Previous attempts to quantify methane (CH
4
) fluxes from tree foliage have yielded ambiguous results, and very few studies have measured
in situ
foliar CH
4
fluxes, particularly in upland sites. ...Here we quantify CH
4
fluxes from tree foliage in upland and lowland temperate forests in central Ontario, Canada. Foliar CH
4
, carbon dioxide, and water vapor fluxes were measured in direct sunlight and imposed darkness using an off-axis-integrated cavity output spectroscopy system, and results were scaled to the stand level using estimates of sunlit and shaded leaf area index. We show that foliage in the upland site was consistently a CH
4
sink during the day (− 0.54 nmol m
−2
s
−1
± 0.06 SE in direct sunlight), representing about 38% of net daytime CH
4
uptake by the ecosystem. Uptake was approximately two times higher in direct sunlight compared to imposed darkness and undetectable at night. The mechanism for uptake is hypothesized to be endophytic methanotrophic bacteria—relationships between CH
4
and water vapor fluxes suggest CH
4
uptake is regulated by transpiration and occurs within foliage tissues. In the lowland site foliage was a CH
4
source (6.06 nmol m
−2
s
−1
± 2.47 SE in direct sunlight) with an emission rate about 8% that of the soil, confirming previous findings suggesting xylem transport of soil-borne CH
4
occurs in lowland forests with net soil methanogenesis. We conclude that tree foliage can act as both a substantial CH
4
sink in upland forests and a CH
4
source in lowland forests and thus is an important component in greenhouse gas budgets.
We apply a spatially-implicit, allometry-based modelling approach to predict stem diameter distributions (SDDs) from low density airborne LiDAR data in a heterogeneous, temperate forest in Ontario, ...Canada. Using a recently published algorithm that relates the density, size, and species of individual trees to the height distribution of first returns, we estimated parameters that succinctly describe SDDs that are most consistent with each 0.25-ha LiDAR tile across a 30,000 ha forest landscape. Tests with independent validation plots showed that the diameter distribution of stems was predicted with reasonable accuracy in most cases (half of validation plots had R2 ≥ 0.75, and another 23% had 0.5 ≤ R2 < 0.75). The predicted frequency of larger stems was much better than that of small stems (8 ≤ x < 11 cm diameter), particularly small conifers. We used the predicted SDDs to calculate aboveground carbon density (ACD; RMSE = 21.4 Mg C/ha), quadratic mean diameter (RMSE = 3.64 cm), basal area (RMSE = 6.99 m2/ha) and stem number (RMSE = 272 stems/ha). The accuracy of our predictions compared favorably with previous studies that have generally been undertaken in simpler conifer-dominated forest types. We demonstrate the utility of our results to spatial forest management planning by mapping SDDs, the proportion of broadleaves, and ACD at a 0.25 ha resolution.
In part I of our two-part study, we compare the timing-adjusted GHG (greenhouse gas) balance and life cycle impacts of potentially using harvest residue (unmerchantable small-diameter roundwood) in ...an existing large (211 MWe) wood pellet-fired (formerly coal-fired) power plant in Ontario, Canada, versus a hypothetical small (250 kWe) wood chip gasification plant that recovers heat in addition to producing electricity. Although the large, retrofitted power plant has a higher electrical efficiency, the small plant has lower environmental impacts (TRACI 2.1), mainly due to the benefits of drying the biomass inputs with recovered heat, having a shorter fuel shipping distance, and reduced biomass processing. The small plant emits 38 g of fossil fuel-derived CO2 eq./kWh, versus 134 g/kWh from its large-scale counterpart. Although these GHG emissions are insignificant relative to the forest carbon emissions from gasification and combustion (1.3–1.4 kg CO2/kWh), the harvest residue would have decomposed over time had it been left on the forest floor. After 100 years, forest carbon storage decreases by 3.8–4.1 kg from the sustained production of 1 kWh of electricity per year. The decline in carbon storage delays net GHG mitigation by 4 (small-scale system) to 7 years (large-scale system) when displacing electricity from coal.
•We estimate GHGs and impacts from using harvest residue to displace coal and propane.•Residue is allocated to small- (250 kWe) and large-scale (211 MWe) bioenergy systems.•Non-biogenic GHGs reach 38 (small-scale system) to 134 (large-scale) g CO2 eq./kWh.•Forest C storage decreases by 3.8–4.1 kg from the sustained production of 1 kWh/yr.•Net GHG mitigation begins at 4 (small-scale system) to 7 (large-scale) years.
Tree stems have been identified as globally significant methane (CH.sub.4) sources; however, little information exists on emissions from tree wounds and branches. CH.sub.4 emissions can occur from ...the decomposition of anaerobic heartwood, which is also associated with wounds; CH.sub.4 may also be transported through the transpiration stream and emitted from branches. We compared CH.sub.4 emissions between tree stems and branches and assessed whether trees with major wounds emit more than those without. CH.sub.4 fluxes were measured from stems, branches, and wounds (classified as major or minor) of two dominant tree species in an upland temperate forest, and from the soil, and scaled up to the stand level. Branches and stems of both species emitted CH.sub.4, and the per unit area emission rates from branches were similar to (or in some cases greater than) stems. Trees with major wounds had greater CH.sub.4 emission rates than those without, from unblemished sections of their stems and from the wounds. At the stand scale, branches, stems, and wounds accounted for 83%, 9%, and 8% of net CH.sub.4 emissions from trees, respectively, and collectively offset 63% of the soil CH.sub.4 sink. These results indicate that tree branches and wounds can be important CH.sub.4 sources in forests.
