Changes in fire regimes are driving the carbon balance of much of the North American boreal forest, but few studies have examined fire-driven changes in evapotranspiration (ET) at a regional scale. This study used a version of the Biome-BGC process model with dynamic and competing vegetation types, and explicit spatial representation of a large (106 km2) region, to simulate the effects of wildfire on ET and its components from 1948 to 2005 by comparing the fire dynamics of the 1948-1967 period with those of 1968-2005. Simulated ET averaged, over the entire temporal and spatial modeling domain, 323 mm yr-1; simulation results indicated that changes in fire in recent decades decreased regional ET by 1.4% over the entire simulation, and by 3.9% in the last 10 years (1996-2005). Conifers dominated the transpiration (EC) flux (120 mm yr-1) but decreased by 18% relative to deciduous broadleaf trees in the last part of the 20th century, when increased fire resulted in increased soil evaporation, lower canopy evaporation, lower EC, and a younger and more deciduous forest. Well- and poorly drained areas had similar rates of evaporation from the canopy and soil, but EC was twice as high in the well-drained areas. Mosses comprised a significant part of the evaporative flux to the atmosphere (22 mm yr-1). Modeled annual ET was correlated with net primary production, but not with temperature or precipitation; ET and its components were consistent with previous field and modeling studies. Wildfire is driving significant changes in hydrological processes by affecting mean stand age, forest species, and energy balance. These changes, particularly in poorly drained areas, may control the future carbon balance of the boreal forest.

Bond-Lamberty, Ben, Scott D. Peckham, Stith T. Gower and Brent E. Ewers. 2009. Effects of fire on regional evapotranspiration in the central Canadian boreal forest. Global Change Biology.
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Bryophytes are the dominant ground cover vegetation layer in many boreal forests and in some of these forests the net primary production of bryophytes exceeds the overstory. Therefore it is necessary to quantify their spatial coverage and species composition in boreal forests to improve boreal forest carbon budget estimates. We present results from a small exploratory test using airborne lidar and multispectral remote sensing data to estimate the percentage of ground cover for mosses in a boreal black spruce forest in Manitoba, Canada. Multiple linear regression was used to fit models that combined spectral reflectance data from CASI and indices computed from the SLICER canopy height profile. Three models explained 63-79% of the measured variation of feathermoss cover while three models explained 69-92% of the measured variation of sphagnum cover. Root mean square errors ranged from 3-15% when predicting feathermoss, sphagnum, and total moss ground cover. The results from this case study warrant further testing for a wider range of boreal forest types and geographic regions

Peckham, Scott D., Douglas E. Ahl and Stith T. Gower. 2009. Bryophyte cover estimation in a boreal black spruce forest using airborne lidar and multispectral sensors. Remote Sensing of Environment.

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Ecosystem models are routinely used to estimate net primary production (NPP) from the stand to global scales. Complex ecosystem models, implemented at small scales (< 10 km2), are impractical at global scales and, therefore, require simplifying logic based on key ecological first principles and model drivers derived from remotely sensed data. There is a need for an improved understanding of the factors that influence the variability of NPP model estimates at different scales so we can improve the accuracy of NPP estimates at the global scale. The objective of this study was to examine the effects of using leaf area index (LAI) and three different aggregated land cover classification products - two factors derived from remotely sensed data and strongly affect NPP estimates - in a light use efficiency (LUE) model to estimate NPP in a heterogeneous temperate forest landscape in northern Wisconsin, USA. Three separate land cover classifications were derived from three different remote sensors with spatial resolutions of 15, 30, and 1000 m. Average modeled net primary production (NPP) ranged from 402 gC m^-2 year^-1 (15 m data) to 431 gC m^-2 year^-1 (1000 m data), for a maximum difference of 7%. Almost 50% of the difference was attributed each to LAI estimates and land cover classifications between the fine and coarse scale NPP estimate. Results from this study suggest that ecosystem models that use biome-level land cover classifications with associated LUE coefficients may be used to model NPP in heterogeneous land cover areas dominated by cover types with similar NPP. However, more research is needed to examine scaling errors in other heterogeneous areas and NPP errors associated with deriving LAI estimates.

