Persistent field soil legacies of cover crops influence maize quality and resistance to herbivory - Sujay M. Paranjape; Kayleigh C. Hauri; Nathaniel McCartney; Elizabeth Wagner; Annett Richter; Brosi Bradley; Jason Kaye; Georg Jander; Jared G. Ali (Agriculture, Ecosystems & Environment, 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)

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.

Legacy effects of cover crops on weed biomass and yield of the subsequent corn crop - Barbara Baraibar; Brosi A. Bradley; Mitchell C. Hunter; Charles M. White; Denise M. Finney; Jason P. Kaye; Megan E. Schipanski; David A. Mortensen (European Journal of Agronomy, 2026)

Systems-Level Phosphoproteomic and RPPA Profiling Reveals Stress and DNA Damage Signalling as Early Drivers of Polymyxin B Neurotoxicity - Maytham Hussein; Thuraya Safaa Ansaf; Terry C. C. Lim Kam Sian; Mark Baker; Pouya Faridi; Zhi Ying Kho; Nivedhitha Selvakumar; Keith S. Kaye; Gauri G. Rao; Jian Li; Tony Velkov (Molecular Neurobiology, 2026)
Polymyxins remain indispensable last-line antibiotics for multidrug-resistant Gram-negative infections, yet their clinical use in central nervous system (CNS) infections is constrained by poorly understood neurotoxicity. Here, we define the early molecular signalling events underlying polymyxin B-induced CNS toxicity using an integrated phosphoproteomic and Reverse Phase Protein Array (RPPA) approach in rat brain following intracerebroventricular administration. Global phosphoproteomics revealed extensive phosphosite coverage but identified a highly selective set of significantly regulated phosphosites, implicating calcium-dependent signalling, transcriptional stress regulation, synaptic signalling, and cytoskeletal control, while parallel total proteomics showed minimal changes in protein abundance. RPPA profiling independently confirmed coordinated modulation of stress, apoptotic and survival-associated signalling pathways, including p53, CREB, SQSTM1, Bcl-2, and NFκB related nodes. Network and functional enrichment analyses converged on DNA damage signalling, apoptotic regulation and growth factor-mediated pathways as central features of the polymyxin B early neurotoxicity response, while phosphor to total protein analyses demonstrated suppression of proliferative and pro-survival signalling. Together, these data establish phosphorylation-driven signalling reprogramming as a primary early mechanism of polymyxin B-induced neurotoxicity, providing a mechanistic framework that links membrane-active antibiotic exposure to neuronal stress signalling and identifies candidate pathways for toxicity biomarkers and neuroprotective strategies.

Drivers of extinction risks and shortfalls across terrestrial vertebrates in the Philippine global biodiversity hotspot - Krizler C. Tanalgo; Kier C. Dela Cruz; Angelo R. Agduma; Asraf K. Lidasan; Janine Edradan; Ryza Kyla L. Dumayas; Jeanrose S. Alagdon; Berfelyn Daniela Villaruz; Glydel Kaye P. Gatoc (Science of The Total Environment, 2025)

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)

Socioeconomic disparities: a more important risk factor for advanced-stage oral cancer in Florida than smoking? - Garrett Forman; Uche C. Ezeh; Isabella Buitron; Sophia Peifer; Liana Shtern; Tonya Aaron; Abdurrahman Al-Awady; Isildinha M. Reis; Erin R. Kaye; Elizabeth Nicolli; David Arnold; Francisco Civantos; et al. (Cancer Causes & Control, 2025)
Purpose To explore the associations between sociodemographic factors with advanced-stage oral cavity cancer (OCC) presentation among Floridians. Methods Demographic and cancer data on OCC patients ( n = 7,826) diagnosed between 2010 and 2017 were retrieved from the Florida Cancer Data System (FCDS). Census tract median income and percentage of population with a bachelor’s degree or higher were used to infer income and education. Pearson’s chi-square tests of independence were used to compare sociodemographic factors between racial/ethnic groups and staging groups. Multinomial logistic regression analyzed predictors of advanced disease. Incidence and percent late-stage diagnosis versus income were mapped using ArcGIS Pro. Results Among 5,252 cases analyzed: 5.7% were Black, 82.4% White Non-Hispanic, 61.5% male, 63.3% publicly insured, 6.5% uninsured, 58.7% current or former smokers, and 73.0% urban residents. Black patients were more likely to present with advanced disease, be single/unmarried, uninsured, and less likely to be former smokers. Male sex, Black race, non-married status, no insurance, Medicaid, VA/military insurance, and lower educational status were associated with increased risk of regional vs. early disease in multivariable analysis (MVA) ( p < 0.05). These factors, in addition to Medicare, were associated with distant disease in MVA. Geospatial mapping revealed higher rates of regional and distant disease presentation in the Tampa Bay and Orlando areas. Conclusion Black race, male sex, non-married status, lower education, Medicaid, VA/Military insurance and no insurance were associated with advanced OCC in Florida. Smoking status was not associated with advanced disease presentation after adjusting for sociodemographic variables.

