Challenges and Opportunities for Strengthening Bottom‐Tow Fisheries Sustainability - Suresh A. Sethi; Robert D. Murphy; Matthew R. Baker; Anita C. Kroska; Haraldur A. Einarsson; Owen S. Hamel; Shelton J. Harley; Pingguo He; James Ianelli; Stan Kotwicki; Robert A. McConnaughey; Chris McGonigle; et al. (Fish and Fisheries, 2026)
Bottom‐tow gear fisheries (trawls and dredges) produce ~24 million mt of harvest annually, representing a globally important animal‐sourced food system. While many are currently sustainably managed, growing concern over the potential for ecosystem impacts from bottom‐tow gears has increased pressure to improve these fisheries. We assembled an international working group of > 30 contributors, including fishing industry participants, managers, non‐governmental ocean conservation organization representatives, and scientists to synthesize obstacles to bottom‐tow fisheries sustainability and to develop expert‐based recommendations to operationalize sustainability advancements moving forward. We identified 30 key gaps impeding bottom‐towed fisheries sustainability spanning 6 core challenge areas including: seafloor disturbance, bycatch and discards, management design and implementation, fishing operations, cross‐sector conflicts, and public perception and communication. We generated 28 priority recommendations to address bottom‐tow fisheries sustainability obstacles with themes including: addressing data gaps, advancing mechanistic understanding and modelling tools, strengthening management processes, and improving knowledge sharing and communication. Cross‐disciplinary and diverse system experience among fisheries and marine ecosystem stakeholders will be critical for operationalizing bottom‐tow fisheries sustainability advancements. As the global human population approaches 10 bn in the next 30 years, ensuring sustainable wild capture fisheries is an imperative for feeding the world. Outputs from this synthesis serve as a resource for fishing and marine ecosystem stakeholders to identify key challenge areas and associated entry points for solutions‐oriented efforts to improve the sustainability of bottom‐tow fisheries.

Evaluating surface fluxes in WRF using eddy-covariance flux measurements in the Western and Eastern U.S. - Fan Wu; Kenneth J. Davis; Li Zhang; Ray G. Anderson; Jason P. Horne; Sarah Goslee; William Munger; Chenxia Cai; Yu Yan Cui; Zhan Zhao; Min Zhong (Agricultural and Forest Meteorology, 2026)

Multi-colored traps can enhance monitoring programs for native and non-native longhorn beetles in forest ecosystems - Laura Besana; Giacomo Santoiemma; Antonio Biondi; Everett G. Booth; Giacomo Cavaletto; Valerio Caruso; Sarah M. Devine; Joseph A. Francese; Emily Franzen; Antonio Gugliuzzo; Jerzy M. Gutowski; Robert Johns; et al. (Forest Ecology and Management, 2026)

Clinical Efficacy of Stem Cell Therapy in Neurotraumatic and Neurodegenerative Conditions: A Comparative Review - Jun Beom Ku; Ray J. Pak; Sarah S. Ku; Robert D. Holland; Han-Soo Kim (Tissue Engineering and Regenerative Medicine, 2025)

Prognostic immunotherapy score (PIS) in patients with advanced urothelial carcinoma treated with pembrolizumab: real-world data and validation from ARON-2 dataset - Alessandro Rizzo; Anas Zayed; Elsa Vitale; Sebastiano Buti; Hideki Takeshita; Simon Crabb; Giandomenico Roviello; Emmanuel Seront; Jose Carlos Tapia; Sarah Scagliarini; Lazar Popovic; Ray Manneh Kopp; et al. (Clinical & Experimental Metastasis, 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)

Understanding Motivators and Challenges to Enrollment in Maternal and Child Health and Nutrition Research: A Mixed Methods Study with Women of Child-Bearing Age and Clinical Practitioners - Alexandra MacMillan Uribe; Rebecca Seguin Fowler; Kelly Fisher; Erica Bender; Galen Eldridge; Margaret Demment; Regan Bailey; A. Catharine Ross; Diane Mitchell; Sarah Ray; Julie Gras-Najjar; Alexandra Early (Journal of Nutrition Education and Behavior, 2025)