Ahl, D., S. T. Gower, D. S. Mackay, S. N. Burrows, J. M. Norman, and G. Diak. 2005. The effects of aggregated land cover data on estimating NPP in northern Wisconsin, USA. Remote Sensing of Environment 97:1-14

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Changes in climate, atmospheric carbon dioxide concentration and fire regimes have been occurring for decades in the global boreal forest, with future climate change likely to increase fire frequency -- the primary disturbance agent in most boreal forests. Previous attempts to assess quantitatively the effect of changing environmental conditions on the net boreal forest carbon balance have not taken into account the competition between different vegetation types on a large scale. Here we use a process model with three competing vascular and non-vascular vegetation types to examine the effects of climate, carbon dioxide concentrations and fire disturbance on net biome production, net primary production and vegetation dominance in 100 Mha of Canadian boreal forest. We find that the carbon balance of this region was driven by changes in fire disturbance from 1948 to 2005. Climate changes affected the variability, but not the mean, of the landscape carbon balance, with precipitation exerting a more significant effect than temperature. We show that more frequent and larger fires in the late twentieth century resulted in deciduous trees and mosses increasing production at the expense of coniferous trees. Our model did not however exhibit the increases in total forest net primary production that have been inferred from satellite data. We find that poor soil drainage decreased the variability of the landscape carbon balance, which suggests that increased climate and hydrological changes have the potential to affect disproportionately the carbon dynamics of these areas. Overall, we conclude that direct ecophysiological changes resulting from global climate change have not yet been felt in this large boreal region. Variations in the landscape carbon balance and vegetation dominance have so far been driven largely by increases in fire frequency.

Bond-Lamberty, Ben, Scott D. Peckham, Douglas E. Ahl, Stith T. Gower. 2007. Fire as the dominant driver of central Canadian boreal forest carbon balance. Nature, 450, 89-93.

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Summary Forested wetlands and peatlands are important in boreal and terrestrial biogeochemical cycling, but most general-purpose forest process models are designed and parameterized for upland systems. We describe changes made to Biome-BGC, an ecophysiological process model, that improve its ability to simulate poorly drained forests. Model changes allowed for: (1) lateral water inflow from a surrounding watershed, and variable surface and subsurface drainage; (2) adverse effects of anoxic soil on decomposition and nutrient mineralization; (3) closure of leaf stomata in flooded soils; and (4) growth of nonvascular plants (i.e., bryophytes). Bryophytes were treated as ectohydric broadleaf evergreen plants with zero stomatal conductance, whose cuticular conductance to CO2 was dependent on plant water content. Individual model changes were parameterized with published data, and ecosystem-level model performance was assessed by comparing simulated output to field data from the northern BOREAS site in Manitoba, Canada. The simulation of the poorly drained forest model exhibited reduced decomposition and vascular plant growth (-90%) compared with that of the well-drained forest model; the integrated bryophyte photosynthetic response accorded well with published data. Simulated net primary production, biomass and soil carbon accumulation broadly agreed with field measurements, although simulated net primary production was higher than observed data in well-drained stands. Simulated net primary production in the poorly drained forest was most sensitive to oxygen restriction on soil processes, and secondarily to stomatal closure in flooded conditions. The modified Biome-BGC remains unable to simulate true wetlands that are subject to prolonged flooding, because it does not track organic soil formation, water table changes, soil redox potential or anaerobic processes.

Bond-Lamberty, Ben, Stith T. Gower and Douglas E. Ahl. 2007. Improved simulation of poorly drained forests using Biome-BGC. Tree Physiol. 27, 703-715.

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This study used the Biome Biogeochemical Cycles (Biome-BGC) process model to simulate boreal forest dynamics, compared the results with a variety of measured carbon content and flux data from two boreal chronosequences in northern Manitoba, Canada, and examined how model output was affected by water and nitrogen limitations on simulated plant production and decomposition. Vascular and nonvascular plant growth were modeled over 151 years in well-drained and poorly drained forests, using as many site-specific model parameters as possible. Measured data included (1) leaf area and carbon content from site-specific allometry data, (2) aboveground and belowground net primary production from allometry and root cores, and (3) flux data, including biometry-based net ecosystem production and tower-based net ecosystem exchange. The simulation used three vegetation types or functional groups (evergreen needleaf trees, deciduous broadleaf trees, and bryophytes). Model output matched some of the observed data well, with net primary production, biomass, and net ecosystem production (NEP) values usually (50 - 80% of data) within the errors of observed values. Leaf area was generally underpredicted. In the simulation, nitrogen limitation increased with stand age, while soil anoxia limited vascular plant growth in the poorly drained simulation. NEP was most sensitive to climate variability in the poorly drained stands. Simulation results are discussed with respect to conceptual issues in, and parameterization of, the Biome-BGC model.

Bond-Lamberty, Ben, Stith T. Gower, Michael L. Goulden, and Andrew McMillan. 2006. Simulation of boreal black spruce chronosequences: Comparison to field measurements and model evaluation. Journal of Geophysical Research, Volume 111(G2):G02014.

