Perceived costs as drivers of wildlife management preferences in rural Tanzanian communities - Christian Kiffner; Justin Raycraft; Reilly Becchina; Danielle Bettermann; Stephen Koester; Elana Kriegel; Kiana Lindsay; Edwin Maingo Ole; Emily Ramirez; Bryan Spizuco; Neil H. Carter (Conservation Biology, 2026)
Effectively managing human–wildlife interactions is crucial for fostering coexistence on shared landscapes. Management options are most effective when aligned with the preferences of people directly affected by wildlife, yet little is known about how socioecological factors influence these preferences. Integrating responses from 680 rural residents of northern Tanzania and remotely sensed data, we parameterized a Bayesian hierarchical model to test predictions of the hazard‐acceptance model. We estimated how perceived costs and benefits, distance to protected areas, and the human footprint index mediate preferences for managing (preventing damage, compensating damage, reducing populations, and doing nothing) interactions with herbivore (elephant, giraffe, buffalo, zebra, wildebeest, and impala) and carnivore (lion, hyena, leopard, cheetah, honey badger, and jackal) species. Most respondents preferred management options that supported coexistence: prevention (41.9%), no management (38.0%), and compensation (11.1%). In contrast, population reduction (9.0%) was least preferred but more frequently selected for carnivores (13.4%) than herbivores (5.3%). Perceived costs strongly influenced management preferences. Respondents perceiving tangible costs were more likely to prefer prevention (posterior mean: 0.57 [95% credible interval 0.00 to 0.99]) over compensation (0.07 [0.00 to 0.66]) or population reduction (0.16 [0.00 to 0.87]), whereas those not perceiving costs leaned toward no management (0.40 [−0.74 to 1.78]). Though perceived benefits were less influential than costs, respondents associating species with intangible (0.10 [0.00 to 0.74]) or tourism benefits (0.06 [0.00 to 0.63]) were less likely to support population reduction than those perceiving no benefits (0.12 [0.00 to 0.82]). Distance to protected areas and the human footprint index had weaker, inconsistent effects, but random intercepts indicated substantial village–village variation in preferred management options. Our results suggest that conservation strategies should primarily address wildlife‐related costs and foster coexistence by more equitably distributing benefits. A possible strategy could include investing tourism revenues into comanaged, locally tailored damage prevention measures.

Analysis of second-generation epigenetic clocks reveals further associations between disproportionate biological ageing and hippocampal volume - Lidija Milicic; Michael Vacher; Vincent Doré; Pierrick Bourgeat; Rosita Shishegar; James D. Doecke; Paul Maruff; Christopher C. Rowe; Victor L. Villemagne; Michael Weiner; Paul Aisen; Ronald Petersen; et al. (GeroScience, 2026)

Evaluating the empirical basis for threat attribution in the IUCN Red List - Ena Humphries; Isaac M. Smith; Mark Ziebell; Charlotte M. Probst; Neil Carter; Brian C. Weeks (Conservation Biology, 2026)
Understanding the impacts of different threats on species is key to successful conservation interventions and policies. The International Union for Conservation of Nature (IUCN) assesses threats to species, and the organization's Red List of Threatened Species is a key conservation tool. We quantified the degree to which threats in IUCN assessments for 3 vertebrate groups (birds, amphibians, and ray‐finned fishes) were based on species‐specific quantitative empirical data. To do this, for 2142 IUCN species assessments, all listed references were reviewed to determine whether they contained species‐specific quantitative data linking a listed threat and the assessed species. Only 7.5% of listed threats across all taxa and categories were based on species‐specific quantitative data. For species with at least one threat listed, only 12.5% of species had species‐specific quantitative data underlying at least one threat. There were more data on threats for some taxa, and there was a trend toward having more information on threats that are generally considered less predictable, such as “invasive/problematic” species and climate change. Understanding how a lack of species‐specific data may affect understanding of extinction processes is crucial for continued improvement of conservation outcomes.

