Community Dinners as a Low-Barrier Health Education Strategy for Underserved Families - Kimi Moore; Alison Biloon; Kristin Kelly (Journal of Nutrition Education and Behavior, 2026)

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

Informing spatial conservation prioritization with species’ traits - Liam A. Trethowan; Laura Jennings; Haerul Arifin; Renata Borosova; Gemma L. C. Bramley; Marie Briggs; Osanna Chu; Ruth P. Clark; Sally Dawson; Kiran L. Dhanjal‐Adams; Yance de Freitas; James Hartup; et al. (Conservation Biology, 2026)
New Guinea, the most botanically diverse island on the planet, is the location for one of the boldest conservation initiatives. The Manokwari Declaration aims to achieve 70% conservation designation for the Bird's Head Peninsula. This is 40% higher than the 2022 Global Biodiversity Framework target. However, there is a lack of species occurrence data to support evidence of where biodiversity can be best protected. To address this, we integrated plant trait data from taxonomic descriptions in species occurrence models that can inform conservation planning. Inclusion of traits improved the performance of co‐occurrence models of ∼800 plant species across the 100,000‐km 2 landscape. Traits generally improved model performance, but not all traits contributed equally (e.g., leaf size and red flower color most improved accuracy of occurrence prediction). Likewise, trait‐parameterized models tended to be most useful with rare species occurrence prediction, but this was inconsistent among traits. Under 70% protection, three‐quarters of the areas selected conserved trait diversity. Critically, trait diversity also increased the chances that areas at high risk of deforestation were selected as conservation priorities. Overall, we found that plant species’ traits, often key parameters of ecosystem function and resilience, improved spatial conservation planning.

Racial and ethnic disparities in environmental chemical exposures and hypertensive disorders of pregnancy: The ECHO-wide cohort study - Hongxiu Liu; Amii M. Kress; Emma X. Yu; Xuejuan Ning; Akhgar Ghassabian; Linda G. Kahn; Shilpi Mehta-Lee; Sara Brubaker; Akram Alshawabkeh; John Meeker; Carlos A. Camargo; Shakira F. Suglia; et al. (Environmental Pollution, 2026)

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.

The Toxicology Investigators Consortium 2024 Annual Report - Kim Aldy; Shao Li; Mari Costantini; Alyssa Falise; Rachel Culbreth; Paul M. Wax; Jeffery Brent; Michael Abesamis; Faiz Ahmed; Salman Ahsan; Peter Akpunonu; Adam Algren; et al. (Journal of Medical Toxicology, 2026)

Analysis of the impact of automaker strategies on lithium price elasticity using a novel bottom-up demand model - Luke Robert Sullivan; Elizabeth A. Moore; Phuong Ho; Alison A. Wang; Gwyneth Margaux Tangog; Karan Bhuwalka; Elsa Olivetti; Richard Roth (Resources, Conservation and Recycling, 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.

Correction: Social and ecological drivers of behavior that prevents aquatic invasive species transport - Alison Moore; Danika Ford; Elizabeth Golebie; North Joffe-Nelson; Greg Hitzroth; Amanda Huegelmann; Sarah King; Jeffrey A. Stein; Carena J. van Riper (Biological Invasions, 2025)

A synthesis of the characteristics and drivers of introduced fishes in prairie streams: can we manage introduced harmful fishes in these dynamic environments? - Alison A. Coulter; Michael J. Moore; Jimena Golcher-Benavides; Frank J. Rahel; Annika W. Walters; Shannon K. Brewer; Mark L. Wildhaber (Biological Invasions, 2024)
Prairie streams of North America support native fishes that are adapted to the dynamic environment that characterizes these ecologically and economically important ecosystems. However, prairie streams have been altered by landscape changes that may affect the proportions of native and introduced species in fish communities. Herein, we investigate drivers of introduced fish in prairie streams, detail common introduced species and their traits and effects, investigate how climate change may alter the balance between native and introduced species, and summarize management options. Commonly introduced fishes are those with the ability to tolerate extreme variations in temperature, hydrology, and salinity and, as a result, most of the introduced fishes were native to other prairie streams within the Great Plains ecoregion. This suggests environmental extremes may act as a filter for establishment or that short-distance translocations are more common than introductions from other ecoregions. The mechanisms or extent to which introduced species affect native fishes is often assumed or understudied. Climate change may amplify environmental disturbances in ways that may favor native or introduced fishes depending on species traits and biotic interactions. Actions such as habitat modifications or disturbances may favor introduced fishes over native fishes. Research to understand the relative roles of trait preadaptation and spatial proximity of source populations in introduced species establishment could benefit future management. Moreover, patterns observed in other ecosystems may not be transferrable to prairie streams, highlighting the need to understand the context dependency of effects of introduced species.

