Subduction of the Early Cretaceous portions of the Samoan and Cook-Austral “hotspot highway” into the Mariana Trench - Matthew G. Jackson; Sunna Harðardóttir; Kevin Konrad; Sarah Beethe; Yifan Du; Natália Gauer Pasqualon; Valerie A. Finlayson; Benjamin L. Byerly; Claudia Martinez; Sæmundur A. Halldórsson; Michael Bizimis; Anthony A.P. Koppers (Earth and Planetary Science Letters, 2026)

Two decades of methane budgets at the sub-national scale in China - Pengfei Zhao; Zhen Zhang; Guanghui Huang; Zhenxuan Wang; Josep G. Canadell; Philippe Ciais; Huilin Chen; Shengqian Chen; Jason Blake Cohen; Fan Dai; Peng Gong; Robert B. Jackson; et al. (Science Bulletin, 2026)

Origin and age of low-temperature carbonates in oceanic hotspot lavas - Ruixia Bai; Matthew G. Jackson; Yifan Du; Andrew Kylander-Clark; Andrea Giuliani; Senan Oesch; Adrian R. Tasistro-Hart; Benjamin Byerly; Gareth Seward; James M.D. Day; Elizabeth A. Bell (Geochimica et Cosmochimica Acta, 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

Equation of state of a low-sulfur iron–nickel alloy up to 143 GPa - Cijin Zhou; Johannes Buchen; Vasilije V. Dobrosavljevic; Benjamin Strozewski; Olivia S. Pardo; Wolfgang Sturhahn; Takayuki Ishii; Thomas S. Toellner; John D. Wilding; Stella Chariton; Bora Kalkan; Martin Kunz; et al. (Physics of the Earth and Planetary Interiors, 2026)

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.

Discovery of young submarine volcanism in the Cook Islands: New constraints on the location of the Rarotonga hotspot - Yifan Du; Matthew G. Jackson; Brian Jicha; Andrew Kylander-Clark; Benjamin L. Byerly; Michael Bizimis; Sæmundur Ari Halldórsson; Gareth G.E. Seward; Olivia E. Anderson; Matthew Rioux; Kevin Konrad; Sunna Harðardóttir; et al. (Geochimica et Cosmochimica Acta, 2026)

Sound velocities of (Al,Fe)-phase H and the seismic visibility of dense oxyhydroxides in Earth’s lower mantle - Benjamin T. Strozewski; Ojashvi Rautela; Johannes Buchen; Wolfgang Sturhahn; Takayuki Ishii; Itaru Ohira; Olivia Pardo; Jiyong Zhao; Thomas S. Toellner; Jennifer M. Jackson (Physics of the Earth and Planetary Interiors, 2025)

Estimating the heterogeneous effects of a utility-scale solar facility on house prices - Michael Cary; Susan Chen; Jessica Douthit; Njeri Jackson; Michael McCloud; Benjamin Rosner (Land Use Policy, 2025)

Variation in estimates of the footprint of large, ground-mounted photovoltaic solar energy in the United States and its associated land-cover change across three datasets - Michael O. Levin; Emma Forester; Elizabeth L. Kalies; Lauren Goodman; Jason S. Hagani; Chevon C. Holmes; Noah Z. Krasner; Caitlin Markus; Jared B. Meek; Anubhav Vanamamalai; Shivani Agarwal; Uzma Ashraf; et al. (Journal of Environmental Management, 2025)

Homing and feral pigeons differ in hippocampal formation neuron size: a Golgi study - Benjamin Brinkman; Sydney D. Irvine; Jackson R. Ham; Andrew N. Iwaniuk (Brain Structure and Function, 2025)

Regional mapping of natural gas compressor stations in the United States and Canada using deep learning on satellite imagery - Benjamin Liu; Jeremy Irvin; Mark Omara; Chenghao Wang; Gil Kornberg; Hao Sheng; Ritesh Gautam; Andrew Y. Ng; Robert B. Jackson (Journal of Environmental Management, 2025)

Matching planting methods to species and site conditions is key in seed-based intertidal seagrass restoration - Lucy Coals; Benjamin L.H. Jones; Ally J. Evans; Richard K.F. Unsworth; Laney Callahan; Rhys A. Coleman; Laura L. Govers; Max L.E. Gräfnings; Emma L. Jackson; Craig D.H. Sherman (Marine Pollution Bulletin, 2025)

BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series - Maria Dornelas; Laura H. Antão; Amanda E. Bates; Viviana Brambilla; Jonathan M. Chase; Cher F. Y. Chow; Ada Fontrodona‐Eslava; Anne E. Magurran; Inês S. Martins; Faye Moyes; Alban Sagouis; Samuel Adu‐Acheampong; et al. (Global Ecology and Biogeography, 2025)
Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

