Boreal Forests Of Interior Alaska Research Articles

Determining the novel pathogen Neodothiora populina as the causal agent of the aspen running canker disease in Alaska

Neodothiora populina Crous, G.C. Adams & Winton was determined to be a new pathogen of trembling aspen (Populus tremuloides) growing in Alaska, based on completion of Koch’s Postulates in replicated forest and growth chamber inoculation trials. The pathogen is responsible for severe damage and widespread rapid mortality of sapling to mature aspen (≥ 80 years) in the boreal forests of interior Alaska, due to large diffuse annual (1–2 years) cankers. Isolation of the pathogen was challenging, and identification based on cultural characters was difficult. Fruiting bodies were not found on wild diseased trees, but erumpent pycnidia were found in bark overlying cankers on several stems inoculated with pure cultures.

Machine learning analyses of remote sensing measurements establish strong relationships between vegetation and snow depth in the boreal forest of Interior Alaska

The seasonal snowpack plays a critical role in Arctic and boreal hydrologic and ecologic processes. Though snow depth can be markedly different from one season to another there are strong repeated relationships between ecotype and snowpack depth. In the diverse vegetative cover of the boreal forest of Interior Alaska, a warming climate has shortened the winter season. Alterations to the seasonal snowpack, which plays a critical role in regulating wintertime soil thermal conditions, have major ramifications for near-surface permafrost. Therefore, relationships between vegetation and snowpack depth are critical for identifying how present and projected future changes in winter season processes or land cover will affect permafrost. Vegetation and snow cover areal extent can be assessed rapidly over large spatial scales with remote sensing methods, however, measuring snow depth remotely has proven difficult. This makes snow depth–vegetation relationships a potential means of assessing snowpack characteristics. In this study, we combined airborne hyperspectral and LiDAR data with machine learning methods to characterize relationships between ecotype and the end of winter snowpack depth. More than 26 000 snow depth measurements were collected between 2014 and 2019 at three field sites representing common boreal ecoregion land cover types. Our results show hyperspectral measurements account for two thirds or more of the variance in the relationship between ecotype and snow depth. Of the three modeling approaches we used, support vector machine yields slightly stronger statistical correlations between snowpack depth and ecotype for most winters. An ensemble analysis of model outputs using hyperspectral and LiDAR measurements yields the strongest relationships between ecotype and snow depth. Our results can be applied across the boreal biome to model the coupling effects between vegetation and snowpack depth.

Soil Metatranscriptomes Under Long-Term Experimental Warming and Drying: Fungi Allocate Resources to Cell Metabolic Maintenance Rather Than Decay.

Earth’s temperature is rising, and with this increase, fungal communities are responding and affecting soil carbon processes. At a long-term soil-warming experiment in a boreal forest in interior Alaska, warming and warming-associated drying alters the function of microbes, and thus, decomposition of carbon. But what genetic mechanisms and resource allocation strategies are behind these community shifts and soil carbon changes? Here, we evaluate fungal resource allocation efforts under long-term experimental warming (including associated drying) using soil metatranscriptomics. We profiled resource allocation efforts toward decomposition and cell metabolic maintenance, and we characterized community composition. We found that under the warming treatment, fungi allocate resources to cell metabolic maintenance at the expense of allocating resources to decomposition. In addition, we found that fungal orders that house taxa with stress-tolerant traits were more abundant under the warmed treatment compared to control conditions. Our results suggest that the warming treatment elicits an ecological tradeoff in resource allocation in the fungal communities, with potential to change ecosystem-scale carbon dynamics. Fungi preferentially invest in mechanisms that will ensure survival under warming and drying, such as cell metabolic maintenance, rather than in decomposition. Through metatranscriptomes, we provide mechanistic insight behind the response of fungi to climate change and consequences to soil carbon processes.

Spatial Factor Models for High-Dimensional and Large Spatial Data: An Application in Forest Variable Mapping.