Island area, isolation and climate effects upon flower traits in a megadiverse archipelago - Liam A. Trethowan; Laura Jennings; Gemma Bramley; Marie Briggs; Ruth Clark; Sally Dawson; Max Fontaine; Charlie Heatubun; Gwilym Lewis; Eve Lucas; Alison Moore; Laura Pearce; et al. (Journal of Biogeography, 2024)
Aim Flower traits are critical to the mutualistic networks that underpin ecosystem function. However, the broad‐scale drivers of flower traits are unclear. Using the megadiverse islands of Malesia, we test three hypotheses: (1) Flower size, openness and colourfulness (i.e. the trend from white to colourful flowers) will decrease with increasing temperature, but not with increasing precipitation seasonality. (2) Flower size, openness and colourfulness will increase with island area, and decrease with isolation. (3) Models parameterised by climate, rather than non‐climatic island characteristics will have the greatest predictive capacity as climate affects both pollinator communities and energetic/physiological constraints upon flower traits. Location Fourteen Malesian islands. Taxon Angiosperms. Methods We applied Bayesian phylogenetic models of occurrence for >2500 species in 400 m elevation bands, across islands, as a function of flower trait interactions with either climatic variables or islands characteristics. We compare predictive capacity of models based on climate versus island characteristics using Leave One Out‐Cross Validation. Results All six flower traits examined varied with at least temperature, precipitation seasonality, island area and isolation. Flowers are larger in cold environments. The lowland tropics are mostly inhabited by white flowered species. At cold high elevations, red and pink flowered species are more frequent whereas green and purple flowered species increase in the drought‐prone seasonally dry tropics. Flower openness declined with precipitation seasonality and increased with isolation. Models parameterised by climate performed best for perianth length, red and white flowers, whereas pink flowers and flower openness were better predicted using island characteristics. Main Conclusions There are relationships between flower traits and climatic gradients within Malesia. However, island characteristics have also left a legacy upon current flower trait distributions. These island biogeographical impacts are likely key for the eco‐evolutionary drivers of flower traits.

Social and ecological drivers of behavior that prevents aquatic invasive species transport - Alison Moore; Danika Ford; Elizabeth Golebie; North Joffe-Nelson; Greg Hitzroth; Amanda Huegelmann; Sarah King; Jeffrey A. Stein; Carena J. van Riper (Biological Invasions, 2024)

Effect of a Technology-Integrated Curriculum on Sugary Drink and Snack Intake of Elementary-Aged Youth Experiencing Low Income - Kate Balestracci; Linda Sebelia; Geoffrey Greene; Adam Moore; Grayson Baird; Kelsi Chappell; Alison Tovar (Journal of Nutrition Education and Behavior, 2024)

Validating assumptions in calculating carbon dioxide removal by enhanced rock weathering in Kantola et al., 2023 - Adam Wolf; Elliot Chang; Ilsa B. Kantola; Elena Blanc‐Betes; Michael D. Masters; Alison Marklein; Caitlin E. Moore; Carl J. Bernacchi; Evan H. DeLucia (Global Change Biology, 2024)