Psychometric framework for coexistence with large carnivores - Benjamin Ghasemi; Gerard Kyle; Tara Teel; Rebeca Niemiec; Kevin Crooks; Jenny Anne Glikman; Neil H. Carter; John A. Vucetich; Michelle L. Lute; Stewart Breck; Beatrice Frank; Dana Hoag; et al. (Conservation Biology, 2026)
Human–carnivore coexistence is essential for biodiversity conservation, yet measuring the attitudes and behaviors that support it remains methodologically challenging. We developed psychometric scales to assess willingness to coexist with carnivores and the underlying beliefs of this coexistence through an iterative expert elicitation process grounded in risk perception theory and moral psychology to ensure strong content validity. The scales measure willingness to coexist and encompass individual and collective behaviors and their cognitive antecedents: perceived positive consequences, perceived negative consequences, and ethical considerations. We validated the scales based on three representative samples of Colorado residents ( n = 434, 442, 433) focused on gray wolves ( Canis lupus ), mountain lions ( Puma concolor ), and black bears ( Ursus americanus ). Validation involved expert review, cognitive interviews, confirmatory factor analyses, and measurement invariance testing across species. The scales demonstrated strong construct validity, with factor structures consistent with theoretical expectations and evidence of convergent and discriminant validity. Concurrent validity was supported through associations with related attitudes and behavioral intentions. These instruments offer researchers a robust, theory‐driven framework for examining human–wildlife interactions that facilitates standardized comparisons across species and contexts. For practitioners, the psychometric scales provide a practical means to assess public readiness for coexistence, monitor attitudinal change over time, and design interventions tailored to specific belief structures.

Resilience thinking for human–wildlife coexistence: Bridging dynamic systems, archetypes, and transformations - Neil H. Carter; Erin K. Buchholtz; Jenny Anne Glikman; A. Sofía Nanni; Mahi Puri (Ambio, 2026)

Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration - Nikhil N. Chaudhari; Owen M. Vega; Phoebe Imms; Jaron M. Kawamura; Nahian F. Chowdhury; Tamara Jafar; Andrei Irimia; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2026)
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can find aging-related structural alterations above and beyond cortical thickness and atrophy. Using a novel approach to DNN interpretability, we mapped brain aging progression in 25,539 cognitively normal UK Biobank adults aged 45–83 years. Cortical aging is found to involve anatomic features becoming prominent during the 50s within frontolateral, mesolimbic, cuneal, and occipitotemporal regions. From these foci, aging-related features propagate to adjacent areas at rates peaking in the 60s. Cortical thinning and atrophy do not trend closely with neurodegeneration, but important DNN-identifiable anatomic features have spatiotemporal dynamics that match those of amyloid or tau. Our results challenge the assumption that MRI cannot map anatomic features trending with neurodegeneration. Interpretable DNNs can empower MRI to quantify anatomic aging as a process of spatial feature expansion from focal regions into nearby structures in the sequence of neurodegenerative pathology. Traditional morphometrics explain only ∼1% of variance in DNN-identifiable features, which clarifies why the former are insensitive to anatomic changes involving neurodegeneration. Our results conceptualize brain aging in the context of spatial and temporal parallels between anatomic senescence and neuropathology. These findings may help to map cognitively normal adults’ neurodegenerative anatomy even without PET measurements. Graphical Abstract

Sex and APOE genotype specific brain regional vulnerability to Alzheimer's Disease - Qi Zeng; Minghui Wang; Erming Wang; Xianxiao Zhou; Peng Xu; Vahram Haroutunian; Dongming Cai; Bin Zhang; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2026)
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), and regional vulnerability was assessed with a composite vulnerability score (CVS) derived from associations between diffusion features and AD severity across clinical traits in each of the four sex-APOE groups (female or male, with or without APOE4). Brain parcellation with the Eve atlas revealed regions consistently affected across sex-APOE groups (e.g., parahippocampal and superior temporal gyri) and regions specific to individual groups (e.g., the cingulum in females with APOE4 and the middle frontal gyrus in males without APOE4). Gene co-expression network analysis of the matched blood expression data identified gene subnetworks linked to group-specific regional vulnerability, including a muscle tissue morphogenesis module regulated by NEURL1B and HIST1H2BN associated with middle frontal gyrus vulnerability. These findings demonstrate that sex and APOE genotype jointly shape region-specific WM vulnerability and its molecular signatures in AD. Understanding these interactions provides novel mechanistic insights and may inform precision approaches to drug development, biomarker discovery, and clinical trial design for AD.