Gathering information about forest variables is an expensive and arduous activity. As such, directly collecting the data required to produce high-resolution maps over large spatial domains is infeasible. Next generation collection initiatives of remotely sensed Light Detection and Ranging (LiDAR) data are specifically aimed at producing complete-coverage maps over large spatial domains. Given that LiDAR data and forest characteristics are often strongly correlated, it is possible to make use of the former to model, predict, and map forest variables over regions of interest. This entails dealing with the high-dimensional (~102) spatially dependent LiDAR outcomes over a large number of locations (~105-106). With this in mind, we develop the Spatial Factor Nearest Neighbor Gaussian Process (SF-NNGP) model, and embed it in a two-stage approach that connects the spatial structure found in LiDAR signals with forest variables. We provide a simulation experiment that demonstrates inferential and predictive performance of the SF-NNGP, and use the two-stage modeling strategy to generate complete-coverage maps of forest variables with associated uncertainty over a large region of boreal forests in interior Alaska.

Black spruce assimilates nitrate in boreal winter.

Winter has long been considered a dormant season in boreal forests regarding plant physiological activity such as nutrient acquisition. However, biogeochemical data clearly show that soil can remain unfrozen with substantial rates of nutrient transformation for several weeks following autumn snowfall. Here we examined nitrate (NO3--N) assimilation by black spruce (Picea mariana (Mill.) Britton, Sterns and Poggenb.) during summer and winter in Interior Alaska to test our hypothesis that this boreal species is able to assimilate NO3--N, even at the very low temperatures typical of early winter. Nitrate reductase activity (NRA) was measured in current year needles and fine roots of black spruce as an indicator of NO3--N assimilation in the summer and winter at two boreal forest sites. Nitrate concentration in the needles and roots were also measured to determine whether NO3--N was available in plant tissue for the enzyme. Nitrate reductase activity and NO3--N were detected in needles and roots in the winter as well as the summer. The results of a generalized linear mixed model showed that season had minimal effects on NRA and NO3--N concentration in this species. Additionally, the effect of incubation temperature for the NRA assays was tested at 30 °C and -3 °C for samples collected in the winter. Substantial enzyme activity was detected in winter-collected samples, even in incubations conducted at -3 °C. These results indicate that this dominant tree species in the boreal forests of Interior Alaska, black spruce, has the capacity to assimilate NO3--N below freezing temperatures, suggesting that the physiological activity required for nitrogen (N) resource acquisition may extend beyond the typical growing season. Our findings coupled to biogeochemical evidence for high microbial activity under the snow also indicate that winter N acquisition should be taken into account when estimating the annual N budgets of boreal forest ecosystems.

In Situ Observations Reveal How Spectral Reflectance Responds to Growing Season Phenology of an Open Evergreen Forest in Alaska

Plant phenology timings, such as spring green-up and autumn senescence, are essential state information characterizing biological responses and terrestrial carbon cycles. Current efforts for the in situ reflectance measurements are not enough to obtain the exact interpretation of how seasonal spectral signature responds to phenological stages in boreal evergreen needleleaf forests. This study shows the first in situ continuous measurements of canopy scale (overstory + understory) and understory spectral reflectance and vegetation index in an open boreal forest in interior Alaska. Two visible and near infrared spectroradiometer systems were installed at the top of the observation tower and the forest understory, and spectral reflectance measurements were performed in 10 min intervals from early spring to late autumn. We found that canopy scale normalized difference vegetation index (NDVI) varied with the solar zenith angle. On the other hand, NDVI of understory plants was less sensitive to the solar zenith angle. Due to the influence of the solar geometry, the annual maximum canopy NDVI observed in the morning satellite overpass time (10–11 am) shifted to the spring direction compared with the standardized NDVI by the fixed solar zenith angle range (60−70°). We also found that the in situ NDVI time-series had a month-long high NDVI plateau in autumn, which was completely out of photosynthetically active periods when compared with eddy covariance net ecosystem exchange measurements. The result suggests that the onset of an autumn high NDVI plateau is likely to be the end of the growing season. In this way, our spectral measurements can serve as baseline information for the development and validation of satellite-based phenology algorithms in the northern high latitudes.

