Species-specific Allometric Equations Research Articles

Species-specific allometric models for reducing uncertainty in estimating above ground biomass at Moist Evergreen Afromontane Forest of Ethiopia

An allometric equation is used to convert easily measured tree variables into biomass. However, limited species-specific biomass equations are available for native tree species grown in various biomes of Ethiopia. The available pantropic generic equation has resulted in biases owing to the uncertainty of the generic model estimation due to the difference in tree nature and response to growth conditions. The objective of the study is, thus, to develop a species-specific allometric equation for reducing uncertainty in biomass estimation at the Moist Evergreen Afromontane Forest in south-central Ethiopia. Five tree species were selected for model development, these selected trees were harvested and weighed in the field. The measured above-ground biomass data related to easily measured tree variables: diameter at stump height, diameter at breast height (dbh), crown diameter, and total tree height. The developed model evaluated and compared with previously published model by using measures of goodness of fit such as coefficient of determination (R2), total relative error, mean prediction error, root mean square error, and Akaike information criteria. The analysis showed that a model with dbh as a single predictor variable was selected as the best model for the estimation of above-ground biomass. It gives the highest R2 for Syzygium guineense (0.992) and the lowest for Bersama abyssinica (0.879). The additions of other tree variables did not improve the model The pantropic model by Brown overestimates the biomass by 9.6–77.8% while both Chave models resulted in an estimation error of 12–50.3%. Our findings indicated that species-specific allometric equations outperformed both site-specific and pantropic models in estimating above-ground biomass by giving 0.1% up to 7.9% estimation error for the respective tree species.

Traditional homegardens change to perennial monocropping of khat (Catha edulis) reduced woody species and enset conservation and climate change mitigation potentials of the Wondo Genet landscape of southern Ethiopia

Smallholder farmers in the Wondo Genet were forced to switch from long-standing, diverse traditional home gardens to monoculture khat production due to increasing population pressure-induced farmland constraints. The composition of woody species and the biomass carbon stock are thought to drop as homegardens transition from polyculture to monoculture; however there is little quantitative evidence to support this claim. This study was started to assess the effects on woody species, enset, and biomass carbon of converting traditional homegardens to a fast spreading perennial monocropping of khat (Catha edulis Forskal). In 10 m × 10 m (100m2) plots from 43 farms with neighboring land use patterns for each homegarden and khat, woody species and enset were inventoried, the total number of tree, shrub, and enset species counted, as well as the height and diameter of each species measured. To determine the biomass carbon stock of each land use type, both general and species-specific allometric equations are used. Simpson's diversity index, Shannon-Wiener, and Shannon equitability were used to evaluate the diversity of enset and woody species. There were 27 different types of woody species identified, with trees making up 67 % of the total and shrubs accounting for 33 %. Shannon, Simpson, and the richness of woody species all decreased by 46 %, 51 %, and 38 %, respectively, in comparison to residential gardens. For homegardens and khat, respectively, the mean Evenness values were 0.876 and 0.539. In homegardens, Coffea arabica was the most valuable woody species, followed by Cordia africana Lam, Persea americana, Eucalyptus camaldulensis, and Grevillea Robusta. In contrast, Catha edulis was the most valuable woody species in the Khat land use type, followed by Coffea arabica, Croton macrostachyus Del, and Cordia africana. In comparison to homegardens, the above-ground, below-ground, and total biomass carbon reported in khat land use types were reduced by 18 %, 63 %, and 42 %, respectively. Grevillea and Eucalyptus species made up 51 % of the total biomass carbon stock in the homegardens, which suggests that khat and quickly expanding fast-growing plants have displaced native woody species.Understanding the long-term effects of agro-biodiversity loss requires greater research on the implications of the decline in woody species diversity and biomass carbon stock on soil fertility and sustainable farming. This is due to the numerous functions that woody species and enset play.

Species-Specific Allometric Equations, Biomass Expansion Factor, and Wood Density of Native Tree Species in the Dry Afromontane Forest of Ethiopia

