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1. A novel generalized spatial mark‐resight model that accounts for group associations

   https://doi.org/10.1111/2041-210x.70271  

   Meyer, Connor J; Whittington, Jesse; Tourani, Mahdieh; Hebblewhite, Mark (April 2026, Methods in Ecology and Evolution)

   Abstract The number and distribution of animals in space form the basis of many wildlife studies. Yet, reliable estimation of population abundance remains challenging. Generalized spatial mark‐resight (gSMR) models are widely applicable abundance estimators that do not require all individuals be uniquely identifiable. Despite their flexibility, gSMR models assume independence in distribution and detections of individuals throughout space. Group‐living species that aggregate (i.e. share activity centres) and move cohesively (i.e. share detections) violate these assumptions, limiting the applicability of gSMR models to solitary species with limited home range overlap.We developed a gSMR model that accounts for group associations to estimate spatial abundance. We treated groups as the measurable ‘units’ and included a submodel that uses Poisson processes to estimate group size. We conducted a simulation study to compare our novel group‐based gSMR to a gSMR that ignores group associations. We generated data across varying levels of aggregation and cohesion parameters. We then quantified and compared the precision and bias of parameter estimates between the two models.The group‐based gSMR model outperformed the individual‐based gSMR under all aggregation and cohesion scenarios. Group‐based 95% Bayesian Credible Intervals (BCI) overlapped the true value of abundance in 91% of simulations, compared to only 15% of simulations in the individual‐based gSMR. Both the group‐based and individual‐based models became less precise and more biased as aggregation and group size increased. However, the group‐based gSMR model was less biased in estimating all parameters when compared to the individual‐based gSMR model.We applied our group‐based gSMR model to grey wolf (Canis lupus) monitoring data within a Canadian national park complex (Banff, Yoho and Kootenay National Parks, and Ya Ha Tinda). We used 12 years (2012–2023) of remote camera data, along with information from GPS radio‐collared wolves (N = 16) to estimate spatiotemporal variation in abundance. Over a 12‐year period, wolf abundance averaged 73 (95% BCI = 20–207) individuals, and a density of 6.69 (95% BCI = 1.83–19.0) wolves per 1000 km²within the park complex. Our novel group‐based gSMR model extends the applicability of spatial mark‐resight to species with group associations. 

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2. Are Simulated Ocean Deoxygenation Rates Consistent with the Observational Reconstructions?

   https://doi.org/10.1146/annurev-earth-032524-123111  

   Ito, Takamitsu; Takano, Yohei; Eddebbar, Yassir A; Tiputra, Jerry F; Wang, Zhankun; Minobe, Shoshiro; Cheng, Lijing; Du, Juan; Abe, Yumi (May 2026, Annual Review of Earth and Planetary Sciences)

   It is currently debated whether Earth system models (ESMs) can reproduce observation-based long-term changes in global and regional deoxygenation rates. Both models and observations include uncertainties, which must be considered when evaluating their consistency. Based on 14 ESMs and 6 observational datasets, the models’ climatological annual mean oxygen matches observations well near the surface. However, significant biases remain in the tropics and in the thermocline. Based on the same set of models and three time-varying observation-based datasets, the models tend to underestimate deoxygenation trends from 1965 to 2014, except for the North Atlantic basin. However, the small number of observational datasets limits this conclusion. One dataset appears to significantly underestimate deoxygenation due to sparse data coverage. This review highlights the need for improvements in model process representations and the development of more observation-based, quality-controlled datasets to better constrain and interpret oxygen changes in the ocean.▪Uncertainties of dissolved oxygen field in CMIP6 ESMs and observational reconstructions are quantified.▪The ESMs can skillfully reproduce long-term average oxygen near the surface, but challenges remain in the thermocline and tropics.▪The ESMs underestimate the deoxygenation trends except for the North Atlantic basin. 