Leaf- and ecosystem-scale photosynthetic parameters for the overstory and understory of boreal forests in interior Alaska

Leaf- and ecosystem-scale photosynthetic parameters for the overstory and understory of boreal forests in interior Alaska

Differences in Human versus Lightning Fires between Urban and Rural Areas of the Boreal Forest in Interior Alaska

In western North America, the carbon-rich boreal forest is experiencing warmer temperatures, drier conditions and larger and more frequent wildfires. However, the fire regime is also affected by direct human activities through suppression, ignition, and land use changes. Models are important predictive tools for understanding future conditions but they are based on regional generalizations of wildfire behavior and weather that do not adequately account for the complexity of human–fire interactions. To achieve a better understanding of the intensity of human influence on fires in this sparsely populated area and to quantify differences between human and lightning fires, we analyzed fires by both ignition types in regard to human proximity in urban (the Fairbanks subregion) and rural areas of interior Alaska using spatial (Geographic Information Systems) and quantitative analysis methods. We found substantial differences in drivers of wildfire: while increases in fire ignitions and area burned were caused by lightning in rural interior Alaska, in the Fairbanks subregion these increases were due to human fires, especially in the wildland urban interface. Lightning fires are starting earlier and fires are burning longer, which is much more pronounced in the Fairbanks subregion than in rural areas. Human fires differed from lightning fires in several ways: they started closer to settlements and highways, burned for a shorter duration, were concentrated in the Fairbanks subregion, and often occurred outside the brief seasonal window for lightning fires. This study provides important insights that improve our understanding of the direct human influence on recently observed changes in wildfire regime with implications for both fire modeling and fire management.

Gap regeneration within mature deciduous forests of Interior Alaska: Implications for future forest change

Increased fire severity in boreal forests of Interior Alaska is shifting forest canopy composition from black spruce (Picea mariana) to deciduous species, including trembling aspen (Populus tremuloides) and Alaska paper birch (Betula neoalaskana). Because deciduous trees are less flammable than black spruce, the dominant disturbance regime in deciduous forests could move away from fire to one of gap disturbances. In this study, we quantified forest gap characteristics and vegetation within eight mature (62–119-yr-old) deciduous stands in Interior Alaska. Canopy gaps were generally small (true gap area <50m2), formed by the mortality of 4–16 gap makers (which were always deciduous trees), and occupied ∼17–29% of the forest except in the oldest stand, where gap fraction exceeded 45%, and in one anomalous 84-yr old stand, where gaps were absent. Canopy openness increased linearly with gap area, but density of both deciduous and evergreen tree recruits was generally low and insufficient to create future stands with densities similar to those currently found in mature stands across the landscape. Canopy openness was instead correlated with decreased leaf litter cover and increased cover of moss, lichen, and evergreen shrubs. Given the low recruitment of trees with canopy gaps and the decreased probability of fire, deciduous stands will likely transition to non-forested areas or low density stands once overstory trees reach maturity and die. This could have numerous implications for ecosystem function, including carbon (C), water, and energy balance, and potential feedbacks to future fire occurrence and regional climate.

Life history patterns, individual heterogeneity, and density dependence in breeding common goldeneyes of the northern boreal forest

Life history patterns and their associated tradeoffs influence population dynamics, as they determine how individuals allocate resources among competing demographic traits. Here we examined life history strategies in common goldeneyes Bucephala clangula (hereafter goldeneye), a cavity‐nesting sea duck, in the northern boreal forest of interior Alaska, USA. We used multistate capture–mark–recapture models to estimate adult survival, breeding probability, first‐year survival, and recruitment probability using a long‐term nest box study (1997–2010). We detected annual variation in adult survival, which varied from 0.74 ± 0.12 (SE) to 0.93 ± 0.06. In contrast, breeding probability remained relatively high and invariant (0.84 ± 0.11) and was positively related to individual nest success the year prior. Nonbreeding individuals in one year were more likely to remain a nonbreeder, than attempt to breed the following year. First‐year survival decreased with smaller residual duckling mass and larger brood sizes. Probability of recruitment into the breeding population conditioned on survival was constant during the study (0.96 ± 0.06), and did not vary among ages 2–5 yr‐old. Overall, goldeneyes exhibited high, but somewhat variable, adult survival, and high breeding and recruitment probabilities, which is consistent with observed patterns in bet‐hedging species that breed annually in high quality breeding environments, but whose reproductive output is often influenced by stochastic events. Demographic estimates from this study are among the first for goldeneyes within Alaska. Life history patterns are known to vary geographically, therefore, we recommend further examination of life history patterns within the distribution of goldeneyes.