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Carbon budgets are developed to understand ecosystem dynamics and are increasingly being used to develop global change policy. Traditionally, forest carbon budgets have focused on the biological carbon cycle; however, it is important to include the industrial forest carbon cycle as well. The overall objective of this study was to quantify the major carbon fluxes associated with the production of Wisconsin's industrial roundwood, by using life cycle inventory (LCI) methodology to produce an industrial forest carbon budget. To achieve this objective we (1) developed carbon LCIs for the harvest process for three major forest ownerships (state, national, and private non-industrial), (2) developed carbon LCIs for a dimensional lumber and two oriented strand board (OSB) mills and (3) completed a scaled version of 1 and 2 to include more Wisconsin forestlands and to incorporate the other major processes within the industrial forest carbon cycle (e.g. primary mill, secondary mill, product use and product disposal processes of the industrial forest carbon cycle). The carbon budgets for the harvesting process of the Chequamegon-Nicolet National Forest (CNNF), the Northern Highland American Legion State Forest (NHAL), and the non-industrial private forests that participated in the managed forest laws of Wisconsin (MFL-NIPF) were 0.10, 0.18 and 0.11 tonnes C ha^-1 year^-1), respectively. The dimensional lumber and OSB products were both net carbon sources, and released 0.05-0.09 tonnes C/ tonnes C processed). More carbon is sequestered than released within the industrial forest carbon cycle of Wisconsin's national (6 g C m^-2 year^-1), state (12 g C m^-2 year^-1) and non-industrial private forests (7 g C m^-2 year^-1). Using published net ecosystem production data we estimate that the net forest carbon cycle budget (sum of the biological and industrial C cycle, [Gower, S.T., 2003. Patterns and mechanisms of the forest carbon cycle. Ann. Rev. Environ. Resour. 28, 169-204]) for the CNNF ranges between -897 and 348 g C m^-2year^-1. Life cycle inventories of wood and paper products should be clear and explicitly state what processes are included, so that results can be used by policy makers and future researchers.

White M.K., S.T. Gower and D.E. Ahl. 2005. Life-cycle inventories of roundwood production in Wisconsin - Inputs into an industrial forest carbon budget. For. Ecol. Manage. 219: 13-2

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Biogeochemical process models are increasingly employed to simulate current and future forest dynamics, but most simulate only a single canopy type. This limitation means that mixed stands, canopy succession and understory dynamics cannot be modeled, severe handicaps in many forests. The goals of this study were to develop a version of Biome-BGC that supported multiple, interacting vegetation types, and to assess its performance and limitations by comparing modeled results to published data from a 150-year boreal black spruce (Picea mariana (Mill.) BSP) chronosequence in northern Manitoba, Canada. Model data structures and logic were modified to support an arbitrary number of interacting vegetation types; an explicit height calculation was necessary to prioritize radiation and precipitation interception. Two vegetation types, evergreen needle-leaf and deciduous broadleaf, were modeled based on site-specific meteorological and physiological data. The new version of Biome-BGC reliably simulated observed changes in leaf area, net primary production and carbon stocks, and should be useful for modeling the dynamics of mixed-species stands and ecological succession. We discuss the strengths and limitations of Biome-BGC for this application, and note areas in which further work is necessary for reliable simulation of boreal biogeochemical cycling at a landscape scale.

Bond-Lamberty, Ben, Stith T. Gower, Douglas E. Ahl and Peter E. Thornton. 2005. Reimplementation of the BIOME-BGC model to simulate successional change. Tree Physiol. 25, 413-424.

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Light use efficiency (LUE) models are often used with remotely sensed data products to estimate net primary production (NPP) from local to global scales. However, data on the variability of the LUE coefficient, ε , on the landscape are minimal and sometimes conflicting. The objectives of this study were to (1) quantify and compare the variability of LUE among five forest cover types: aspen, northern hardwoods, red pine, forested wetland, and upland conifer; and (2) quantify the variability of e between two years, 1999 and 2000, and relate differences to environmental conditions. The study site was in a northern temperate forest in Wisconsin, USA. Northern hardwood forests, primarily consisting of sugar maple, had the highest e each year followed by aspen, red pine, forested wetlands, and upland conifer. NPP was estimated using radial growth measurements and published allometric equations. Absorbed photosynthetically active radiation (APAR) was estimated optically using a Li-Cor Plant Canopy Analyzer. Growing season ε of all forest cover types increased significantly from 0.42 in 1999 to 0.47 (gC MJ^-1) in 2000. Annual ε of all forest cover types increased significantly from 0.33 in 1999 to 0.36 (gC MJ^-1) in 2000. Growing season and annual e differed significantly ( p ≤ 0.001) among forest cover types for each year. Future research should consider variations in LUE among mixtures of many land cover types, especially forested wetlands. Results from this study show that LUE models should consider species-specific efficiency factors rather than biome-specific factors. Remote sensing-based land cover classifications should also reflect species differences for this area if the classification map is used in estimating NPP with an LUE model.

Ahl, D, ST Gower, DS Mackay, SN Burrows, JM Norman, and G Diak. 2004. Light use efficiency of a heterogeneous forest in northern Wisconsin: Implications for remote sensing and modeling net primary production, Remote Sensing of Environment 93:168-178.

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