Efficacy of unbaited and baited green multi-funnel traps for detection of Agrilus species and other wood-boring beetle taxa - Giacomo Santoiemma; Jon Sweeney; Everett G. Booth; Giacomo Cavaletto; Gianfranco Curletti; Sarah M. Devine; Joseph A. Francese; Emily K. L. Franzen; Filippo Giannone; Mischa Giasson; Jerzy M. Gutowski; Cory Hughes; et al. (Journal of Pest Science, 2025)
Semiochemical-baited traps are a key component of post-border surveillance for detection of non-native and potentially invasive bark and wood-boring beetles (Buprestidae, Cerambycidae, Curculionidae: Scolytinae) at risk of introduction in untreated woody materials used in global trade. Because the particular species that may arrive with imported goods is unknown, plant protection agencies need trapping protocols that effectively survey all three taxa. Baiting traps with host volatiles and aggregation/sex pheromones of longhorn beetles increases efficacy of detecting Cerambycidae and Scolytinae, but its effect on detection of Agrilus species and other jewel beetles is unknown. In this multi-country trapping study we found that the addition of ethanol and common aggregation/sex pheromones of longhorn beetles to green multi-funnel traps placed in the mid-upper forest canopy had negative effects on abundance of Agrilus species and other jewel beetles collected but no effect on their species richness, and significant positive effects on species richness and abundance of Cerambycidae and Scolytinae. Baiting green canopy traps with longhorn beetle pheromones increased the efficacy of traps for detecting total target taxa of bark and wood-boring beetles at risk of international movement in untreated woody materials. This information is beneficial for the design of multi-taxa surveys, potentially saving money and resources without decreasing trapping efficacy.

Life history strategies determine response to SRT driven crash in anammox bioreactors - Christian A. White; Edmund H. Antell; Sarah L. Schwartz; Jennifer E. Lawrence; Ray Keren; Lijie Zhou; Ke Yu; Wei-Qin Zhuang; Lisa Alvarez-Cohen (Water Research, 2025)

Trends in Arctic-nesting loon (Gavia spp.) populations in North America - Ingrid L. Pollet; Sarah E. Gutowsky; Ray T. Alisauskas; William Harvey; Dana K. Kellett; Kristen M. Lalla; Josée Lefebvre; Jake Russell-Mercier; Jennifer F. Provencher; Emily D. Silverman; Paul A. Smith; Mark L. Mallory (Polar Biology, 2024)

Efficacy of trapping protocols for Agrilus jewel beetles: a multi-country assessment - Giacomo Santoiemma; David Williams; Everett G. Booth; Giacomo Cavaletto; James Connell; Gianfranco Curletti; Maarten de Groot; Sarah M. Devine; Abigail Enston; Joseph A. Francese; Emily K. L. Franzen; Mischa Giasson; et al. (Journal of Pest Science, 2024)
The genus Agrilus is one of the most diverse insect genera worldwide. The larval feeding activity causes extensive damage in both forests and orchards. In addition, more than 30 species have been introduced outside their native range so far, including the emerald ash borer Agrilus planipennis Fairmaire. Thus, the availability of efficient trapping protocols for early detection of Agrilus species at entry points is of utmost importance. In this study we tested whether trapping protocols developed for surveillance of A. planipennis in North America were also effective for other Agrilus species. In particular, through a multi-country assessment we compared the efficacy of detecting Agrilus species on: (i) green glue-coated prism traps vs. green Fluon-coated multi-funnel traps when baited with the green leaf volatile ( Z )-3-hexenol or left unbaited; and (ii) green multi-panel traps vs. green multi-panel traps baited with dead adult Agrilus beetles (decoys). A total of 23,481 individuals from 45 Agrilus species were caught. Trap design significantly affected both species richness and abundance of Agrilus species in several of the countries where the trapping experiments were carried out, and green prism traps outperformed green multi-funnel traps in most cases. On the contrary, the addition of a ( Z )-3-hexenol lure or dead adult beetle decoys on to traps did not improve trap catches. Our study highlights that reliable trap models to survey Agrilus species are already available, but also that there is the clear need to further investigate chemical ecology of Agrilus species to develop semiochemical lures that can improve detection efficacy.

