Chemical composition and antifungal activity of essential oils from Amazonian Aniba species can be modulated by irradiance - Aurora Maria Rosa de Oliveira; Josiane Celerino de Carvalho; Elmer Viana Gonçalves; Diego Pereira de Souzas; Nicole Vieira Jorge; Andreia Varmes Fernandes; Alberdan Silva Santos; Paulo Roberto Ribeiro; Marcio Viana Ramos; Michelle Robin; José Francisco de Carvalho Gonçalves (Biochemical Systematics and Ecology, 2026)

Analysis of second-generation epigenetic clocks reveals further associations between disproportionate biological ageing and hippocampal volume - Lidija Milicic; Michael Vacher; Vincent Doré; Pierrick Bourgeat; Rosita Shishegar; James D. Doecke; Paul Maruff; Christopher C. Rowe; Victor L. Villemagne; Michael Weiner; Paul Aisen; Ronald Petersen; et al. (GeroScience, 2026)

Cerebrospinal fluid glucose levels and their association with disability, depression, and cognitive function in multiple sclerosis - Lilith Hauck; Carolin Franz; Kimberly Koerbel; Michelle Maiworm; Valentin Krueger; Robin Zeltner; Antonia Hermanns; Clara Baensch; Hendrik Becker; Dilara Dabanli; Sharmili Edwin Thanarajah; Yavor Yalachkov (Metabolic Brain Disease, 2026)
Glucose dysregulation in the CNS contributes to both inflammation and neurodegeneration in multiple sclerosis (MS). While glucose levels are routinely measured in peripheral blood, these levels do not necessarily reflect glucose levels in the central nervous system. We analysed data of n = 88 treatment-naive, newly-diagnosed MS patients. Primary outcomes included Expanded Disability Status Scale (EDSS), Symbol Digit Modalities Test (SDMT), Fatigue Scale for Motor and Cognitive Functions (FSMC) and Beck Depression Inventory-II (BDI-II) as well as cerebrospinal fluid (CSF) and serum glucose levels obtained at the time of initial diagnosis. Additionally, we analysed CSF lactate concentration. All blood and CSF samples were collected before the patients received any glucocorticoid treatment. Linear regression analysis revealed that after adjusting for age, sex, BMI and CSF/serum albumin quotient, there was a significant association between CSF glucose levels and EDSS (ß=0.260, p = 0.020), SDMT z scores (ß=-0.245, p = 0.033) and BDI (ß=0.279, p = 0.026). There were no associations with serum glucose levels (ß ranging from − 0.067 to 0.170, all p > 0.05). CSF lactate concentration was not significantly associated with the clinical parameters (ß ranging from − 0.048 to 0.184, all p > 0.05). Patients with higher CSF but not serum glucose concentrations exhibited higher physical disability, more cognitive impairment and worse depressive symptoms. Increased CSF glucose in MS might be a compensatory mechanism for CNS damage but also a landmark of mitochondrial dysfunction and trigger of further neuroinflammation and neurodegeneration. More research is necessary to elucidate the role of glucose-related metabolic processes in MS.

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.

Misinterpreting the results: patient misconceptions about genetic cancer risk after obstetrical carrier screening - Alex Raghunandan; Sonali Iyer; Shayan Dioun; Jessica Scholl; Robin B Kalish; Michelle Primiano; Amanda Laterza Ozarowski; Ravi N Sharaf; Melissa K. Frey (Familial Cancer, 2026)

Stakeholder values on the management of African elephants for large tree conservation in protected areas - Robin M. Cook; Ed T. F. Witkowski; Michelle D. Henley (European Journal of Wildlife Research, 2025)
Stakeholder perspectives play a crucial role in conservation decisions, particularly for species with complex ecological and social impacts, such as African savanna elephants ( Loxodonta africana ). In a South African protected area experiencing high elephant densities and significant tree loss, we surveyed 170 stakeholders, including conservation managers, property owners, tourists, and tourism personnel. Using a Likert scale and thematic analysis, we evaluated their attitudes towards tree protection, waterhole closures, contraception, and culling to mitigate elephant impacts on large trees. Results showed strong support for waterhole closures and tree protection, particularly among younger conservation managers and property owners, who viewed these methods as effective in dispersing elephant populations and safeguarding valuable trees. Conversely, tourists and younger stakeholders preferred non-lethal strategies like contraception, while conservation managers expressed practical concerns about its feasibility. Culling emerged as the most divisive strategy, supported primarily by older and male stakeholders in conservation but largely opposed by tourists due to ethical concerns. The chord diagram illustrated distinct patterns, with conservation managers aligning more with waterhole closures and culling, while property owners and tourists favoured tree protection and contraception. These findings highlight the diversity in stakeholder values, shaped by demographic factors, and underscore the need for adaptive, context-specific management strategies. Our study provides a framework for conservation policies that balance ecological objectives with social acceptability, promoting sustainable coexistence between elephants, large trees, and diverse stakeholder interests.

