TropiRoot 1.0: Database of tropical root characteristics across environments - Amanda L. Cordeiro; Daniela F. Cusack; Nathaly Guerrero‐Ramírez; Richard J. Norby; Laura Toro; Michelle Y. Wong; S. Joseph Wright; Kristine Grace M. Cabugao; Kelly M. Andersen; Lucia Fuchslueger; Colleen M. Iversen; Fiona Soper; et al. (Ecology, 2025)
Tropical ecosystems contain the world's largest biodiversity of vascular plants. Yet, our understanding of tropical functional diversity and its contribution to global diversity patterns is constrained by data availability. This discrepancy underscores an urgent need to bridge data gaps by incorporating comprehensive tropical root data into global datasets. Here, we provide a database of tropical root characteristics. This new database, TropiRoot 1.0, will be instrumental in evaluating an array of hypotheses pertaining to root functional ecology and plant biogeography, both within the tropics and relative to other global biomes. The data compilation was conducted by the TropiRoot Initiative, in partnership with the Fine‐Root Ecology Database (FRED) and the Global Root Trait (GRooT) database, Colorado State University (CSU) and the Smithsonian Tropical Research Institute (STRI). Literature search and data extraction were conducted between 2020 and 2024. Literature was identified using Web of Science, Scopus, and complemented using the expert knowledge of members of TropiRoot. To provide broad environmental and geographical distributions, literature searches included root characteristics (traits) across global change drivers, natural gradients, and from different continents. We adopted FRED standardized data columns and streamlined the format to enhance accessibility for data extraction across various user groups. This optimized framework resulted in a smaller, yet comprehensive datasheet. To make the database compatible with other global root trait initiatives, column identification was standardized following the codes provided by FRED. These efforts culminated in data extracted from 104 new sources, resulting in more than 8000 rows of data (either species or community data). Most of the data in TropiRoot 1.0 include root characteristics such as root biomass, morphology, root dynamics, mass fraction, architecture, anatomy, physiology, and root chemistry. This initiative represents a 30% increase in the currently available data for tropical roots in FRED. TropiRoot 1.0 contains root characteristics from 25 different countries, where seven are located in Asia, six in South America, five in Central America and the Caribbean, four in Africa, two in North America, and 1 in Oceania. Due to the volume of data, when ancillary data were available, including soil data, these data were either extracted and included in the database or its availability was recorded in an additional column. Multiple contributors checked the entries for outliers during the collation process to ensure data quality. For text‐based observations, we examined all cells to ensure that their content relates to their specific categories. For numerical observations, we ordered each numerical value from least to greatest and plotted the values, checking apparent outliers against the data in their respective sources and correcting or removing incorrect or impossible values. Some data (soil and aboveground) have different columns for the same variable presented in different units, including originally published units, but root characteristics data had units converted to match those reported in FRED. By filling a gap from global databases, TropiRoot 1.0 expands our knowledge of otherwise so far underrepresented regions and our ability to assess global trends. This advancement can be used to improve tropical forest representation in vegetation models. The data are freely available and should be cited when used.

Tropical root responses to global changes: A synthesis - Daniela Yaffar; Laynara F. Lugli; Michelle Y. Wong; Richard J. Norby; Shalom D. Addo‐Danso; Marie Arnaud; Amanda L. Cordeiro; Lee H. Dietterich; Milton H. Diaz‐Toribio; Ming Y. Lee; Om Prakash Ghimire; Chris M. Smith‐Martin; et al. (Global Change Biology, 2024)
Tropical ecosystems face escalating global change. These shifts can disrupt tropical forests' carbon (C) balance and impact root dynamics. Since roots perform essential functions such as resource acquisition and tissue protection, root responses can inform about the strategies and vulnerabilities of ecosystems facing present and future global changes. However, root trait dynamics are poorly understood, especially in tropical ecosystems. We analyzed existing research on tropical root responses to key global change drivers: warming, drought, flooding, cyclones, nitrogen (N) deposition, elevated (e) CO 2 , and fires. Based on tree species‐ and community‐level literature, we obtained 266 root trait observations from 93 studies across 24 tropical countries. We found differences in the proportion of root responsiveness to global change among different global change drivers but not among root categories. In particular, we observed that tropical root systems responded to warming and eCO 2 by increasing root biomass in species‐scale studies. Drought increased the root: shoot ratio with no change in root biomass, indicating a decline in aboveground biomass. Despite N deposition being the most studied global change driver, it had some of the most variable effects on root characteristics, with few predictable responses. Episodic disturbances such as cyclones, fires, and flooding consistently resulted in a change in root trait expressions, with cyclones and fires increasing root production, potentially due to shifts in plant community and nutrient inputs, while flooding changed plant regulatory metabolisms due to low oxygen conditions. The data available to date clearly show that tropical forest root characteristics and dynamics are responding to global change, although in ways that are not always predictable. This synthesis indicates the need for replicated studies across root characteristics at species and community scales under different global change factors.

