison A. Coulter (Biological Conservation, 2023)

Parsing variance by marker type: Testing biogeographic hypotheses and differential contribution of historical processes to population structure in a desert lizard - Iris A. Holmes; Ivan V. Monagan; Michael F. Westphal; Paul J. Johnson; Alison R. Davis Rabosky (Molecular Ecology, 2023)
A fundamental goal of population genetic studies is to identify historical biogeographic patterns and understand the processes that generate them. However, localized demographic events can skew population genetic inference. Assessing populations with multiple types of genetic markers, each with unique mutation rates and responses to changes in population size, can help to identify potentially confounding population‐specific demographic processes. Here, we compared population structure and connectivity inferred from microsatellites and restriction site‐associated DNA loci among 17 populations of an arid‐specialist lizard, the desert night lizard, Xantusia vigilis , in central California to test among historical processes structuring population genetic diversity. We found that both marker types yielded generally concordant insights into population genetic structure including a major phylogenetic break maintained between two populations separated by less than 10 km, suggesting that either marker type could be used to understand generalized demographic patterns across the region for management purposes. However, we also found that the effects of demography on marker discordance could be used to elucidate population histories and distinguish among competing biogeographic hypotheses. Our results suggest that comparisons of within‐population diversity across marker types provide powerful opportunities for leveraging marker discordance, particularly for understanding the creation and maintenance of contact zones among clades.

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.

Guiding principles for rewilding - Steve Carver; Ian Convery; Sally Hawkins; Rene Beyers; Adam Eagle; Zoltan Kun; Erwin Van Maanen; Yue Cao; Mark Fisher; Stephen R. Edwards; Cara Nelson; George D. Gann; et al. (Conservation Biology, 2021)
There has been much recent interest in the concept of rewilding as a tool for nature conservation, but also confusion over the idea, which has limited its utility. We developed a unifying definition and 10 guiding principles for rewilding through a survey of 59 rewilding experts, a summary of key organizations’ rewilding visions, and workshops involving over 100 participants from around the world. The guiding principles convey that rewilding exits on a continuum of scale, connectivity, and level of human influence and aims to restore ecosystem structure and functions to achieve a self‐sustaining autonomous nature. These principles clarify the concept of rewilding and improve its effectiveness as a tool to achieve global conservation targets, including those of the UN Decade on Ecosystem Restoration and post‐2020 Global Biodiversity Framework. Finally, we suggest differences in rewilding perspectives lie largely in the extent to which it is seen as achievable and in specific interventions. An understanding of the context of rewilding projects is the key to success, and careful site‐specific interpretations will help achieve the aims of rewilding.

Semiarid grasslands and extreme precipitation events: do experimental results scale to the landscape? - Alison K. Post; Kristin P. Davis; Jillian LaRoe; David L. Hoover; Alan K. Knapp (Ecology, 2021)
The frequency and magnitude of deluges (extremely large rain events) are increasing globally as the atmosphere warms. Small‐scale experiments suggest that semiarid grasslands are particularly sensitive to both the timing and size of deluge events. However, the assumption that plot‐scale results can be extrapolated across landscapes with variable soil textures, plant communities, and grazing regimes has seldom been tested, despite being key to forecasting regional consequences of precipitation extremes. We used precipitation data from an extensive rain gauge network to identify natural deluges (mean size = 60 ± 31 mm, 1984–2012) that occurred across a ˜60‐km 2 heterogeneous native shortgrass steppe landscape in Colorado. We then related spatial variation in deluge precipitation to postdeluge responses in canopy greenness (normalized difference vegetation index, NDVI) via satellite imagery. Consistent with results from experiments, this semiarid grassland was most sensitive to mid–growing‐season deluges, and postdeluge canopy greenness usually increased linearly (67% of the time) with increasing deluge size. This suggests that aboveground productivity in these semiarid systems will likely increase, rather than asymptote, with forecasted increases in deluge size. Importantly, differences in grazing regime did not significantly alter deluge responses, indicating that these patterns are robust to this widespread management practice.