Worldwide Soundscapes: A Synthesis of Passive Acoustic Monitoring Across Realms - Kevin F. A. Darras; Rodney A. Rountree; Steven L. Van Wilgenburg; Anna F. Cord; Frederik Pitz; Youfang Chen; Lijun Dong; Agnès Rocquencourt; Camille Desjonquères; Patrick Mauritz Diaz; Tzu‐Hao Lin; Théophile Turco; et al. (Global Ecology and Biogeography, 2025)
Aim The urgency for remote, reliable and scalable biodiversity monitoring amidst mounting human pressures on ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), which can track life underwater and on land. However, we lack a unified methodology to report this sampling effort and a comprehensive overview of PAM coverage to gauge its potential as a global research and monitoring tool. To address this gap, we created the Worldwide Soundscapes project, a collaborative network and growing database comprising metadata from 416 datasets across all realms (terrestrial, marine, freshwater and subterranean). Location Worldwide, 12,343 sites, all ecosystem types. Time Period 1991 to present. Major Taxa Studied All soniferous taxa. Methods We synthesise sampling coverage across spatial, temporal and ecological scales using metadata describing sampling locations, deployment schedules, focal taxa and audio recording parameters. We explore global trends in biological, anthropogenic and geophysical sounds based on 168 selected recordings from 12 ecosystems across all realms. Results Terrestrial sampling is spatially denser (46 sites per million square kilometre—Mkm 2 ) than aquatic sampling (0.3 and 1.8 sites/Mkm 2 in oceans and fresh water) with only two subterranean datasets. Although diel and lunar cycles are well sampled across realms, only marine datasets (55%) comprehensively sample all seasons. Across the 12 ecosystems selected for exploring global acoustic trends, biological sounds showed contrasting diel patterns across ecosystems, declined with distance from the Equator, and were negatively correlated with anthropogenic sounds. Main Conclusions PAM can inform macroecological studies as well as global conservation and phenology syntheses, but representation can be improved by expanding terrestrial taxonomic scope, sampling coverage in the high seas and subterranean ecosystems, and spatio‐temporal replication in freshwater habitats. Overall, this worldwide PAM network holds promise to support cross‐realm biodiversity research and monitoring efforts.

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.

Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups - John F. Benson; David A. Keiter; Peter J. Mahoney; Benjamin L. Allen; Lee Allen; Francisco Álvares; Morgan L. Anderson; Shannon M. Barber‐Meyer; Adi Barocas; James C. Beasley; Linda Behrendorff; Jerrold L. Belant; et al. (Ecology, 2025)
Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group‐level processes such as subgroup formation and fission–fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals. We tracked 574 individuals from six species within the genus Canis in 15 countries on four continents with GPS telemetry to estimate the time that pairs of individuals within social groups spent in close proximity and test hypotheses regarding drivers of cohesion. Pairs of social canids ( Canis spp.) varied widely in the proportion of time they spent together (5%–100%) during seasonal monitoring periods relative to both intrinsic characteristics and environmental conditions. The majority of our data came from three species of wolves (gray wolves, eastern wolves, and red wolves) and coyotes. For these species, cohesion within social groups was greatest between breeding pairs and varied seasonally as the nature of cooperative activities changed relative to annual life history patterns. Across species, wolves were more cohesive than coyotes. For wolves, pairs were less cohesive in larger groups, and when suitable, small prey was present reflecting the constraints of food resources and intragroup competition on social associations. Pair cohesion in wolves declined with increased anthropogenic modification of the landscape and greater climatic variability, underscoring challenges for conserving social top predators in a changing world. We show that pairwise cohesion in social groups varies strongly both within and across Canis species, as individuals respond to changing ecological context defined by resources, competition, and anthropogenic disturbance. Our work highlights that cohesion is a highly plastic component of animal sociality that holds significant promise for elucidating ecological and evolutionary mechanisms underlying cooperative behavior.

Rab Proteins as Potential Therapeutic Targets Applied to Crustacean Aquaculture: Rab7 Case Analysis - Carlos Fajardo; Marcos De Donato; Patai Charoonnart; Vanvimon Saksmerprome; Harry O. Jackson; Juan Miguel Mancera; Benjamin Costas (Reviews in Aquaculture, 2025)
Rab proteins constitute an important subfamily of molecular effectors whose function is related to the modulation of several important cellular and metabolic processes, including controlling intracellular endocytic vesicle trafficking, phagosome formation, endosome maturation, and innate immunity. In crustaceans, the study and characterization of these proteins have garnered great interest, mainly due to their pivotal role in the innate immune response mechanisms against infections. Among the Rab family, the Rab7 stands out as a prominent example of the potential of these proteins as therapeutic targets for the development of genetic therapies to control viral pathogens in crustacean aquaculture. In this review, a compendium of the information currently available in relation to Rab proteins in crustaceans is made, taking the Rab7 protein as a model, emphasizing not only its general aspects of functioning at the molecular level, but also describing in‐depth both mechanisms of action and potential interactions, as well as its implications in relation to the immune system, particularly in shrimp.