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.

Biochar mitigates methane emissions from organic mulching in urban soils: Evidence from a long-term mesocosm experiment - Imrul Kayes; Md Abdul Halim; Sean C. Thomas (Journal of Environmental Management, 2025)

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)

Water quality impacts of recycling nutrients using organic fertilizers in circular agricultural scenarios - W. Lisenbee; A. Saha; P. Mohammadpour; R. Cibin; J. Kaye; C. Grady; I. Chaubey (Agricultural Systems, 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)

Non-avian dinosaur eggshell calcite can contain ancient, endogenous amino acids - Evan T. Saitta; Jakob Vinther; Molly K. Crisp; Geoffrey D. Abbott; Lucy Wheeler; Samantha Presslee; Thomas G. Kaye; Ian Bull; Ian Fletcher; Xinqi Chen; Daniel Vidal; Fernando Sanguino; et al. (Geochimica et Cosmochimica Acta, 2024)

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)

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.

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)

From Surface Water to the Deep Sea: A Review on Factors Affecting the Biodegradation of Spilled Oil in Marine Environment - Hernando Pactao Bacosa; Sheila Mae B. Ancla; Cris Gel Loui A. Arcadio; John Russel A. Dalogdog; Dioniela Mae C. Ellos; Heather Dale A. Hayag; Jiza Gay P. Jarabe; Ahl Jimhar T. Karim; Carl Kenneth P. Navarro; Mae Princess I. Palma; Rodolfo A. Romarate; Kaye M. Similatan; et al. (Journal of Marine Science and Engineering, 2022)
Over the past century, the demand for petroleum products has increased rapidly, leading to higher oil extraction, processing and transportation, which result in numerous oil spills in coastal-marine environments. As the spilled oil can negatively affect the coastal-marine ecosystems, its transport and fates captured a significant interest of the scientific community and regulatory agencies. Typically, the environment has natural mechanisms (e.g., photooxidation, biodegradation, evaporation) to weather/degrade and remove the spilled oil from the environment. Among various oil weathering mechanisms, biodegradation by naturally occurring bacterial populations removes a majority of spilled oil, thus the focus on bioremediation has increased significantly. Helping in the marginal recognition of this promising technique for oil-spill degradation, this paper reviews recently published articles that will help broaden the understanding of the factors affecting biodegradation of spilled oil in coastal-marine environments. The goal of this review is to examine the effects of various environmental variables that contribute to oil degradation in the coastal-marine environments, as well as the factors that influence these processes. Physico-chemical parameters such as temperature, oxygen level, pressure, shoreline energy, salinity, and pH are taken into account. In general, increase in temperature, exposure to sunlight (photooxidation), dissolved oxygen (DO), nutrients (nitrogen, phosphorous and potassium), shoreline energy (physical advection—waves) and diverse hydrocarbon-degrading microorganisms consortium were found to increase spilled oil degradation in marine environments. In contrast, higher initial oil concentration and seawater pressure can lower oil degradation rates. There is limited information on the influences of seawater pH and salinity on oil degradation, thus warranting additional research. This comprehensive review can be used as a guide for bioremediation modeling and mitigating future oil spill pollution in the marine environment by utilizing the bacteria adapted to certain conditions.

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.

COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data - Ben Bond‐Lamberty; Danielle S. Christianson; Avni Malhotra; Stephanie C. Pennington; Debjani Sihi; Amir AghaKouchak; Hassan Anjileli; M. Altaf Arain; Juan J. Armesto; Samaneh Ashraf; Mioko Ataka; Dennis Baldocchi; et al. (Global Change Biology, 2020)
Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO 2 flux, commonly though imprecisely termed soil respiration ( R S ), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency R S measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured R S , the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.