Surface-based morphometry reveals divergent aging trajectories in veterans with and without traumatic brain injury - Michelle C. Eliason; Amrutha Bindu Nagella; Cristian Cuadra; David S. Wack; Ghazala T. Saleem; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowki; Arthur W. Toga; et al. (GeroScience, 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.

Voxel-wise insights into early Alzheimer’s disease pathology progression: the association with APOE and memory decline - Maha Wybitul; Nicolas Langer; Christoph Hock; Anton Gietl; Valerie Treyer; Michael Weiner; Paul Aisen; Ronald-Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowski; Arthur W. Toga; et al. (GeroScience, 2025)
Longitudinal investigation of the Apolipoprotein E (APOE) genotype’s impact on Alzheimer’s disease (AD) biomarker progression, focusing on amyloid beta (Aβ) accumulation and gray matter (GM) atrophy, integrating cognitive decline and baseline levels. Longitudinal florbetapir-PET and T1-weighted MRI data from 100 cognitively normal (CN) and mild cognitive impaired (MCI) participants both with considerable global Aβ accumulation (“high Aβ accumulators”) were analyzed using a voxel-wise approach. Associations of APOE genotype and memory decline with Aβ accumulation and GM atrophy were examined separately for each neuroimaging modality, controlling for baseline Aβ levels and diagnosis. Alternatively, the effect of baseline diagnosis, while controlling for memory decline, was investigated. A multimodal analysis evaluated interactions between genotype, memory decline, and GM atrophy on Aβ accumulation. High Aβ accumulators displayed extensive Aβ pathology predominantly in the medial orbito-frontal cortex, cingulate cortex, and precuneus, along with GM atrophy in temporal, occipital, orbito-frontal, and parietal areas. ɛ4 carriers with memory decline exhibited greater Aβ accumulation and GM atrophy in selective regions compared to non-carriers with memory decline, while no genotype difference was observed in individuals without decline. No interaction effect was observed for MCI diagnosis. Regional associations between the two biomarkers were similarly dependent on genotype and memory decline. ɛ4 carriers exhibiting memory decline present an accelerated neurobiological pattern at predementia stages, supporting early ɛ4 carrier monitoring and interventions in this at-risk group. Importantly, memory decline might be more informative than MCI regarding AD pathology progression emphasizing the importance of repeated cognitive assessments.

Dynamic proportional loss of functional connectivity revealed change of left superior frontal gyrus in subjective cognitive decline: an explanatory study based on Chinese and Western cohorts - Luyao Wang; Wenjing Hu; Fan Dong; Can Sheng; Jinglong Wu; Ying Han; Jiehui Jiang; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2025)

Complementary value of molecular, phenotypic, and functional aging biomarkers in dementia prediction - Andreas Engvig; Karl Trygve Kalleberg; Lars T. Westlye; Esten Høyland Leonardsen; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowski; Arthur W. Toga; Laurel Beckett; et al. (GeroScience, 2024)
DNA methylation age (MA), brain age (BA), and frailty index (FI) are putative aging biomarkers linked to dementia risk. We investigated their relationship and combined potential for prediction of cognitive impairment and future dementia risk using the ADNI database. Of several MA algorithms, DunedinPACE and GrimAge2, associated with memory, were combined in a composite MA alongside BA and a data-driven FI in predictive analyses. Pairwise correlations between age- and sex-adjusted measures for MA (aMA), aBA, and aFI were low. FI outperformed BA and MA in all diagnostic tasks. A model including age, sex, and aFI achieved an area under the curve (AUC) of 0.94 for differentiating cognitively normal controls (CN) from dementia patients in a held-out test set. When combined with clinical biomarkers (apolipoprotein E ε4 allele count, memory, executive function), a model including aBA and aFI predicted 5-year dementia risk among MCI patients with an out-of-sample AUC of 0.88. In the prognostic model, BA and FI offered complementary value (both β s 0.50). The tested MAs did not improve predictions. Results were consistent across FI algorithms, with data-driven health deficit selection yielding the best performance. FI had a stronger adverse effect on prognosis in males, while BA’s impact was greater in females. Our findings highlight the complementary value of BA and FI in dementia prediction. The results support a multidimensional view of dementia, including an intertwined relationship between the biomarkers, sex, and prognosis. The tested MA’s limited contribution suggests caution in their use for individual risk assessment of dementia.

