Aboveground Tree Biomass Research Articles

Compost applications increase bacterial community diversity in the apple rhizosphere

AbstractSustainable practices are key to the improvement of soil fertility and quality in apple (Malus × domestica Borkh.) orchards. Rootstock genotype and fertilizer inputs can alter soil biology, as well as aboveground traits including nutrient acquisition. In this study, a factorial design was used to assess the interaction between two apple rootstocks, ‘Geneva 41’ (‘G.41’) and ‘Malling 9’ (‘M.9’) with four fertilizer treatments [chicken‐litter compost, yardwaste compost, fertigation using Ca(NO3)2, and an unamended control]. The bacterial community in the rhizosphere was assessed for its impact on both plant and soil properties for each rootstock × fertilizer treatment combination. The bacterial community was dominated by Acidobacteria, Proteobacteria, and Planctomycetes, but Verrucomicrobia and Chloroflexi were the most responsive to the fertilizer treatments. The chicken litter and yardwaste treatments had a greater effect on bacterial community structure than the control. Yardwaste, in particular, was associated with increased relative abundance of Chloroflexi, which was correlated with soil nutrient concentrations. Malling 9 had a greater bacterial diversity than G.41, but the rootstock treatment had no independent effect on the rhizosphere community structure. There was, however, a strong interaction between the rootstock and fertilizer treatments. Carbon cycling was the most prominent functional change associated with the soil bacterial community. These results suggest that compost amendments have a more positive effect on soil bacterial activity and nutrient availability than Ca(NO3)2. Our work shows that waste‐stream amendments can lead to multiple positive responses, such as increasing aboveground tree biomass, thus potentially improving orchard productivity.

Current aboveground live tree carbon stocks and annual net change in forests of conterminous United States

BackgroundWith the introduction of the Trillion Trees Initiative and similar programs, forests’ ability to absorb carbon dioxide is increasingly in the spotlight. Many states have mandates to develop climate action plans, of which forest carbon is an important component, and planners need current information on forest carbon stocks and rates of change at relevant spatial scales. To this end, we examine rates of average annual change in live aboveground tree carbon in different forest type groups and provide state-wide and regional summaries of current live tree carbon stock and rates of change for the forests of the conterminous United States. Forest carbon summaries are presented in a format designed to meet the needs of managers, policymakers, and others requiring current estimates of aboveground live tree carbon at state and regional scales.ResultsRegional average aboveground live tree carbon stocks (represented on a per area basis) are generally between 40 and 75 tC/ha but range from 12.8 tC/ha in the Great Plains to 130 tC/ha in the Pacific Northwest West (west-side of Cascades). Regional average annual change in live aboveground tree carbon varies from a low of − 0.18 mtC/ha/y in the Rocky Mountain South to a high value of 1.74 mtC/ha/y in Pacific Northwest West. For individual states, carbon per unit area varies widely, from a low of 11.9 tC/ha in Nevada to a high of 96.4 tC/ha in Washington, with half the states falling between 50 and 75 tC/ha. Rates of average annual change in live aboveground tree carbon vary from a high of 1.82 tC/ha/y in Mississippi to a low of − 0.47 tC/ha/y in Colorado.ConclusionsAboveground live tree carbon stocks and rates of average annual change vary by forest type within regions. While softwood forest types currently exhibit a higher rate of increase in the amount of carbon in aboveground live tree biomass, the current standing stock of carbon per unit area does not consistently follow this pattern. For this reason, we recommend computing and considering both measures -standing stock and average annual change—of carbon storage. The relative importance of each component will depend on management and policy objectives and the time frame related to those objectives. Harvesting and natural disturbance also affect forest carbon stock and change and may need to be considered if developing projections of potential carbon storage.