A forest is a storehouse of carbon released from different sources when the activities of sustainable forest management, planting, and rehabilitation exist. However, few allometric equations are present to determine its contribution to carbon reduction. The target of the study was to develop species-specific allometric equations and establish a database for biomass expansion factor and wood density for five tree species grown in the dry Afromontane forest of Ethiopia. A direct or destructive sampling method was used on 62 trees from different diameter classes. The diameter at breast height and the total height of selected trees ranged from 7 to 48 cm and 6.7 to 23.4 m, respectively. Trees were felled and divided into various biomass sections. Stem and big branch discs were sampled to determine the wood density and volume of the trees. Sample wood and foliage were oven-dried for three days and two days at 105°C and 70°C, respectively, to get their dry weight. Total above-ground biomass was regressed using diameter at breast height, total height, wood density, and average crown diameter as independent variables. R software version 4.0.1 was used to fit the biomass equations. The best biomass models were determined to have lower AIC and RSE and highest adj. R2. The biomass expansion factor and wood density of five tree species ranged from 1.19 to 1.40 and 0.53 to 0.74 g/cm−3, respectively. Species-specific allometric equations were better than both mixed species and pan tropical models for the assessment of above-ground biomass in the Chilimo dry Afromontane forest of Ethiopia.

Multilevel allometric growth equations improve accuracy of carbon monitoring during forest restoration

Managing disturbed forests for climate mitigation and biodiversity requires monitoring the carbon (C) cycle consequences of replacing established exotic vegetation with native seedlings. Standard approaches rely on allometric growth equations with unexplored limitations for measuring C changes during restoration. Most plants lack species-specific allometric growth equations. Additionally, these equations may perform poorly for different growth forms, especially when applied to both mature trees and seedlings. To address these limitations, we generated and compared allometric growth equations for four woody species with different biogeographic origins and growth forms, including two high impact invasive species, Cupaniopisis anacardioides and Schinus terebinthifolia. By borrowing strength from sampling across species to reduce estimation error within species, Bayesian multilevel models generated more accurate estimates than either independent species-level models or generic equations, although improvements over independent species-level models were modest. Because errors systematically changed with plant size, especially for species with unusual growth forms, allometric growth equations from custom multilevel models generated higher baseline aboveground biomass estimates and lower post-restoration estimates, which has important implications for monitoring C consequences of invasive tree management.

CO2-assimilation, sequestration, and storage by urban woody species growing in parks and along streets in two climatic zones

Using two cities, Rimini (Italy, Cfa climate) and Krakow (Poland, Cfb), as living laboratories, this research aimed at measuring in situ the capacity of 15 woody species to assimilate, sequester, and store CO2. About 1712 trees of the selected species were identified in parks or along streets of the two cities, and their age, DBH, height, and crown radius were measured. The volume of trunk and branches was measured using a terrestrial LiDAR. The true Leaf Area Index was calculated by correcting transmittance measurements conducted using a plant-canopy-analyser for leaf angle distribution, woody area index, and clumping. Dendrometric traits were fitted using age or DBH as independent variable to obtain site- and species-specific allometric equations. Instantaneous and daily net CO2-assimilation per unit leaf area was measured using an infra-red gas-analyser on full-sun and shaded leaves and upscaled to the unit crown-projection area and to the whole tree using both a big-leaf and a multilayer approach. Results showed that species differed for net CO2-assimilation per unit leaf area, leaf area index, and for the contribution of shaded leaves to overall canopy carbon gain, which yielded significant differences among species in net CO2-assimilation per unit crown-projection-area (AcpaML(d)). AcpaML(d) was underestimated by 6–30 % when calculated using the big-leaf, compared to the multilayer model. While maximizing AcpaML(d) can maximize CO2-assimilation for a given canopy cover, species which matched high AcpaML(d) and massive canopy spread, such as mature Platanus x acerifolia and Quercus robur, provided higher CO2-assimilation (Atree) at the individual tree scale. Land use (park or street), did not consistently affect CO2-assimilation per unit leaf or crown-projection area, although Atree can decline in response to specific management practices (e.g. heavy pruning). CO2-storage and sequestration, in general, showed a similar pattern as Atree, although the ratio between CO2-sequestration and CO2-assimilation decreased at increasing DBH.

Using terrestrial laser scanning to evaluate non-destructive aboveground biomass allometries in diverse Northern California forests