The relationship between extreme inter-individual variation in macrophage gene expression and genetic susceptibility to inflammatory bowel disease - Claire L. O’Brien; Kim M. Summers; Natalia M. Martin; Dylan Carter-Cusack; Yuanhao Yang; Rasel Barua; Ojas V. A. Dixit; David A. Hume; Paul Pavli (Human Genetics, 2024)
The differentiation of resident intestinal macrophages from blood monocytes depends upon signals from the macrophage colony-stimulating factor receptor (CSF1R). Analysis of genome-wide association studies (GWAS) indicates that dysregulation of macrophage differentiation and response to microorganisms contributes to susceptibility to chronic inflammatory bowel disease (IBD). Here, we analyzed transcriptomic variation in monocyte-derived macrophages (MDM) from affected and unaffected sib pairs/trios from 22 IBD families and 6 healthy controls. Transcriptional network analysis of the data revealed no overall or inter-sib distinction between affected and unaffected individuals in basal gene expression or the temporal response to lipopolysaccharide (LPS). However, the basal or LPS-inducible expression of individual genes varied independently by as much as 100-fold between subjects. Extreme independent variation in the expression of pairs of HLA-associated transcripts ( HLA-B/C, HLA-A/F and HLA-DRB1/DRB5 ) in macrophages was associated with HLA genotype. Correlation analysis indicated the downstream impacts of variation in the immediate early response to LPS. For example, variation in early expression of IL1B was significantly associated with local SNV genotype and with subsequent peak expression of target genes including IL23A, CXCL1, CXCL3, CXCL8 and NLRP3 . Similarly, variation in early IFNB1 expression was correlated with subsequent expression of IFN target genes. Our results support the view that gene-specific dysregulation in macrophage adaptation to the intestinal milieu is associated with genetic susceptibility to IBD.

Atmospheric microfibrous deposition over the Eastern Red Sea coast - Anastasiia Martynova; Luca Genchi; Sergey P. Laptenok; Michael Cusack; Georgiy L. Stenchikov; Carlo Liberale; Carlos M. Duarte (Science of The Total Environment, 2024)

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)

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.

Response to “Connectivity and pore accessibility in models of soil carbon cycling” - Bonnie G. Waring; Benjamin N. Sulman; Sasha Reed; A. Peyton Smith; Colin Averill; Courtney A. Creamer; Daniela F. Cusack; Steven J. Hall; Julie D. Jastrow; Andrea Jilling; Kenneth M. Kemner; Markus Kleber; et al. (Global Change Biology, 2021)
Here we respond to Baveye and colleagues' recent critique of our PROMISE model, describing how this new framework significantly advances our understanding of soil spatial heterogeneity and its influence on organic matter transformations.