Beyond procedural justice for coexistence with biodiversity: Response to Pooley (2024) - JeremyT. Bruskotter; Neil H. Carter; Matthew Hamilton; John A. Vucetich (Conservation Biology, 2026)

Vulnerability of marine megafauna to global at‐sea anthropogenic threats - Michelle VanCompernolle; Juliet Morris; Hannah J. Calich; Jorge P. Rodríguez; Sarah A. Marley; Jessica R. Pearce; Briana Abrahms; Katya Abrantes; André S. Afonso; Alex Aguilar; Andrews Agyekumhene; Tomonari Akamatsu; et al. (Conservation Biology, 2026)
Marine megafauna species are affected by a wide range of anthropogenic threats. To evaluate the risk of such threats, species’ vulnerability to each threat must first be determined. We build on the existing threats classification scheme and ranking system of the International Union for Conservation of Nature (IUCN) Red List of Threatened Species by assessing the vulnerability of 256 marine megafauna species to 23 at‐sea threats. The threats we considered included individual fishing gear types, climate‐change‐related subthreats not previously assessed, and threats associated with coastal impacts and maritime disturbances. Our ratings resulted in 70 species having high vulnerability ( v > 0.778 out of 1) to at least 1 threat, primarily drifting longlines, temperature extremes, or fixed gear. These 3 threats were also considered to have the most severe effects (i.e., steepest population declines). Overall, temperature extremes and plastics and other solid waste were rated as affecting the largest proportion of populations. Penguins, pinnipeds, and polar bears had the highest vulnerability to temperature extremes. Bony fishes had the highest vulnerability to drifting longlines and plastics and other solid waste; pelagic cetaceans to 4 maritime disturbance threats; elasmobranchs to 5 fishing threats; and flying birds to drifting longlines and 2 maritime disturbance threats. Sirenians and turtles had the highest vulnerability to at least one threat from all 4 categories. Despite not necessarily having severe effects for most taxonomic groups, temperature extremes were rated among the top threats for all taxa except bony fishes. The vulnerability scores we provide are an important first step in estimating the risk of threats to marine megafauna. Importantly, they help differentiate scope from severity, which is key to identifying threats that should be prioritized for mitigation.

Restoring the wild east: Predicting public support for cougar and red wolf reintroduction in the eastern United States - Benjamin Ghasemi; Jeremy T. Bruskotter; John A. Vucetich; L. Mark Elbroch; Robyn S. Wilson; Neil H. Carter; Axel Moehrenschlager; Shelby Perry; Joseph W. Hinton (Biological Conservation, 2026)

Methyl-processing metabolisms play central roles in methane cycling during rice cultivation - Raegan Paul; Emily K. Bechtold; Jared Ellenbogen; Reed Woyda; Thomas Holloway; Neil Carter; George Heslop-Harrison; Kelly C. Wrighton; Michael J. Wilkins (Agriculture, Ecosystems & Environment, 2026)

Surface-based morphometry reveals divergent aging trajectories in veterans with and without traumatic brain injury - Michelle C. Eliason; Amrutha Bindu Nagella; Cristian Cuadra; David S. Wack; Ghazala T. Saleem; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowki; Arthur W. Toga; et al. (GeroScience, 2025)

Bridging social and ecological science to create spatially explicit models of human-caused mortality of carnivores - Jeremy T. Bruskotter; Neil H. Carter; Richard Berl; Joseph Hinton; Jazmin Murphy; L. Mark Elbroch; John A. Vucetich (Ambio, 2025)
Research indicates that human-caused mortality (HCM) is a key factor limiting numerous large carnivore populations. However, efforts to represent HCM in spatially explicit models have generally been limited in scope—often relying on proxies, such as road or human density. Yet such efforts fail to distinguish different sources of HCM, which can arise from different antecedent processes. We offer a systems-based conceptual framework for understanding the antecedents of HCMs that is grounded in theory from the social and behavioral sciences. Specifically, we first explain how HCMs are usefully distinguished into four types (e.g., accidental, harvest, illicit, control actions), then discuss how these different types tend to be driven by different sets of psychological and sociopolitical processes. We contend that improvements in understanding the spatial variation in HCMs would rise from more explicit attention to the various antecedent processes that precede each mortality type.

Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning - Marthe Mieling; Mushfa Yousuf; Nico Bunzeck; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; Susan Landau; Monica Rivera-Mindt; Leslie M. Shaw; Edward B. Lee; et al. (GeroScience, 2025)
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70–77% accuracy and 61–83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

Voxel-wise insights into early Alzheimer’s disease pathology progression: the association with APOE and memory decline - Maha Wybitul; Nicolas Langer; Christoph Hock; Anton Gietl; Valerie Treyer; Michael Weiner; Paul Aisen; Ronald-Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowski; Arthur W. Toga; et al. (GeroScience, 2025)
Longitudinal investigation of the Apolipoprotein E (APOE) genotype’s impact on Alzheimer’s disease (AD) biomarker progression, focusing on amyloid beta (Aβ) accumulation and gray matter (GM) atrophy, integrating cognitive decline and baseline levels. Longitudinal florbetapir-PET and T1-weighted MRI data from 100 cognitively normal (CN) and mild cognitive impaired (MCI) participants both with considerable global Aβ accumulation (“high Aβ accumulators”) were analyzed using a voxel-wise approach. Associations of APOE genotype and memory decline with Aβ accumulation and GM atrophy were examined separately for each neuroimaging modality, controlling for baseline Aβ levels and diagnosis. Alternatively, the effect of baseline diagnosis, while controlling for memory decline, was investigated. A multimodal analysis evaluated interactions between genotype, memory decline, and GM atrophy on Aβ accumulation. High Aβ accumulators displayed extensive Aβ pathology predominantly in the medial orbito-frontal cortex, cingulate cortex, and precuneus, along with GM atrophy in temporal, occipital, orbito-frontal, and parietal areas. ɛ4 carriers with memory decline exhibited greater Aβ accumulation and GM atrophy in selective regions compared to non-carriers with memory decline, while no genotype difference was observed in individuals without decline. No interaction effect was observed for MCI diagnosis. Regional associations between the two biomarkers were similarly dependent on genotype and memory decline. ɛ4 carriers exhibiting memory decline present an accelerated neurobiological pattern at predementia stages, supporting early ɛ4 carrier monitoring and interventions in this at-risk group. Importantly, memory decline might be more informative than MCI regarding AD pathology progression emphasizing the importance of repeated cognitive assessments.

Dynamic proportional loss of functional connectivity revealed change of left superior frontal gyrus in subjective cognitive decline: an explanatory study based on Chinese and Western cohorts - Luyao Wang; Wenjing Hu; Fan Dong; Can Sheng; Jinglong Wu; Ying Han; Jiehui Jiang; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2025)

Complementary value of molecular, phenotypic, and functional aging biomarkers in dementia prediction - Andreas Engvig; Karl Trygve Kalleberg; Lars T. Westlye; Esten Høyland Leonardsen; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowski; Arthur W. Toga; Laurel Beckett; et al. (GeroScience, 2024)
DNA methylation age (MA), brain age (BA), and frailty index (FI) are putative aging biomarkers linked to dementia risk. We investigated their relationship and combined potential for prediction of cognitive impairment and future dementia risk using the ADNI database. Of several MA algorithms, DunedinPACE and GrimAge2, associated with memory, were combined in a composite MA alongside BA and a data-driven FI in predictive analyses. Pairwise correlations between age- and sex-adjusted measures for MA (aMA), aBA, and aFI were low. FI outperformed BA and MA in all diagnostic tasks. A model including age, sex, and aFI achieved an area under the curve (AUC) of 0.94 for differentiating cognitively normal controls (CN) from dementia patients in a held-out test set. When combined with clinical biomarkers (apolipoprotein E ε4 allele count, memory, executive function), a model including aBA and aFI predicted 5-year dementia risk among MCI patients with an out-of-sample AUC of 0.88. In the prognostic model, BA and FI offered complementary value (both β s 0.50). The tested MAs did not improve predictions. Results were consistent across FI algorithms, with data-driven health deficit selection yielding the best performance. FI had a stronger adverse effect on prognosis in males, while BA’s impact was greater in females. Our findings highlight the complementary value of BA and FI in dementia prediction. The results support a multidimensional view of dementia, including an intertwined relationship between the biomarkers, sex, and prognosis. The tested MA’s limited contribution suggests caution in their use for individual risk assessment of dementia.

