Testing water banking recovery policies to secure drought water supply in semi-arid areas with a changing climate - Peter Dillon; Bridget R. Scanlon; Rebecca Bernat; Dennis Gonzalez; Constantin Seidl; Declan Page; Rebecca Doble; John Radcliffe; Adam Hutchinson; Sharon B. Megdal (Groundwater for Sustainable Development, 2026)

Comparative life cycle assessment of a modular cross-laminated timber residential building designed for disassembly and reuse versus traditional wood frame construction - Kieren H. McCord; Heather E. Dillon; Annie Hu; Sadie Carlson; Adam R. Phillips; Yun Joon Jung; Patricia Gunderson; Brittany Tarufelli; Chrissi A. Antonopoulos (Journal of Cleaner Production, 2025)

Chemical recycling of polyethylene terephthalate, an industrial and sustainable opportunity for Northwest of England - William Thomas Lang; Sulaiman Adam Mehta; Mischelle Mary Thomas; Dillon Openshaw; Ewan Westgate; Giuseppe Bagnato (Journal of Environmental Chemical Engineering, 2023)

A survey of coastal conditions around the continental US using a high-resolution ocean reanalysis - Michael A. Alexander; James D. Scott; Michael G. Jacox; Clara Deser; Dillon J. Amaya; Antonietta Capotondi; Adam S. Phillips (Progress in Oceanography, 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)

The search for loci under selection: trends, biases and progress - Collin W. Ahrens; Paul D. Rymer; Adam Stow; Jason Bragg; Shannon Dillon; Kate D. L. Umbers; Rachael Y. Dudaniec (Molecular Ecology, 2018)
Detecting genetic variants under selection using F ST outlier analysis (OA) and environmental association analyses (EAAs) are popular approaches that provide insight into the genetic basis of local adaptation. Despite the frequent use of OA and EAA approaches and their increasing attractiveness for detecting signatures of selection, their application to field‐based empirical data have not been synthesized. Here, we review 66 empirical studies that use Single Nucleotide Polymorphisms (SNPs) in OA and EAA. We report trends and biases across biological systems, sequencing methods, approaches, parameters, environmental variables and their influence on detecting signatures of selection. We found striking variability in both the use and reporting of environmental data and statistical parameters. For example, linkage disequilibrium among SNPs and numbers of unique SNP associations identified with EAA were rarely reported. The proportion of putatively adaptive SNPs detected varied widely among studies, and decreased with the number of SNPs analysed. We found that genomic sampling effort had a greater impact than biological sampling effort on the proportion of identified SNPs under selection. OA identified a higher proportion of outliers when more individuals were sampled, but this was not the case for EAA. To facilitate repeatability, interpretation and synthesis of studies detecting selection, we recommend that future studies consistently report geographical coordinates, environmental data, model parameters, linkage disequilibrium, and measures of genetic structure. Identifying standards for how OA and EAA studies are designed and reported will aid future transparency and comparability of SNP‐based selection studies and help to progress landscape and evolutionary genomics.

Hierarchical land cover and vegetation classification using multispectral data acquired from an unmanned aerial vehicle - Oumer S. Ahmed; Adam Shemrock; Dominique Chabot; Chris Dillon; Griffin Williams; Rachel Wasson; Steven E. Franklin (International Journal of Remote Sensing, 2017)

Adaptive divergence despite strong genetic drift: genomic analysis of the evolutionary mechanisms causing genetic differentiation in the island fox ( Urocyon littoralis ) - W. Chris Funk; Robert E. Lovich; Paul A. Hohenlohe; Courtney A. Hofman; Scott A. Morrison; T. Scott Sillett; Cameron K. Ghalambor; Jesus E. Maldonado; Torben C. Rick; Mitch D. Day; Nicholas R. Polato; Sarah W. Fitzpatrick; et al. (Molecular Ecology, 2016)
The evolutionary mechanisms generating the tremendous biodiversity of islands have long fascinated evolutionary biologists. Genetic drift and divergent selection are predicted to be strong on islands and both could drive population divergence and speciation. Alternatively, strong genetic drift may preclude adaptation. We conducted a genomic analysis to test the roles of genetic drift and divergent selection in causing genetic differentiation among populations of the island fox ( Urocyon littoralis ). This species consists of six subspecies, each of which occupies a different California Channel Island. Analysis of 5293 SNP loci generated using Restriction‐site Associated DNA ( RAD ) sequencing found support for genetic drift as the dominant evolutionary mechanism driving population divergence among island fox populations. In particular, populations had exceptionally low genetic variation, small N e (range = 2.1–89.7; median = 19.4), and significant genetic signatures of bottlenecks. Moreover, islands with the lowest genetic variation (and, by inference, the strongest historical genetic drift) were most genetically differentiated from mainland grey foxes, and vice versa, indicating genetic drift drives genome‐wide divergence. Nonetheless, outlier tests identified 3.6–6.6% of loci as high F ST outliers, suggesting that despite strong genetic drift, divergent selection contributes to population divergence. Patterns of similarity among populations based on high F ST outliers mirrored patterns based on morphology, providing additional evidence that outliers reflect adaptive divergence. Extremely low genetic variation and small N e in some island fox populations, particularly on San Nicolas Island, suggest that they may be vulnerable to fixation of deleterious alleles, decreased fitness and reduced adaptive potential.