There is currently much interest in developing general approaches for mapping forest aboveground carbon density using structural information contained in airborne LiDAR data. The most widely utilized ...model in tropical forests assumes that aboveground carbon density is a compound power function of top of canopy height (a metric easily derived from LiDAR), basal area and wood density. Here we derive the model in terms of the geometry of individual tree crowns within forest stands, showing how scaling exponents in the aboveground carbon density model arise from the height-diameter (H-D) and projected crown area-diameter (C-D) allometries of individual trees. We show that a power function relationship emerges when the C-D scaling exponent is close to 2, or when tree diameters follow a Weibull distribution (or other specific distributions) and are invariant across the landscape. In addition, basal area must be closely correlated with canopy height for the approach to work. The efficacy of the model was explored for a managed uneven-aged temperate forest in Ontario, Canada within which stands dominated by sugar maple (Acer saccharum Marsh.) and mixed stands were identified. A much poorer goodness-of-fit was obtained than previously reported for tropical forests (R2 = 0.29 vs. about 0.83). Explanations for the poor predictive power on the model include: (1) basal area was only weakly correlated with top canopy height; (2) tree size distributions varied considerably across the landscape; (3) the allometry exponents are affected by variation in species composition arising from timber management and soil conditions; and (4) the C-D allometric power function was far from 2 (1.28). We conclude that landscape heterogeneity in forest structure and tree allometry reduces the accuracy of general power-function models for predicting aboveground carbon density in managed forests. More studies in different forest types are needed to understand the situations in which power functions of LiDAR height are appropriate for modelling forest carbon stocks.
We have developed a dynamic land model (LM3V) able to simulate ecosystem dynamics and exchanges of water, energy, and CO2 between land and atmosphere. LM3V is specifically designed to address the ...consequences of land use and land management changes including cropland and pasture dynamics, shifting cultivation, logging, fire, and resulting patterns of secondary regrowth. Here we analyze the behavior of LM3V, forced with the output from the Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric model AM2, observed precipitation data, and four historic scenarios of land use change for 1700–2000. Our analysis suggests a net terrestrial carbon source due to land use activities from 1.1 to 1.3 GtC/a during the 1990s, where the range is due to the difference in the historic cropland distribution. This magnitude is substantially smaller than previous estimates from other models, largely due to our estimates of a secondary vegetation sink of 0.35 to 0.6 GtC/a in the 1990s and decelerating agricultural land clearing since the 1960s. For the 1990s, our estimates for the pastures' carbon flux vary from a source of 0.37 to a sink of 0.15 GtC/a, and for the croplands our model shows a carbon source of 0.6 to 0.9 GtC/a. Our process‐based model suggests a smaller net deforestation source than earlier bookkeeping models because it accounts for decelerated net conversion of primary forest to agriculture and for stronger secondary vegetation regrowth in tropical regions. The overall uncertainty is likely to be higher than the range reported here because of uncertainty in the biomass recovery under changing ambient conditions, including atmospheric CO2 concentration, nutrients availability, and climate.
A better understanding of the relationship between stand structure and productivity is required for the development of: a) scalable models that can accurately predict growth and yield dynamics for ...the world's forests; and b) stand management regimes that maximize wood and/or timber yield, while maintaining structural and species diversity.
We develop a cohort-based canopy competition model ("CAIN"), parameterized with inventory data from Ontario, Canada, to examine the relationship between stand structure and productivity. Tree growth, mortality and recruitment are quantified as functions of diameter and asymmetric competition, using a competition index (CAI(h)) defined as the total projected area of tree crowns at a given tree's mid-crown height. Stand growth, mortality, and yield are simulated for inventoried stands, and also for hypothetical stands differing in total volume and tree size distribution.
For a given diameter, tree growth decreases as CAI(h) increases, whereas the probability of mortality increases. For a given CAI(h), diameter growth exhibits a humped pattern with respect to diameter, whereas mortality exhibits a U-shaped pattern reflecting senescence of large trees. For a fixed size distribution, stand growth increases asymptotically with total density, whereas mortality increases monotonically. Thus, net productivity peaks at an intermediate volume of 100-150 m(3)/ha, and approaches zero at 250 m(3)/ha. However, for a fixed stand volume, mortality due to senescence decreases if the proportion of large trees decreases as overall density increases. This size-related reduction in mortality offsets the density-related increase in mortality, resulting in a 40% increase in yield.
Size-related variation in growth and mortality exerts a profound influence on the relationship between stand structure and productivity. Dense stands dominated by small trees yield more wood than stands dominated by fewer large trees, because the relative growth rate of small trees is higher, and because they are less likely to die.
