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Urban forests are gaining recognition as a nature-based solution to climate change and other social-environmental issues in cities. Yet, the integration of urban forests may conflict with other climate measures such as urban densification, which may create hostile growing conditions for trees and lead to tree decline or loss. While previous studies have identified conflicts between densification and urban forests, there is a lack of research mapping the relationships among climate action, urban planning, and urban forest policies. This study involved semi-structured interviews with 14 key informants in Metro Vancouver, Canada, a rapidly-densifying region. Twenty-six trade-offs and 24 synergies were identified in five areas/sectors, such as (re)development and infrastructure. While strategic policies often highlighted synergies, policy implementation processes and outcomes often encountered trade-offs due to factors such as limited budgets and low political priority. Notably, most trade-offs and synergies were found in the same areas - (re)development and infrastructure - and shared the same contributing factors, such as political priority of urban forestry, suggesting areas of opportunity to transform trade-offs into synergies through appropriate planning and monitoring. The study also highlighted the need for further research on the interactions and impacts among municipal policies for more effective implementation and outcomes. • The study is among the first attempts to explore policy interactions on climate action, urban planning, and urban forest. • Semi-structured interviews were conducted with key informants with relevant expertise in cities of Metro Vancouver, Canada. • Results revealed key trade-offs and synergies among policies and practices, especially in development and infrastructure. • Connections between trade-offs and synergies suggest opportunities for compact, climate-proofed, and green cities. [ABSTRACT FROM AUTHOR]

• Substitution factors for forest products for the Canadian context were developed. • Substitution factors ranging from 0.51 to 0.91 tC/tC were found. • They will lead to more accurate assessments of the forest GHG mitigation potential. • These factors will help governments to manage forest and fight climate change. Evaluating the climate change mitigation potential of the forest sector requires a holistic approach based on forest carbon (C) sequestration, C storage in harvested wood products (HWP) and substitution on markets. High uncertainty is associated with substitution factors, that express avoided fossil greenhouse gas (GHG) emissions from the use of forest-based products in replacement of GHG-intensive materials and fossil fuels. Few studies have focused on the development of substitution factors in Canada, resulting in the use of unrepresentative generic data. Here, we provide a framework to reduce uncertainties related to substitution factors for primary wood products in a Canadian context. A life cycle assessment framework is used to quantify fossil GHG emissions for a baseline and a wood-intensive scenario. For solid product substitution, we focused on the construction sector and analyzed a range of innovative wood buildings with steel and reinforced concrete as alternative materials. We found non-weighted averages of 0.80 tC/tC for sawnwood and 0.81 tC/tC for panels. For energy substitution, we analyzed cases with different specifications on biomass product, facility type and alternative fossil fuel source in non-residential heat production and biofuel transportation sectors. We found a non-weighted average of 0.80 tC/tC for non-residential heat production and 0.51 tC/tC for biofuel transportation, that can be interpreted as 0.91 tC/tC for heavy fuel oil, 0.69 tC/tC for light fuel oil and 0.68 tC/tC for natural gas substitution. These results provide a benchmark for substitution factors in Canada, to help guide forest management strategies for climate change mitigation. [ABSTRACT FROM AUTHOR]

• Innovate a BaPMI method for macro-scale distributed hydrologic modeling. • Apply it to a typical large cold-region watershed, Athabasca River Basin in Canada. • Verify feasibility & advantages in characterizing macro-scale cold-region hydrology. • Quantify parametric & hyperparametric sensitivities for facilitating its applications. • Reveal variabilities of climate-driven cross-scale uppermost hydro-variational effects. At macroscales (e.g., large river basins, nations, continents, or the globe), hydro-hazard mitigation under climate change requires accurate, applicable hydrologic models, especially over cold regions of complicated hydroclimatic relations. As an effort to address such a challenge, we innovate a macroscale distributed hydro-modeling method, Bayesian principal-monotonicity inference (BaPMI), based on climate classification, representative-grids selection, statistical hydrology, surrogates-based Bayesian optimization, and variance-based sensitivity analyses. The method is applied to a typical large cold-region watershed, i.e., Athabasca River Basin in Canada, and reveals a series of findings such as the following representatives. BaPMI shows promising skills in quantitatively characterizing macroscale cold-region hydrology under overall impacts of heterogeneous climates. Bayesian optimization of which hyperparameters are insensitive decreases hydro-modeling computational time by up to 96.3% and, together with climate classification, largely enhances BaPMI applicability while ensuring modeling accuracies. Individual BaPMI hydro-model parameters can explain over ¾ of the variation of hydro-modeling accuracies and, due to their interaction, joint calibration is required for avoiding underestimation of the impacts. Climatic conditions dominating cross-scale uppermost hydrologic variations consist of night temperature (40%), day temperature (38%), and precipitation (22%) for all catchments; all river flows along the mainstem are associated with upstream climatic events such as glacier melts. Climatic impacts decline from upstream to downstream and from summer, spring, winter to autumn; this may relate to tempo-spatial heterogeneity of soil, vegetation, geology, human interference and other non-climatic factors. Without this study, macroscale distributed hydrologic modeling would lack one advanced method (i.e., BaPMI) that can immunize against effects of data uncertainty, subjective judgement and climatic collinearity, adapt to complicated hydroclimatic relations and diverse hydro-variable(s) distributions, reveal cross-scale uppermost hydrologic variations and, through inexpensive computations, enhance hydro-modeling accuracies to avoid climatic-impact underestimation. The findings of this study could facilitate BaPMI applications and advance macroscale (cold-region) hydrology. [ABSTRACT FROM AUTHOR]