Investigating impacts of the mycothiazole chemotype as a chemical probe for the study of mitochondrial function and aging - Naibedya Dutta; Joe A. Gerke; Sofia F. Odron; Joseph D. Morris; Adam Hruby; Juri Kim; Toni Castro Torres; Sarah J. Shemtov; Jacqueline G. Clarke; Michelle C. Chang; Hooriya Shaghasi; Marissa N. Ray; et al. (GeroScience, 2024)
Small molecule inhibitors of the mitochondrial electron transport chain (ETC) hold significant promise to provide valuable insights to the field of mitochondrial research and aging biology. In this study, we investigated two molecules: mycothiazole (MTZ) - from the marine sponge C. mycofijiensis and its more stable semisynthetic analog 8- O -acetylmycothiazole (8-OAc) as potent and selective chemical probes based on their high efficiency to inhibit ETC complex I function. Similar to rotenone (Rote), MTZ, a newly employed ETC complex I inhibitor, exhibited higher cytotoxicity against cancer cell lines compared to certain non-cancer cell lines. Interestingly, 8-OAc demonstrated greater selectivity for cancer cells when compared to both MTZ and Rote, which has promising potential for anticancer therapeutic development. Furthermore, in vivo experiments with these small molecules utilizing a C. elegans model demonstrate their unexplored potential to investigate aging studies. We observed that both molecules have the ability to induce a mitochondria-specific unfolded protein response (UPR MT ) pathway, that extends lifespan of worms when applied in their adult stage. We also found that these two molecules employ different pathways to extend lifespan in worms. Whereas MTZ utilizes the transcription factors ATFS-1 and HSF1, which are involved in the UPR MT and heat shock response (HSR) pathways respectively, 8-OAc only required HSF1 and not ATFS-1 to mediate its effects. This observation underscores the value of applying stable, potent, and selective next generation chemical probes to elucidate an important insight into the functional roles of various protein subunits of ETC complexes and their regulatory mechanisms associated with aging. Graphical Abstract

Ginsenosides enhance P2X7-dependent cytokine secretion from LPS-primed rodent macrophages - Kshitija Dhuna; Ray Helliwell; Simone N. De Luca; Sarah J. Spencer; Leanne Stokes (Purinergic Signalling, 2024)
The activation of P2X7 is a well-known stimulus for the NLRP3-caspase 1 inflammasome and subsequent rapid IL-1β secretion from monocytes and macrophages. Here we show that positive allosteric modulators of P2X7, ginsenosides, can enhance the release of three important cytokines, IL-1β, IL-6 and TNF-α from LPS-primed rodent macrophages using the J774 mouse macrophage cell line and primary rat peritoneal macrophages. We compared the immediate P2X7 responses in un-primed and LPS-primed macrophages and found no difference in calcium response amplitude or kinetics. These results suggest that under inflammatory conditions positive allosteric modulators are capable of increasing cytokine secretion at lower concentrations of ATP, thus boosting the initial pro-inflammatory signal. This may be important in the control of intracellular infections.