Optimizing process flow diagrams to guide implementation of a colorectal cancer screening intervention in new settings - Meghan C. O’Leary; Kristen Hassmiller Lich; Daniel S. Reuland; Alison T. Brenner; Alexis A. Moore; Shana Ratner; Sarah A. Birken; Stephanie B. Wheeler (Cancer Causes & Control, 2023)
Purpose The goal of this study was to assess acceptability of using process flow diagrams (or process maps) depicting a previously implemented evidence-based intervention (EBI) to inform the implementation of similar interventions in new settings. Methods We developed three different versions of process maps, each visualizing the implementation of the same multicomponent colorectal cancer (CRC) screening EBI in community health centers but including varying levels of detail about how it was implemented. Interviews with community health professionals and practitioners at other sites not affiliated with this intervention were conducted. We assessed their preferences related to the map designs, their potential utility for guiding EBI implementation, and the feasibility of implementing a similar intervention in their local setting given the information available in the process maps. Results Eleven community health representatives were interviewed. Participants were able to understand how the intervention was implemented and engage in discussions around the feasibility of implementing this type of complex intervention in their local system. Potential uses of the maps for supporting implementation included staff training, role delineation, monitoring and quality control, and adapting the components and implementation activities of the existing intervention. Conclusion Process maps can potentially support decision-making about the adoption, implementation, and adaptation of existing EBIs in new contexts. Given the complexities involved in deciding whether and how to implement EBIs, these diagrams serve as visual, easily understood tools to inform potential future adopters of the EBI about the activities, resources, and staffing needed for implementation.

Uptake of colorectal cancer screening after mailed fecal immunochemical test (FIT) outreach in a newly eligible 45–49-year-old community health center population - Meghan C. O’Leary; Daniel S. Reuland; Sara Y. Correa; Alexis A. Moore; Teri L. Malo; Xianming Tan; Catherine L. Rohweder; Stephanie B. Wheeler; Alison T. Brenner (Cancer Causes & Control, 2023)
Purpose We assessed fecal immunochemical test (FIT) uptake following a mailed FIT intervention among 45–49-year-olds newly eligible for colorectal cancer (CRC) screening based on 2021 United States Preventive Services Task Force screening recommendations. We also tested the effect of an enhanced versus plain mailing envelope on FIT uptake. Methods In February 2022 we mailed FITs to eligible 45–49-year-olds at one Federally Qualified Health Center (FQHC) clinic. We determined the proportion who completed FITs within 60 days. We also conducted a nested randomized trial comparing uptake using an enhanced envelope (padded with tracking label and colored messaging sticker) versus plain envelope. Finally, we determined the change in CRC screening by any modality (e.g., FIT, colonoscopy) among all clinic patients in this age group (i.e., clinic-level screening) between baseline and 6 months post-intervention. Results We mailed FITs to 316 patients. Sample characteristics: 57% female, 58% non-Hispanic Black, and 50% commercially insured. Overall, 54/316 (17.1%) returned a FIT within 60 days, including 34/158 (21.5%) patients in the enhanced envelope arm versus 20/158 (12.7%) in the plain envelope arm (difference 8.9 percentage points, 95% CI: 0.6–17.2). Clinic-level screening among all 45–49-year-olds increased 16.6 percentage points (95% CI: 10.9–22.3), from 26.7% at baseline to 43.3% at 6 months. Conclusion CRC screening appeared to increase following a mailed FIT intervention among diverse FQHC patients aged 45–49. Larger studies are needed to assess acceptability and completion of CRC screening in this younger population. Visually appealing mailers may improve uptake when implementing mailed interventions. Trial registration The trial was registered on May 28, 2020 at ClinicalTrials.gov (identifier NCT04406714).