Evaluating the relationship between wildfire extent and nitrogen dry deposition in a boreal forest in interior Alaska

Alaska wildfires may play an important role in nitrogen (N) dry deposition in Alaskan boreal forests. Here we used annual N dry deposition data measured by CASTNET at Denali National Park (DEN417) during 1999–2013, to evaluate the relationships between wildfire extent and N dry deposition in Alaska. We established six potential factors for multiple regression analysis, including burned area within 100 km of DEN417 (BA100km) and in other distant parts of Alaska (BAAK), the sum of indexes of North Atlantic Oscillation and Arctic Oscillation (OI), number of days with negative OI (OIday), precipitation (PRCP), and number of days with PRCP (PRCPday). Multiple regression analysis was conducted for both time scales, annual (using only annual values of factors) and six-month (using annual values of BAAK and BA100km, and fire and non-fire seasons' values of other four factors) time scales. Together, BAAK, BA100km, and OIday, along with PRCPday in the case of the six-month scale, explained more than 92% of the interannual variation in N dry deposition. The influence of BA100km on N dry deposition was ten-fold greater than from BAAK; the qualitative contribution was almost zero, however, due to the small BA100km. BAAK was the leading explanatory factor, with a 15 ± 14% contribution. We further calculated N dry deposition during 1950–2013 using the obtained regression equation and long-term records for the factors. The N dry deposition calculated for 1950–2013 revealed that an increased occurrence of wildfires during the 2000s led to the maximum N dry deposition exhibited during this decade. As a result, the effect of BAAK on N dry deposition remains sufficiently large, even when large possible uncertainties (>40%) in the measurement of N dry deposition are taken into account for the multiple regression analysis.

Modeling and mapping forest diversity in the boreal forest of interior Alaska

Patterns of forest diversity are less well known in the boreal forest of interior Alaska than in most ecosystems of North America. Proactive forest planning requires spatially accurate information about forest diversity. Modeling is a cost-efficient way of predicting key forest diversity measures as a function of human and environmental factors. Investigate and predict the patterns and processes in tree species and tree size-class diversity within the boreal forest of Alaska for a first mapped quantitative baseline. For the boreal forest of Alaska, USA, we employed Random Forest Analysis (machine learning) and the Boruta algorithm in R to predict tree species and tree size-class diversity for the entire region using a combination of forest inventory data and a suite of 30 predictors from public open-access data archives that included climatic, distance, and topographic variables. We developed prediction maps in a GIS for the current levels (Year 2012) of tree size-class and species diversity. The method employed here yielded good accuracy for the huge Alaskan landscape despite the exclusion of spectral reflectance data. It’s the first quantified GIS prediction baseline. The results indicate that the geographic pattern of tree species diversity differs from the pattern of tree size-class diversity across this forest type. The results suggest that human factors combined with topographical factors had a large impact on predicting the patterns of diversity in the boreal forest of interior Alaska.