A crucial part of carbon accounting is quantifying a tree’s aboveground biomass (AGB) using allometric equations, but species-specific equations are limited because data to inform these equations requires destructive harvesting of many trees which is difficult and time-consuming. Here, we used terrestrial laser scanning (TLS) to non-destructively estimate AGB for 282 trees from 5 species at 3 locations in Northern California using stem and branch volume estimates from quantitative structure models (QSMs) and wood density from the literature. We then compared TLS QSM estimates of AGB with published allometric equations and used TLS-based AGB, diameter at breast height (DBH), and height to derive new species-specific allometric AGB equations for our study species. To validate the use of TLS, we used traditional forestry approaches to collect DBH (n = 550) and height (n = 291) data on individual trees. TLS-based DBH and height were not significantly different from field inventory data (R2 = 0.98 for DBH, R2 = 0.95 for height). Across all species, AGB calculated from TLS QSM volumes were approximately 30% greater than AGB estimates using published Forest Service’s Forest Inventory and Analysis Program equations, and TLS QSM AGB estimates were 10% greater than AGB calculated with existing equations, although this variation was species-dependent. In particular, TLS AGB estimates for Quercus agrifolia and Sequoia sempervirens differed the most from AGB estimates calculated using published equations. New allometric equations created using TLS data with DBH and height performed better than equations that only included DBH and matched most closely with AGB estimates generated from QSMs. Our results support the use of TLS as a method to rapidly estimate height, DBH, and AGB of multiple trees at a plot-level when species are identified and wood density is known. In addition, the creation of new TLS-based non-destructive allometric equations for our 5 study species may have important applications and implications for carbon quantification over larger spatial scales, especially since our equations estimated greater AGB than previous approaches.

Species-based aboveground mangrove carbon stock estimation using WorldView-2 image data

The carbon stocks of a mangrove ecosystem depend to some extent on the diversity of its constituent species, which have different biophysical characteristics. The high-resolution remote sensing imagery from WorldView-2 (2 m pixel size) provides a data source for estimating aboveground mangrove carbon (mangrove AGC) stocks across species. This study was designed to (i) map mangrove species by applying the GEOBIA method, (ii) calculate mangrove AGC using species-specific allometric equations, and (iii) map the spatial distribution of mangrove AGC at the species level. It combined the species map from GEOBIA with carbon stock estimation by generating a model based on the vegetation index (spectral transformation of several WorldView-2 bands) over the Clungup Mangrove Conservation (CMC) area in Malang, East Java, Indonesia. GEOBIA was used to classify mangrove species based on the homogeneous segments of each species depicted in the image, while the carbon stocks in the field were calculated using species-specific allometric equations. A regression function between the carbon stocks and the vegetation index value stored in each pixel was applied to the derived mangrove species map. The GEOBIA species mapping using the nearest neighbor algorithm identified six dominant species in the CMC area, namely Bruguiera gymnorrhiza, Ceriops tagal, Rhizophora apiculata, Rhizophora mucronata, Sonneratia alba, and Nypa fruticans, with an 84% overall accuracy. Based on the regression analysis results, the vegetation index values varied across species. The mangrove AGC estimation and mapping at the species level produced favorable results, with a maximum accuracy of 54.94% for B. gymnorrhiza, 55.55% for C. tagal, 41.43% for R. apiculata, 51.38% for R. mucronata, and 54.87% for S. alba. Also, the range of the estimated carbon stocks differed for each species. This research contributes an innovative development by combining methods of mangrove species mapping with mangrove AGC estimation at the species level.

Mapping of Prosopis juliflora rate of expansion and developing species-specific allometric equations to estimate its aboveground biomass in the dry land of Ethiopia

Mapping of Prosopis juliflora rate of expansion and developing species-specific allometric equations to estimate its aboveground biomass in the dry land of Ethiopia

Allometric equations for biomass and carbon stock estimation of small diameter woody species from tropical dry deciduous forests: Support to REDD+

In order to assess the contribution to the overall carbon stock and generate carbon credits under REDD+, it is essential to have an accurate estimation of biomass of different forest components. Forest cover in India is gradually increasing due to the active restoration of degraded land and plantation on waste and barren lands leading to an increase in the abundance of small diameter woody species. However, these were not included in biomass studies due to the non- availability of adequate allometric equations and low carbon stocks compared to mature individuals. We have harvested 589 individuals belonging to 23 woody species at the seedling and sapling stage from a tropical dry deciduous forest and developed species specific allometric equation and general allometric equation for aboveground biomass estimation. Further, the belowground biomass equation of 9 species were also developed using above ground biomass and root to shoot ratio as predictor variable. In the case of general equation, the combination of diameter with height and diameter, height and wood specific gravity exhibited highest adjusted R2 value. In case of species-specific allometric equations, combination of diameter with height predicts above ground biomass more precisely as compared to the diameter and wood specific gravity. Since the estimation of wood specific gravity requires destruction of lower diameter individuals, usage of diameter and height for biomass estimation would help protecting regeneration as both methods yield same results. All the equations developed in the present study for below ground biomass predicts biomass precisely. We suggest use of species specific allometric model developed with diameter and height for estimation of biomass. Further, general models consisting of height and diameter may be used for biomass estimation in case of non-availability of species specific equations without destroying the regeneration.