Estrogenic Effects in Feral Male Common Carp (Cyprinus carpio) from Laguna de Bay, Philippines - Michelle Grace V. Paraso; Justinne Kaye C. Morales; Angelo A. Clavecillas; Ma. Suzanneth Epifania G. Lola (Bulletin of Environmental Contamination and Toxicology, 2017)

A multi-lake study of seasonal variation in lake surface evaporation using MODIS satellite-derived surface temperature - R. C. Phillips; J. R. Saylor; N. B. Kaye; J. M. Gibert (Limnology, 2016)

Stand-replacing wildfires increase nitrification for decades in southwestern ponderosa pine forests - Valerie J. Kurth; Stephen C. Hart; Christopher S. Ross; Jason P. Kaye; Peter Z. Fulé (Oecologia, 2014)

Microclimate and ecological threshold responses in a warming and wetting experiment following whole tree harvest - M. D. McDaniel; R. J. Wagner; C. R. Rollinson; B. A. Kimball; M. W. Kaye; J. P. Kaye (Theoretical and Applied Climatology, 2014)

Ecosystem Carbon Remains Low for Three Decades Following Fire and Constrains Soil CO2 Responses to Precipitation in Southwestern Ponderosa Pine Forests - Christopher S. Ross; Jason P. Kaye; Margot W. Kaye; Valerie J. Kurth; Rachel Brimmer; Stephen C. Hart; Peter Z. Fulé (Ecosystems, 2012)

Short-term soil inorganic N pulse after experimental fire alters invasive and native annual plant production in a Mojave Desert shrubland - Todd C. Esque; Jason P. Kaye; Sara E. Eckert; Lesley A. DeFalco; C. Richard Tracy (Oecologia, 2010)

Evidence for indirect effects of plant diversity and composition on net nitrification - Daniel C. Laughlin; Stephen C. Hart; Jason P. Kaye; Margaret M. Moore (Plant and Soil, 2010)

Long‐term impact of a stand‐replacing fire on ecosystem CO 2 exchange of a ponderosa pine forest - S. DORE; T. E. KOLB; M. MONTES‐HELU; B. W. SULLIVAN; W. D. WINSLOW; S. C. HART; J. P. KAYE; G. W. KOCH; B. A. HUNGATE (Global Change Biology, 2008)
Ponderosa pine ( Pinus ponderosa ) forests of the southwestern United States are a mosaic of stands where undisturbed forests are carbon sinks, and stands recovering from wildfires may be sources of carbon to the atmosphere for decades after the fire. However, the relative magnitude of these sinks and sources has never been directly measured in this region, limiting our understanding of the role of fire in regional and US carbon budgets. We used the eddy covariance technique to measure the CO 2 exchange of two forest sites, one burned by fire in 1996, and an unburned forest. The fire was a high‐intensity stand‐replacing burn that killed all trees. Ten years after the fire, the burned site was still a source of CO 2 to the atmosphere [109±6 (SEM) g C m −2 yr −1 ], whereas the unburned site was a sink (−164±23 g C m −2 yr −1 ). The fire reduced total carbon storage and shifted ecosystem carbon allocation from the forest floor and living biomass to necromass. Annual ecosystem respiration was lower at the burned site (480±5 g C m −2 yr −1 ) than at the unburned site (710±54 g C m −2 yr −1 ), but the difference in gross primary production was even larger (372±13 g C m −2 yr −1 at the burned site and 858±37 g C m −2 yr −1 at the unburned site). Water availability controlled carbon flux in the warm season at both sites, and the burned site was a source of carbon in all months, even during the summer, when wet and warm conditions favored respiration more than photosynthesis. Our study shows that carbon losses following stand‐replacing fires in ponderosa pine forests can persist for decades due to slow recovery of the gross primary production. Because fire exclusion is becoming increasingly difficult in dry western forests, a large US forest carbon sink could shift to a decadal‐scale carbon source.

