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)

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.

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)

Insect Larvae Meal as a Complementary Functional Ingredient in High Soybean Meal‐Based Diets Improve the Health of Rainbow Trout ( Oncorhynchus mykiss ) - Jie Ma; Krishna Pada Singha; Mosope F. Abanikannda; Veronica Myrsell; Nicholas Romano; Elizabeth Koutsos; Daniel Adams; Kenneth D. Cain; Vikas Kumar (Journal of Fish Diseases, 2025)
This study explores the integration of black soldier fly larvae (BSFL) as a complementary functional ingredient to increase the soybean meal (SBM) inclusion in rainbow trout ( Oncorhynchus mykiss ) diets. Six experimental diets were formulated including a control diet as fishmeal (FM), an SBM‐based diet, and 2.5% and 5% whole‐body (WB) or defatted (DB) BSFL‐supplemented SBM‐based diets. Results revealed that BSFL inclusion positively influences gut health, immune response and survival rates following challenge with Flavobacterium psychrophilum . Dietary lauric acid content significantly impacted whole‐body lauric acid levels in a dose‐dependent manner, with BSFL diets showing higher levels than FM and SBM diets. Fish fed diets with BSFL exhibited enhanced survivability against F. psychrophilum infection compared to SBM‐fed fish, with the highest survival rates observed in the WB5 (5% whole‐body BSFL) group. Histological analysis demonstrated improved intestinal morphology in BSFL‐fed fish, particularly evident in the absence of pathogenic enteritis. Gene expression analysis revealed upregulated proinflammatory markers (IL‐8, TNF‐α, C5) in BSFL‐fed fish post‐challenge, indicating an enhanced immune response. These findings indicate the potential of BSFL as a functional feed ingredient to complement high SBM inclusion in rainbow trout with improved health and performance. By strategically reducing inclusion levels and repositioning BSFL as a functional feed ingredient instead of fishmeal replacer in aquafeed formulations, one can mitigate economic concerns while maximising the benefits of this sustainable alternative.

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)

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)

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.

Initial Mild Traumatic Brain Injury Characteristics and Recovery Patterns Among Females Across the United States Military Service Academies: A Report from the NCAA-DoD CARE Consortium - Landon B. Lempke; Elsa Ermer; Adrian J. Boltz; Jaclyn Caccese; Thomas A. Buckley; Kenneth L. Cameron; Sara P. D. Chrisman; Christopher D’Lauro; James T. Eckner; Carrie Esopenko; Tamerah N. Hunt; Divya Jain; et al. (Annals of Biomedical Engineering, 2024)

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)

Reimagining the language of engagement in a post-stakeholder world - Mark S. Reed; Bethann Garramon Merkle; Elizabeth J. Cook; Caitlin Hafferty; Adam P. Hejnowicz; Richard Holliman; Ian D. Marder; Ursula Pool; Christopher M. Raymond; Kenneth E. Wallen; David Whyte; Marta Ballesteros; et al. (Sustainability Science, 2024)
Language matters in shaping perceptions and guiding behaviour. The term stakeholder is widely used, yet little attention is paid to the possibility that its use may inadvertently perpetuate colonial narratives and reinforce systemic inequities. In this article, we critically examine the limitations of the stakeholder concept and its ambiguity, normativity, and exclusionary implications. We emphasise the importance of using language that gives a voice to marginalised groups, promotes inclusion and equity, and fosters meaningful and reflexive participation in decision-making processes. In critiquing the use of the term and calling for alternative practices, we aim to contribute to the decolonisation of research norms and the creation of more inclusive and equitable societies. Therefore, rather than advocating a single alternative term, we suggest a focus on the people, places, and species affected by decisions, interventions, projects, and issues.

Reproducible responses of geochemical and microbial successional patterns in the subsurface to carbon source amendment - Jonathan P. Michael; Andrew D. Putt; Yunfeng Yang; Benjamin G. Adams; Kathryn R. McBride; Yupeng Fan; Kenneth A. Lowe; Daliang Ning; Sindhu Jagadamma; Ji Won Moon; Dawn M. Klingeman; Ping Zhang; et al. (Water Research, 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)

Ambient air pollution and rate of spontaneous abortion - Amelia K. Wesselink; Kipruto Kirwa; Perry Hystad; Joel D. Kaufman; Adam A. Szpiro; Mary D. Willis; David A. Savitz; Jonathan I. Levy; Kenneth J. Rothman; Ellen M. Mikkelsen; Anne Sofie Dam Laursen; Elizabeth E. Hatch; et al. (Environmental Research, 2024)