Potential of Alnus acuminata based agroforestry for carbon sequestration and other ecosystem services in Rwanda

Alnus acuminata Kunth. (alnus) is widely used in agroforestry systems across the globe and is believed to provide multiple ecosystem services; however, evidence is lacking in agroforestry literature to support the perceived benefits, particularly in Rwanda. To understand carbon sequestration potential and other benefits of alnus, a household survey, tree inventory and destructive sampling were conducted in north-western Rwanda. Over 75% of the respondents had alnus trees in their farms. The trees provide stakes for climbing beans, firewood and timber. They also improve soil fertility and control soil erosion. Farmers had between 130 and 161 alnus trees per hectare with an average height of 7.7 ± 0.59 m and diameter at breast height of 16.3 ± 1.39 cm. The largest biomass proportion was found in stems (70.5%) while branches and leaves stock about 16.5 and 13% of the total biomass, respectively. At farm level, aboveground biomass of alnus trees was estimated to be 27.2 ± 0.7 Mg ha−1 representing 13.6 Mg of carbon (C) per hectare. Biomass carbon increased with tree size, from 7.1 ± 0.2 Mg C ha−1 in 3 years old trees to 34.4 ± 2.2 Mg C ha−1 in 10 years old trees. The converse was observed with elevation; biomass carbon decreased with increasing elevation from 21.4 ± 1.29 Mg C ha−1 at low (2011–2110 m) to 9.6 ± 0.75 Mg C ha−1 in the high elevation (> 2510 m). In conclusion, alnus agroforestry significantly contributes to carbon sequestration, although the magnitude of these benefits varies with tree age and elevation. Planting alnus trees on farms can meet local needs for stakes for climbing beans, wood and soil fertility improvement, as well as the global need for regulation of climate change.

Trade-Offs and Synergies Between Food and Fodder Production and Other Ecosystem Services in an Actively Restored Forest, Natural Forest and an Agroforestry System in Ghana

Active restoration of degraded areas with multi-purpose tree species has been proposed as a measure to counter the losses from deforestation and mitigate consequences for local human communities. In a restoration project at a former mining site in Ghana, ecosystem services (ES) proxies in an actively restored forest were compared to a local agroforestry system and a natural forest. The results provide information about trade-offs and synergies between proxies of multiple ES(s). ES proxies were assessed according to the following categories: (a) food-tree ES: biomass of food and fodder trees, (b) other trees ES: biomass of fuelwood, medicine or mulch trees, (c) ES-providing arthropods: the number of detritivorous and predaceous arthropods, (d) carbon storage, and (e) tree diversity. Eight replicated plots with sizes of 20 m × 20 m were established in each forest type, and the following ES proxies were quantified: tree diversity was estimated as taxonomic richness of all trees with a diameter at breast height ≥ 10 cm in each plot. Tree species were then classified into ES categories (food, fodder, fuelwood, medicine, or mulch). Ground-dwelling arthropods were sampled for 10 weeks with five pitfall traps in each plot and categorized as decomposers and predators. Tree above-ground biomass was estimated based on the measured tree diameter, height, and specific wood density using an improved allometric equation. The above-ground biomass was later converted into carbon storage by assuming 50% of the above-ground biomass of each tree. ES proxies based on tree biomass were highest in the natural forest. Fodder, medicine, fuelwood, and mulch ES proxies were significantly higher in the restored forest than the agroforestry system. Decomposer arthropods were most dominant in the natural forest, followed by the restored forest and the agroforestry system. Predacious arthropods were more dominant in the restored forest than in the other forest types. Carbon storage was highest in the natural forest, followed by the agroforestry system and the restored forest. The actively restored forest took an intermediate position between the agroforestry system and the natural forest regarding values for all nine ES proxies. Out of the 14 possible relationships between food or fodder and other ES proxies, five were significantly positive (synergies) with no observed trade-offs (significant negative relationships). High fodder production in the restored and natural forests went along with higher values of other biomass ES proxies and numbers of beneficial arthropods, while higher food biomass also correlated positively with numbers of decomposing arthropods. Our results document that active restoration of degraded sites provides a valuable framework to promote ES provision to local communities compared to agroforestry system, but at the cost of lower food and fuelwood biomass and carbon storage compared to natural forests.

Aboveground and belowground tree biomass and carbon stocks in the miombo woodlands of the Copperbelt in Zambia