Local molecular and connectomic contributions of tau-related neurodegeneration - Fardin Nabizadeh; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowski; Arthur W. Toga; Laurel Beckett; Robert C. Green; Andrew J. Saykin; John Morris; et al. (GeroScience, 2024)

Jaguar conservation is caught in the crossfire of America's 'War on Drugs' - Nicholas R. Magliocca; Neil H. Carter; Jennifer A. Devine; Erik A. Nielsen; Steven E. Sesnie (Biological Conservation, 2024)

Predictions & perceptions: A social-ecological analysis of human-carnivore conflict in Botswana - Dylan E. Feldmeier; Oswald J. Schmitz; Neil H. Carter; Gaseitsiwe S. Masunga; Kaggie D. Orrick (Biological Conservation, 2024)

Sex differences in interacting genetic and functional connectivity biomarkers in Alzheimer’s disease - Jordan N. Williamson; Shirley A. James; Sean P. Mullen; Bradley P. Sutton; Tracey Wszalek; Beni Mulyana; Peter Mukli; Andriy Yabluchanskiy; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2024)

Glucose metabolism in posterior cingulate cortex has supplementary value to predict the progression of cognitively unimpaired to dementia due to Alzheimer’s disease: an exploratory study of 18F-FDG-PET - Qi Zhang; Chunqiu Fan; Luyao Wang; Taoran Li; Min Wang; Ying Han; Jiehui Jiang; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2023)

Pulsed ultraviolet (PUV) disinfection of artificially contaminated seawater seeded with high levels of pathogen disease indicators as an alternative for the shellfish industry depuration systems - Gustavo Waltzer Fehrenbach; Emma Murphy; Robert Pogue; Frank Carter; Eoghan Clifford; Ian Major; Neil Rowan (Environmental Science and Pollution Research, 2023)
The increase in pathogen levels in seawater threatens the safety of entire aquatic ecosystems. Foodborne pathogens can potentially accumulate in shellfish, especially in filter feeders such as bivalves, requiring an efficient depuration process before consumption. Alternative approaches to promote a cost-efficient purge at depuration plants are urgently needed. A small prototype pulsed ultraviolet (PUV) light recirculation system was designed, and its depuration potential was tested in a seawater matrix artificially contaminated with high levels of microbial pathogens Escherichia coli , Staphylococcus aureus , Salmonella typhimurium , Bacillus cereus and Candida albicans . The analysis of treatment parameters including voltage, number of pulses and duration of treatment was performed to ensure the highest reduction in contaminant levels. Optimal PUV disinfection was attained at 60 pulses/min at 1 kV for 10 min (a UV output of 12.9 J/cm 2 ). All reductions were statistically significant, and the greatest was observed for S. aureus (5.63 log 10 ), followed by C. albicans (5.15 log 10 ), S. typhimurium (5 log 10 ), B. cereus (4.59 log 10 ) and E. coli (4.55 log 10 ). PUV treatment disrupted the pathogen DNA with the result that S. aureus , C. albicans and S. typhimurium were not detectable by PCR. Regulations were reviewed to address the applicability of PUV treatment as a promising alternative to assist in the reduction of microbial pathogens at depuration plants due to its high efficiency, short treatment period, high UV dose and recirculation system as currently employed in shellfish depuration plants.

Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment - Jiehui Jiang; Can Sheng; Guanqun Chen; Chunhua Liu; Shichen Jin; Lanlan Li; Xueyan Jiang; Ying Han; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2022)

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume - Lidija Milicic; Michael Vacher; Tenielle Porter; Vincent Doré; Samantha C. Burnham; Pierrick Bourgeat; Rosita Shishegar; James Doecke; Nicola J. Armstrong; Rick Tankard; Paul Maruff; Colin L. Masters; et al. (GeroScience, 2022)
The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes.