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3. Planning for the future: Grasslands, herbivores, and nature‐based solutions

   https://doi.org/10.1111/1365-2745.14323  

   Borer, Elizabeth T; Risch, Anita C (November 2024, Journal of Ecology)

   Abstract Global interest and investment in nature‐based solutions (NbS) are rapidly increasing because of the potential of this approach to concurrently counter biodiversity loss, provide cost‐effective measures for climate change adaptations, and maintain natural processes that underpin human health and wellbeing.Recognition is growing that grasslands in many regions will protect carbon stores more effectively than forests in the warmer, drier, more fire‐prone conditions of the future while also serving as hotspots for biodiversity. Yet grasslands have received less attention for their NbS potential. Despite the wide‐ranging goals of this approach, many investments in nature‐based solutions also have focused narrowly on using plants to meet climate pledges, often without considering plant interactions with herbivores and the abiotic environment that jointly control ecosystem functioning and underpin the success of nature‐based solutions.Here, we review the roles that large and small vertebrate and invertebrate herbivores play in the ability of the world's grasslands to provide nature‐based solutions, with a focus on wild herbivore impacts on biodiversity and carbon storage.Synthesis. Planning for nature‐based solutions with a holistic, ecologically informed view that includes the role of herbivores and their interaction with plants and the environment will allow NbS investments to more likely achieve successful, sustainable outcomes. 

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4. P-PIM: A Parallel Processing-in-DRAM Framework Enabling Row Hammer Protection

   https://doi.org/10.23919/DATE56975.2023.10137204  

   Zhou, Ranyang; Tabrizchi, Sepehr; Morsali, Mehrdad; Roohi, Arman; Angizi, Shaahin (April 2023, 2023 Design, Automation & Test in Europe Conference (DATE 2023))

   In this work, we propose a Parallel Processing-In-DRAM architecture named P-PIM leveraging the high density of DRAM to enable fast and flexible computation. P-PIM enables bulk bit-wise in-DRAM logic between operands in the same bit-line by elevating the analog operation of the memory sub-array based on a novel dual-row activation mechanism. With this, P-PIM can opportunistically perform a complete and inexpensive in-DRAM RowHammer (RH) self-tracking and mitigation technique to protect the memory unit against such a challenging security vulnerability. Our results show that P-PIM achieves ~72% higher energy efficiency than the fastest charge-sharing-based designs. As for the RH protection, with a worst-case slowdown of ~0.8%, P-PIM archives up to 71% energy-saving over the SRAM/CAM-based frameworks and about 90% saving over DRAM-based frameworks. 

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5. Conceptualizing Indigenous strengths-based health and wellness research using group concept mapping

   https://doi.org/10.1186/s13690-023-01066-7  

   O’Keefe, Victoria M; Maudrie, Tara L; Cole, Ashley B; Ullrich, Jessica S; Fish, Jillian; Hill, Kyle X; White, Lauren A; Redvers, Nicole; Jernigan, Valarie_Blue Bird; Lewis, Jordan P; et al (December 2023, Archives of Public Health)

   Abstract BackgroundIn recent years public health research has shifted to more strengths or asset-based approaches to health research but there is little understanding of what this concept means to Indigenous researchers. Therefore our purpose was to define an Indigenous strengths-based approach to health and well-being research. MethodsUsing Group Concept Mapping, Indigenous health researchers (N = 27) participated in three-phases. Phase 1: Participants provided 218 unique responses to the focus prompt “Indigenous Strengths-Based Health and Wellness Research…” Redundancies and irrelevant statements were removed using content analysis, resulting in a final set of 94 statements. Phase 2: Participants sorted statements into groupings and named these groupings. Participants rated each statement based on importance using a 4-point scale. Hierarchical cluster analysis was used to create clusters based on how statements were grouped by participants. Phase 3: Two virtual meetings were held to share and invite researchers to collaboratively interpret results. ResultsA six-cluster map representing the meaning of Indigenous strengths-based health and wellness research was created. Results of mean rating analysis showed all six clusters were rated on average as moderately important. ConclusionsThe definition of Indigenous strengths-based health research, created through collaboration with leading AI/AN health researchers, centers Indigenous knowledges and cultures while shifting the research narrative from one of illness to one of flourishing and relationality. This framework offers actionable steps to researchers, public health practitioners, funders, and institutions to promote relational, strengths-based research that has the potential to promote Indigenous health and wellness at individual, family, community, and population levels. 

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