North American boreal forests are a large carbon source due to wildfires from 1986 to 2016.

Wildfires are a major disturbance to forest carbon (C) balance through both immediate combustion emissions and post-fire ecosystem dynamics. Here we used a process-based biogeochemistry model, the Terrestrial Ecosystem Model (TEM), to simulate C budget in Alaska and Canada during 1986-2016, as impacted by fire disturbances. We extracted the data of difference Normalized Burn Ratio (dNBR) for fires from Landsat TM/ETM imagery and estimated the proportion of vegetation and soil C combustion. We observed that the region was a C source of 2.74 Pg C during the 31-year period. The observed C loss, 57.1 Tg C year-1, was attributed to fire emissions, overwhelming the net ecosystem production (1.9 Tg C year-1) in the region. Our simulated direct emissions for Alaska and Canada are within the range of field measurements and other model estimates. As burn severity increased, combustion emission tended to switch from vegetation origin towards soil origin. When dNBR is below 300, fires increase soil temperature and decrease soil moisture and thus, enhance soil respiration. However, the post-fire soil respiration decreases for moderate or high burn severity. The proportion of post-fire soil emission in total emissions increased with burn severity. Net nitrogen mineralization gradually recovered after fire, enhancing net primary production. Net ecosystem production recovered fast under higher burn severities. The impact of fire disturbance on the C balance of northern ecosystems and the associated uncertainties can be better characterized with long-term, prior-, during- and post-disturbance data across the geospatial spectrum. Our findings suggest that the regional source of carbon to the atmosphere will persist if the observed forest wildfire occurrence and severity continues into the future.

Evaluating autumn phenology derived from field observations, satellite data, and carbon flux measurements in a northern mixed forest, USA.

Common approaches currently used to monitor forest phenology include direct field observation and indirect approaches such as satellite remote sensing and carbon flux measurements. However, differences in both temporal and spatial scales of these methods make direct comparison challenging. In order to evaluate the reliability of indirect measures of autumn phenology in estimating direct observations, we compared the timing of three transition dates and the rate of autumn progression derived from (i) satellite data (MOD13Q1 006 enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) products, 2000-2017), (ii) carbon flux measurements (net ecosystem exchange (NEE) and gross primary production (GPP), 1997-2016), and (iii) field observation (2010, 2012 for the north site and 2010, 2012, and 2013 for the south site) from a mixed forest in northern Wisconsin, USA. Overall, the transition dates and progression rates derived from NDVI were closest to that of field observations. Furthermore, the start of autumn derived from satellite data was earlier than directly observed leaf coloration (LC), which resulted from species-specific canopy senescence patterns and the sensitivity of the vegetation indices. Even after full leaf fall was reached, EVI continued to detect coloring which was likely due to the presence of understory plant species. Finally, NEE and GPP changes tended to start before LC as a result of tree physiological and environmental changes and continued after full leaf fall possibly due to understory and coniferous activity. These results highlight the need for long-term field observations of both trees and understory species, information on species-specific canopy senescence patterns, and species composition in understanding the efficiency of indirect approaches in estimating autumn forest phenology.