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Predictions of future fire activity over Canada's boreal forests have primarily been generated from climate data following assumptions that direct effects of weather will stand alone in contributing to changes in burning. However, this assumption needs explicit testing. First, areas recently burned can be less likely to burn again in the near term, and this endogenous regulation suggests the potential for self-limiting, negative biotic feedback to regional climate-driven increases in fire. Second, forest harvest is ongoing, and resulting changes in vegetation structure have been shown to affect fire activity. Consequently, we tested the assumption that fire activity will be driven by changes in fire weather without...
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For climate-change projections to be useful, the magnitude of change must be understood relative to the magnitude of uncertainty in model predictions. We quantified the signal-to-noise ratio in projected distributional responses of boreal birds to climate change, and compared sources of uncertainty. Boosted regression tree models of abundance were generated for 80 boreal-breeding bird species using a comprehensive dataset of standardized avian point counts (349,629 surveys at 122,202 unique locations) and 4-km climate, land-use and topographic data. For projected changes in abundance, we calculated signal-to-noise ratios, and examined variance components related to choice of global climate model (GCM) and two sources...
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For climate-change projections to be useful, the magnitude of change must be understood relative to the magnitude of uncertainty in model predictions. We quantified the signal-to-noise ratio in projected distributional responses of boreal birds to climate change, and compared sources of uncertainty. Boosted regression tree models of abundance were generated for 80 boreal-breeding bird species using a comprehensive dataset of standardized avian point counts (349,629 surveys at 122,202 unique locations) and 4-km climate, land-use and topographic data. For projected changes in abundance, we calculated signal-to-noise ratios, and examined variance components related to choice of global climate model (GCM) and two sources...
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For climate-change projections to be useful, the magnitude of change must be understood relative to the magnitude of uncertainty in model predictions. We quantified the signal-to-noise ratio in projected distributional responses of boreal birds to climate change, and compared sources of uncertainty. Boosted regression tree models of abundance were generated for 80 boreal-breeding bird species using a comprehensive dataset of standardized avian point counts (349,629 surveys at 122,202 unique locations) and 4-km climate, land-use and topographic data. For projected changes in abundance, we calculated signal-to-noise ratios, and examined variance components related to choice of global climate model (GCM) and two sources...
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For climate-change projections to be useful, the magnitude of change must be understood relative to the magnitude of uncertainty in model predictions. We quantified the signal-to-noise ratio in projected distributional responses of boreal birds to climate change, and compared sources of uncertainty. Boosted regression tree models of abundance were generated for 80 boreal-breeding bird species using a comprehensive dataset of standardized avian point counts (349,629 surveys at 122,202 unique locations) and 4-km climate, land-use and topographic data. For projected changes in abundance, we calculated signal-to-noise ratios, and examined variance components related to choice of global climate model (GCM) and two sources...
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