Assessment of Biodiversity and Blue Carbon in Mangroves, Sea grasses, Salt Marshes and Algae in Mannar, Northern Sri Lanka

Blue carbon is the carbon stored in coastal and marine ecosystems. Coastal ecosystems such as mangroves, tidal marshes, seagrass meadows and algae sequester and store more carbon per unit area than terrestrial forests and are now being recognised for their role in mitigating climate change. The objective of this study was to assess the biodiversity and carbon storage capacities in these ecosystems. The study was conducted in Vidathalathivu in Mannar, Kiranchi in Kilinochchi and Pooneryn. In mangroves, belt transects were taken from the shore towards the land. Nested circular plots having 7 m radius were established, large trees were sampled for diameter. Small trees (<3 cm dbh) were sampled in 2 m radius. Litter, pneumatophores and seedlings were sampled in plots of 30×30 cm area. Soil samples were taken at depths; 0-30 cm, 30-60 cm, 60-100 cm for the measurement of bulk density and carbon content. The biomass of the mangrove plants was measured using species specific allometric equations. In the salt marshes, 1×1 m plots were sampled. In the seagrass beds and algae, several 30×30 cm grids were sampled. In each plot, the species composition and the number of plants in each species were assessed. Samples of seagrasses and salt marsh vegetation were uprooted and taken to the laboratory for oven dry analysis. Three soil cores were taken using the soil auger which was inserted to a depth of 1 m in each ecosystem. The soil samples were taken from the core to represent the following depths; 0-30 and 30-60, 60-90. The data was analysed using MINITAB statistical software. The results showed natural mangroves in the study sites comprised of Avicennia marina, Ceriops tagal, Excoecaria agallocha, Luminetzera racemosa, Rhizophora murconata and Pemphis acidula. In sea grasses, Thalassima hemprichii, Cymodocea serrulate, Ruppia maritima and Syringodium isoiifolium were observed. Kappaphycus alvarezii and Eucheuma spinosum were the cultivated algae and Padina antillarum, Caulerpa racemosa, Ulva lactuca, Sargassum illifolium and Gelidium sp. were natural ones observed. Suaeda sp. and Salicornia sp. were the salt marsh species observed. The carbon content of these ecosystems were assessed. Keywords: Blue carbon, Mangroves, Seagrasses, Salt marshes, Algae, Carbon sequestration

Aboveground carbon stocks and sequestration rates of forests under different management regimes in Churia region of Nepal

The impact of forest management activities on the ability of forest ecosystems to sequester and store atmospheric carbon is of increasing scientific and social concern. This research estimated the aboveground carbon stocks and carbon sequestration rates of forests under various management regimes in the Churia region of Nepal. We used tree data from 469 permanent sample plots distributed across the region from the data archive of Forest Research and Training Centre for the study. The data from 2012 and 2017 were used. The volumes of individual trees were calculated using species–specific allometric equations, which were then converted to biomasses using their respective wood densities. The carbon content was calculated by multiplying the biomass by 0.47 and was converted to the amount of sequestrated CO2 by multiplying by 3.67. We found that the average estimated aboveground carbon stock increased from 78.43 t ha–1 in 2012 to 89.20 t ha–1 in 2017, resulting in an average annual carbon sequestration rate of 5.34 t ha–1 yr–1 (i.e. 7.90 t CO2 ha–1 yr–1). The results showed significant differences in aboveground carbon stocks and annual carbon sequestration rates among different forest management regimes in the region. Generally, aboveground carbon stock was found to be the highest in protected areas in both years whereas, the annual carbon sequestration rate was found to be the highest in government–managed forests. It can be concluded that the Churia region has great potential in terms of carbon sequestration. The evidence of the strong association of carbon stock and sequestration rate with management regimes provides valuable information for policymakers to maintain and further enhance carbon storage in a geographically vulnerable region like Churia.

진주시에 식재된 은행나무, 느티나무, 왕벚나무의 탄소저장량 추정식에 관한 연구

Quantitative evaluation for carbon storage of trees planted in an urban area is important for carbon sequestration management. This study was conducted to develop allometric equations to estimate the carbon storage of three representative urban tree species [Ginkgo biloba Linn., Zelkova serrata (Thunb.) Makino., and Prunus × yedoense Matsum.] planted in Jinju, Gyeongsangnam-do, Korea. Carbon concentrations in tree components were significantly different among three tree species, except for roots and branches. Allometric equations for carbon storage using generalized method of moments with diameter at breast height (DBH) or DBH2 × height (H) as independent variables were significant in all three species with high coefficient of determination (R2 = 0.92 0.99). There was little difference of coefficient of determination and root mean squared errors (RMSE) between allometric equations using DBH and DBH2 × H as independent variables. Generalized allometric equations for foliage, branches and aboveground carbon storage for three tree species were significantly different (P < 0.05) in regression coefficients (slope). These results suggest that the accuracy of estimates for carbon storage of three tree species planted in an urban area could be improved by using species-specific carbon concentration and species-specific allometric equations.