Applying Mendelian randomization to appraise causality in relationships between nutrition and cancer - Kaitlin H. Wade; James Yarmolinsky; Edward Giovannucci; Sarah J. Lewis; Iona Y. Millwood; Marcus R. Munafò; Fleur Meddens; Kimberley Burrows; Joshua A. Bell; Neil M. Davies; Daniela Mariosa; Noora Kanerva; et al. (Cancer Causes & Control, 2022)
Dietary factors are assumed to play an important role in cancer risk, apparent in consensus recommendations for cancer prevention that promote nutritional changes. However, the evidence in this field has been generated predominantly through observational studies, which may result in biased effect estimates because of confounding, exposure misclassification, and reverse causality. With major geographical differences and rapid changes in cancer incidence over time, it is crucial to establish which of the observational associations reflect causality and to identify novel risk factors as these may be modified to prevent the onset of cancer and reduce its progression. Mendelian randomization (MR) uses the special properties of germline genetic variation to strengthen causal inference regarding potentially modifiable exposures and disease risk. MR can be implemented through instrumental variable (IV) analysis and, when robustly performed, is generally less prone to confounding, reverse causation and measurement error than conventional observational methods and has different sources of bias (discussed in detail below). It is increasingly used to facilitate causal inference in epidemiology and provides an opportunity to explore the effects of nutritional exposures on cancer incidence and progression in a cost-effective and timely manner. Here, we introduce the concept of MR and discuss its current application in understanding the impact of nutritional factors (e.g., any measure of diet and nutritional intake, circulating biomarkers, patterns, preference or behaviour) on cancer aetiology and, thus, opportunities for MR to contribute to the development of nutritional recommendations and policies for cancer prevention. We provide applied examples of MR studies examining the role of nutritional factors in cancer to illustrate how this method can be used to help prioritise or deprioritise the evaluation of specific nutritional factors as intervention targets in randomised controlled trials. We describe possible biases when using MR, and methodological developments aimed at investigating and potentially overcoming these biases when present. Lastly, we consider the use of MR in identifying causally relevant nutritional risk factors for various cancers in different regions across the world, given notable geographical differences in some cancers. We also discuss how MR results could be translated into further research and policy. We conclude that findings from MR studies, which corroborate those from other well-conducted studies with different and orthogonal biases, are poised to substantially improve our understanding of nutritional influences on cancer. For such corroboration, there is a requirement for an interdisciplinary and collaborative approach to investigate risk factors for cancer incidence and progression.

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.

Artificial night light and anthropogenic noise interact to influence bird abundance over a continental scale - Ashley A. Wilson; Mark A. Ditmer; Jesse R. Barber; Neil H. Carter; Eliot T. Miller; Luke P. Tyrrell; Clinton D. Francis (Global Change Biology, 2021)
The extent of artificial night light and anthropogenic noise (i.e., “light” and “noise”) impacts is global and has the capacity to threaten species across diverse ecosystems. Existing research involving impacts of light or noise has primarily focused on noise or light alone and single species; however, these stimuli often co‐occur and little is known about how co‐exposure influences wildlife and if and why species may vary in their responses. Here, we had three aims: (1) to investigate species‐specific responses to light, noise, and the interaction between the two using a spatially explicit approach to model changes in abundance of 140 prevalent bird species across North America, (2) to investigate responses to the interaction between light exposure and night length, and (3) to identify functional traits and habitat affiliations that explain variation in species‐specific responses to these sensory stimuli with phylogenetically informed models. We found species that responded to noise exposure generally decreased in abundance, and the additional presence of light interacted synergistically with noise to exacerbate its negative effects. Moreover, the interaction revealed negative emergent responses for several species that only reacted when light and noise co‐occurred. Additionally, an interaction between light and night length revealed 47 species increased in abundance with light exposure during longer nights. In addition to modifying behavior with optimal temperature and potential foraging opportunities, birds might be attracted to light, yet suffer inadvertent physiological consequences. The trait that most strongly related to avian response to light and noise was habitat affiliation. Specifically, species that occupy closed habitat were less tolerant of both sensory stressors compared to those that occupy open habitat. Further quantifying the contexts and intrinsic traits that explain how species respond to noise and light will be fundamental to understanding the ecological consequences of a world that is ever louder and brighter.