Local molecular and connectomic contributions of tau-related neurodegeneration - Fardin Nabizadeh; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowski; Arthur W. Toga; Laurel Beckett; Robert C. Green; Andrew J. Saykin; John Morris; et al. (GeroScience, 2024)

Stronger together than apart: The role of social support in adopting a healthy plant-based eating pattern - Robin Ortiz; Rachel E. Massar; Michelle McMacken; Stephanie L. Albert (Appetite, 2024)

Sex differences in interacting genetic and functional connectivity biomarkers in Alzheimer’s disease - Jordan N. Williamson; Shirley A. James; Sean P. Mullen; Bradley P. Sutton; Tracey Wszalek; Beni Mulyana; Peter Mukli; Andriy Yabluchanskiy; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2024)

Household Food Insecurity and Maternal-Toddler Fruit and Vegetable Dietary Concordance - Carol Duh-Leong; Robin Ortiz; Mary Jo Messito; Michelle W. Katzow; Christina N. Kim; Radhika Teli; Rachel S. Gross (Journal of Nutrition Education and Behavior, 2024)

Characterisation of typical enteropathogenic Escherichia coli (tEPEC) lineages and novel bfpA variants detected in Australian fruit bats (Pteropus poliocephalus) - Fiona McDougall; David Gordon; Roy Robins-Browne; Vicki Bennett-Wood; Wayne S.J. Boardman; Petra L. Graham; Michelle Power (Science of The Total Environment, 2023)

Improving the rigor and utility of botanical toxicity studies: Recommended resources - Deval Patel; Barbara C. Sorkin; Constance A. Mitchell; Michelle R. Embry; Sharline Rina-Kong; Rebecca E. Adams; Emily R. DeTemple; Aalekhya Reddam; Stefan Gafner; Olaf Kelber; Cynthia V. Rider; Hellen Oketch-Rabah; et al. (Regulatory Toxicology and Pharmacology, 2023)

Survival trends (2008–2020) of three tree species in response to elephant impact, environmental variation, and stem wire-netting protection in an African savanna - Robin M. Cook; Ed T.F. Witkowski; Michelle D. Henley (Forest Ecology and Management, 2023)

Glucose metabolism in posterior cingulate cortex has supplementary value to predict the progression of cognitively unimpaired to dementia due to Alzheimer’s disease: an exploratory study of 18F-FDG-PET - Qi Zhang; Chunqiu Fan; Luyao Wang; Taoran Li; Min Wang; Ying Han; Jiehui Jiang; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2023)

Melissopalynological investigations of seasonal honey samples from the Greater Kruger National Park, Savanna biome of South Africa - Nikiwe Ndlovu; Frank H. Neumann; Michelle D. Henley; Robin M. Cook; Chevonne Reynolds (Palynology, 2023)

Childhood Cancer Information-Seeking: Findings from the National Cancer Institute’s Cancer Information Service - Robin C. Vanderpool; Grace Huang; Ashley Wilson; Rebecca Gordon; Michelle A. Mollica; Candace Deaton Maynard (Journal of Cancer Education, 2023)

Regional variability in peatland burning at mid-to high-latitudes during the Holocene - Thomas G. Sim; Graeme T. Swindles; Paul J. Morris; Andy J. Baird; Angela V. Gallego-Sala; Yuwan Wang; Maarten Blaauw; Philip Camill; Michelle Garneau; Mark Hardiman; Julie Loisel; Minna Vӓliranta; et al. (Quaternary Science Reviews, 2023)

Corrigendum to “Priorities to inform research on marine plastic pollution in Southeast Asia” [Sci. Total Environ. volume 841 (2022) Article 156704] - Lucy C.M. Omeyer; Emily M. Duncan; Kornrawee Aiemsomboon; Nicola Beaumont; Sujaree Bureekul; Bin Cao; Luis R. Carrasco; Suchana Chavanich; James R. Clark; Muhammad R. Cordova; Fay Couceiro; Simon M. Cragg; et al. (Science of The Total Environment, 2023)