Globally, belowground biomass (BGB) accounts for 20–26% of total biomass, and as such it is an important carbon (C) pool for many vegetation types. However, large uncertainty exists for belowground biomass C compared to aboveground stocks. Using data from 108 destructively harvested trees belonging to 36 miombo species, we estimated root to shoot ratios, and developed models for estimation of aboveground biomass (AGB), BGB and total biomass C stocks in the Copperbelt province of Zambia. We also validated our models using independent datasets from elsewhere in Zambia and Malawi. The C fractions in wood ranged between 51.9 and 58.9%, which was higher than the IPCC default value. The root to shoot ratio was found to be 0.303. The analysis also demonstrated isometric scaling of BGB with AGB. According to cross-validation results, the model that incorporated wood density (ρ), diameter at breast height (D) and total stem height (H) formulated as AGB =0.093(ρD2H)0.97 *1.08 outperformed existing models developed for the miombo woodlands in Zambia. The best model for BGB was BGB = 0.476(AGB)0.88*1.126. Using the top-ranked models, the stand-level AGB stocks were estimated at 222.2 Mg ha−1, while BGB stocks were estimated at 52.4 Mg ha−1. Aboveground and belowground C stocks were 125.3 Mg ha−1 and 29.5 Mg ha−1, respectively. Total biomass C stocks were estimated at 152.1 Mg ha−1 or 558.3 Mg ha−1 CO2 equivalent sequestered in tree biomass. These estimates may be used as baseline data for future carbon management and for emerging payment for ecosystem services projects in miombo woodlands.

Tropical tree allometry and crown allocation, and their relationship with species traits in central Africa

Common allometric patterns have been reported across the tropics and good performance on independent data was retrieved for the most recent pantropical model predicting tree aboveground biomass (AGB) from stem diameter, wood density and total height. General models are undoubtedly useful for the estimation and monitoring of biomass and carbon stocks in tropical forests, however specific allometry, allocation, and traits, are at the core of many models of vegetation dynamics, and there is lack of such information for some regions and species. In this study, we specifically evaluated how size-dependent changes in above-ground biomass and biomass allocation to crown relate to other allometric and life-history traits for tropical tree species. We gathered destructive data available in eight terra firme forest sites across central Africa and the combined dataset consisted of 1,023 trees belonging to 54 tropical tree species phylogenetically dispersed, with only two congeneric species. A huge body of field and laboratory measurements was used for computing AGB and crown mass ratio (CMR) at the tree level, and to derive key allometric traits at the species level. For the latter, species-specific relationships between tree diameter and total height, crown exposure to light, wood density, and bark thickness were fitted for 50 species. Our results show interspecific variation in the relationships relating tree diameter to both AGB and CMR, and including species traits in a multi-specific AGB model confirmed that interspecific variation in biomass allometry is primarily determined by species wood density. We also showed that the allocation of biomass to crown increases linearly with tree diameter for most species, and that interspecific variation in the CMR model is associated with the species dispersal mode and maximum height. Trait covariations among our set of tropical tree species widespread and/or locally abundant in central Africa, revealed a continuum between large-statured species, which tended to be light-demanding, deciduous and wind-dispersed, and species with opposite attributes. Information on allometry, allocation, and traits provided here could further be used in comparative ecology and for parameterizing dynamic and succession models. Also importantly, the species-specific AGB models fitted for major tree species, including most timber species of central Africa, will help improve biomass estimates.

Influence of climate and forest attributes on aboveground carbon storage in Burkina Faso, West Africa

West African ecosystems play an important role in offsetting carbon inputs and climate change impacts. However, whereas the role of these ecosystems in carbon sequestration has been investigated, there is a paucity in the literature regarding the spatial variation and the drivers of carbon storage in tree aboveground biomass (AGB). This study aimed to analyze the spatial patterns and the drivers of carbon storage in tree AGB in Burkina Faso. We related aboveground carbon density to five structural attributes, three diversity attributes and two climatic variables, using field measurements of 4575 shrubs and trees across four protected areas and two climatic zones. The analysis of variance showed no significant variation of carbon density between the four forests. Yet, carbon density increased significantly from the sudano-sahelian zone to the sudanian zone. The mean carbon density ranged between 47.82 – 67.95 MgC ha−1 across forest sites, and between 48.48 – 64.02 MgC ha−1 across climatic zones. Carbon density was positively correlated with mean annual precipitation (MAP), stand basal area, tree diameter at breast height (DBH), tree height and tree cover, but negatively correlated with mean annual temperature (MAT). Structural attributes explained 13.49–72.61% of carbon storage variation, whereas climate explained 2.62–3.35% of carbon variation. Stand basal area (69.52%) and tree height (27.77%) explained the highest carbon variation. MAP and MAT significantly influenced tree mean DBH and height. This study showed that carbon density in the sudanian region of West Africa is driven by stand structure and climatic variables which directly influence the dendrometric parameters. These findings underscore the fact that drastic changes in climatic conditions in West African region may influence stand structure, and thereby, carbon storage in tree AGB.