SNAPSHOT USA 2019: a coordinated national camera trap survey of the United States - Michael V. Cove; Roland Kays; Helen Bontrager; Claire Bresnan; Monica Lasky; Taylor Frerichs; Renee Klann; Thomas E. Lee; Seth C. Crockett; Anthony P. Crupi; Katherine C. B. Weiss; Helen Rowe; et al. (Ecology, 2021)
With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14‐week period (17 August–24 November of 2019). We sampled wildlife at 1,509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian’s eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the United States. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban–wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot‐usa, as will future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species‐specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication.

Emergent conservation outcomes of shared risk perception in human‐wildlife systems - Neil H. Carter; Andres Baeza; Nicholas R. Magliocca (Conservation Biology, 2020)
Human perception of risks related to economic damages caused by nearby wildlife can be transmitted through social networks. Understanding how sharing risk information within a human community alters the spatial dynamics of human‐wildlife interactions has important implications for the design and implementation of effective conservation actions. We developed an agent‐based model that simulates farmer livelihood decisions and activities in an agricultural landscape shared with a population of a generic wildlife species (wildlife‐human interactions in shared landscapes [WHISL]). In the model, based on risk perception and economic information, farmers decide how much labor to allocate to farming and whether and where to exclude wildlife from their farms (e.g., through fencing, trenches, or vegetation thinning). In scenarios where the risk perception of farmers was strongly influenced by other farmers, exclusion of wildlife was widespread, resulting in decreased quality of wildlife habitat and frequency of wildlife damages across the landscape. When economic losses from encounters with wildlife were high, perception of risk increased and led to highly synchronous behaviors by farmers in space and time. Interactions between wildlife and farmers sometimes led to a spillover effect of wildlife damage displaced from socially and spatially connected communities to less connected neighboring farms. The WHISL model is a useful conservation‐planning tool because it provides a test bed for theories and predictions about human‐wildlife dynamics across a range of different agricultural landscapes.

Governing trade‐offs in ecosystem services and disservices to achieve human–wildlife coexistence - Silvia Ceauşu; Rose A. Graves; Alexander K. Killion; Jens‐Christian Svenning; Neil H. Carter (Conservation Biology, 2019)
Sustaining wildlife populations, which provide both ecosystem services and disservices, represents a worldwide conservation challenge. The ecosystem services and Ostrom's social–ecological systems frameworks have been adopted across natural and social sciences to characterize benefits from nature. Despite their generalizability, individually they do not include explicit tools for addressing the sustainable management of many wildlife populations. For instance, Ostrom's framework does not specifically address competing perspectives on wildlife, whereas the ecosystem services framework provides a limited representation of the social and governance context wherein such competing perspectives are embedded. We developed a unified social–ecological framework of ecosystem disservices and services (SEEDS) that advances both frameworks by explicitly acknowledging the importance of competing wildlife perspectives embedded in the social and governance contexts. The SEEDS framework emulates the hierarchical structure of Ostrom's social–ecological systems, but adds subsystems reflecting heterogeneous stakeholder views and experiences of wildlife‐based services and disservices. To facilitate operationalizing SEEDS and further broader analyses across human–wildlife systems, we devised a list of variables to describe SEEDS subsystems, such as types and level of services and disservices, cost and benefit sharing, and social participation of stakeholders. Steps to implement SEEDS involve engaging local communities and stakeholders to define the subsystems, analyze interactions and outcomes, and identify leverage points and actions to remedy unwanted outcomes. These steps connect SEEDS with other existing approaches in social–ecological research and can guide analyses across systems or within individual systems to provide new insights and management options for sustainable human–wildlife coexistence.