Hydra bioassay for the evaluation of chlordecone toxicity at environmental concentrations, alone or in complex mixtures with dechlorinated byproducts: experimental observations and modeling by experimental design - Xavier Moreau; Magalie Claeys-Bruno; Jean-Pascal Andraud; Hervé Macarie; Daniel E. Martínez; Maxime Robin; Michelle Sergent; Laetitia De Jong (Environmental Science and Pollution Research, 2022)

Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment - Jiehui Jiang; Can Sheng; Guanqun Chen; Chunhua Liu; Shichen Jin; Lanlan Li; Xueyan Jiang; Ying Han; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2022)

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume - Lidija Milicic; Michael Vacher; Tenielle Porter; Vincent Doré; Samantha C. Burnham; Pierrick Bourgeat; Rosita Shishegar; James Doecke; Nicola J. Armstrong; Rick Tankard; Paul Maruff; Colin L. Masters; et al. (GeroScience, 2022)
The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes.

TRY plant trait database – enhanced coverage and open access - Jens Kattge; Gerhard Bönisch; Sandra Díaz; Sandra Lavorel; Iain Colin Prentice; Paul Leadley; Susanne Tautenhahn; Gijsbert D. A. Werner; Tuomas Aakala; Mehdi Abedi; Alicia T. R. Acosta; George C. Adamidis; et al. (Global Change Biology, 2020)
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Chronosequence predictions are robust in a Neotropical secondary forest, but plots miss the mark - Justin M. Becknell; Stephen Porder; Steven Hancock; Robin L. Chazdon; Michelle A. Hofton; James B. Blair; James R. Kellner (Global Change Biology, 2018)
Tropical secondary forests (TSF) are a global carbon sink of 1.6 Pg C/year. However, TSF carbon uptake is estimated using chronosequence studies that assume differently aged forests can be used to predict change in aboveground biomass density (AGBD) over time. We tested this assumption using two airborne lidar datasets separated by 11.5 years over a Neotropical landscape. Using data from 1998, we predicted canopy height and AGBD within 1.1 and 10.3% of observations in 2009, with higher accuracy for forest height than AGBD and for older TSFs in comparison to younger ones. This result indicates that the space‐for‐time assumption is robust at the landscape‐scale. However, since lidar measurements of secondary tropical forest are rare, we used the 1998 lidar dataset to test how well plot‐based studies quantify the mean TSF height and biomass in a landscape. We found that the sample area required to produce estimates of height or AGBD close to the landscape mean is larger than the typical area sampled in secondary forest chronosequence studies. For example, estimating AGBD within 10% of the landscape mean requires more than thirty 0.1 ha plots per age class, and more total area for larger plots. We conclude that under‐sampling in ground‐based studies may introduce error into estimations of the TSF carbon sink, and that this error can be reduced by more extensive use of lidar measurements.

Evaluating Tidal Wetland Restoration Performance Using National Estuarine Research Reserve System Reference Sites and the Restoration Performance Index (RPI) - Kenneth B. Raposa; Scott Lerberg; Craig Cornu; John Fear; Nina Garfield; Christopher Peter; Robin L.J. Weber; Gregg Moore; David Burdick; Michelle Dionne (Estuaries and Coasts, 2018)

Recovery rates of bottlenose dolphin ( Tursiops truncatus ) carcasses estimated from stranding and survival rate data - James V. Carretta; Kerri Danil; Susan J. Chivers; David W. Weller; David S. Janiger; Michelle Berman‐Kowalewski; Keith M. Hernandez; James T. Harvey; Robin C. Dunkin; David R. Casper; Shelbi Stoudt; Maureen Flannery; et al. (Marine Mammal Science, 2016)
Recovery of cetacean carcasses provides data on levels of human‐caused mortality, but represents only a minimum count of impacts. Counts of stranded carcasses are negatively biased by factors that include at‐sea scavenging, sinking, drift away from land, stranding in locations where detection is unlikely, and natural removal from beaches due to wave and tidal action prior to detection. We estimate the fraction of carcasses recovered for a population of coastal bottlenose dolphins ( Tursiops truncatus ), using abundance and survival rate data to estimate annual deaths in the population. Observed stranding numbers are compared to expected deaths to estimate the fraction of carcasses recovered. For the California coastal population of bottlenose dolphins, we estimate the fraction of carcasses recovered to be 0.25 (95% CI = 0.20–0.33). During a 12 yr period, 327 animals (95% CI = 253–413) were expected to have died and been available for recovery, but only 83 carcasses attributed to this population were documented. Given the coastal habits of California coastal bottlenose dolphins, it is likely that carcass recovery rates of this population greatly exceed recovery rates of more pelagic dolphin species in the region.