Fentanyl Exposure and Detection Strategies Utilized by Clinical Trial Participants Seeking Linkage to Opioid Use Disorder Treatment at a Syringe Service Program - Dennis P. Watson; Bradley Ray; Peter Phalen; Sarah E. Duhart Clarke; Lisa Taylor; James Swartz; Nicole Gastala (Journal of Medical Toxicology, 2024)
Introduction The USA continues to face a fentanyl-driven overdose epidemic. Prior research has demonstrated users of illicit opioids are concerned about fentanyl exposure and overdose, but the strategies they report using to detect fentanyl’s presence lack empirical support. This study compares self-report and biologically detected fentanyl use and investigates overdose risk and risk reduction behaviors among a sample of high-risk people who use opioids. Methods Structured enrollment interviews conducted as part of a larger clinical trial assessed self-reported fentanyl exposure as well as strategies used to determine believed fentanyl exposure and prevent overdose among 240 participants enrolled at a Chicago, IL syringe service program. Urinalysis measured actual fentanyl exposure. Results Most participants identified as African American (66.7%) and had considerable overdose experience (76.7% lifetime and 48% in the past year). Most also tested positive for fentanyl (93.75%) despite reporting no past year use of fentanyl or fentanyl-adulterated drugs (64.17%). The most utilized approaches reported for identifying fentanyl exposure were stronger effects of the drug (60.7%), sight or taste (46.9%), and being told by someone using the same drugs (34.2%). Few participants (14%) reported using fentanyl test strips. No significant associations were identified between self-report and urinalysis measures or urinalysis results and risk reduction strategies. Conclusion This study adds to prior fentanyl exposure risk research. The disconnect between participants’ fentanyl detection methods and reported overdose experiences supports the need for more research to identify and understand factors driving access and use of overdose prevention resources and strategies.

The Ontology of Biological Attributes (OBA)—computational traits for the life sciences - Ray Stefancsik; James P. Balhoff; Meghan A. Balk; Robyn L. Ball; Susan M. Bello; Anita R. Caron; Elissa J. Chesler; Vinicius de Souza; Sarah Gehrke; Melissa Haendel; Laura W. Harris; Nomi L. Harris; et al. (Mammalian Genome, 2023)
Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.

Combining Community Wastewater Genomic Surveillance with State Clinical Surveillance: A Framework for SARS-CoV-2 Public Health Practice - Ted Smith; Rochelle H. Holm; Ray Yeager; Joseph B. Moore; Eric C. Rouchka; Kevin J. Sokoloski; Erin M. Elliott; Daymond Talley; Vaneet Arora; Sarah Moyer; Aruni Bhatnagar (Food and Environmental Virology, 2022)
This study aimed to develop a framework for combining community wastewater surveillance with state clinical surveillance for the confirmation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants within the community and to provide recommendations on how to expand on such research and apply the findings in public health responses. Wastewater samples were collected weekly from 17 geographically resolved locations in Louisville/Jefferson County, Kentucky (USA), from February 10 to December 13, 2021. Genomic surveillance and quantitative reverse transcription PCR (RT-qPCR) platforms were used to screen for SARS-CoV-2 in wastewater, and state clinical surveillance was used for confirmation. The study results highlighted an increased epidemiological value of combining community wastewater genomic surveillance and RT-qPCR with conventional case-auditing methods. The spatial scale and temporal frequency of wastewater sampling provided promising sensitivity and specificity for gaining public health screening insights about SARS-CoV-2 emergence, seeding, and spread in communities. Improved national surveillance systems are needed against future pathogens and variants, and wastewater-based genomic surveillance exhibits great potential when coupled with clinical testing. This paper presents evidence that complementary wastewater and clinical testing are cost-effectively enhanced when used in combination, as they provide a strong tool for a joint public health framework. Future pathogens of interest may be examined in either a targeted fashion or using a more global approach where all pathogens are monitored. This study has also provided novel insights developed from evidence-based public health practices.

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.

A Review of the Opportunities and Challenges for Using Remote Sensing for Management of Surface-Canopy Forming Kelps - Kyle C. Cavanaugh; Tom Bell; Maycira Costa; Norah E. Eddy; Lianna Gendall; Mary G. Gleason; Margot Hessing-Lewis; Rebecca Martone; Meredith McPherson; Ondine Pontier; Luba Reshitnyk; Rodrigo Beas-Luna; et al. (Frontiers in Marine Science, 2021)
Surface-canopy forming kelps provide the foundation for ecosystems that are ecologically, culturally, and economically important. However, these kelp forests are naturally dynamic systems that are also threatened by a range of global and local pressures. As a result, there is a need for tools that enable managers to reliably track changes in their distribution, abundance, and health in a timely manner. Remote sensing data availability has increased dramatically in recent years and this data represents a valuable tool for monitoring surface-canopy forming kelps. However, the choice of remote sensing data and analytic approach must be properly matched to management objectives and tailored to the physical and biological characteristics of the region of interest. This review identifies remote sensing datasets and analyses best suited to address different management needs and environmental settings using case studies from the west coast of North America. We highlight the importance of integrating different datasets and approaches to facilitate comparisons across regions and promote coordination of management strategies.