Tree Crowns Cause Border Effects in Area-Based Biomass Estimations from Remote Sensing

The estimation of forest biomass by remote sensing is constrained by different uncertainties. An important source of uncertainty is the border effect, as tree crowns are not constrained by plot borders. Lidar remote sensing systems record the canopy height within a certain area, while the ground-truth is commonly the aboveground biomass of inventory trees geolocated at their stem positions. Hence, tree crowns reaching out of or into the observed area are contributing to the uncertainty in canopy-height–based biomass estimation. In this study, forest inventory data and simulations of a tropical rainforest’s canopy were used to quantify the amount of incoming and outgoing canopy volume and surface at different plot sizes (10, 20, 50, and 100 m). This was performed with a bottom-up approach entirely based on forest inventory data and allometric relationships, from which idealized lidar canopy heights were simulated by representing the forest canopy as a 3D voxel space. In this voxel space, the position of each voxel is known, and it is also known to which tree each voxel belongs and where the stem of this tree is located. This knowledge was used to analyze the role of incoming and outgoing crowns. The contribution of the border effects to the biomass estimation uncertainty was quantified for the case of small-footprint lidar (a simulated canopy height model, CHM) and large-footprint lidar (simulated waveforms with footprint sizes of 23 and 65 m, corresponding to the GEDI and ICESat GLAS sensors). A strong effect of spatial scale was found: e.g., for 20-m plots, on average, 16% of the CHM surface belonged to trees located outside of the plots, while for 100-m plots this incoming CHM fraction was only 3%. The border effects accounted for 40% of the biomass estimation uncertainty at the 20-m scale, but had no contribution at the 100-m scale. For GEDI- and GLAS-based biomass estimates, the contributions of border effects were 23% and 6%, respectively. This study presents a novel approach for disentangling the sources of uncertainty in the remote sensing of forest structures using virtual canopy modeling.

Estimation of tree height and aboveground biomass of coniferous forests in North China using stereo ZY-3, multispectral Sentinel-2, and DEM data

The forest tree height and aboveground biomass (AGB) are important indicators for monitoring changes and trends in forest carbon storage and terrestrial carbon fluxes. Accurate large-scale wall-to-wall mapping of the forest tree height and AGB remain challenging due to the limited data availability for extraction tree height and the data signal saturation problem in AGB estimation. In this study, we explored the potential of forest tree height mapping using stereo imageries, and analyzed whether accounting for such information, in addition to optical sensor data, could improve the performance of AGB estimations of coniferous forests in a case study in North China. First, a spatially continuous tree height product was obtained using Ziyuan-3 satellite (ZY-3) stereo images combined with a digital elevation model (DEM) obtained from Advanced Land Observing Satellite (ALOS) data. Second, two AGB estimation models were established by combining the forest tree height with vegetation index, spectral, biophysical (from Sentinel-2 images), and topographic variables. A random forest algorithm was utilized to evaluate the effect of including the tree height variable in the AGB estimation. The results showed that the tree height estimation using the nadir and forward views of the ZY-3 stereo images was more accurate than that based on the nadir and backward views from the same images. The AGB estimation model incorporating the tree height variable with a coefficient of determination value of 0.7789, a root mean square error (RMSE) value of 29.815 Mg/ha and a relative RMSE of 23.42% was more robust and effective, thereby demonstrating thatthe tree height variable can be used to alleviate the data signal saturation issue successfully. The proposed approach can provide new insight into forest tree height mapping and AGB products obtained from satellite stereo images and freely accessible Sentinel-2 multispectral images.

Habitat Quality Differentiation and Consequences for Ecosystem Service Provision of an Amazonian Hyperdominant Tree Species.