Uncovering the magnitude of African pangolin poaching with extensive nanopore DNA genotyping of seized scales - Darren Yeo; Amy H. J. Chan; Kum Chew Hiong; Jasmine Ong; Jun Yuan Ng; Jie Min Lim; Wendy Zhang; Sara R. Lim; Charlene J. Fernandez; Anna M‐S. Wong; Benjamin P. Y‐H. Lee; Max D. Y. Khoo; et al. (Conservation Biology, 2024)
Trade in pangolins is illegal, and yet tons of their scales and products are seized at various ports. These large seizures are challenging to process and comprehensively genotype for upstream provenance tracing and species identification for prosecution. We implemented a scalable DNA barcoding pipeline in which rapid DNA extraction and MinION sequencing were used to genotype a substantial proportion of pangolin scales subsampled from 2 record shipments seized in Singapore in 2019 (37.5 t). We used reference sequences to match the scales to phylogeographical regions of origin. In total, we identified 2346 cytochrome b ( cytb ) barcodes of white‐bellied ( Phataginus tricuspis ) (from 1091 scales), black‐bellied ( Phataginus tetradactyla ) (227 scales), and giant ( Smutsia gigantea ) (1028 scales) pangolins. Haplotype diversity was higher for P. tricuspis scales (121 haplotypes, 66 novel) than that for P. tetradactyla (22 haplotypes, 15 novel) and S. gigantea (25 haplotypes, 21 novel) scales. Of the novel haplotypes, 74.2% were likely from western and west‐central Africa, suggesting potential resurgence of poaching and newly exploited populations in these regions. Our results illustrate the utility of extensively subsampling large seizures and outline an efficient molecular approach for rapid genetic screening that should be accessible to most forensic laboratories and enforcement agencies.

Quantifying the impact of climate smart agricultural practices on soil carbon storage relative to conventional management - Adam P. Schreiner-McGraw; Curtis J. Ransom; Kristen S. Veum; Jeffrey D. Wood; Kenneth A. Sudduth; Lori J. Abendroth (Agricultural and Forest Meteorology, 2024)

Wind, waves, sediment transport, and potential for shoreline development on Earth and on Mars - Kenneth D. Adams (Icarus, 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)

Geographic and taxonomic variation in adaptive capacity among mountain-dwelling small mammals: Implications for conservation status and actions - Erik A. Beever; Jennifer L. Wilkening; Peter D. Billman; Lindsey L. Thurman; Kristina A. Ernest; David H. Wright; Alisha M. Gill; April C. Craighead; Nolan A. Helmstetter; Leona K. Svancara; Meghan J. Camp; Sabuj Bhattacharyya; et al. (Biological Conservation, 2023)

Agriculture accentuates interannual variability in water fluxes but not carbon fluxes, relative to native prairie, in the U.S. Corn Belt - Adam P. Schreiner-McGraw; Jeffrey D. Wood; Megan E. Metz; E. John Sadler; Kenneth A. Sudduth (Agricultural and Forest Meteorology, 2023)

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.

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.

The San Diego Nathan Shock Center: tackling the heterogeneity of aging - Gerald S. Shadel; Peter D. Adams; W. Travis Berggren; Jolene K. Diedrich; Kenneth E. Diffenderfer; Fred H. Gage; Nasun Hah; Malene Hansen; Martin W. Hetzer; Anthony J. A. Molina; Uri Manor; Kurt Marek; et al. (GeroScience, 2021)

A global analysis of complexity–biodiversity relationships on marine artificial structures - Elisabeth M. A. Strain; Peter D. Steinberg; Maria Vozzo; Emma L. Johnston; Marco Abbiati; Moises A. Aguilera; Laura Airoldi; J. David Aguirre; Gail Ashton; Maritina Bernardi; Paul Brooks; Benny K. K. Chan; et al. (Global Ecology and Biogeography, 2021)
Aim Topographic complexity is widely accepted as a key driver of biodiversity, but at the patch‐scale, complexity–biodiversity relationships may vary spatially and temporally according to the environmental stressors complexity mitigates, and the species richness and identity of potential colonists. Using a manipulative experiment, we assessed spatial variation in patch‐scale effects of complexity on intertidal biodiversity. Location 27 sites within 14 estuaries/bays distributed globally. Time period 2015–2017. Major taxa studied Functional groups of algae, sessile and mobile invertebrates. Methods Concrete tiles of differing complexity (flat; 2.5‐cm or 5‐cm complex) were affixed at low–high intertidal elevation on coastal defence structures, and the richness and abundance of the colonizing taxa were quantified after 12 months. Results The patch‐scale effects of complexity varied spatially and among functional groups. Complexity had neutral to positive effects on total, invertebrate and algal taxa richness, and invertebrate abundances. However, effects on the abundance of algae ranged from positive to negative, depending on location and functional group. The tidal elevation at which tiles were placed accounted for some variation. The total and invertebrate richness were greater at low or mid than at high intertidal elevations. Latitude was also an important source of spatial variation, with the effects of complexity on total richness and mobile mollusc abundance greatest at lower latitudes, whilst the cover of sessile invertebrates and sessile molluscs responded most strongly to complexity at higher latitudes. Conclusions After 12 months, patch‐scale relationships between biodiversity and habitat complexity were not universally positive. Instead, the relationship varied among functional groups and according to local abiotic and biotic conditions. This result challenges the assumption that effects of complexity on biodiversity are universally positive. The variable effect of complexity has ramifications for community and applied ecology, including eco‐engineering and restoration that seek to bolster biodiversity through the addition of complexity.