The Path to an Ecosystem Approach for Forage Fish Management: A Case Study of Atlantic Menhaden - Kristen A. Anstead; Katie Drew; David Chagaris; Amy M. Schueller; Jason E. McNamee; Andre Buchheister; Geneviève Nesslage; Jim H. Uphoff Jr.; Michael J. Wilberg; Alexei Sharov; Micah J. Dean; Jeffrey Brust; et al. (Frontiers in Marine Science, 2021)
Atlantic menhaden ( Brevoortia tyrannus ) support the largest fishery by volume on the United States East Coast, while also playing an important role as a forage species. Managers’ and stakeholders’ increasing concerns about the impact of Atlantic menhaden harvest on ecosystem processes led to an evolution in the assessment and management of this species from a purely single-species approach to an ecosystem approach. The first coastwide stock assessment of Atlantic menhaden for management used a single-species virtual population analysis (VPA). Subsequent assessments used a forward projecting statistical catch-at-age framework that incorporated estimates of predation mortality from a multispecies VPA while analytical efforts continued toward the development of ecosystem models and explicit ecological reference points (ERPs) for Atlantic menhaden. As an interim step while ecosystem models were being developed, a series of ad hoc measures to preserve Atlantic menhaden biomass for predators were used by managers. In August 2020, the Atlantic States Marine Fisheries Commission formally adopted an ecological modeling framework as a tool to set reference points and harvest limits for the Atlantic menhaden that considers their role as a forage fish. This is the first example of a quantitative ecosystem approach to setting reference points on the United States Atlantic Coast and it represents a significant advance for forage fish management. This case study reviews the history of Atlantic menhaden stock assessments and management, outlines the progress on the current implementation of ERPs for this species, and highlights future research and management needs to improve and expand ecosystem-based fisheries management.

Investigating the Mechanical Behavior of Clot Analogues Through Experimental and Computational Analysis - Sarah Johnson; Ray McCarthy; Michael Gilvarry; Peter E. McHugh; J. Patrick McGarry (Annals of Biomedical Engineering, 2021)

Trawl fishing impacts on the status of seabed fauna in diverse regions of the globe - Tessa Mazor; C. Roland Pitcher; Wayne Rochester; Michel J. Kaiser; Jan G. Hiddink; Simon Jennings; Ricardo Amoroso; Robert A. McConnaughey; Adriaan D. Rijnsdorp; Ana M. Parma; Petri Suuronen; Jeremy Collie; et al. (Fish and Fisheries, 2021)
Bottom trawl fishing is a controversial activity. It yields about a quarter of the world's wild seafood, but also has impacts on the marine environment. Recent advances have quantified and improved understanding of large‐scale impacts of trawling on the seabed. However, such information needs to be coupled with distributions of benthic invertebrates (benthos) to assess whether these populations are being sustained under current trawling regimes. This study collated data from 13 diverse regions of the globe spanning four continents. Within each region, we combined trawl intensity distributions and predicted abundance distributions of benthos groups with impact and recovery parameters for taxonomic classes in a risk assessment model to estimate benthos status. The exposure of 220 predicted benthos‐group distributions to trawling intensity (as swept area ratio) ranged between 0% and 210% (mean = 37%) of abundance. However, benthos status, an indicator of the depleted abundance under chronic trawling pressure as a proportion of untrawled state, ranged between 0.86 and 1 (mean = 0.99), with 78% of benthos groups > 0.95. Mean benthos status was lowest in regions of Europe and Africa, and for taxonomic classes Bivalvia and Gastropoda. Our results demonstrate that while spatial overlap studies can help infer general patterns of potential risk, actual risks cannot be evaluated without using an assessment model that incorporates trawl impact and recovery metrics. These quantitative outputs are essential for sustainability assessments, and together with reference points and thresholds, can help managers ensure use of the marine environment is sustainable under the ecosystem approach to management.