Response to ‘Stochastic and deterministic interpretation of pool models’ - Bonnie G. Waring; Benjamin N. Sulman; Sasha Reed; A. Peyton Smith; Colin Averill; Courtney A. Creamer; Daniela F. Cusack; Steven J. Hall; Julie D. Jastrow; Andrea Jilling; Kenneth M. Kemner; Markus Kleber; et al. (Global Change Biology, 2021)

From pools to flow: The PROMISE framework for new insights on soil carbon cycling in a changing world - Bonnie G. Waring; Benjamin N. Sulman; Sasha Reed; A. Peyton Smith; Colin Averill; Courtney A. Creamer; Daniela F. Cusack; Steven J. Hall; Julie D. Jastrow; Andrea Jilling; Kenneth M. Kemner; Markus Kleber; et al. (Global Change Biology, 2020)
Soils represent the largest terrestrial reservoir of organic carbon, and the balance between soil organic carbon (SOC) formation and loss will drive powerful carbon‐climate feedbacks over the coming century. To date, efforts to predict SOC dynamics have rested on pool‐based models, which assume classes of SOC with internally homogenous physicochemical properties. However, emerging evidence suggests that soil carbon turnover is not dominantly controlled by the chemistry of carbon inputs, but rather by restrictions on microbial access to organic matter in the spatially heterogeneous soil environment. The dynamic processes that control the physicochemical protection of carbon translate poorly to pool‐based SOC models; as a result, we are challenged to mechanistically predict how environmental change will impact movement of carbon between soils and the atmosphere. Here, we propose a novel conceptual framework to explore controls on belowground carbon cycling: P robabilistic R epresentation of O rganic M atter I nteractions within the S oil E nvironment (PROMISE). In contrast to traditional model frameworks, PROMISE does not attempt to define carbon pools united by common thermodynamic or functional attributes. Rather, the PROMISE concept considers how SOC cycling rates are governed by the stochastic processes that influence the proximity between microbial decomposers and organic matter, with emphasis on their physical location in the soil matrix. We illustrate the applications of this framework with a new biogeochemical simulation model that traces the fate of individual carbon atoms as they interact with their environment, undergoing biochemical transformations and moving through the soil pore space. We also discuss how the PROMISE framework reshapes dialogue around issues related to SOC management in a changing world. We intend the PROMISE framework to spur the development of new hypotheses, analytical tools, and model structures across disciplines that will illuminate mechanistic controls on the flow of carbon between plant, soil, and atmospheric pools.

The Global Ocean Ship-Based Hydrographic Investigations Program (GO-SHIP): A Platform for Integrated Multidisciplinary Ocean Science - Bernadette M. Sloyan; Rik Wanninkhof; Martin Kramp; Gregory C. Johnson; Lynne D. Talley; Toste Tanhua; Elaine McDonagh; Caroline Cusack; Eleanor O’Rourke; Evin McGovern; Katsuro Katsumata; Steve Diggs; et al. (Frontiers in Marine Science, 2019)

Scaling Up From Regional Case Studies to a Global Harmful Algal Bloom Observing System - Clarissa R. Anderson; Elisa Berdalet; Raphael M. Kudela; Caroline K. Cusack; Joe Silke; Eleanor O’Rourke; Darcy Dugan; Molly McCammon; Jan A. Newton; Stephanie K. Moore; Kelli Paige; Steve Ruberg; et al. (Frontiers in Marine Science, 2019)

The ICES Working Group on Oceanic Hydrography: A Bridge From In-situ Sampling to the Remote Autonomous Observation Era - César González-Pola; Paula Fratantoni; Karin M. H. Larsen; N. Penny Holliday; Stephen Dye; Kjell Arne Mork; Agnieszka Beszczynska-Möller; Hedinn Valdimarsson; Alexander Trofimov; Hjalte Parner; Holger Klein; Boris Cisewski; et al. (Frontiers in Marine Science, 2019)

Anniston community health survey: Follow-up and dioxin analyses (ACHS-II)—methods - Linda S. Birnbaum; N. D. Dutton; C. Cusack; S. T. Mennemeyer; M. Pavuk (Environmental Science and Pollution Research, 2016)

Electron backscatter diffraction (EBSD) as a tool for detection of coral diagenesis - M. Cusack; J. England; P. Dalbeck; A. W. Tudhope; A. E. Fallick; N. Allison (Coral Reefs, 2008)