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.

Survival costs of reproduction are mediated by parasite infection in wild Soay sheep - Jessica A. Leivesley; Luc F. Bussière; Josephine M. Pemberton; Jill G. Pilkington; Kenneth Wilson; Adam D. Hayward (Ecology Letters, 2019)
A trade‐off between current and future fitness potentially explains variation in life‐history strategies. A proposed mechanism behind this is parasite‐mediated reproductive costs: individuals that allocate more resources to reproduction have fewer to allocate to defence against parasites, reducing future fitness. We examined how reproduction influenced faecal egg counts ( FEC ) of strongyle nematodes using data collected between 1989 and 2008 from a wild population of Soay sheep in the St. Kilda archipelago, Scotland (741 individuals). Increased reproduction was associated with increased FEC during the lambing season: females that gave birth, and particularly those that weaned a lamb, had higher FEC than females that failed to reproduce. Structural equation modelling revealed future reproductive costs: a positive effect of reproduction on spring FEC and a negative effect on summer body weight were negatively associated with overwinter survival. Overall, we provide evidence that parasite resistance and body weight are important mediators of survival costs of reproduction.

Monitoring programs of the U.S. Gulf of Mexico: inventory, development and use of a large monitoring database to map fish and invertebrate spatial distributions - Arnaud Grüss; Holly A. Perryman; Elizabeth A. Babcock; Skyler R. Sagarese; James T. Thorson; Cameron H. Ainsworth; Evan John Anderson; Kenneth Brennan; Matthew D. Campbell; Mary C. Christman; Scott Cross; Michael D. Drexler; et al. (Reviews in Fish Biology and Fisheries, 2018)

Late Pleistocene climate inferences from a water balance model of Jakes Valley, Nevada (USA) - Cornelia Barth; Douglas P. Boyle; Benjamin J. Hatchett; Scott D. Bassett; Christopher B. Garner; Kenneth D. Adams (Journal of Paleolimnology, 2016)

Optimising the settlement and hatchery culture of Saccharina latissima (Phaeophyta) by manipulation of growth medium and substrate surface condition - Philip D. Kerrison; Michele S. Stanley; Maeve Kelly; Adrian MacLeod; Kenneth D. Black; Adam D. Hughes (Journal of Applied Phycology, 2016)

The 2011–2016 Transdisciplinary Research on Energetics and Cancer (TREC) Initiative: Rationale and Design - Ruth E. Patterson; Graham A. Colditz; Frank B. Hu; Kathryn H. Schmitz; Rexford S. Ahima; Ross C. Brownson; Kenneth R. Carson; Jorge E. Chavarro; Lewis A. Chodosh; Sarah Gehlert; Jeff Gill; Karen Glanz; et al. (Cancer Causes & Control, 2013)

Haplotype structure in Ashkenazi Jewish BRCA1 and BRCA2 mutation carriers - Kate M. Im; Tomas Kirchhoff; Xianshu Wang; Todd Green; Clement Y. Chow; Joseph Vijai; Joshua Korn; Mia M. Gaudet; Zachary Fredericksen; V. Shane Pankratz; Candace Guiducci; Andrew Crenshaw; et al. (Human Genetics, 2011)

Application of Biochemical and Physiological Indicators for Assessing Recovery of Fish Populations in a Disturbed Stream - S. Marshall Adams; Kenneth D. Ham (Environmental Management, 2011)

New insights into the role of angiotensin-converting enzyme obtained from the analysis of genetically modified mice - Xiao Z. Shen; Hong D. Xiao; Ping Li; Chentao X. Lin; Sandrine Billet; Derick Okwan-Duodu; Jon W. Adams; Ellen A. Bernstein; Yi Xu; Sebastien Fuchs; Kenneth E. Bernstein (Journal of Molecular Medicine, 2008)

Discovery of Substituted Human Urocortin 1 Analogs with Improved CRF2 Receptor Selectivity and Increased Efficacy in Preventing Skeletal Muscle Atrophy - Robert J. Isfort; Feng Wang; Michelle Tscheiner; Elizabeth Dolan; Mary Beth Bauer; Frank Lefever; Deborah Reichart; Richard T. Hinkle; Kenneth R. Wehmeyer; Raymond A. Reilman; Bradly D. Keck; Adam W. Mazur (International Journal of Peptide Research and Therapeutics, 2007)

The dual functions of sea urchin gonads are reflected in the temporal variations of their biochemistry - Adam D. Hughes; Maeve S. Kelly; David K. A. Barnes; Ana I. Catarino; Kenneth D. Black (Marine Biology, 2006)

A 500-kb region on chromosome 16p13.1 contains the pseudoxanthoma elasticum locus: high-resolution mapping and genomic structure - Li Cai; Berthold Struk; Mark D. Adams; Wan Ji; Thomas Haaf; Hyung-Lyun Kang; So Hee Dho; Xuequn Xu; Franziska Ringpfeil; Julie Nancarrow; Stéphanie Zäch; Lori Schaen; et al. (Journal of Molecular Medicine, 2000)