Not withering on the evolutionary vine: systematic revision of the Brown Vine Snake (Reptilia: Squamata: Oxybelis) from its northern distribution - Robert C. Jadin; Christopher Blair; Sarah A. Orlofske; Michael J. Jowers; Gilson A. Rivas; Laurie J. Vitt; Julie M. Ray; Eric N. Smith; John C. Murphy (Organisms Diversity & Evolution, 2020)

Correction to: Documenting lemming population change in the Arctic: Can we detect trends? - Dorothée Ehrich; Niels M. Schmidt; Gilles Gauthier; Ray Alisauskas; Anders Angerbjörn; Karin Clark; Frauke Ecke; Nina E. Eide; Erik Framstad; Jay Frandsen; Alastair Franke; Olivier Gilg; et al. (Ambio, 2020)

Documenting lemming population change in the Arctic: Can we detect trends? - Dorothée Ehrich; Niels M. Schmidt; Gilles Gauthier; Ray Alisauskas; Anders Angerbjörn; Karin Clark; Frauke Ecke; Nina E. Eide; Erik Framstad; Jay Frandsen; Alastair Franke; Olivier Gilg; et al. (Ambio, 2020)

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.

Prolonged exposure to manure from livestock‐administered antibiotics decreases ecosystem carbon‐use efficiency and alters nitrogen cycling - Carl Wepking; Brian Badgley; John E. Barrett; Katharine F. Knowlton; Jane M. Lucas; Kevan J. Minick; Partha P. Ray; Sarah E. Shawver; Michael S. Strickland (Ecology Letters, 2019)
Microbial communities drive soil ecosystem function but are also susceptible to environmental disturbances. We investigated whether exposure to manure sourced from cattle either administered or not administered antibiotics affected microbially mediated terrestrial ecosystem function. We quantified changes in microbial community composition via amplicon sequencing, and terrestrial elemental cycling via a stable isotope pulse‐chase. Exposure to manure from antibiotic‐treated cattle caused: (i) changes in microbial community structure; and (ii) alterations in elemental cycling throughout the terrestrial system. This exposure caused changes in fungal : bacterial ratios, as well as changes in bacterial community structure. Additionally, exposure to manure from cattle treated with pirlimycin resulted in an approximate two‐fold increase in ecosystem respiration of recently fixed‐carbon, and a greater proportion of recently added nitrogen in plant and soil pools compared to the control manure. Manure from antibiotic‐treated cattle therefore affects terrestrial ecosystem function via the soil microbiome, causing decreased ecosystem carbon use efficiency, and altered nitrogen cycling.

Dynamic N ‐occupancy models: estimating demographic rates and local abundance from detection‐nondetection data - Sam Rossman; Charles B. Yackulic; Sarah P. Saunders; Janice Reid; Ray Davis; Elise F. Zipkin (Ecology, 2016)
Occupancy modeling is a widely used analytical technique for assessing species distributions and range dynamics. However, occupancy analyses frequently ignore variation in abundance of occupied sites, even though site abundances affect many of the parameters being estimated (e.g., extinction, colonization, detection probability). We introduce a new model (“dynamic N ‐occupancy”) capable of providing accurate estimates of local abundance, population gains (reproduction/immigration), and apparent survival probabilities while accounting for imperfect detection using only detection/nondetection data. Our model utilizes heterogeneity in detection based on variations in site abundances to estimate latent demographic rates via a dynamic N ‐mixture modeling framework. We validate our model using simulations across a wide range of values and examine the data requirements, including the number of years and survey sites needed, for unbiased and precise estimation of parameters. We apply our model to estimate spatiotemporal heterogeneity in abundances of barred owls ( Strix varia ) within a recently invaded region in Oregon (USA). Estimates of apparent survival and population gains are consistent with those from a nearby radio‐tracking study and elucidate how barred owl abundances have increased dramatically over time. The dynamic N ‐occupancy model greatly improves inferences on individual‐level population processes from occupancy data by explicitly modeling the latent population structure.