Ecosystem services of Amazonian forests are disproportionally produced by a limited set of hyperdominant tree species. Yet the spatial variation in the delivery of ecosystem services by individual hyperdominant species across their distribution ranges and corresponding environmental gradients is poorly understood. Here, we use the concept of habitat quality to unravel the effect of environmental gradients on seed production and aboveground biomass (AGB) of the Brazil nut, one of Amazonia’s largest and most long-lived hyperdominants. We find that a range of climate and soil gradients create trade-offs between density and fitness of Brazil nut trees. Density responses to environmental gradients were in line with predictions under the Janzen–Connell and Herms–Mattson hypotheses, whereas tree fitness responses were in line with resource requirements of trees over their life cycle. These trade-offs resulted in divergent responses in area-based seed production and AGB. While seed production and AGB of individual trees (i.e., fitness) responded similarly to most environmental gradients, they showed opposite tendencies to tree density for almost half of the gradients. However, for gradients creating opposite fitness-density responses, area-based seed production was invariable, while trends in area-based AGB tended to mirror the response of tree density. We conclude that while the relation between environmental gradients and tree density is generally indicative of the response of AGB accumulation in a given area of forest, this is not necessarily the case for fruit production.

Above-ground biomass references for urban trees from terrestrial laser scanning data.

Background and AimsWithin extending urban areas, trees serve a multitude of functions (e.g. carbon storage, suppression of air pollution, mitigation of the ‘heat island’ effect, oxygen, shade and recreation). Many of these services are positively correlated with tree size and structure. The quantification of above-ground biomass (AGB) is of especial importance to assess its carbon storage potential. However, quantification of AGB is difficult and the allometries applied are often based on forest trees, which are subject to very different growing conditions, competition and form. In this article we highlight the potential of terrestrial laser scanning (TLS) techniques to extract highly detailed information on urban tree structure and AGB.MethodsFifty-five urban trees distributed over seven cities in Switzerland were measured using TLS and traditional forest inventory techniques before they were felled and weighed. Tree structure, volume and AGB from the TLS point clouds were extracted using quantitative structure modelling. TLS-derived AGB estimates were compared with AGB estimates based on forest tree allometries dependent on diameter at breast height only. The correlations of various tree metrics as AGB predictors were assessed.Key ResultsEstimates of AGB derived by TLS showed good performance when compared with destructively harvested references, with an R2 of 0.954 (RMSE = 556 kg) compared with 0.837 (RMSE = 1159 kg) for allometrically derived AGB estimates. A correlation analysis showed that different TLS-derived wood volume estimates as well as trunk diameters and tree crown metrics show high correlation in describing total wood AGB, outperforming tree height.ConclusionsWood volume estimates based on TLS show high potential to estimate tree AGB independent of tree species, size and form. This allows us to retrieve highly accurate non-destructive AGB estimates that could be used to establish new allometric equations without the need for extensive destructive harvesting.

Aboveground biomass and carbon sequestration potential of tea and shade trees in <i>Miang</i> tea gardens, an agroforestry system in Northern Thailand

Aboveground biomass and carbon sequestration potential of tea and shade trees in <i>Miang</i> tea gardens, an agroforestry system in Northern Thailand

Height–diameter allometry in African monodominant forest close to mixed forest

AbstractAfrican monodominant forests are frequently formed byGilbertiodendron dewevrei(De Wild.) J. Leonard and commonly found close to mixed forests. However, previous studies have ignored differences between these two forest types in height–diameter allometry, which is extremely important for aboveground biomass (AGB) estimates. This study aims to evaluate the performance of height–diameter models and their effects on height attributes and AGB estimations in African monodominant and mixed forests. Four 1-ha plots divided in 16 subplots (0.25 ha) were installed in each forest type in northern Republic of Congo. We measured diameter of all trees ≥ 10 cm diameter for each subplot and we measured the height of 264 trees over a large range of 7–64 m in two forest types. There was a significant difference in height–diameter allometry between two forest types and trees were taller and had greater AGB in monodominant forests than in mixed forests. Two height–diameter models from the literature generated the lowest error values when predicting tree height and AGB in mixed forests, whereas no model derived from the literature was appropriate for monodominant forests. The variation in height–diameter allometry between monodominant and mixed forests influences AGB estimates that have practical implications for carbon monitoring.