Infrastructure Development Accelerates Range Expansion of Trembling Aspen (&lt;i&gt;Populus tremuloides&lt;/i&gt;, Salicaceae) into the Arctic

Interacting forces of climate change and increased human activity in the Arctic are driving rapid changes in ecosystem structure, function, and biodiversity. One such change is the northern range expansion of tree species. We present the first account of the boreal tree species trembling aspen (Populus tremuloides, Salicaceae) growing beyond the latitudinal treeline in the northern foothills of the Brooks Range, Alaska. The four trembling aspen stands described in this paper are located on abandoned gravel roads or pads created for construction purposes. We hypothesize that gravel pads create islands of substrate suitable for tree growth within the Arctic by providing greater rooting depth, well-drained microsites, an extended growing season, and acid-buffering capacity. Further, traffic along the south-to-north oriented Dalton Highway from the boreal forest in Interior Alaska to the Arctic may aid seed dispersal across the topographic barrier of the Brooks Range. Therefore, increased development in the Arctic will likely accelerate the establishment of trees as climate becomes more favorable for tree growth. Tree colonization associated with infrastructure development would contrast sharply with prior conceptual models of gradual treeline advance following disturbance.

Stable carbon isotope analysis reveals widespread drought stress in boreal black spruce forests.

Unprecedented rates of climate warming over the past century have resulted in increased forest stress and mortality worldwide. Decreased tree growth in association with increasing temperatures is generally accepted as a signal of temperature-induced drought stress. However, variations in tree growth alone do not reveal the physiological mechanisms behind recent changes in tree growth. Examining stable carbon isotope composition of tree rings in addition to tree growth can provide a secondary line of evidence for physiological drought stress. In this study, we examined patterns of black spruce growth and carbon isotopic composition in tree rings in response to climate warming and drying in the boreal forest of interior Alaska. We examined trees at three nested scales: landscape, toposequence, and a subsample of trees within the toposequence. At each scale, we studied the potential effects of differences in microclimate and moisture availability by sampling on northern and southern aspects. We found that black spruce radial growth responded negatively to monthly metrics of temperature at all examined scales, and we examined ∆(13)C responses on a subsample of trees as representative of the wider region. The negative ∆(13)C responses to temperature reveal that black spruce trees are experiencing moisture stress on both northern and southern aspects. Contrary to our expectations, ∆(13)C from trees on the northern aspect exhibited the strongest drought signal. Our results highlight the prominence of drought stress in the boreal forest of interior Alaska. We conclude that if temperatures continue to warm, we can expect drought-induced productivity declines across large regions of the boreal forest, even for trees located in cool and moist landscape positions.

Tundra and boreal forest of interior Alaska during terminal MIS 6 and MIS 5e

Two sites within the boreal forest of interior Alaska shed light on the climate and vegetation of terminal marine isotope stage (MIS) 6 (ca. 140–130 kyr ago) and MIS 5e (125–116 kyr ago). The Birch Creek and Koyukuk localities are river-cut exposures with sediments dating from the penultimate glaciation (at least) to the present. Plant macrofossils, pollen, and beetles were analyzed at these sites. Terminal MIS 6-aged samples indicate a cooler than modern climate and the presence of shrub tundra. During MIS 5e, boreal forest grew at the sites and temperatures were similar to modern times. However, the forest may also have been more mesic than today, as indicated by relatively abundant ferns. Winters may have been warmer than today, as suggested by beetle-based climatic reconstructions as well as the presence of two extralimital taxa that today live in regions where winter temperatures are up to 15 °C warmer than at the site localities.

Modeling the effects of fire severity and climate warming on active layer thickness and soil carbon storage of black spruce forests across the landscape in interior Alaska