Recent advances in remote sensing technology provide sufficient spatial detail to achieve species-level classification over large vegetative ecosystems. In deciduous-dominated forests, however, as ...tree species diversity and forest structural diversity increase, the frequency of spectral overlap between species also increases and our ability to classify tree species significantly decreases. This study proposes an operational workflow of individual tree-based species classification for a temperate, mixed deciduous forest using three-seasonal WorldView images, involving three steps of individual tree crown (ITC) delineation, non-forest gap elimination, and object-based classification. The process of species classification started with ITC delineation using the spectral angle segmentation algorithm, followed by object-based random forest classifications. A total of 672 trees was located along three triangular transects for training and validation. For single-season images, the late-spring, mid-summer, and early-fall images achieve the overall accuracies of 0.46, 0.42, and 0.35, respectively. Combining the spectral information of the early-spring, mid-summer, and early-fall images increases the overall accuracy of classification to 0.79. However, further adding the late-fall image to separate deciduous and coniferous trees as an extra step was not successful. Compared to traditional four-band (Blue, Green, Red, Near-Infrared) images, the four additional bands of WorldView images (i.e., Coastal, Yellow, Red Edge, and Near-Infrared2) contribute to the species classification greatly (OA: 0.79 vs. 0.53). This study gains insights into the contribution of the additional spectral bands and multi-seasonal images to distinguishing species with seemingly high degrees of spectral overlap.
Two types of nonparametric modeling techniques and various metrics derived from airborne laser scanning (ALS) data were examined in terms of their utility for modeling stem diameter distributions in ...an uneven-aged tolerant hardwood forest in Ontario, Canada. Using an area-based approach (ABA), the frequency distribution of trees across 6 size classes was predicted using k-nearest neighbor (k-NN) imputation and Random Forest (RF) regression. Predictor variables derived from ALS height and intensity data were divided into 3 groups: height only, intensity only, and all metrics. Prediction results demonstrated that the first 2 groups of predictor variables exhibited similar predictive accuracy, whereas the synergy of both resulted in enhanced performance. The utility of intensity-based metrics was corroborated by an importance measure obtained from RF. The size class-specific stem density estimation approach based on RF was more accurate and flexible than the simultaneous estimation approach based on k-NN models. After the predicted diameter distributions were grouped into 9 structural groups, heterogeneous accuracy scores revealed the challenges for predicting select diameter distributions. Although successes were observed for certain size classes, there remains additional research (e.g., development of additional metrics or data types) to be done to accurately predict a complete range of size classes.
•Soil respiration was elevated for three years following partial harvesting.•Respiration differences between harvesting and control treatments varied seasonally.•Large autumn differences were linked ...to increased fine woody debris.•Low summer differences and were associated with reduced tree cover.•Increasing relative Q10 values in harvested plots linked to understorey regrowth.
Disturbances can alter CO2 efflux from soils (FCO2) by altering the microclimate, structure, and biogeochemical properties of forest ecosystems. Results of prior studies are unclear if and how partial harvesting of northern deciduous forests affects FCO2. These mixed responses may be due to differences in harvesting levels, time since harvest, and the spatial and seasonal heterogeneity of treatment effects and soil properties. To account for this spatio-temporal dependence, we produced subject-level regression models from regular measurements of FCO2 and soil temperatures during the 2010–2012 growing seasons following tree-length (TL) and more intensive biomass (BIO) harvests. In this paper, we compare seasonal and inter-annual post-harvest recovery trends for measured and temperature-corrected soil respiration rates and the sensitivity of soil respiration to temperature (as Q10).
FCO2 values from TL/BIO treatments exceeded unharvested controls, recurrently peaking in the autumn (average for TL/BIO: 28%/17%, p⩽0.05) and waning in the summer (14%/10%, not significant). A comparison of measured FCO2 vs. modelled respiration values corrected for temperature differences indicated that higher soil temperatures following canopy thinning accounted for 34–41% of these differences in 2010 but <15% by 2012. Initially lower in 2010, Q10 and summer respiration values for harvested treatments exceeded those of controls by 2012, and despite waning temperature differences, average annual effect sizes corrected for temperature differences did not decline. Autumn and basal respiration rates were correlated with post-harvest fine woody debris volumes in 2010 (r2=0.58/0.57, p=0.01), summer rates in all years decreased with harvested tree basal area (r2=0.43–0.58, p⩽0.05), and the post-harvest basal area of understorey vegetation predicted increasing Q10 effect sizes from 2010 to 2012 (r2=0.81, p⩽0.01). With consideration to studies demonstrating that the contribution of root respiration (RR) to FCO2 is highest in summer, we propose that partial harvesting initially restricts RR and peak summer respiration rates, but compensates for this decline by increasing basal respiration rates and FCO2 through elevated soil temperatures and decomposition rates from canopy thinning and harvest residue substrate inputs (i.e., woody debris and root necromass). During post-harvest recovery, forest understorey regrowth reduces soil temperatures but influences patterns of FCO2 by increasing summer respiration and Q10 values in harvested treatments, likely by increasing RR.
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