Greenland’s peripheral glaciers and ice caps contribute disproportionately to sea-level rise relative to their small area. Winter snow accumulation directly influences glacier mass balance and downstream hydrology, but spatially extensive observations of this important mass balance component remain sparse. In this study, we present a unique multi-year (2008–2024) dataset of winter snow accumulation over A.P. Olsen Ice Cap, Northeast Greenland, from ground-penetrating radar surveys covering an average of 47 km per survey year. Our results reveal strong spatial heterogeneity that is likely influenced by wind redistribution and local topography, especially in the ablation zone. We compare our findings with automatic weather station data from three sites and outputs from the Copernicus Arctic Regional Reanalysis (CARRA). Governed by the high spatial variability, the automatic weather station point-based observations significantly underestimate regional accumulation by 40–45%. Despite the high spatial variability, the CARRA accumulated precipitation variable provides a reasonable overall mean winter snow accumulation (RMSE of 0.07 m w.e.); however, it fails to reproduce the complex non-linear relationship between snow depth and elevation observed in the radar data. Our findings emphasize the need for high-resolution, spatially extensive measurements to better understand snow accumulation on ice caps and glaciers and improve reanalysis assessments.

Al-Hoorie, Hiver, and In’nami (2024) offer compelling arguments for why L2 motivational self-system research is currently in a state of validation crisis. Seeking a constructive resolution to the crisis, in this response we argue that two fundamental conditions are needed for the field to emerge stronger: psychological readiness and methodological maturity. For psychological readiness, we call for a reframing of the “crisis” narrative. We highlight the need to value controversy, to normalize failure and (self-)correction, and to resist the allure of novelty. For methodological maturity, we suggest that an argument-based approach to validation can provide a constructive solution to current controversies. We present an integrated framework that can guide systematic validation efforts, and we demonstrate its application using a recent validation study as an example.

Small-leaf spiderwort (Tradescantia fluminensis Vell.) is a low-growing perennial ground cover that has become increasingly problematic in Florida due to its ability to quickly spread vegetatively over large areas and outcompete native vegetation. Prior research has identified several herbicides that can be used to manage T. fluminensis, but the effect of application timing on herbicidal efficacy is unknown. Therefore, the objective of this study was to evaluate the efficacy of selected postemergence herbicide applications and to understand differences in the efficacy of these timings (i.e., spring and fall), including on the rate of regrowth of target plants. Specific herbicides evaluated in this study included 2,4-D, 2,4-D + triclopyr amine, aminopyralid, glyphosate, and triclopyr (as acid and amine). An additional aspect of this study was to reapply treatments when coverage ratings exceeded 25% to assess the impact of sequential applications when using less efficacious herbicides that might provide greater selectivity to non-target plants. Overall, the data showed that initial treatment timing had little to no impact on efficacy for most of the herbicides evaluated. Triclopyr (acid or amine) tended to provide the highest level of control and required no retreatment over a 12-mo evaluation period. Other effective options included glyphosate and 2,4-D + triclopyr amine, which provided results similar to triclopyr on most evaluation dates. The 2,4-D and aminopyralid treatments were in general the least efficacious options, requiring retreatment at either 3, 6, or 9 mo following the initial application to achieve less than 25% T. fluminensis coverage. Results indicate that practitioners would likely achieve similar levels of T. fluminensis control regardless of application timing. Data also suggest triclopyr would be the most effective option, while a low level of control would be expected with 2,4-D, even following multiple applications.

Theories, models, and frameworks (TMFs) are essential tools in dissemination and implementation (D&I) research, yet selecting and applying the most appropriate TMF is routinely a challenge, particularly for those new to the field. To address this need, we developed the Dissemination and Implementation Models in Health webtool (www.dissemination-implementation.org) a free, interactive, and evolving online resource designed to support the thoughtful use of D&I TMFs across all phases of research and practice – from planning through assessment. Created through a multi-institutional collaboration and refined using human-centered design, the webtool includes features such as logic model development, D&I TMF selection and comparison, guidance on combining and adapting models, strategies for application, and linkages to measurement tools. Since its initial release in 2014, the webtool has expanded to include over 110 D&I TMFs and new thematic content areas, including a section dedicated to health equity. It can be used in D&I trainings, proposal development, consultations, and academic coursework. Usage analytics and community feedback reflect ongoing relevance, utility, and evolving needs. The webtool continues to address a significant gap in D&I infrastructure by guiding users in selecting and operationalizing D&I TMFs, ultimately supporting more rigorous, context-sensitive translational research and practice.

This article offers a view of the prospects of nuclear fusion as a sustainable energy source, with a focus on magnetic confinement fusion and tokamaks. It highlights the key theme of integration and presents the EUROfusion programme as a model for coordinated fusion R&D in Europe while stressing the need for public–private partnerships to bridge the gap between laboratory innovation and industrial implementation. A crucial element is human capital development, i.e. the training of a new, diverse generation of scientists, engineers, and technicians. A broader educational effort is called for, with industry–academia collaboration, hands-on training, and mechanisms to retain and transfer knowledge from legacy projects such as JET.

Carbon credits have become increasingly important for supporting sustainable forest management and mitigating climate change. However, carbon projects can be challenging for local communities and smallholders to implement due to high expenses and complicated protocols. Forest projects often suffer from inefficiency, lack of transparency, and uneven benefit distribution. This study suggests a blockchain-based framework for aggregating forest carbon projects. This framework is the first in the forest sector to provide a reward mechanism for local communities or smallholders with a direct integration into an accredited registry protocol of Monitoring, Reporting, and Verification. The system combines digital identities, smart contracts, and automated incentives to improve transparency, responsibility, and trust among stakeholders. Two types of tokens are introduced: (i) Carbon Coin represents verified carbon credits within the system; and (ii) Forest Coin functions as a security token used to proportionally distribute project revenue among stakeholders. The revenue distribution was demonstrated in scenarios of afforestation, reforestation, and conservation. In addition, a web application was developed so that users can monitor project details. Unlike most blockchain carbon platforms that focus on investment and trading, this framework addresses upstream challenges, prioritising equitable benefit-sharing. The framework supports project aggregation and prioritises community ownership, advancing inclusive access to the carbon market. This study demonstrates how technological advantages can be transferred to community-driven ecological conservation.