Sport-Specific Recovery Trajectories for NCAA Collegiate Athletes Following Concussion - Spencer W. Liebel; Kathryn L. Van Pelt; Paul F. Pasquina; Thomas W. McAllister; Michael A. McCrea; Steven P. Broglio; Scott Anderson; Holly Benjamin; Thomas Buckley; Kenneth Cameron; Sara Chrisman; James Clugston; et al. (Annals of Biomedical Engineering, 2024)

Planet’s Biomass Proxy for monitoring aboveground agricultural biomass and estimating crop yield - Pierre C. Guillevic; Benjamin Aouizerats; Rogier Burger; Nadja Den Besten; Daniel Jackson; Margot Ridderikhoff; Ariel Zajdband; Rasmus Houborg; Trenton E. Franz; G. Philip Robertson; Richard De Jeu (Field Crops Research, 2024)

Evaluation of coal mine drainage and associated precipitates for radium and rare earth element concentrations - Bonnie McDevitt; Charles A. Cravotta; Ryan J. McAleer; John C. Jackson; Aaron M. Jubb; Glenn D. Jolly; Benjamin C. Hedin; Nathaniel R. Warner (International Journal of Coal Geology, 2024)

Early Aboriginal pottery production and offshore island occupation on Jiigurru (Lizard Island group), Great Barrier Reef, Australia - Sean Ulm; Ian J. McNiven; Glenn R. Summerhayes; Pei-hua Wu; Magdalena M.E. Bunbury; Fiona Petchey; Quan Hua; Robert Skelly; Ariana B.J. Lambrides; Cassandra Rowe; Kelsey M. Lowe; Christian H. Reepmeyer; et al. (Quaternary Science Reviews, 2024)

Modeling coupled dynamics of an empirical predator-prey system to predict top predator recovery - Samantha N.M. Hamilton; M. Tim Tinker; Joseph Jackson; Joseph A. Tomoleoni; Michael C. Kenner; Julie L. Yee; Tom W. Bell; Max C.N. Castorani; Benjamin H. Becker; Brent B. Hughes (Biological Conservation, 2024)

Studying interactions among anthropogenic stressors in freshwater ecosystems: A systematic review of 2396 multiple‐stressor experiments - James A. Orr; Samuel J. Macaulay; Adriana Mordente; Benjamin Burgess; Dania Albini; Julia G. Hunn; Katherin Restrepo‐Sulez; Ramesh Wilson; Anne Schechner; Aoife M. Robertson; Bethany Lee; Blake R. Stuparyk; et al. (Ecology Letters, 2024)
Understanding the interactions among anthropogenic stressors is critical for effective conservation and management of ecosystems. Freshwater scientists have invested considerable resources in conducting factorial experiments to disentangle stressor interactions by testing their individual and combined effects. However, the diversity of stressors and systems studied has hindered previous syntheses of this body of research. To overcome this challenge, we used a novel machine learning framework to identify relevant studies from over 235,000 publications. Our synthesis resulted in a new dataset of 2396 multiple‐stressor experiments in freshwater systems. By summarizing the methods used in these studies, quantifying trends in the popularity of the investigated stressors, and performing co‐occurrence analysis, we produce the most comprehensive overview of this diverse field of research to date. We provide both a taxonomy grouping the 909 investigated stressors into 31 classes and an open‐source and interactive version of the dataset ( https://jamesaorr.shinyapps.io/freshwater‐multiple‐stressors/ ). Inspired by our results, we provide a framework to help clarify whether statistical interactions detected by factorial experiments align with stressor interactions of interest, and we outline general guidelines for the design of multiple‐stressor experiments relevant to any system. We conclude by highlighting the research directions required to better understand freshwater ecosystems facing multiple stressors.

SNAPSHOT USA 2021: A third coordinated national camera trap survey of the U nited S tates - Hila Shamon; Roi Maor; Michael V. Cove; Roland Kays; Jessie Adley; Peter D. Alexander; David N. Allen; Maximilian L. Allen; Cara L. Appel; Evan Barr; Erika L. Barthelmess; Carolina Baruzzi; et al. (Ecology, 2024)
SNAPSHOT USA is a multicontributor, long‐term camera trap survey designed to survey mammals across the United States. Participants are recruited through community networks and directly through a website application ( https://www.snapshot-usa.org/ ). The growing Snapshot dataset is useful, for example, for tracking wildlife population responses to land use, land cover, and climate changes across spatial and temporal scales. Here we present the SNAPSHOT USA 2021 dataset, the third national camera trap survey across the US. Data were collected across 109 camera trap arrays and included 1711 camera sites. The total effort equaled 71,519 camera trap nights and resulted in 172,507 sequences of animal observations. Sampling effort varied among camera trap arrays, with a minimum of 126 camera trap nights, a maximum of 3355 nights, a median 546 nights, and a mean 656 ± 431 nights. This third dataset comprises 51 camera trap arrays that were surveyed during 2019, 2020, and 2021, along with 71 camera trap arrays that were surveyed in 2020 and 2021. All raw data and accompanying metadata are stored on Wildlife Insights ( https://www.wildlifeinsights.org/ ), and are publicly available upon acceptance of the data papers. SNAPSHOT USA aims to sample multiple ecoregions in the United States with adequate representation of each ecoregion according to its relative size. Currently, the relative density of camera trap arrays varies by an order of magnitude for the various ecoregions (0.22–5.9 arrays per 100,000 km 2 ), emphasizing the need to increase sampling effort by further recruiting and retaining contributors. There are no copyright restrictions on these data. We request that authors cite this paper when using these data, or a subset of these data, for publication. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government.

