加拿大自然资源部

Airborne laser scanning (ALS) provides spatially explicit measurements of forest height change that can support the development of climate-sensitive growth and yield models. We integrated bitemporal ALS acquisitions (2011 and 2022) with climate and topographic variables to develop age-independent height growth models in interior dry conifer forests of British Columbia, Canada. Height and height increment were derived at a 20 m resolution, models were fit for five species groups using nonlinear mixed-effects modelling with stand-level random effects and residual spatial correlation. Climatic and topographic predictors were incorporated as modifiers of the of the asymptotic height and growth-rate parameters. Validation showed a low overall bias and RMSE of 1.06-1.25 m. Compared with baseline dynamic models without environmental predictors, the climate-sensitive formulations reduced the independent validation RMSE by 3.1–9.4% across the five species groups. Height growth rates varied substantially among species groups and along climatic gradients, confirming that (1) maximum height is modulated by persistent site conditions, (2) height growth rate responds to climate gradients, and (3) several species groups exhibit optimal non-linear responses to temperature and precipitation. Summer and autumn temperature and precipitation were key drivers of growth rate for four out of five species groups. Quadratic transformations of climate predictors captured nonlinear, unimodal responses and identified climatic conditions associated with peak height growth. Wetter sites, as assessed using the topographic wetness index, were associated with greater maximum height, highlighting the role of soil moisture availability in regulating site potential in the region. Because climatic variables were summarized over a single 11-year interval, these relationships represent spatial associations with realized growth rather than interannual climate sensitivity. This framework provides a robust basis for developing next-generation growth models that incorporate ALS information and climatic sensitivity capable of supporting adaptive forest management under changing climatic conditions.

Transition-metal high-entropy oxides (TM-HEOs) are emerging as a versatile platform across anodes, cathodes, and solid-state electrolytes (SSEs) for Li- and Na-ion batteries. This review establishes a comprehensive “synthesis-structure-properties-devices” framework integrating 2019-2025 advances to link processing routes with morphology, defects, and crystallography for enhanced battery performance and safety. The review distills actionable design rules: balancing entropy stabilization with charge compensation and uniform cation mixing, controlling oxygen vacancies and local chemistry for cathodes, and applying aliovalent multi-cation strategies alongside rapid densification for solid-state electrolytes (SSEs). An interface-centric perspective is emphasized, highlighting coatings, graded or compliant interlayer, and mixed ionic-electronic networks to suppress side reactions and reduce impedance. A data-driven roadmap is proposed that couples operando characterization with automated, closed-loop processing to accelerate discovery and scale-up. Together these elements provide a coherent, cross-component playbook to convert TM-HEO promise into manufacturable LIB and NIB technologies.

The soils of mixed boreal forests can suffer a loss of productivity after logging, particularly when soil conditions are altered. Poor vegetation recovery may further lead to nutrient loss, despite increased availability following disturbance. This study investigated the effects of amendments on chemical properties of a plantation established on a site poorly regenerated by natural regeneration. Biochar (2.6 Mg ha⁻1), wood ash (7 Mg ha⁻1), and manure (105 Mg ha⁻1) were applied alone or in combination in a randomized complete block design. After two growing seasons, soil pH, total carbon, macro- and micronutrient concentrations, and CEC were measured in the mineral soil at two depths (0–15 cm and 15–30 cm). Biochar did not change total C and N but it decreased Al and CEC (-18

This study addresses a critical gap in forest management by introducing a Universal Transfer-Response Function (UTRF) to predict Lodgepole Pine (Pinus contorta var. latifola Dougl.) maximum height under varying climate conditions in British Columbia. Using long-term provenance trial data, we developed a two-stage modeling approach: first, fitting a logistic height-age curve to estimate individual tree growth potential, and second, applying a cubic polynomial UTRF incorporating site, provenance, and climate transfer variables. The model explained approximately 62% of variation in maximum height and was used to simulate future growth under multiple climate scenarios. Results indicate that southern lodgepole pine populations will experience severe declines in height growth under warming conditions, while northern populations may benefit temporarily, reflecting a northward shift in the species' climatic niche. Spatial predictions further highlight regions becoming unsuitable for lodgepole pine by 2100, emphasizing the urgency of climate-based seed transfer and assisted migration strategies. By integrating UTRF into operational growth and yield models, forest managers can simulate adaptive strategies to mitigate timber yield losses. This finding represents a significant advancement in climate-sensitive forestry modeling and provides a foundation for sustainable management under future climate uncertainty.

Rainfall-triggered debris flows represent one of the greatest growing threats to co-located populations, infrastructure, and communities on or adjacent to steep slopes worldwide. Landslide-triggering rainfall thresholds are formulated to provide practical warnings of debris flow hazards. Statistical models, intensity-duration (I-D) curves or some adaptation thereof, account for about 70