Improved net carbon budgets in the US Midwest through direct measured impacts of enhanced weathering - Ilsa B. Kantola; Elena Blanc‐Betes; Michael D. Masters; Elliot Chang; Alison Marklein; Caitlin E. Moore; Adam von Haden; Carl J. Bernacchi; Adam Wolf; Dimitar Z. Epihov; David J. Beerling; Evan H. DeLucia (Global Change Biology, 2023)
Terrestrial enhanced weathering (EW) through the application of Mg‐ or Ca‐rich rock dust to soil is a negative emission technology with the potential to address impacts of climate change. The effectiveness of EW was tested over 4 years by spreading ground basalt (50 t ha −1 year −1 ) on maize/soybean and miscanthus cropping systems in the Midwest US. The major elements of the carbon budget were quantified through measurements of eddy covariance, soil carbon flux, and biomass. The movement of Mg and Ca to deep soil, released by weathering, balanced by a corresponding alkalinity flux, was used to measure the drawdown of CO 2 , where the release of cations from basalt was measured as the ratio of rare earth elements to base cations in the applied rock dust and in the surface soil. Basalt application stimulated peak biomass and net primary production in both cropping systems and caused a small but significant stimulation of soil respiration. Net ecosystem carbon balance (NECB) was strongly negative for maize/soybean (−199 to −453 g C m −2 year −1 ) indicating this system was losing carbon to the atmosphere. Average EW (102 g C m −2 year −1 ) offset carbon loss in the maize/soybean by 23%–42%. NECB of miscanthus was positive (63–129 g C m −2 year −1 ), indicating carbon gain in the system, and EW greatly increased inorganic carbon storage by an additional 234 g C m −2 year −1 . Our analysis indicates a co‐deployment of a perennial biofuel crop (miscanthus) with EW leads to major wins—increased harvested yields of 29%–42% with additional carbon dioxide removal (CDR) of 8.6 t CO 2 ha −1 year −1 . EW applied to maize/soybean drives a CDR of 3.7 t CO 2 ha −1 year −1 , which partially offsets well‐established carbon losses from soil from this crop rotation. EW applied in the US Midwest creates measurable improvements to the carbon budgets perennial bioenergy crops and conventional row crops.

Improving data collection in pregnancy safety studies: Towards standardization of data elements in pregnancy reports from public and private partners (ConcePTION) - Guillaume Favre; Jonathan L. Richardson; Alan Moore; Yvonne Geissbühler; Valentine Jehl; Alison Oliver; Svetlana Shechtman; Orna Diav-Citrin; Maya Berlin; Tal De-Haan; Anil Mor; Meritxell Sabidó; et al. (Neurotoxicology and Teratology, 2023)

IMI ConcePTION core data elements for pregnancy pharmacovigilance studies using primary source data collection methods - Jonathan Richardson; Alan Moore; Rebecca Bromley; Michael Stellfeld; Yvonne Geissbühler; Matthew Bluett-Duncan; Ursula Winterfeld; Guillaume Favre; Kenneth Hodson; Alison Oliver; Amalia Alexe; Yrea van Rijt-Weetink; et al. (Neurotoxicology and Teratology, 2023)

Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network - Jason Beringer; Caitlin E. Moore; Jamie Cleverly; David I. Campbell; Helen Cleugh; Martin G. De Kauwe; Miko U. F. Kirschbaum; Anne Griebel; Sam Grover; Alfredo Huete; Lindsay B. Hutley; Johannes Laubach; et al. (Global Change Biology, 2022)
In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20 th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO 2 sink to a net CO 2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under‐represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long‐term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.

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.

Integrating Coral Restoration Data With a Novel Coral Sample Registry - Amelia Moura; Brian Beck; Renee Duffey; Lucas McEachron; Margaret Miller; Jennifer Moore; Alison Moulding; R. Scott Winters (Frontiers in Marine Science, 2021)
In the past decade, the field of coral reef restoration has experienced a proliferation of data detailing the source, genetics, and performance of coral strains used in research and restoration. Resource managers track the multitude of permits, species, restoration locations, and performance across multiple stakeholders while researchers generate large data sets and data pipelines detailing the genetic, genomic, and phenotypic variants of corals. Restoration practitioners, in turn, maintain records on fragment collection, genet performance, outplanting location and survivorship. While each data set is important in its own right, collectively they can provide deeper insights into coral biology and better guide coral restoration endeavors – unfortunately, current data sets are siloed with limited ability to cross-mine information for deeper insights and hypothesis testing. Herein we present the Coral Sample Registry (CSR), an online resource that establishes the first step in integrating diverse coral restoration data sets. Developed in collaboration with academia, management agencies, and restoration practitioners in the South Florida area, the CSR centralizes information on sample collection events by issuing a unique accession number to each entry. Accession numbers can then be incorporated into existing and future data structures. Each accession number is unique and corresponds to a specific collection event of coral tissue, whether for research, archiving, or restoration purposes. As such the accession number can serve as the key to unlock the diversity of information related to that sample’s provenance and characteristics across any and all data structures that include the accession number field. The CSR is open-source and freely available to users, designed to be suitable for all coral species in all geographic regions. Our goal is that this resource will be adopted by researchers, restoration practitioners, and managers to efficiently track coral samples through all data structures and thus enable the unlocking of a broader array of insights.