Fighting the War Against COVID-19 via Cell-Based Regenerative Medicine: Lessons Learned from 1918 Spanish Flu and Other Previous Pandemics - You Jeong Park; Jeffrey Farooq; Justin Cho; Nadia Sadanandan; Blaise Cozene; Bella Gonzales-Portillo; Madeline Saft; Maximillian C. Borlongan; Mia C. Borlongan; R. Douglas Shytle; Alison E. Willing; Svitlana Garbuzova-Davis; et al. (Stem Cell Reviews and Reports, 2021)
The human population is in the midst of battling a rapidly-spreading virus— Severe Acute Respiratory Syndrome Coronavirus 2, responsible for Coronavirus disease 2019 or COVID-19. Despite the resurgences in positive cases after reopening businesses in May, the country is seeing a shift in mindset surrounding the pandemic as people have been eagerly trickling out from federally-mandated quarantine into restaurants, bars, and gyms across America. History can teach us about the past, and today’s pandemic is no exception. Without a vaccine available, three lessons from the 1918 Spanish flu pandemic may arm us in our fight against COVID-19. First, those who survived the first wave developed immunity to the second wave, highlighting the potential of passive immunity-based treatments like convalescent plasma and cell-based therapy. Second, the long-term consequences of COVID-19 are unknown. Slow-progressive cases of the Spanish flu have been linked to bacterial pneumonia and neurological disorders later in life, emphasizing the need to reduce COVID-19 transmission. Third, the Spanish flu killed approximately 17 to 50 million people, and the lack of human response, overcrowding, and poor hygiene were key in promoting the spread and high mortality. Human behavior is the most important strategy for preventing the virus spread and we must adhere to proper precautions. This review will cover our current understanding of the pathology and treatment for COVID-19 and highlight similarities between past pandemics. By revisiting history, we hope to emphasize the importance of human behavior and innovative therapies as we wait for the development of a vaccine.

Cell-Free Extracellular Vesicles Derived from Human Bone Marrow Endothelial Progenitor Cells as Potential Therapeutics for Microvascular Endothelium Restoration in ALS - Svitlana Garbuzova-Davis; Alison E. Willing; Jared Ehrhart; Lianchun Wang; Paul R. Sanberg; Cesario V. Borlongan (NeuroMolecular Medicine, 2020)

Better off dead: assessment of aquatic disinfectants and thermal shock treatments to prevent the spread of invasive freshwater bivalves - Neil E. Coughlan; Stephanie J. Bradbeer; Ross N. Cuthbert; Eoghan M. Cunningham; Kate Crane; Stephen Potts; Joe M. Caffrey; Frances E. Lucy; Alison M. Dunn; Eithne Davis; Trevor Renals; Claire Quinn; et al. (Wetlands Ecology and Management, 2020)
Biosecurity protocols designed to prevent further spread of invasive alien species have become a key component of invader management strategies. Yet, the species-specific efficacy of many biosecurity treatments are frequently unclear or unknown. Invasive quagga, Dreissena bugensis , and zebra mussels, D. polymorpha , are a serious threat to freshwater ecosystems worldwide. Here, we examine the effectiveness of immersion (≤ 90 min) within 2% or 4% solutions for two commonly used disinfectants (Virasure® Aquatic and Virkon® Aquatic) to cause mortality of adult Dreissena bivalves . Further, we assessed the effectiveness of thermal treatments: steam spray (≥ 100 °C; ≤ 120 s); hot air (− 500 °C; ≤ 60 s); and dry ice exposure (− 78 °C; ≤ 300 g; 15 min). Complete mortality of D. polymorpha was observed following exposure to both disinfectants for 90 min, at both concentrations. However, high but incomplete mortality (40–90%) was recorded for D. bugensis across disinfectant treatments. For both species, complete mortality was achieved following 30 s of steam. In addition, 10 s of hot air and 15 min exposure to 300 g of dry ice can both completely killed groups of D. polymorpha . Overall, although the disinfectants did not cause complete mortality, it appears that relatively brief exposure to thermal treatments could be used to curtail the further spread of Dreissena species.

Environmental heterogeneity and not vicariant biogeographic barriers generate community‐wide population structure in desert‐adapted snakes - Edward A. Myers; Alexander T. Xue; Marcelo Gehara; Christian L. Cox; Alison R. Davis Rabosky; Julio Lemos‐Espinal; Juan E. Martínez‐Gómez; Frank T. Burbrink (Molecular Ecology, 2019)
Genetic structure can be influenced by local adaptation to environmental heterogeneity and biogeographic barriers, resulting in discrete population clusters. Geographic distance among populations, however, can result in continuous clines of genetic divergence that appear as structured populations. Here, we evaluate the relevant importance of these three factors over a landscape characterized by environmental heterogeneity and the presence of a hypothesized biogeographic barrier in producing population genetic structure within 13 codistributed snake species using a genomic data set. We demonstrate that geographic distance and environmental heterogeneity across western North America contribute to population genomic divergence. Surprisingly, landscape features long thought to contribute to biogeographic barriers play little role in divergence community wide. Our results suggest that isolation by environment is the most important contributor to genomic divergence. Furthermore, we show that models of population clustering that incorporate spatial information consistently outperform nonspatial models, demonstrating the importance of considering geographic distances in population clustering. We argue that environmental and geographic distances as drivers of community‐wide divergence should be explored before assuming the role of biogeographic barriers.