Wave climate projections for Ireland for the end of the 21st century including analysis of EC ‐Earth winds over the North Atlantic Ocean - Sarah Gallagher; Emily Gleeson; Roxana Tiron; Ray McGrath; Frédéric Dias (International Journal of Climatology, 2016)
This study aims to quantify the potential impact of global climate change on Ireland's marine resource, which is of significant economic and social importance. Global climate models predict warming of the Earth's atmosphere and oceans, which will consequently affect mean sea levels, the frequency and severity of extreme weather events, winds and ocean waves. Such changes need to be carefully assessed for long‐term marine and coastal planning. We derived future wave climate projections for Ireland using the EC ‐Earth global climate model and the WAVEWATCH III wave model, by comparing the future 30‐year period 2070–2099 to 1980–2009 for the RCP4 .5 and the RCP8 .5 forcing scenarios. This data set is currently the highest resolution wave projection data set available for Ireland. EC ‐Earth predicts decreases in means (up to 3%) and extremes (up to 14% for the 95th percentile) of 10 m wind speeds over the North Atlantic Ocean (5–75°N, 0–80°W) by the end of the century. Similarly, the model projections show decreases in the frequency and intensity of wind storms crossing Ireland but these changes are not statistically significant. The WAVEWATCH III model predicts an overall decrease in mean (up to 15%) and extreme (up to 15% for the 95th percentile) annual, boreal winter and summer significant wave heights around Ireland.

Genome-wide association of familial prostate cancer cases identifies evidence for a rare segregating haplotype at 8q24.21 - Craig C. Teerlink; Daniel Leongamornlert; Tokhir Dadaev; Alun Thomas; James Farnham; Robert A. Stephenson; Shaun Riska; Shannon K. McDonnell; Daniel J. Schaid; William J. Catalona; S. Lilly Zheng; Kathleen A. Cooney; et al. (Human Genetics, 2016)

Association analysis of 9,560 prostate cancer cases from the International Consortium of Prostate Cancer Genetics confirms the role of reported prostate cancer associated SNPs for familial disease - Craig C. Teerlink; Stephen N. Thibodeau; Shannon K. McDonnell; Daniel J. Schaid; Antje Rinckleb; Christiane Maier; Walther Vogel; Geraldine Cancel-Tassin; Christophe Egrot; Olivier Cussenot; William D. Foulkes; Graham G. Giles; et al. (Human Genetics, 2014)

Effect of Age and Exercise on the Viscoelastic Properties of Rat Tail Tendon - Andrew S. LaCroix; Sarah E. Duenwald-Kuehl; Stacey Brickson; Tiffany L. Akins; Gary Diffee; Judd Aiken; Ray Vanderby; Roderic S. Lakes (Annals of Biomedical Engineering, 2013)