Aboveground tree biomass of Araucaria araucana in southern Chile: measurements and multi-objective optimization of biomass models

Abstract: Estimating carbon stocks in wooded systems is crucial to quantify national greenhouse gas balance estimates. However, inaccurate estimates are likely due to the divergent architecture of many species. The monkey puzzle tree Araucaria araucana, with its umbrella-like architecture is a vivid example. This species, often found in monodominant stands at high elevations, is the greatest carbon reservoir in the landscape, hence estimating its carbon storage is crucial. To provide the necessary basis for these estimations, we documented the variation in basic density and moisture content along the stem profile, identified the most suitable biomass estimation models, and quantified biomass allocation for three age ranges. We measured, felled, weighed, and separated trees into three categories: stem wood, stem bark, and foliage (branches + scaly leaves). The log-linear form of the simple allometric equation Y = aXb, based on diameter at breast height as the explanatory variable, covered a large part of the variation and showed good cross-validation performance (>0.96). Models using more covariates achieved lower absolute errors, but the estimation of the additional model parameters was associated with greater uncertainty. A multi-objective model comparison revealed that the best additional covariate to further improve biomass estimation was total tree height. The mean absolute percentage error was 9.8% for the total aboveground biomass, 8% for stem wood, 12% for stem bark and 24% for foliage. Changes in biomass distribution among tree components were related to age. For older trees, there was a relative increase in stem wood, a decreased proportion of foliage, but no change in stem bark. The proportion of stem bark biomass is similar to that of Araucaria angustifolia, but higher than in other conifers and most trees in general. Our results provide key properties for A. araucana and general guidance for the selection of easily-measurable variables allowing for excellent predictive power for local biomass estimation.

Using allometric models to estimate aboveground biomass and predict carbon stocks of mango (Mangifera indica L.) parklands in the Sudanian zone of Burkina Faso

Tree growth is an important means of capturing and storing atmospheric carbon and is thus a key to mitigating the effects of climate change. Over recent decades, mango (Mangifera indica L.) parklands have expanded in Burkina Faso, due to the species’ fast growth and its compatibility with local agricultural crops. However, the contribution of mango parklands to reducing atmospheric CO2 remains unknown, due to the lack of local tools for aboveground biomass (AGB) estimation. The aim of this study was to develop accurate allometric equations for estimating the AGB and carbon (C) stocks of mango parklands. A field survey was carried out to select mango parklands according to their age. These parklands were then classified into six groups age (0≦y<5, 5≦y<10, 10≦y<15, 15≦y<20, 20≦y<25, y≧25) and dendrometric measurements were taken within 72 plots of 2500m² each. Inventoried mango trees were grouped into 5 diameter at breast eight (DBH) classes and the number of trees sampled per DBH class was a function of the class homogeneity. Twenty-five (25) mango trees were destructively sampled to estimate tree AGB. The belowground biomass was calculated based on existing mango root-to-shoot ratio data. The C content in tree aboveground components was evaluated using the ash method. Power and linear models were tested and fitted to the total AGB. The validated equations showed a good fit and performance with high explained variance (R² = 95%). The power model was the best model with DBH alone being the best predictor. The obtained means (±Standard deviation) AGB, belowground and total biomass were 326.64±279.1; 84.93±72.58 and 411.56±351.75 kg tree−1 respectively. The C content of the leaves, branches and trunk were 53.79, 54.78 and 55.79% respectively, whereas the mean C stock for aboveground, belowground and total C were 179.90; 42.46 and 222.36 kg tree−1 respectively. For a density of 152.30 ± 36.83ind ha−1, the mean aboveground and belowground biomass was 62.67 t ha−1, giving a total C stock of 33.85 t C ha−1for the studied mango parklands.

Aboveground Biomass Allocation of Boreal Shrubs and Short-Stature Trees in Northwestern Canada