An inducible expression system in the alga Nannochloropsis gaditana controlled by the nitrate reductase promoter - Harry O. Jackson; Adokiye Berepiki; Alison J. Baylay; Matthew J. Terry; C. Mark Moore; Thomas S. Bibby (Journal of Applied Phycology, 2019)

Denial of long‐term issues with agriculture on tropical peatlands will have devastating consequences - Lahiru S. Wijedasa; Jyrki Jauhiainen; Mari Könönen; Maija Lampela; Harri Vasander; Marie‐Claire Leblanc; Stephanie Evers; Thomas E. L. Smith; Catherine M. Yule; Helena Varkkey; Massimo Lupascu; Faizal Parish; et al. (Global Change Biology, 2017)

Securing the Demographic and Genetic Future of Tuatara through Assisted Colonization - KIMBERLY A. MILLER; HILARY C. MILLER; JENNIFER A. MOORE; NICOLA J. MITCHELL; ALISON CREE; FRED W. ALLENDORF; STEPHEN D. SARRE; SUSAN N. KEALL; NICOLA J. NELSON (Conservation Biology, 2012)
Climate change poses a particular threat to species with fragmented distributions and little or no capacity to migrate. Assisted colonization, moving species into regions where they have not previously occurred, aims to establish populations where they are expected to survive as climatic envelopes shift. However, adaptation to the source environment may affect whether species successfully establish in new regions. Assisted colonization has spurred debate among conservation biologists and ecologists over whether the potential benefits to the threatened species outweigh the potential disruption to recipient communities. In our opinion, the debate has been distracted by controversial examples, rather than cases where assisted colonization may be a viable strategy. We present a strategic plan for the assisted migration of tuatara ( Sphenodon punctatus ), an endemic New Zealand reptile. The plan includes use of extant populations as reference points for comparisons with assisted‐colonization populations with respect to demography, phenotypic plasticity, and phenology; optimization of genetic variation; research to fill knowledge gaps; consideration of host and recipient communities; and inclusion of stakeholders in the planning stage. When strategically planned and monitored, assisted colonization could meet conservation and research goals and ultimately result in the establishment of long‐term sustainable populations capable of persisting during rapid changes in climate.

Identification of germline genomic copy number variation in familial pancreatic cancer - Wigdan Al-Sukhni; Sarah Joe; Anath C. Lionel; Nora Zwingerman; George Zogopoulos; Christian R. Marshall; Ayelet Borgida; Spring Holter; Aaron Gropper; Sara Moore; Melissa Bondy; Alison P. Klein; et al. (Human Genetics, 2012)

A Structural Investigation into the Compaction Behavior of Pharmaceutical Composites Using Powder X-ray Diffraction and Total Scattering Analysis - Michael D. Moore; Alison M. Steinbach; Ira S. Buckner; Peter L. D. Wildfong (Pharmaceutical Research, 2009)

Improving Map Accuracy of Soil Variables Using Soil Electrical Conductivity as a Covariate - Alison B. Tarr; Kenneth J. Moore; Donald G. Bullock; Philip M. Dixon; C. Lee Burras (Precision Agriculture, 2005)

Sequence variation in the CHAT locus shows no association with late-onset Alzheimer's disease - Denise Harold; Timothy Peirce; Valentina Moskvina; Simon Lovestone; John Powell; Catherine Foy; Nicola Archer; Sarah Walter; Amanda Edmonson; Stephen McIlroy; David Craig; Peter A. Passmore; et al. (Human Genetics, 2003)