Forest wildfires consume fuel and are followed by post-fire fuel accumulation. This study examines post-fire surface fuel dynamics over 9 years across a wide range of conditions characteristic of California fires in dry conifer and hardwood forests. We estimated post-fire surface fuel loadings (Mg ha−1) from 191 repeatedly measured United States national inventory plots in dry conifer and hardwood stands of 49 California forest wildfires and identified differences across fire severity classes – low, moderate and high. No significant change in duff load was detected within the first 9 years post-fire across all forest types and fire severities. Litter, 1-h and 10-h fuels exhibited a quadratic trend over time in dry conifer stands, peaking ~6 years after fire, whereas hardwood stands displayed a constant rate of increase in those fuel types. For 100- and 1000-h fuels, the annual rate of change was constant for dry conifer and hardwood stands with differing rates of change across fire severity classes. This study was based on an extensive, spatially balanced sample across burned dry conifer and hardwood forests of California. Therefore, the estimated patterns of fuel accumulation are generally applicable to wildfires within this population.

Wildfires are a common disturbance event in the Canadian boreal forest. Within event boundaries, the level of vegetation mortality varies greatly. Understanding where surviving vegetation occurs within fire events and how this relates to pre-fire vegetation, topography, and fire weather can inform forest management decisions. We used pre-fire forest inventory data, digital elevation maps, and records of fire weather for 37 naturally-occurring wildfires (1961 to 1982; 30 to 5500 ha) covering a wide range of conditions in the western Canadian boreal forest to investigate these relationships using multinomial logistic models. Overall, vegetation mortality related to a combination of factors representing different spatial scales. Lower vegetation mortality occurred where there was lower fuel continuity and when fires occurred under non-drought conditions. Higher classification accuracy occurred for class extremes of no mortality (i.e., unburned areas within the burn event) and high mortality; partial vegetation mortality classes were harder to distinguish. This research contributes to the knowledge required for natural pattern emulation strategies, and developing responses to climate change.

As the frequency and size of wildfires increase, accurate assessment of burn severity is essential for understanding fire effects and evaluating post-fire vegetation impacts. Remotely-sensed imagery allows for rapid assessment of burn severity, but it also needs to be field validated. Permanent forest inventory plots can provide burn severity information for the field validation of remotely-sensed burn severity metrics, although there is often a mismatch between the size and shape of the inventory plot and the resolution of the rasterized images. For this study, we used two distinct datasets: (1) ground-based inventory data from the United States national forest inventory to calculate ground-based burn severity; and (2) remotely-sensed data from the Monitoring Trends in Burn Severity (MTBS) database to calculate different remotely-sensed burn severity metrics based on six weighting scenarios. Our goals were to test which MTBS metric would best align with the burn severity of national inventory plots observed on the ground, and to identify the superior weighting scenarios to extract pixel values from a raster image in order to match burn severity of the national inventory plots. We fitted logistic and ordinal regression models to predict the ground-based burn severity from the remotely-sensed burn severity averaged from six weighting scenarios. Among the weighting scenarios, two scenarios assigned weights to pixels based on the area of a pixel that intersected any parts of a national inventory plot. Based on our analysis, 9-pixel weighted averages of the Relative differenced Normalized Burn Ratio (RdNBR) values best predicted the ground-based burn severity of national inventory plots. Finally, the pixel specific weights that we present can be used to link other Landsat-derived remote sensing metrics with United States forest inventory plots.

Climate change has driven forest growth modellers to develop different climate sensitivity implementations (CSIs) for their models. Among others, a model can rely on annual climate variables or average climate variables, such as 30-year normals. The novelty of this study was to develop a framework based on lifetime analysis to enable annual or average CSI in empirical models of tree mortality. Using this framework, we compared models of individual tree mortality based on an annual CSI with similar models relying on two average CSIs, one using interval-averaged climate variables, and the other, 30-year normals. We fitted these models to permanent-plot data of eight species in Ontario and tested the effects of summer and winter temperature as well as spring and summer precipitation in the models. Our results showed that the annual CSI was not superior to the average CSIs, but could be a valid alternative for some species. Warmer winter temperature was detrimental to the survival of Betula papyrifera, Picea glauca, and Pinus strobus, whereas greater spring and summer precipitation resulted in greater mortality occurrence for Picea mariana, Pinus banksiana, and Populus tremuloides. In most cases, the effects of climate variables were contrary to our initial hypotheses. We conclude that the effects of climate on tree mortality occurrence interact with other factors such as species distribution and ecophysiology.

We assessed the impacts of three approaches to thinning from below with varying spatial patterns on several stand and individual tree variables for interior Douglas-fir ( Pseudotsuga menziesii var. glauca (Beissn.) Franco), interior spruce ( Picea glauca (Moench) Voss × Picea engelmannii Engelm.), and lodgepole pine ( Pinus contorta Dougl. Ex Loud. var. latifolia Englem.) in central British Columbia, Canada. The three thinning treatments were two experimental “clumped” treatments (3 m Clumped and 5 m Clumped) and the Standard (more uniform spacing) thinning treatment that was employed operationally at that time. We used long-term data from 24 plots measured five times over 21 years. Thinning increased stand basal area increment, with the plots that received the 5 m Clumped treatment having significantly higher periodic annual relative basal area increment than the unthinned Control plots. The responses for the two clumped treatments were not any lower than the Standard. The 3 m Clumped treatment was best if one is concerned about fast recovery of the growing space; however, the 5 m Clumped spacing treatment may be preferable if higher individual tree vigour is needed for resistance and resilience to fire, insects, and disease.