There is a substantial amount of carbon stored in the permafrost soils of boreal forest ecosystems, where it is currently protected from decomposition. The surface organic horizons insulate the deeper soil from variations in atmospheric temperature. The removal of these insulating horizons through consumption by fire increases the vulnerability of permafrost to thaw, and the carbon stored in permafrost to decomposition. In this study we ask how warming and fire regime may influence spatial and temporal changes in active layer and carbon dynamics across a boreal forest landscape in interior Alaska. To address this question, we (1) developed and tested a predictive model of the effect of fire severity on soil organic horizons that depends on landscape-level conditions and (2) used this model to evaluate the long-term consequences of warming and changes in fire regime on active layer and soil carbon dynamics of black spruce forests across interior Alaska. The predictive model of fire severity, designed from the analysis of field observations, reproduces the effect of local topography (landform category, the slope angle and aspect and flow accumulation), weather conditions (drought index, soil moisture) and fire characteristics (day of year and size of the fire) on the reduction of the organic layer caused by fire. The integration of the fire severity model into an ecosystem process-based model allowed us to document the relative importance and interactions among local topography, fire regime and climate warming on active layer and soil carbon dynamics. Lowlands were more resistant to severe fires and climate warming, showing smaller increases in active layer thickness and soil carbon loss compared to drier flat uplands and slopes. In simulations that included the effects of both warming and fire at the regional scale, fire was primarily responsible for a reduction in organic layer thickness of 0.06 m on average by 2100 that led to an increase in active layer thickness of 1.1 m on average by 2100. The combination of warming and fire led to a simulated cumulative loss of 9.6 kgC m−2 on average by 2100. Our analysis suggests that ecosystem carbon storage in boreal forests in interior Alaska is particularly vulnerable, primarily due to the combustion of organic layer thickness in fire and the related increase in active layer thickness that exposes previously protected permafrost soil carbon to decomposition.

Changes in Soil Fungal Communities, Extracellular Enzyme Activities, and Litter Decomposition Across a Fire Chronosequence in Alaskan Boreal Forests

Wildfires are a pervasive disturbance in boreal forests, and the frequency and intensity of boreal wildfires is expected to increase with climate warming. Boreal forests store a large fraction of global soil organic carbon (C), but relatively few studies have documented how wildfires affect soil microbial communities and soil C dynamics. We used a fire chronosequence in upland boreal forests of interior Alaska with sites that were 1, 7, 12, 24, 55, ~90, and ~100 years post-fire to examine the short- and long-term responses of fungal community composition, fungal abundance, extracellular enzyme activity, and litter decomposition to wildfires. We hypothesized that post-fire changes in fungal abundance and community composition would constrain decomposition following fires. We found that wildfires altered the composition of soil fungal communities. The relative abundance of ascomycetes significantly increased following fire whereas basidiomycetes decreased. Post-fire decreases in basidiomycete fungi were likely attributable to declines in ectomycorrhizal fungi. Fungal hyphal lengths in the organic horizon significantly declined in response to wildfire, and they required at least 24 years to return to pre-fire levels. Post-fire reductions in fungal hyphal length were associated with decreased activities of hydrolytic extracellular enzymes. In support of our hypothesis, the decomposition rate of aspen and black spruce litter significantly increased as forests recovered from fire. Our results indicate that post-fire reductions in soil fungal abundance and activity likely inhibit litter decomposition following boreal wildfires. Slower rates of litter decay may lead to decreased heterotrophic respiration from soil following fires and contribute to a negative feedback to climate warming.

Improving PolSAR Land Cover Classification With Radiometric Correction of the Coherency Matrix

The brightness of a SAR image is affected by topography due to varying projection between ground and image coordinates. For polarimetric SAR (PolSAR) imagery being used for purposes of land cover classification, this radiometric variability is shown to affect the outcome of a Wishart unsupervised classification in areas of moderate topography. The intent of this paper is to investigate the impact of applying a radiometric correction to the PolSAR coherency matrix for a region of boreal forest in interior Alaska. The gamma naught radiometric correction estimates the local illuminated area at each grid point in the radar geometry. Then, each element of the coherency matrix is divided by the local area to produce a polarimetric product that is radiometrically “flat.” This paper follows two paths, one with and one without radiometric correction, to investigate the impact upon classification accuracy. Using a Landsat-derived land cover reference, the radiometric correction is shown to bring about significant qualitative and quantitative improvements in the land cover map. Confusion matrix analysis confirms the accuracy for most classes and shows a 15% improvement in the classification of the deciduous forest class.