Status of agriculture and food security in post-COVID-19 Africa: Impacts and lessons learned - Victoria A. Uyanga; Semiu Folaniyi Bello; Nzeyimana Jean Bosco; Saheed O. Jimoh; Ifunanya J. Mbadianya; Unisa C. Kanu; Charles O. Okoye; Ebenezer Afriyie; Erastus Mak-Mensah; Kwadwo G. Agyenim-Boateng; Solabomi O. Ogunyemi; Jackson N. Nkoh; et al. (Food and Humanity, 2024)

Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems - Sarah Feron; Avni Malhotra; Sheel Bansal; Etienne Fluet‐Chouinard; Gavin McNicol; Sara H. Knox; Kyle B. Delwiche; Raul R. Cordero; Zutao Ouyang; Zhen Zhang; Benjamin Poulter; Robert B. Jackson (Global Change Biology, 2024)
Climate warming is expected to increase global methane (CH 4 ) emissions from wetland ecosystems. Although in situ eddy covariance (EC) measurements at ecosystem scales can potentially detect CH 4 flux changes, most EC systems have only a few years of data collected, so temporal trends in CH 4 remain uncertain. Here, we use established drivers to hindcast changes in CH 4 fluxes (FCH 4 ) since the early 1980s. We trained a machine learning (ML) model on CH 4 flux measurements from 22 [methane‐producing sites] in wetland, upland, and lake sites of the FLUXNET‐CH 4 database with at least two full years of measurements across temperate and boreal biomes. The gradient boosting decision tree ML model then hindcasted daily FCH 4 over 1981–2018 using meteorological reanalysis data. We found that, mainly driven by rising temperature, half of the sites ( n = 11) showed significant increases in annual, seasonal, and extreme FCH 4 , with increases in FCH 4 of ca. 10% or higher found in the fall from 1981–1989 to 2010–2018. The annual trends were driven by increases during summer and fall, particularly at high‐CH 4 ‐emitting fen sites dominated by aerenchymatous plants. We also found that the distribution of days of extremely high FCH 4 (defined according to the 95th percentile of the daily FCH 4 values over a reference period) have become more frequent during the last four decades and currently account for 10–40% of the total seasonal fluxes. The share of extreme FCH 4 days in the total seasonal fluxes was greatest in winter for boreal/taiga sites and in spring for temperate sites, which highlights the increasing importance of the non‐growing seasons in annual budgets. Our results shed light on the effects of climate warming on wetlands, which appears to be extending the CH 4 emission seasons and boosting extreme emissions.

Lattice dynamics, sound velocities, and atomic environments of szomolnokite at high pressure - Olivia S. Pardo; Vasilije V. Dobrosavljevic; Wolfgang Sturhahn; Thomas S. Toellner; Benjamin Strozewski; Jennifer M. Jackson (Physics and Chemistry of Minerals, 2023)

Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates - Kuang‐Yu Chang; William J. Riley; Nathan Collier; Gavin McNicol; Etienne Fluet‐Chouinard; Sara H. Knox; Kyle B. Delwiche; Robert B. Jackson; Benjamin Poulter; Marielle Saunois; Naveen Chandra; Nicola Gedney; et al. (Global Change Biology, 2023)
The recent rise in atmospheric methane (CH 4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH 4 source, estimates of global wetland CH 4 emissions vary widely among approaches taken by bottom‐up (BU) process‐based biogeochemical models and top‐down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi‐model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH 4 emission estimates and model performance. We find that using better‐performing models identified by observational constraints reduces the spread of wetland CH 4 emission estimates by 62% and 39% for BU‐ and TD‐based approaches, respectively. However, global BU and TD CH 4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH 4 year −1 ) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter‐site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH 4 models to move beyond static benchmarking and focus on evaluating site‐specific and ecosystem‐specific variabilities inferred from observations.

Capturing twenty years of change in ecosystem services provided by coastal Massachusetts habitats - Benjamin L. Branoff; Giancarlo Cicchetti; Susan Jackson; Margherita Pryor; Leah M. Sharpe; Emily Shumchenia; Susan H. Yee (Ecosystem Services, 2023)

Understanding Sentinel-1 backscatter response to sugarcane yield variability and waterlogging - Nadja den Besten; Susan Steele Dunne; Ashfak Mahmud; Daniel Jackson; Benjamin Aouizerats; Richard de Jeu; Rogier Burger; Rasmus Houborg; Mark McGlinchey; Pieter van der Zaag (Remote Sensing of Environment, 2023)

Evaluating cancer genetic services in a safety net system: overcoming barriers for a lasting impact beyond the CHARM research project - Sonia Okuyama; Larissa L. White; Katherine P. Anderson; Elizabeth Medina; Sonia Deutsch; Chelese Ransom; Paige Jackson; Tia L. Kauffman; Kathleen F. Mittendorf; Michael C. Leo; Joanna E. Bulkley; Benjamin S. Wilfond; et al. (Journal of Community Genetics, 2023)
Underserved patients face substantial barriers to receiving cancer genetic services. The Cancer Health Assessments Reaching Many (CHARM) study evaluated ways to increase access to genetic testing for individuals in underserved populations at risk for hereditary cancer syndromes (HCS). Here, we report the successful implementation of CHARM in a low-resource environment and the development of sustainable processes to continue genetic risk assessment in this setting. The research team involved key clinical personnel and patient advisors at Denver Health to provide input on study methods and materials. Through iterative and collaborative stakeholder engagement, the team identified barriers and developed solutions that would both facilitate participation in CHARM and be feasible to implement and sustain long term in clinical care. With a focus on infrastructure building, educational modules were developed to increase awareness among referring providers, and standard methods of identifying and managing HCS patients were implemented in the electronic medical record. Three hundred sixty-four DH patients successfully completed the risk assessment tool within the study, and we observed a sustained increase in referrals to genetics for HCS (from 179 in 2017 to 427 in 2021 post-intervention). Implementation of the CHARM study at a low-resourced safety net health system resulted in sustainable improvements in access to cancer genetic risk assessment and services that continue even after the study ended. Trial registration NCT03426878