Patient Educational Needs of Patients Undergoing Surgery for Lung Cancer - Judy King; Paul Chamberland; Anissa Rawji; Amanda Ager; Renée Léger; Robin Michaels; Renée Poitras; Deborah Skelton; Michelle Warren (Journal of Cancer Education, 2014)

The fundamental hominin niche in late Pleistocene Central Asia: a preliminary refugium model - Tyler A. Beeton; Michelle M. Glantz; Anna K. Trainer; Sayat S. Temirbekov; Robin M. Reich (Journal of Biogeography, 2014)
Aim We examine hominin presence in Central Asia during the late Pleistocene in order to identify the abiotic characteristics that best predict site distribution during interglacial and glacial periods. Our goal is to build a preliminary framework for climate‐mediated hominin dispersals in this understudied part of the Old World. Location Tajikistan, Uzbekistan. Methods We developed an ecological niche model using presence‐only data to explain the spatial relationship of abiotic variables and hominin locations ( n = 15) during glacial–interglacial transitions. The model was evaluated using the Cramér–von Mises goodness‐of‐fit statistic and empirical K ‐function. Results Hominin locations were spatially aggregated during both glacial and interglacial periods. Of the abiotic variables analysed on a small scale (30‐m resolution), only distance to water differed significantly between glacial and interglacial periods, although most locations were within 5 km of water. At a coarse scale (5‐km resolution), hominin locations appear to have been constrained by low temperatures during glacial periods, but not during interglacials. Main conclusions Hominin groups did not abandon Central Asia during colder periods. This suggests one of three possibly complementary scenarios: (1) late Pleistocene hominin groups had a more flexible behavioural repertoire than previously anticipated and were able to buffer climatic instability culturally; (2) our study area was not as hostile an environment as traditionally considered; and (3) the area examined here represents a refugium during late Pleistocene glaciations.

Eco‐evolutionary dynamics: fluctuations in population growth rate reduce effective population size in chinook salmon - Robin S. Waples; David W. Jensen; Michelle McClure (Ecology, 2010)
We empirically assess the relationship between population growth rate (λ, a parameter central to ecology) and effective population size ( N e , a key parameter in evolutionary biology). Recent theoretical and numerical studies indicate that in semelparous species with variable age at maturity (such as Pacific salmon, many monocarpic plants, and various other species), differences in mean reproductive success among individuals reproducing in different years leads to variation in λ, and this in turn can reduce N e . However, this phenomenon has received little empirical evaluation. We examined time series of abundance data for 56 populations of chinook salmon ( Onchorhynchus tshawytscha ) from the northwestern United States and compared N e (calculated from demographic data) with the total number of spawners each generation ( N T ). Important results include: (1) The mean multigenerational ratio xÑ e / xÑ T was 0.64 (median = 0.67), indicating that annual variation in λ reduces effective population size in chinook salmon by an average of ∼35%. These reductions are independent of, and in addition to, factors that reduce N e within individual cohorts (uneven sex ratio and greater‐than‐random variance in reproductive success). (2) The coefficient of variation of λ was the most important factor associated with reductions in N e , explaining up to two‐thirds of the variance in xÑ e / xÑ T . (3) Within individual generations, N e was lower when there was a negative correlation between annual N i and λ, i.e., when relatively few breeders produced relatively high numbers of offspring. Our results thus highlight an important and little‐studied eco‐evolutionary trade‐off: density‐dependent compensation has generally favorable ecological consequences (promoting stability and long‐term viability) but incurs an evolutionary cost (reducing N e because a few individuals make a disproportionate genetic contribution). (4) For chinook salmon, Nx^ eH (an estimator based on the harmonic mean number of breeders per year) is generally a good proxy for true N e and requires much less data to calculate.

Surveillance and management of upper gastrointestinal disease in Familial Adenomatous Polyposis - Michelle C. Gallagher; Robin K. S. Phillips; Steffen Bulow (Familial Cancer, 2006)

Ultrastructure of the membrane systems in the unicellular cyanobacterium Synechocystis sp. strain PCC 6803 - Michelle Liberton; R. Howard Berg; John Heuser; Robin Roth; Himadri B. Pakrasi (Protoplasma, 2006)

Artesian blister wetlands, a perennial water resource in the semi-arid rift valley of East Africa - Gail M. Ashley; Michelle Goman; Victoria C. Hover; R. Bernhart Owen; Robin W. Renaut; A. Muthama Muasya (Wetlands, 2002)