In this follow-on study on aboveground biomass of shrubs and short-stature trees, we provide plant component aboveground biomass (herein ‘AGB’) as well as plant component AGB allometric models for five common boreal shrub and four common boreal short-stature tree genera/species. The analyzed plant components consist of stem, branch, and leaf organs. We found similar ratios of component biomass to total AGB for stems, branches, and leaves amongst shrubs and deciduous tree genera/species across the southern Northwest Territories, while the evergreen Picea genus differed in the biomass allocation to aboveground plant organs compared to the deciduous genera/species. Shrub component AGB allometric models were derived using the three-dimensional variable volume as predictor, determined as the sum of line-intercept cover, upper foliage width, and maximum height above ground. Tree component AGB was modeled using the cross-sectional area of the stem diameter as predictor variable, measured at 0.30 m along the stem length. For shrub component AGB, we achieved better model fits for stem biomass (60.33 g ≤ RMSE ≤ 163.59 g; 0.651 ≤ R2 ≤ 0.885) compared to leaf biomass (12.62 g ≤ RMSE ≤ 35.04 g; 0.380 ≤ R2 ≤ 0.735), as has been reported by others. For short-stature trees, leaf biomass predictions resulted in similar model fits (18.21 g ≤ RMSE ≤ 70.0 g; 0.702 ≤ R2 ≤ 0.882) compared to branch biomass (6.88 g ≤ RMSE ≤ 45.08 g; 0.736 ≤ R2 ≤ 0.923) and only slightly better model fits for stem biomass (30.87 g ≤ RMSE ≤ 11.72 g; 0.887 ≤ R2 ≤ 0.960), which suggests that leaf AGB of short-stature trees (&lt;4.5 m) can be more accurately predicted using cross-sectional area as opposed to diameter at breast height for tall-stature trees. Our multi-species shrub and short-stature tree allometric models showed promising results for predicting plant component AGB, which can be utilized for remote sensing applications where plant functional types cannot always be distinguished. This study provides critical information on plant AGB allocation as well as component AGB modeling, required for understanding boreal AGB and aboveground carbon pools within the dynamic and rapidly changing Taiga Plains and Taiga Shield ecozones. In addition, the structural information and component AGB equations are important for integrating shrubs and short-stature tree AGB into carbon accounting strategies in order to improve our understanding of the rapidly changing boreal ecosystem function.

First-Decade Biomass and Carbon Accumulation, and Woody Community Change after Severe Wind Damage in a Hemlock-White Pine Forest Remnant

Studies of biomass and carbon dynamics and community composition change after forest wind disturbance have predominantly examined trends after low and intermediate severity events, while studies after very severe wind disturbance have been few. This study documents trends in aboveground biomass and carbon across 10 years of forest recovery after severe wind disturbance. In July 1989, a tornado struck mature Tsugacanadensis-Pinusstrobus forest in northwest Connecticut, USA, causing damage across roughly 8 ha. Canopy tree damage and regeneration were surveyed in 1991 and 1999. Two primary hypotheses were tested, both of which derive from regeneration being primarily via the release of suppressed saplings rather than new seedling establishment: (1) Biomass and carbon accumulation will be faster than accumulation reported from a similar forest that experienced similar severity of wind disturbance; and (2) The stand will experience very little change in species composition or diversity. Estimated immediate post-disturbance (1989) aboveground live-tree carbon was 20.7 ± 43.9 Mg ha−1 (9.9% of pre-disturbance) Ten years after the disturbance, carbon in aboveground live tree biomass increased to 37.1 ± 47.9 Mg ha−1; thus for the first decade, annual accumulation averaged 1.6 Mg ha−1 of carbon; this was significantly faster than the rate reported in a similar forest that experienced similar severity of wind disturbance. The species diversity of woody stems ten years after the disturbance was significantly higher (nonoverlapping confidence intervals of rarefaction curves) than pre-disturbance canopy trees. Thus, hypothesis 1 was confirmed while hypothesis 2 was rejected. This study augments the limited number of longer-term empirical studies that report biomass and carbon accumulation rates after wind disturbance, and can therefore serve as a benchmark for mechanistic and modeling research.

Mega-dams and extreme rainfall: Disentangling the drivers of extensive impacts of a large flooding event on Amazon Forests.

Extreme weather events and the presence of mega-hydroelectric dams, when combined, present an emerging threat to natural habitats in the Amazon region. To understand the magnitude of these impacts, we used remote sensing data to assess forest loss in areas affected by the extreme 2014 flood in the entire Madeira River basin, the location of two mega-dams. In addition, forest plots (26 ha) were monitored between 2011 and 2015 (14,328 trees) in order to evaluate changes in tree mortality, aboveground biomass (AGB), species composition and community structure around the Jirau reservoir (distance between plots varies from 1 to 80 km). We showed that the mega-dams were the main driver of tree mortality in Madeira basin forests after the 2014 extreme flood. Forest loss in the areas surrounding the reservoirs was 56 km2 in Santo Antônio, 190 km2 in Jirau (7.4–9.2% of the forest cover before flooding), and 79.9% above that predicted in environmental impact assessments. We also show that climatic anomalies, albeit with much smaller impact than that created by the mega-dams, resulted in forest loss along different Madeira sub-basins not affected by dams (34–173 km2; 0.5–1.7%). The impact of flooding was greater in várzea and transitional forests, resulting in high rates of tree mortality (88–100%), AGB decrease (89–100%), and reduction of species richness (78–100%). Conversely, campinarana forests were more flood-tolerant with a slight decrease in species richness (6%) and similar AGB after flooding. Taking together satellite and field measurements, we estimate that the 2014 flood event in the Madeira basin resulted in 8.81–12.47 ∙ 106 tons of dead biomass. Environmental impact studies required for environmental licensing of mega-dams by governmental agencies should consider the increasing trend of climatic anomalies and the high vulnerability of different habitats to minimize the serious impacts of dams on Amazonian biodiversity and carbon stocks.