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions - Masahito Ueyama; Sara H. Knox; Kyle B. Delwiche; Sheel Bansal; William J. Riley; Dennis Baldocchi; Takashi Hirano; Gavin McNicol; Karina Schafer; Lisamarie Windham‐Myers; Benjamin Poulter; Robert B. Jackson; et al. (Global Change Biology, 2023)
Wetlands are the largest natural source of methane (CH 4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH 4 , but interpreting its spatiotemporal variations is challenging due to the co‐occurrence of CH 4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data‐model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data‐constrained model—iPEACE—reasonably reproduced CH 4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH 4 production appeared to be the most important process, followed by oxidation in explaining inter‐site variations in CH 4 emissions. Based on a sensitivity analysis, CH 4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant‐mediated transport appeared to be the major pathway for CH 4 transport. Contributions from ebullition and diffusion were relatively high during low LAI ( 4 production and CH 4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH 4 production, plant‐mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH 4 emissions across biomes. These processes and associated parameters for CH 4 emissions among and within the wetlands provide useful insights for interpreting observed net CH 4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH 4 fluxes.

Biodiversity patterns diverge along geographic temperature gradients - Charlie J. G. Loewen; Donald A. Jackson; Benjamin Gilbert (Global Change Biology, 2023)
Models applying space‐for‐time substitution, including those projecting ecological responses to climate change, generally assume an elevational and latitudinal equivalence that is rarely tested. However, a mismatch may lead to different capacities for providing climatic refuge to dispersing species. We compiled community data on zooplankton, ectothermic animals that form the consumer basis of most aquatic food webs, from over 1200 mountain lakes and ponds across western North America to assess biodiversity along geographic temperature gradients spanning nearly 3750 m elevation and 30° latitude. Species richness, phylogenetic relationships, and functional diversity all showed contrasting responses across gradients, with richness metrics plateauing at low elevations but exhibiting intermediate latitudinal maxima. The nonmonotonic/hump‐shaped diversity trends with latitude emerged from geographic interactions, including weaker latitudinal relationships at higher elevations (i.e. in alpine lakes) linked to different underlying drivers. Here, divergent patterns of phylogenetic and functional trait dispersion indicate shifting roles of environmental filters and limiting similarity in the assembly of communities with increasing elevation and latitude. We further tested whether gradients showed common responses to warmer temperatures and found that mean annual (but not seasonal) temperatures predicted elevational richness patterns but failed to capture consistent trends with latitude, meaning that predictions of how climate change will influence diversity also differ between gradients. Contrasting responses to elevation‐ and latitude‐driven warming suggest different limits on climatic refugia and likely greater barriers to northward range expansion.

Paddy rice methane emissions across Monsoon Asia - Zutao Ouyang; Robert B. Jackson; Gavin McNicol; Etienne Fluet-Chouinard; Benjamin R.K. Runkle; Dario Papale; Sara H. Knox; Sarah Cooley; Kyle B. Delwiche; Sarah Feron; Jeremy Andrew Irvin; Avni Malhotra; et al. (Remote Sensing of Environment, 2023)

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)

Regional trends and drivers of the global methane budget - Ann R. Stavert; Marielle Saunois; Josep G. Canadell; Benjamin Poulter; Robert B. Jackson; Pierre Regnier; Ronny Lauerwald; Peter A. Raymond; George H. Allen; Prabir K. Patra; Peter Bergamaschi; Phillipe Bousquet; et al. (Global Change Biology, 2022)
The ongoing development of the Global Carbon Project (GCP) global methane (CH 4 ) budget shows a continuation of increasing CH 4 emissions and CH 4 accumulation in the atmosphere during 2000–2017. Here, we decompose the global budget into 19 regions (18 land and 1 oceanic) and five key source sectors to spatially attribute the observed global trends. A comparison of top‐down (TD) (atmospheric and transport model‐based) and bottom‐up (BU) (inventory‐ and process model‐based) CH 4 emission estimates demonstrates robust temporal trends with CH 4 emissions increasing in 16 of the 19 regions. Five regions—China, Southeast Asia, USA, South Asia, and Brazil—account for >40% of the global total emissions (their anthropogenic and natural sources together totaling >270 Tg CH 4 yr −1 in 2008–2017). Two of these regions, China and South Asia, emit predominantly anthropogenic emissions (>75%) and together emit more than 25% of global anthropogenic emissions. China and the Middle East show the largest increases in total emission rates over the 2000 to 2017 period with regional emissions increasing by >20%. In contrast, Europe and Korea and Japan show a steady decline in CH 4 emission rates, with total emissions decreasing by ~10% between 2000 and 2017. Coal mining, waste (predominantly solid waste disposal) and livestock (especially enteric fermentation) are dominant drivers of observed emissions increases while declines appear driven by a combination of waste and fossil emission reductions. As such, together these sectors present the greatest risks of further increasing the atmospheric CH 4 burden and the greatest opportunities for greenhouse gas abatement.