Asynchronous food‐web pathways could buffer the response of Serengeti predators to El Niño Southern Oscillation - A. R. E. Sinclair; Kristine L. Metzger; John M. Fryxell; Craig Packer; Andrea E. Byrom; Meggan E. Craft; Katie Hampson; Tiziana Lembo; Sarah M. Durant; Guy J. Forrester; John Bukombe; John Mchetto; et al. (Ecology, 2013)
Understanding how entire ecosystems maintain stability in the face of climatic and human disturbance is one of the most fundamental challenges in ecology. Theory suggests that a crucial factor determining the degree of ecosystem stability is simply the degree of synchrony with which different species in ecological food webs respond to environmental stochasticity. Ecosystems in which all food‐web pathways are affected similarly by external disturbance should amplify variability in top carnivore abundance over time due to population interactions, whereas ecosystems in which a large fraction of pathways are nonresponsive or even inversely responsive to external disturbance will have more constant levels of abundance at upper trophic levels. To test the mechanism underlying this hypothesis, we used over half a century of demographic data for multiple species in the Serengeti (Tanzania) ecosystem to measure the degree of synchrony to variation imposed by an external environmental driver, the El Niño Southern Oscillation (ENSO). ENSO effects were mediated largely via changes in dry‐season vs. wet‐season rainfall and consequent changes in vegetation availability, propagating via bottom‐up effects to higher levels of the Serengeti food web to influence herbivores, predators and parasites. Some species in the Serengeti food web responded to the influence of ENSO in opposite ways, whereas other species were insensitive to variation in ENSO. Although far from conclusive, our results suggest that a diffuse mixture of herbivore responses could help buffer top carnivores, such as Serengeti lions, from variability in climate. Future global climate changes that favor some pathways over others, however, could alter the effectiveness of such processes in the future.

Temporal Healing in Rat Achilles Tendon: Ultrasound Correlations - Connie S. Chamberlain; Sarah E. Duenwald-Kuehl; Gregory Okotie; Sabrina H. Brounts; Geoffrey S. Baer; Ray Vanderby (Annals of Biomedical Engineering, 2013)

Damage Mechanics of Porcine Flexor Tendon: Mechanical Evaluation and Modeling - Sarah Duenwald-Kuehl; Jaclyn Kondratko; Roderic S. Lakes; Ray Vanderby (Annals of Biomedical Engineering, 2012)

Validation of prostate cancer risk-related loci identified from genome-wide association studies using family-based association analysis: evidence from the International Consortium for Prostate Cancer Genetics (ICPCG) - Guangfu Jin; Lingyi Lu; Kathleen A. Cooney; Anna M. Ray; Kimberly A. Zuhlke; Ethan M. Lange; Lisa A. Cannon-Albright; Nicola J. Camp; Craig C. Teerlink; Liesel M. FitzGerald; Janet L. Stanford; Kathleen E. Wiley; et al. (Human Genetics, 2012)

Dependence of pathogen molecule-induced Toll-like receptor activation and cell function on Neu1 sialidase - Schammim Ray Amith; Preethi Jayanth; Susan Franchuk; Sarah Siddiqui; Volkan Seyrantepe; Katrina Gee; Sameh Basta; Rudi Beyaert; Alexey V. Pshezhetsky; Myron R. Szewczuk (Glycoconjugate Journal, 2009)

Viscoelastic Relaxation and Recovery of Tendon - Sarah E. Duenwald; Ray Vanderby; Roderic S. Lakes (Annals of Biomedical Engineering, 2009)

Sleep disturbance in adults with Angelman syndrome - Kirstie N ANDERSON; Samantha PILSWORTH; Sarah JAMIESON; Julian RAY; John M SHNEERSON; Graeme G LENNOX (Sleep and Biological Rhythms, 2008)

Characterization of the complete genome of influenza A (H5N1) virus isolated during the 2006 outbreak in poultry in India - Koninika Ray; Varsha A. Potdar; Sarah S. Cherian; Shailesh D. Pawar; Santosh M. Jadhav; Shamal R. Waregaonkar; Anshu A. Joshi; Akhilesh C. Mishra (Virus Genes, 2008)

Stratification by CARD15 variant genotype in a genome-wide search for inflammatory bowel disease susceptibility loci - Sarah H. Shaw; Jochen Hampe; Ray White; Christopher G. Mathew; Mark E. Curran; Stefan Schreiber (Human Genetics, 2003)

Contributory presentations/posters - N. Manoj; V. R. Srinivas; A. Surolia; M. Vijayan; K. Suguna; R. Ravishankar; K. Suguna; A. Surolia; M. Vijayan; R. Schwarzenbacher; K. Zeth; Diederichs; et al. (Journal of Biosciences, 1999)