Global Perspectives on Observing Ocean Boundary Current Systems - Robert E. Todd; Francisco P. Chavez; Sophie Clayton; Sophie Cravatte; Marlos Goes; Michelle Graco; Xiaopei Lin; Janet Sprintall; Nathalie V. Zilberman; Matthew Archer; Javier Arístegui; Magdalena Balmaseda; et al. (Frontiers in Marine Science, 2019)

Delimitation of Alosa species (Teleostei: Clupeiformes) from the Sea of Azov: integrating morphological and molecular approaches - Oksana V. Vernygora; Corey S. Davis; Alison M. Murray; Felix A. H. Sperling (Journal of Fish Biology, 2018)
Shads of the genus Alosa are essential to commercial fisheries across North America and Europe, but in some areas their species boundaries remain controversial. Traditional morphology‐based taxonomy of Alosa spp. has relied heavily on the number of gill rakers and body proportions, but these can be highly variable. We use mitochondrial (mt)DNA ( coI and cytb ) and genome‐wide single nucleotide polymorphisms (SNP) along with morphological characters to assess differentiation among endemic Ponto‐Caspian shads in the Sea of Azov. Morphological species assignments based on gill‐raker number were not congruent with genetic lineages shown by mtDNA and SNPs. Iterative analysis revealed that genetic lineages were associated with sampling location and several other morphometric traits (caudal peduncle depth, pre‐anal length and head length). Phylogenetic analysis of the genus placed Ponto‐Caspian Alosa spp. in the same evolutionary lineage as endangered Alosa spp. endemic to Greece, highlighting the importance of these findings to conservation management. We conclude that gill‐raker number is not reliable for delimiting species of Alosa. This taxonomic uncertainty should be addressed by examining type material to provide a robust integrative classification for these commercially important fishes.

Hydrological Outlook UK: an operational streamflow and groundwater level forecasting system at monthly to seasonal time scales - Christel Prudhomme; Jamie Hannaford; Shaun Harrigan; David Boorman; Jeff Knight; Victoria Bell; Christopher Jackson; Cecilia Svensson; Simon Parry; Nuria Bachiller-Jareno; Helen Davies; Richard Davis; et al. (Hydrological Sciences Journal, 2017)

Computational Modeling of Pathophysiologic Responses to Exercise in Fontan Patients - Ethan Kung; James C. Perry; Christopher Davis; Francesco Migliavacca; Giancarlo Pennati; Alessandro Giardini; Tain-Yen Hsia; Alison Marsden (Annals of Biomedical Engineering, 2015)

Molecular systematics of the genus Sonora (Squamata: Colubridae) in central and western Mexico - Christian L. Cox; Alison R. Davis Rabosky; Jacobo Reyes-Velasco; Paulino Ponce-Campos; Eric N. Smith; Oscar Flores-Villela; Jonathan A. Campbell (Systematics and Biodiversity, 2012)

The SUMO conjugation pathway in Populus: genomic analysis, tissue-specific and inducible SUMOylation and in vitro de-SUMOylation - Jon M. Reed; Christopher Dervinis; Alison M. Morse; John M. Davis (Planta, 2010)

Elasticity analysis in epidemiology: an application to tick‐borne infections - Amy Matser; Nienke Hartemink; Hans Heesterbeek; Alison Galvani; Stephen Davis (Ecology Letters, 2009)
Ecology Letters (2009) 12: 1298–1305 Abstract The application of projection matrices in population biology to plant and animal populations has a parallel in infectious disease ecology when next‐generation matrices (NGMs) are used to characterize growth in numbers of infected hosts ( R 0 ). The NGM is appropriate for multi‐host pathogens, where each matrix element represents the number of cases of one type of host arising from a single infected individual of another type. For projection matrices, calculations of the sensitivity and elasticity of the population growth rate to changes in the matrix elements has generated insight into plant and animal populations. These same perturbation analyses can be used for infectious disease systems. To illustrate this in detail we parameterized an NGM for seven tick‐borne zoonoses and compared them in terms of the contributions to R 0 from three different routes of transmission between ticks, and between ticks and vertebrate hosts. The definition of host type may be the species of the host or the route of infection, or, as was the case for the set of tick‐borne pathogens, a combination of species and the life stage at infection. This freedom means that there is a broad range of disease systems and questions for which the methodology is appropriate.

Evolution and diversity of invertase genes in Populus trichocarpa - Philip N. Bocock; Alison M. Morse; Christopher Dervinis; John M. Davis (Planta, 2008)

Genetic dissection of fusiform rust and pitch canker disease traits in loblolly pine - Gogce C. Kayihan; Dudley A. Huber; Alison M. Morse; Timothy L. White; John M. Davis (Theoretical and Applied Genetics, 2005)

Pine genes regulated by the necrotrophic pathogen Fusarium circinatum - Alison M. Morse; C. Dana Nelson; Sarah F. Covert; Angela G. Holliday; Katherine E. Smith; John M. Davis (Theoretical and Applied Genetics, 2004)