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales - Sara H. Knox; Sheel Bansal; Gavin McNicol; Karina Schafer; Cove Sturtevant; Masahito Ueyama; Alex C. Valach; Dennis Baldocchi; Kyle Delwiche; Ankur R. Desai; Eugenie Euskirchen; Jinxun Liu; et al. (Global Change Biology, 2021)
While wetlands are the largest natural source of methane (CH 4 ) to the atmosphere, they represent a large source of uncertainty in the global CH 4 budget due to the complex biogeochemical controls on CH 4 dynamics. Here we present, to our knowledge, the first multi‐site synthesis of how predictors of CH 4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet‐based multi‐resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat‐dominated sites, with drops in PA coinciding with synchronous releases of CH 4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH 4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1‐ to 4‐h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH 4 emissions.

Forest responses to last‐millennium hydroclimate variability are governed by spatial variations in ecosystem sensitivity - Christine R. Rollinson; Andria Dawson; Ann M. Raiho; John W. Williams; Michael C. Dietze; Thomas Hickler; Stephen T. Jackson; Jason McLachlan; David JP Moore; Benjamin Poulter; Tristan Quaife; Jörg Steinkamp; et al. (Ecology Letters, 2021)
Forecasts of future forest change are governed by ecosystem sensitivity to climate change, but ecosystem model projections are under‐constrained by data at multidecadal and longer timescales. Here, we quantify ecosystem sensitivity to centennial‐scale hydroclimate variability, by comparing dendroclimatic and pollen‐inferred reconstructions of drought, forest composition and biomass for the last millennium with five ecosystem model simulations. In both observations and models, spatial patterns in ecosystem responses to hydroclimate variability are strongly governed by ecosystem sensitivity rather than climate exposure. Ecosystem sensitivity was higher in models than observations and highest in simpler models. Model‐data comparisons suggest that interactions among biodiversity, demography and ecophysiology processes dampen the sensitivity of forest composition and biomass to climate variability and change. Integrating ecosystem models with observations from timescales extending beyond the instrumental record can better understand and forecast the mechanisms regulating forest sensitivity to climate variability in a complex and changing world.

Refining national greenhouse gas inventories - Leehi Yona; Benjamin Cashore; Robert B. Jackson; Jean Ometto; Mark A. Bradford (Ambio, 2020)
The importance of greenhouse gas inventories cannot be overstated: the process of producing inventories informs strategies that governments will use to meet emissions reduction targets. The Intergovernmental Panel on Climate Change (IPCC) leads an effort to develop and refine internationally agreed upon methodologies for calculating and reporting greenhouse gas emissions and removals. We argue that these guidelines are not equipped to handle the task of developing national greenhouse gas inventories for most countries. Inventory guidelines are vital to implementing climate action, and we highlight opportunities to improve their timeliness and accuracy. Such reforms should provide the means to better understand and advance the progress countries are making toward their Paris commitments. Now is the time to consider challenges posed by the current process to develop the guidelines, and to avail the policy community of recent major advances in quantitative and expert synthesis to overhaul the process and thereby better equip multi-national efforts to limit climate change.

Climate warming moderates the impacts of introduced sportfish on multiple dimensions of prey biodiversity - Charlie J. G. Loewen; Angela L. Strecker; Benjamin Gilbert; Donald A. Jackson (Global Change Biology, 2020)
Human‐assisted introductions of exotic species are a leading cause of anthropogenic change in biodiversity; however, context dependencies and interactions with co‐occurring stressors impede our ability to predict their ecological impacts. The legacy of historical sportfish stocking in mountainous regions of western North America creates a unique, natural quasiexperiment to investigate factors moderating invasion impacts on native communities across broad geographic and environmental gradients. Here we synthesize fish stocking records and zooplankton relative abundance for 685 mountain lakes and ponds in the Cascade and Canadian Rocky Mountain Ranges, to reveal the effects of predatory sportfish introduction on multiple taxonomic, functional and phylogenetic dimensions of prey biodiversity. We demonstrate an innovative analytical approach, combining exploratory random forest machine learning with confirmatory multigroup analysis using multivariate partial least‐squares structural equation models, to generate and test hypotheses concerning environmental moderation of stocking impacts. We discovered distinct effects of stocking across different dimensions of diversity, including negligible (nonsignificant) impacts on local taxonomic richness (i.e. alpha diversity) and trophic structure, in contrast to significant declines in compositional uniqueness (i.e. beta diversity) and body size. Furthermore, we found that stocking impacts were moderated by cross‐scale interactions with climate and climate‐related land‐cover variables (e.g. factors linked to treeline position and glaciers). Interactions with physical morphometric and lithological factors were generally of lesser importance, though catchment slope and habitat size constraints were relevant in certain dimensions. Finally, applying space‐for‐time substitution, a strong antagonistic (i.e. dampening) interaction between sportfish predation and warmer temperatures suggests redundancy of their size‐selective effects, meaning that warming will lessen the consequences of introductions in the future and stocked lakes may be less impacted by subsequent warming. While both stressors drive biotic homogenization, our results have important implications for fisheries managers weighing the costs/benefits of stocking—or removing established non‐native populations—under a rapidly changing climate.