Implications of increased deciduous cover on stand structure and aboveground carbon pools of Alaskan boreal forests

Fire activity in boreal forests has increased recently with climate warming, altering stand structure and composition in many areas. Changes in stand dynamics have the potential to alter C cycling and biophysical processes, with feedbacks to global and regional climate. Here, we assess the interactions between fire, stand structure, and aboveground C accumulation and storage within boreal forests of interior Alaska, where increased fire severity is predicted to shift forest composition from predominantly black spruce (Picea mariana) to greater deciduous cover. We measured aboveground biomass and net primary productivity (ANPP) of trees and large shrubs, snags, and downed woody debris across 44 mid‐successional (20–59 years since fire) stands of varying deciduous importance value (IV), determined by relative density, basal area, and frequency of deciduous trees and large shrubs within each stand. Aboveground biomass, ANPP, and deciduous snag biomass increased significantly with increased deciduous IV and years since fire. Deciduous IV had little influence on evergreen snag biomass and downed woody debris, but both C pools decreased with years since fire. Forest type also affected stand structure and C pools. Black spruce stands had shorter trees with less basal area and aboveground biomass and slower rates of biomass accumulation and ANPP compared to those dominated by trembling aspen (Populus tremuloides) or Alaska birch (Betula neoalaskana). These parameters in black spruce stands were similar to mixed stands of black spruce and aspen but were often lower than mixed stands of black spruce and Alaska birch. Much of the biomass accumulation in deciduous stands was attributed to higher tree‐level ANPP, allowing individual stems of deciduous species to accumulate more stemwood/bark faster than black spruce trees. If increased fire activity shifts stand composition from black spruce to increased deciduous cover, ANPP, aboveground tree/large shrub biomass, and deciduous snag biomass will increase, leading to increased aboveground C pools in mid‐successional forest stands of interior Alaska. While species dominance shifts like these will impact aboveground patterns of landscape‐level C cycling in boreal forests, variations in soil C pools and forest properties like albedo must also be assessed to accurately determine implications for global and regional climate.

A multi-sensor lidar, multi-spectral and multi-angular approach for mapping canopy height in boreal forest regions

Spatially explicit representations of vegetation canopy height over large regions are necessary for a wide variety of inventory, monitoring, and modeling activities. Although airborne lidar data has been successfully used to develop vegetation canopy height maps in many regions, for vast, sparsely populated regions such as the boreal forest biome, airborne lidar is not widely available. An alternative approach to canopy height mapping in areas where airborne lidar data is limited is to use spaceborne lidar measurements in combination with multi-angular and multi-spectral remote sensing data to produce comprehensive canopy height maps for the entire region. This study uses spaceborne lidar data from the Geosciences Laser Altimeter System (GLAS) as training data for regression tree models that incorporate multi-angular and multi-spectral data from the Multi-Angle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging SpectroRadiometer (MODIS) to map vegetation canopy height across a 1,300,000km2 swath of boreal forest in Interior Alaska. Results are compared to in situ height measurements as well as airborne lidar data. Although many of the GLAS-derived canopy height estimates are inaccurate, applying a series of filters incorporating both data associated with the GLAS shots as well as ancillary data such as land cover can identify the majority of height estimates with significant errors, resulting in a filtered dataset with much higher accuracy. Results from the regression tree models indicate that late winter MISR imagery acquired under snow-covered conditions is effective for mapping canopy heights ranging from 5 to 15m, which includes the vast majority of forests in the region. It appears that neither MISR nor MODIS imagery acquired during the growing season is effective for canopy height mapping, although including summer multi-spectral MODIS data along with winter MISR imagery does appear to provide a slight increase in the accuracy of resulting height maps. The finding that winter, snow-covered MISR imagery can be used to map canopy height is important because clear sky days are nearly three times as common during the late winter period as during the growing season. The increased odds of acquiring cloud-free imagery during the target acquisition period make regularly updated forest height inventories for Interior Alaska much more feasible. A major advantage of the GLAS–MISR–MODIS canopy height mapping methodology described here is that this approach uses only data that is freely available worldwide, making the approach potentially applicable across the entire circumpolar boreal forest region.