Tracking a half century of media reporting on gray wolves - Alexander K. Killion; Tracy Melvin; Eric Lindquist; Neil H. Carter (Conservation Biology, 2019)
Natural resource and wildlife managers must balance the disparate priorities of a diversity of stakeholders. To manage these priorities, a firm understanding of topics salient to the public is needed. The media often report on issues of importance to the public; therefore, these reports may be a useful measure of public interest. However, efficient methods for distinguishing diverse topics related to a wildlife management issue reported in the media and changes in the salience of those topics have been lacking. We used latent Dirichlet allocation, a Bayesian mixture model, to quantitatively assess the salience of topics surrounding the gray wolf ( Canis lupus ), which was reintroduced to Idaho (U.S.A.) in 1995. We analyzed articles published from 1960 to 2015 in an Idaho newspaper. We identified 6 distinct topics associated with gray wolves: policy, hunting, biological status, implementation of management, recovery, and human‐wolf conflict. The salience of topics pre‐ and postreintroduction of wolves (1995) and pre‐ and postdelisting of wolves from the U.S. Endangered Species Act (2009) differed significantly, underscoring that these events were turning points in how issues were being publicly discussed and framed. Articles written by the local reporters were more likely to report on topics regarding conflict between humans and wolves, whereas articles sourced from a national outlet reported more on topics pertaining to wolf policy and biological status. In the context of managing a contentious, far‐ranging, and long‐lived wildlife species, our methods can help guide the location and timing of a suite of management strategies (e.g., media relation plans and stakeholder engagement) that promote human‐wildlife coexistence across different landscapes.

Climate change, disease range shifts, and the future of the Africa lion - Neil H. Carter; Paola Bouley; Sean Moore; Michael Poulos; Jérémy Bouyer; Stuart L. Pimm (Conservation Biology, 2018)
Article impact statement : Understanding causes and consequences of disease range shifts can help mitigate negative effects of such shifts on lions and other wildlife.

A conceptual framework for understanding illegal killing of large carnivores - Neil H. Carter; José Vicente López-Bao; Jeremy T. Bruskotter; Meredith Gore; Guillaume Chapron; Arlyne Johnson; Yaffa Epstein; Mahendra Shrestha; Jens Frank; Omar Ohrens; Adrian Treves (Ambio, 2017)

Reduced motor preparation during dual-task performance: evidence from startle - Dana Maslovat; Neil M. Drummond; Michael J. Carter; Anthony N. Carlsen (Experimental Brain Research, 2015)

Spatial Assessment of Attitudes Toward Tigers in Nepal - Neil H. Carter; Shawn J. Riley; Ashton Shortridge; Binoj K. Shrestha; Jianguo Liu (Ambio, 2014)

Pacific Rim Forestry / Silviculture and Forest Ecology - Vishal Singh Negi; Archana Pal; Ratnesh Singh; Dulal Borthakur; Archana Pala; Vishal Singh Negi; Dulal Borthakur; Isabel Rushanaedy; Tyler Jones; Nicklos Dudley; Dulal Borthakur; Jannai Yafuso; et al. (Journal of Forestry, 2011)
Leucaena leucocephala (leucaena) is an important agroforestry tree of tropics and subtropics due to its protein rich foliages, ability to grow on poor soils, and high level of tolerance to various stresses including drought and diseases. We hypothesized that leucaena have a unique set of genes which confer tolerance to various abiotic and biotic stresses and these genes are either absent or not expressed in other legumes that are susceptible to these stress conditions. Interspecies suppression subtractive hybridization (iSSH) was performed to identify some unique genes from leucaena using cDNAs from leucaena and Acacia confusa (acacia) as the tester and driver, respectively. We identified 100 leucaena genes showing homology to various plant genes with known functions, of which 23 genes had homology to various stress-related proteins including chitinase, PR-10 protein, wound-stress protein, type-2 metallothionein, thaumatin-like protein, disease resistance response protein, cysteine proteinase, and kunitz trypsin inhibitor. We also identified 50 leucaena genes which either had homology to hypothetical proteins (HyPs) or had no homology at all. Putative functions of 15 HyPs were predicted using conserved domain and PSI-BLAST analyses. Linear motif analyses identified 17 HyPs with MAPK recognition motif, which is involved in signaling pathways, including stress responses. This study identified 23 known and some putative unique stress-related genes from leucaena which may serve as a useful source of stress-tolerance genes for tree and crop improvement in the future.

Genome-wide association analysis of canine atopic dermatitis and identification of disease related SNPs - Shona Hiedi Wood; Xiayi Ke; Tim Nuttall; Neil McEwan; William E. Ollier; Stuart D. Carter (Immunogenetics, 2009)