Isolation, Characterisation and Experimental Evolution of Phage that Infect the Horse Chestnut Tree Pathogen, Pseudomonas syringae pv. aesculi - Sarah L. James; Mojgan Rabiey; Benjamin W. Neuman; Glynn Percival; Robert W. Jackson (Current Microbiology, 2020)
Bleeding canker of horse chestnut trees is a bacterial disease, caused by the bacterium Pseudomonas syringae pv. aesculi, estimated to be present in ~ 50% of UK horse chestnut trees. Currently, the disease has no cure and tree removal can be a common method of reducing inoculum and preventing spread. One potential method of control could be achieved using naturally occurring bacteriophages infective to the causative bacterium. Bacteriophages were isolated from symptomatic and asymptomatic horse chestnut trees in three locations in the South East of England. The phages were found to be belonging to both the Myoviridae and Podoviridae families by RAPD PCR and transmission electron microscopy. Experimental coevolution was carried out to understand the dynamics of bacterial resistance and phage infection and to determine whether new infective phage genotypes would emerge. The phages exhibited different coevolution patterns with their bacterial hosts across time. This approach could be used to generate novel phages for use in biocontrol cocktails in an effort to reduce the potential emergence of bacterial resistance.

Influence of turbulence and in-stream structures on the transport and survival of grass carp eggs and larvae at various developmental stages - Andres F. Prada; Amy E. George; Benjamin H. Stahlschmidt; Patrick Ryan Jackson; Duane C. Chapman; Rafael O. Tinoco (Aquatic Sciences, 2020)
Understanding the response of grass carp to flow and turbulence regimes during early life stages is fundamental to monitoring and controlling their spread. A comprehensive set of hydrodynamic experiments was conducted with live grass carp eggs and larvae, to better understand their drifting and swimming patterns with 3 different in-stream obstructions: (1) a gravel bump, (2) a single cylinder, and (3) submerged vegetation. The hydrodynamic behavior of eggs and larvae with each obstruction was continuously monitored for about 85 consecutive hours. Transient spatial distributions of the locations of eggs and larvae throughout the water column were generated for each flow scenario. Results show that the active swimming capabilities of larvae allow them to seek areas of low turbulence and low shear stresses, and that eggs are susceptible to damage by high levels of turbulence, which was further corroborated with tests in an oscillating grid-stirred turbulence tank. Our study seeks to better inform field collection of grass carp during early life stages, and to guide the design of alternative approaches to control the dispersal of this invasive species in North America.

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.

Faster‐X evolution: Theory and evidence from Drosophila - Brian Charlesworth; José L. Campos; Benjamin C. Jackson (Molecular Ecology, 2018)
A faster rate of adaptive evolution of X‐linked genes compared with autosomal genes can be caused by the fixation of recessive or partially recessive advantageous mutations, due to the full expression of X‐linked mutations in hemizygous males. Other processes, including recombination rate and mutation rate differences between X chromosomes and autosomes, may also cause faster evolution of X‐linked genes. We review population genetics theory concerning the expected relative values of variability and rates of evolution of X‐linked and autosomal DNA sequences. The theoretical predictions are compared with data from population genomic studies of several species of Drosophila . We conclude that there is evidence for adaptive faster‐X evolution of several classes of functionally significant nucleotides. We also find evidence for potential differences in mutation rates between X‐linked and autosomal genes, due to differences in mutational bias towards GC to AT mutations. Many aspects of the data are consistent with the male hemizygosity model, although not all possible confounding factors can be excluded.

Role of DNA methylation in the dietary restriction mediated cellular memory - Archana Unnikrishnan; Jordan Jackson; Stephanie A. Matyi; Niran Hadad; Benjamin Wronowski; Constantin Georgescu; Karla P. Garrett; Jonathan D. Wren; Willard M. Freeman; Arlan Richardson (GeroScience, 2017)

Diplomacy for science: strategies to promote international collaboration - Igor Linkov; Sankar Basu; Cathleen Fisher; Nancy Jackson; Adam C. Jones; Maija M. Kuklja; Benjamin D. Trump (Environment Systems and Decisions, 2016)

A global meta‐analysis of the relative extent of intraspecific trait variation in plant communities - Andrew Siefert; Cyrille Violle; Loïc Chalmandrier; Cécile H. Albert; Adrien Taudiere; Alex Fajardo; Lonnie W. Aarssen; Christopher Baraloto; Marcos B. Carlucci; Marcus V. Cianciaruso; Vinícius de L. Dantas; Francesco de Bello; et al. (Ecology Letters, 2015)
Recent studies have shown that accounting for intraspecific trait variation ( ITV ) may better address major questions in community ecology. However, a general picture of the relative extent of ITV compared to interspecific trait variation in plant communities is still missing. Here, we conducted a meta‐analysis of the relative extent of ITV within and among plant communities worldwide, using a data set encompassing 629 communities (plots) and 36 functional traits. Overall, ITV accounted for 25% of the total trait variation within communities and 32% of the total trait variation among communities on average. The relative extent of ITV tended to be greater for whole‐plant (e.g. plant height) vs. organ‐level traits and for leaf chemical (e.g. leaf N and P concentration) vs. leaf morphological (e.g. leaf area and thickness) traits. The relative amount of ITV decreased with increasing species richness and spatial extent, but did not vary with plant growth form or climate. These results highlight global patterns in the relative importance of ITV in plant communities, providing practical guidelines for when researchers should include ITV in trait‐based community and ecosystem studies.