Stand structure determines aboveground biomass across temperate forest types and species mixture along a local-scale elevational gradient

Greater variation in stand structure (i.e., individual tree size variation and stand density) is thought to promote aboveground biomass (AGB) better than species richness due to the canopy packing by different sized trees in the forest community. Here, we hypothesized that the relationships amongst species richness, stand density, individual tree size variation and AGB are dependent on forest types but single-species dominated forest stands matter much for higher AGB through higher stand density and individual tree size variation. To do this, we analyzed the forest inventory data (i.e., tree diameter, tree height, and species names) from 365 forest plots (each 0.1 ha) which was taken at different elevational gradients of temperate forest types (i.e., dense pure conifer, dense mixed forests, sparse mixed forests, sparse pure broadleaved, sparse pure conifer, and dense pure broadleaved) as well as species mixture groups (single-species and multi-species stands) in the northern area (namely Gilgit-Baltistan) of Pakistan. We mainly used piecewise structural equation modeling for testing the fixed effects of elevation, species richness, individual tree size variation and stand density as well as the random effect of either forest types or species mixture on AGB, and then we used linear structural equation modeling to test the models across forest types and species mixtures. We found the consistent positive effect of stand density on AGB across whole data, forest types and species mixtures, albeit species richness also showed a positive effect in some of the forest types. Individual tree size variation had a greater positive effect on AGB in single-species dominated stands compared to multi-species dominated stands. Elevation declined AGB directly and indirectly via stand density. We conclude that variation in stand structures (stand density and individual tree size variation of single-species dominated stands) are key to higher AGB in most of the temperate forest types. The positive effects of stand density and species richness on AGB may provide support to the niche complementarity effect through stand packing, whereas the greater effect of individual tree size variation on AGB in single-species rather than multi-species dominated stands may also confirm the selection or competitive exclusion effect. Therefore, we argue that both of the niche complementarity and selection effects are acting simultaneously to determine the relationships amongst species richness, stand structure and AGB in the studied temperate forests.

Aboveground Biomass and Carbon Accumulation 19 Years Post-Windthrow and Salvage Logging

Natural disturbances shape forest ecosystem characteristics, including carbon storage and structure. Often, natural disturbances are compounded with anthropogenic disturbances, which may alter the trajectory of forest carbon stock recovery. Heterogeneous levels of disturbance severity in compound disturbance events add an additional layer of complexity. This paper examines the effect of a moderate-severity wind disturbance and subsequent salvage logging on forest biomass and carbon stock recovery over 19 years. We investigate the recovery of aboveground tree biomass following a wind disturbance and salvage logging and examine the role of wind disturbance severity on biomass accumulation rates. We use pre-disturbance, 3 years post-wind disturbance and 19 years post-wind disturbance measurements of tree biomass across two adjacent sites at Natchez Trace State Forest for Site A and Site B in east central Tennessee. We found no significant difference in the carbon storage at Site A (pre = 92 MgC/ha; 19 years post-disturbance = 83 MgC/ha) or Site B (pre = 66 MgC/ha; 19 years post-disturbance = 67) when comparing the pre-disturbance level of aboveground tree carbon storage with the 19-years post-disturbance levels. Furthermore, we found no evidence that salvage logging reduced the rate of live tree carbon accumulation. The corresponding rates of mean annual carbon accumulation (MgC/ha) are as follows: Site A Unsalvaged (1.07), Site A Salvaged (1.25) and Site B Salvaged (2.02). Contrary to our prediction, greater wind damage severity was weakly associated with higher rates of biomass accumulation (R2 = 0.17). While we found no negative effect of salvage logging on the aboveground tree carbon accumulation rate, salvage logging alters other carbon pools, including coarse woody debris. Salvage logging did not reduce the rate of carbon stock recovery, and a higher wind disturbance severity was associated with a greater rate of carbon stock recovery.