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Abstract Plant ecological strategies are shaped by numerous functional traits and their trade‐offs. Trait network analysis enables testing hypotheses for the shifting of trait correlation architecture across communities differing in climate and productivity.We built plant trait networks (PTNs) for 118 species within six communities across an aridity gradient, from forest to semi‐desert across the California Floristic Province, based on 34 leaf and wood functional traits, representing hydraulic and photosynthetic function, structure, economics and size. We developed hypotheses for the association of PTN parameters with climate and ecosystem properties, based on theory for the adaptation of species to low resource/stressful environments versus higher resource availability environments with greater potential niche differentiation. Thus, we hypothesized that across community PTNs, trait network connectivity (i.e., the degree that traits are intercorrelated) and network complexity (i.e., the number of trait modules, and the degree of trait integration among modules) would be lower for communities adapted to arid climates and higher for communities adapted to greater water availability, similarly to trends expected for phylogenetic diversity, functional richness and productivity. Further, within given PTNs, we hypothesized that traits would vary strongly in their network connectivity and that the traits most centrally connected within PTNs would be those with the least across‐species variation.Across communities from more arid to wetter climates, PTN architecture varied from less to more interconnected and complex, in association with functional richness, but PTN architecture was independent of phylogenetic diversity and ecosystem productivity. Within the community PTNs, traits with lower species variation were more interconnected.Synthesis. The responsiveness of PTN architecture to climate highlights how a wide range of traits contributes to physiological and ecological strategies with an architecture that varies among plant communities. Communities in more arid environments show a lower degree of phenotypic integration, consistent with lesser niche differentiation. Our study extends the usefulness of PTNs as an approach to quantify tradeoffs among multiple traits, providing connectivity and complexity parameters as tools that clarify plant environmental adaptation and patterns of trait associations that would influence species distributions, community assembly, and ecosystem resilience in response to climate change. 

Abstract Wildfire is an essential earth‐system process, impacting ecosystem processes and the carbon cycle. Forest fires are becoming more frequent and severe, yet gaps exist in the modeling of fire on vegetation and carbon dynamics. Strategies for reducing carbon dioxide (CO₂) emissions from wildfires include increasing tree harvest, largely based on the public assumption that fires burn live forests to the ground, despite observations indicating that less than 5% of mature tree biomass is actually consumed. This misconception is also reflected though excessive combustion of live trees in models. Here, we show that regional emissions estimates using widely implemented combustion coefficients are 59%–83% higher than emissions based on field observations. Using unique field datasets from before and after wildfires and an improved ecosystem model, we provide strong evidence that these large overestimates can be reduced by using realistic biomass combustion factors and by accurately quantifying biomass in standing dead trees that decompose over decades to centuries after fire (“snags”). Most model development focuses on area burned; our results reveal that accurately representing combustion is also essential for quantifying fire impacts on ecosystems. Using our improvements, we find that western US forest fires have emitted 851 ± 228 Tg CO₂(~half of alternative estimates) over the last 17 years, which is minor compared to 16,200 Tg CO₂from fossil fuels across the region.