Biological invaders can alter ecosystem processes via multiple pathways, yet few studies have compared the relative importance of these pathways. We assessed the impacts of exotic, invasive grasses on ecosystem nitrogen (N) cycling in the seasonal submontane woodlands of Hawaii Volcanoes National Park, where native grasses have been historically rare. Exotic grasses have become abundant over the past 30 yr and have altered two controls over N cycling: plant species composition and fire regime. Here we synthesize the results of a long-term investigation of species impacts in this system. To determine effects of grasses and fire on internal N cycling, we compared litterfall, decomposition, N mineralization from soil organic matter (SOM), and plant N uptake and production in invaded unburned forest, grass-removal plots within the forest, and woodland converted to grassland by fire. We measured ecosystem N loss via fire by comparing N pools among unburned, naturally burned, and experimentally burned sites. We also assessed the effects of fire on annual N fixation in the unburned forest vs. the grassland.Exotic grasses had relatively small effects on N cycling in the unburned woodland despite being abundant in the understory for 30 yr. Grasses contributed ϳ30% of fine litterfall and primary-production mass and N in the unburned woodland. However, these contributions did not result in significantly increased totals because litterfall and production of Metrosideros polymorpha, the dominant native tree, was reduced in the invaded woodland relative to grass-removal plots, presumably due to competition with grasses. Although areaweighted decomposition was lower in the grass-removal treatment than in the control, net N mineralization from litter and SOM were similar between these treatments. Annual plant N uptake was similar to annual net N mineralization from SOM in both treatments.By contrast, the burned grassland exhibited much lower rates of litterfall and production mass and N, but higher rates of net N mineralization from SOM than the woodland. As a result, total annual plant N uptake was only 17% of annual net mineralization. This change was primarily due to the loss of native species. Aboveground N pools were significantly reduced with fire. Native species were largely eliminated by fire. However, across all burned and unburned sites there was no change in total ecosystem N because the N contained in biomass was relatively small compared to N in litter and soil. Soil contained Ͼ95% of ecosystem N in all sites. Only in the high-intensity experimental burn was there significant loss of N from the soil pool. Fire reduced N inputs through asymbiotic N fixation mainly due to the loss of M. polymorpha, whose litter is an important site of asymbiotic N fixation, and alteration of the soil O-layer. This reduction in N inputs makes it unlikely that fixation activity will replace N lost via combustion before the next fire. Fire and the ensuing loss of native species led to decreased N inputs, increased rates of N mineralizati...

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Abstract. Fire is the dominant disturbance agent in Alaskan and Canadian boreal ecosystems and releases large amounts of carbon into the atmosphere. Burned area and carbon emissions have been increasing with climate change, which have the potential to alter the carbon balance and shift the region from a historic sink to a source. It is therefore critically important to track the spatiotemporal changes in burned area and fire carbon emissions over time. Here we developed a new burned area detection algorithm between 2001–2019 across Alaska and Canada at 500 meters (m) resolution that utilizes finer-scale 30 m Landsat imagery to account for land cover unsuitable for burning. This method strictly balances omission and commission errors at 500 m to derive accurate landscape- and regional-scale burned area estimates. Using this new burned area product, we developed statistical models to predict burn depth and carbon combustion for the same period within the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) core and extended domain. Statistical models were constrained using a database of field observations across the domain and were related to a variety of response variables including remotely-sensed indicators of fire severity, fire weather indices, local climate, soils, and topographic indicators. The burn depth and aboveground combustion models performed best, with poorer performance for belowground combustion. We estimate 2.37 million hectares (Mha) burned annually between 2001–2019 over the ABoVE domain (2.87 Mha across all of Alaska and Canada), emitting 79.3 +/- 27.96 (+/- 1 standard deviation) Teragrams of carbon (C) per year, with a mean combustion rate of 3.13 +/- 1.17 kilograms C m-2. Mean combustion and burn depth displayed a general gradient of higher severity in the northwestern portion of the domain to lower severity in the south and east. We also found larger fire years and later season burning were generally associated with greater mean combustion. Our estimates are generally consistent with previous efforts to quantify burned area, fire carbon emissions, and their drivers in regions within boreal North America; however, we generally estimate higher burned area and carbon emissions due to our use of Landsat imagery, greater availability of field observations, and improvements in modeling. The burned area and combustion data sets described here (the ABoVE Fire Emissions Database, or ABoVE-FED) can be used for local to continental-scale applications of boreal fire science.

Abstract. Fire is the dominant disturbance agent in Alaskan and Canadian boreal ecosystems and releases large amounts of carbon into the atmosphere. Burned area and carbon emissions have been increasing with climate change, which have the potential to alter the carbon balance and shift the region from a historic sink to a source. It is therefore critically important to track the spatiotemporal changes in burned area and fire carbon emissions over time. Here we developed a new burned-area detection algorithm between 2001–2019 across Alaska and Canada at 500 m (meters) resolution that utilizes finer-scale 30 m Landsat imagery to account for land cover unsuitable for burning. This method strictly balances omission and commission errors at 500 m to derive accurate landscape- and regional-scale burned-area estimates. Using this new burned-area product, we developed statistical models to predict burn depth and carbon combustion for the same period within the NASA Arctic–Boreal Vulnerability Experiment (ABoVE) core and extended domain. Statistical models were constrained using a database of field observations across the domain and were related to a variety of response variables including remotely sensed indicators of fire severity, fire weather indices, local climate, soils, and topographic indicators. The burn depth and aboveground combustion models performed best, with poorer performance for belowground combustion. We estimate 2.37×106 ha (2.37 Mha) burned annually between 2001–2019 over the ABoVE domain (2.87 Mha across all of Alaska and Canada), emitting 79.3 ± 27.96 Tg (±1 standard deviation) of carbon (C) per year, with a mean combustion rate of 3.13 ± 1.17 kg C m−2. Mean combustion and burn depth displayed a general gradient of higher severity in the northwestern portion of the domain to lower severity in the south and east. We also found larger-fire years and later-season burning were generally associated with greater mean combustion. Our estimates are generally consistent with previous efforts to quantify burned area, fire carbon emissions, and their drivers in regions within boreal North America; however, we generally estimate higher burned area and carbon emissions due to our use of Landsat imagery, greater availability of field observations, and improvements in modeling. The burned area and combustion datasets described here (the ABoVE Fire Emissions Database, or ABoVE-FED) can be used for local- to continental-scale applications of boreal fire science.

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