The genetic structure of Nautilus pompilius populations surrounding Australia and the Philippines - Rachel C. Williams; Benjamin C. Jackson; Ludovic Duvaux; Deborah A. Dawson; Terry Burke; William Sinclair (Molecular Ecology, 2015)
Understanding the distribution of genetic diversity in exploited species is fundamental to successful conservation. Genetic structure and the degree of gene flow among populations must be assessed to design appropriate strategies to prevent the loss of distinct populations. The cephalopod Nautilus pompilius is fished unsustainably in the Philippines for the ornamental shell trade and has limited legislative protection, despite the species' recent dramatic decline in the region. Here, we use 14 microsatellite markers to evaluate the population structure of N. pompilius around Australia and the Philippines. Despite their relative geographical proximity, Great Barrier Reef individuals are genetically isolated from Osprey Reef and Shark Reef in the Coral Sea ( F ST = 0.312, 0.229, respectively). Conversely, despite the larger geographical distances between the Philippines and west Australian reefs, samples display a small degree of genetic structure ( F ST = 0.015). Demographic scenarios modelled using approximate Bayesian computation analysis indicate that this limited divergence is not due to contemporary gene flow between the Philippines and west Australia. Instead, present‐day genetic similarity can be explained by very limited genetic drift that has occurred due to large average effective population sizes that persisted at both locations following their separation. The lack of connectivity among populations suggests that immigrants from west Australia would not facilitate natural recolonization if Philippine populations were fished to extinction. These data help to rectify the paucity of information on the species' biology currently inhibiting their conservation classification. Understanding population structure can allow us to facilitate sustainable harvesting, thereby preserving the diversity of genetically distinct stocks.

Global relationship of wood and leaf litter decomposability: the role of functional traits within and across plant organs - Katherina A. Pietsch; Kiona Ogle; Johannes H. C. Cornelissen; William K. Cornwell; Gerhard Bönisch; Joseph M. Craine; Benjamin G. Jackson; Jens Kattge; Duane A. Peltzer; Josep Penuelas; Peter B. Reich; David A. Wardle; et al. (Global Ecology and Biogeography, 2014)
Aim Recent meta‐analyses have revealed that plant traits and their phylogenetic history influence decay rates of dead wood and leaf litter, but it remains unknown if decay rates of wood and litter covary over a wide range of tree species and across ecosystems. We evaluated the relationships between species‐specific wood and leaf litter decomposability, as well as between wood and leaf traits that control their respective decomposability. Location Global. Methods We compiled data on rates of wood and leaf litter decomposition for 324 and 635 tree species, respectively, and data on six functional traits for both organs. We used hierarchical Bayesian meta‐analysis to estimate, for the first time, species‐specific values for wood and leaf litter decomposability standardized to reference conditions ( k * wood and k * leaf ) across the globe. With these data, we evaluated the relationships: (1) between wood and leaf traits, (2) between each k * and the selected traits within and across organs, and (3) between wood and leaf k *. Results Across all species k * wood and k * leaf were positively correlated, phylogenetically clustered and correlated with plant functional traits within and across organs. k * of both organs was usually better described as a function of within‐ and cross‐organ traits, than of within‐organ traits alone. When analysed for angiosperms and gymnosperms separately, wood and leaf k * were no longer significantly correlated, but each k * was still significantly correlated to the functional traits. Main conclusions We demonstrate important relationships among wood and leaf litter decomposability as after‐life effects of traits from the living plants. These functional traits influence the decomposability of senesced tissue which could potentially lead to alterations in the rates of biogeochemical cycling, depending on the phylogenetic structure of the species pool. These results provide crucial information for a better representation of decomposition rates in dynamic global vegetation models.

The effects of the moss layer on the decomposition of intercepted vascular plant litter across a post-fire boreal forest chronosequence - Benjamin G. Jackson; Marie-Charlotte Nilsson; David A. Wardle (Plant and Soil, 2013)

Recombination-suppression: how many mechanisms for chromosomal speciation? - Benjamin Charles Jackson (Genetica, 2011)

Predatory activity of the nematophagous fungus Duddingtonia flagrans on horse cyathostomin infective larvae - Fabio R. Braga; Jackson V. Araújo; André. R. Silva; Rogério O. Carvalho; Juliana M. Araujo; Sebastião R. Ferreira; Laércio A. Benjamin (Tropical Animal Health and Production, 2010)

Amino acid abundance and proteolytic potential in North American soils - Kirsten S. Hofmockel; Noah Fierer; Benjamin P. Colman; Robert B. Jackson (Oecologia, 2010)

Perchlorate Distribution, Excretion, and Depuration in Prairie Voles and Deer Mice - Qiuqiong Cheng; Fujun Liu; Philip N. Smith; W. Andrew Jackson; Scott T. McMurry; Michael J. Hooper; Ernest E. Smith; Benjamin C. Blount; Liza Valentin-Blasini; Todd A. Anderson (Water, Air, & Soil Pollution, 2008)

The effects of kainic acid lesions on locomotor responses to haloperidol and clozapine - M. E. Bardgett; Jamie L. Jackson; Benjamin M. Taylor; John G. Csernansky (Psychopharmacology, 1998)