Serotonin transporter binding after recovery from eating disorders - Ursula F. Bailer; Guido K. Frank; Shannan E. Henry; Julie C. Price; Carolyn C. Meltzer; Carl Becker; Scott K. Ziolko; Chester A. Mathis; Angela Wagner; Nicole C. Barbarich-Marsteller; Karen Putnam; Walter H. Kaye (Psychopharmacology, 2007)

Poster abstracts - J. Ferrie; M. Shipley; F. Cappuccio; E. Brunner; M. Miller; M. Kumari; M. Marmot; A. Coenen; J. L. Castillo; F. Araya; G. Bustamante; L. Montecino; et al. (Sleep and Biological Rhythms, 2007)

Carbon fluxes, nitrogen cycling, and soil microbial communities in adjacent urban, native and agricultural ecosystems - J. P. Kaye; R. L. McCulley; I. C. Burke (Global Change Biology, 2005)
Urban ecosystems are expanding globally, and assessing the ecological consequences of urbanization is critical to understanding the biology of local and global change related to land use. We measured carbon (C) fluxes, nitrogen (N) cycling, and soil microbial community structure in a replicated ( n =3) field experiment comparing urban lawns to corn, wheat–fallow, and unmanaged shortgrass steppe ecosystems in northern Colorado. The urban and corn sites were irrigated and fertilized. Wheat and shortgrass steppe sites were not fertilized or irrigated. Aboveground net primary productivity (ANPP) in urban ecosystems (383±11 C m −2 yr −1 ) was four to five times greater than wheat or shortgrass steppe but significantly less than corn (537±44 C m −2 yr −1 ). Soil respiration (2777±273 g C m −2 yr −1 ) and total belowground C allocation (2602±269 g C m −2 yr −1 ) in urban ecosystems were both 2.5 to five times greater than any other land‐use type. We estimate that for a large (1578 km 2 ) portion of Larimer County, Colorado, urban lawns occupying 6.4% of the land area account for up to 30% of regional ANPP and 24% of regional soil respiration from land‐use types that we sampled. The rate of N cycling from urban lawn mower clippings to the soil surface was comparable with the rate of N export in harvested corn (both ∼12–15 g N m −2 yr −1 ). A one‐time measurement of microbial community structure via phospholipid fatty acid analysis suggested that land‐use type had a large impact on microbial biomass and a small impact on the relative abundance of broad taxonomic groups of microorganisms. Our data are consistent with several other studies suggesting that urbanization of arid and semiarid ecosystems leads to enhanced C cycling rates that alter regional C budgets.

Targeted mapping of a sugarcane rust resistance gene (Bru1) using bulked segregant analysis and AFLP markers - C. Asnaghi; D. Roques; S. Ruffel; C. Kaye; J.-Y. Hoarau; H. Télismart; J. C. Girard; L. M. Raboin; A. M. Risterucci; L. Grivet; A. D’Hont (Theoretical and Applied Genetics, 2004)

Application of synteny across Poaceae to determine the map location of a sugarcane rust resistance gene - C. Asnaghi; F. Paulet; C. Kaye; L. Grivet; M. Deu; J. C. Glaszmann; A. D’Hont (Theoretical and Applied Genetics, 2000)

The effects of increasing CO 2 and temperature on oak leaf palatability and the implications for herbivorous insects - S. J. Dury; J. E. G. Good; C. M. Perrins; A. Buse; T. Kaye (Global Change Biology, 1998)
Rising levels of atmospheric CO 2 are expected to perturb forest ecosystems, although the extent to which specific ecological interactions will be modified is unclear. This research evaluates the effects of elevated CO 2 and temperature, alone and in combination, on the leaf nutritional quality of Pendunculate oak ( Quercus robur L. ), and the implications for herbiverous insect defoliators are discussed. A 3 °C temperature rise reduced leaf nutritional quality, by reducing foliar nitrogen concentration and increasing condensed tannin content. Doubling atmospheric CO 2 temporarily increased total phenolics, but also reduced leaf toughness. The nutritional quality of the second leaf flush (lammas growth) was considerably reduced at elevated CO 2 . It is concluded that larval development of spring‐feeding defoliators and hence adult fecundity may be adversely affected by increased temperatures.

Genotype by environment effects and selection for drought tolerance in tropical maize. II. Three-mode pattern analysis - Scott C. Chapman; José Crossa; Kaye E. Basford; Pieter M. Kroonenberg (Euphytica, 1997)