The distribution of carbon stocks between tree woody biomass and soil differs between Scots pine and broadleaved species (beech, oak) in European forests.

While the impacts of forest management options on carbon (C) storage are well documented, the way they affect C distribution among ecosystem components remains poorly investigated. Yet, partitioning of total forest C stocks, particularly between aboveground woody biomass and the soil, greatly impacts the stability of C stocks against disturbances in forest ecosystems. This study assessed the impact of species composition and stand density on C storage in aboveground woody biomass (stem + branches), coarse roots, and soil, and their partitioning in pure and mixed forests in Europe. We used 21 triplets (5 beech-oak, 8 pine-beech, 8 pine-oak mixed stands, and their respective monocultures at the same sites) in seven European countries. We computed biomass C stocks from total stand inventories and species-specific allometric equations, and soil organic C data down to 40 cm depth. On average, the broadleaved species stored more C in aboveground woody biomass than soil, while C storage in pine was equally distributed between both components. Stand density had a strong effect on C storage in tree woody biomass but not in the soil. After controlling for stand basal area, the mixed stands had, on average, similar total C stocks (in aboveground woody biomass + coarse roots + soil) to the most performing monocultures. Although species composition and stand density affect total C stocks and its partitioning between aboveground woody biomass and soil, a large part of variability in soil C storage was unrelated to stand characteristics.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10342-022-01453-9.

Biomass carbon stock assessment of mangrove ecosystem in Pannikiang Island South Sulawesi Indonesia

One of the essential services provided by mangroves is carbon sequestration, and therefore climate change mitigation. While previous assessments of mangrove carbon stocks and sequestrations have focused on the estuarine and deltaic mangrove setting, there are still limited studies carried out at small island mangroves. The study aims to assess mangrove biomass carbon stocks in Pannikiang, a small island in South Sulawesi, Indonesia, which occupies 91.64 ha of species-rich pristine mangrove forests. A field-based data collection survey was performed using a circular plot approach, while above-ground tree carbon (AGC) and below-ground root carbon (BGC) stocks were estimated using available species-specific allometric equations. The mean AGC and BGC were 5.34 ± 0.17 and 1.68 ± 0.04 Mg C ha-1, respectively. Bruguiera gymnorrhiza mangrove species stored the greatest of carbon stocks, followed by Scyphiphora hydrophyllacea. Carbon stocks obtained from small island mangroves in this study were lower than stocks assessed from other mangrove locations across Indonesia and Southeast Asia. However, historical rates of deforestation in Pannikiang Island may generate emissions to approximately 82.17 Mg CO2-eq. Findings from this study will be beneficial in providing baseline data for policy decision-making on climate change mitigation in the region, specifically for improved land use management via a low carbon development agenda.

Estimation of aboveground mangrove carbon stocks from WorldView-2 imagery based on generic and species-specific allometric equations

The aboveground mangrove carbon stock can be estimated and mapped from remote-sensing data using allometric equations. However, the distinct effects of applying the generic or species-specific allometric equations remain unclear in the mangrove environment. The aims of this study are to (1) describe the relationship between field biomass and image pixels using generic and species-specific allometric equations, (2) estimate and map the mangrove carbon stock at the generic and species-specific levels, and (3) compare the accuracy and distribution of the resulting mangrove carbon stock maps. We tested the performance of these allometric equations using a resampled WorldView-2 image (6 m pixel size). The study site was in Clungup Mangrove Conservation (CMC), Malang, East Java and included natural mangrove forests and well-planted mangroves. We used the simple ratio (SR) vegetation index to estimate and map the aboveground carbon stock (AGC) of the mangroves based on the WorldView-2 image. Overall, the results indicate that the use of a generic allometric equation estimates mangrove AGC more accurately than the species-specific equations. However, we found a low coefficient of determination (R2) for both models: 0.2175 for the generic model and 0.1801 for the species-specific one. This may be due to the mangrove objects’ high variation in internal spectral reflectance at the tested image pixel size. The total estimated mangrove AGC obtained was 3,834.15 tons with a standard error of 0.12 for the generic model and 4,927.90 tons with a standard error of 0.17 for the species-specific model. Our findings substantiate the importance of the selection of allometric equations for mangrove AGC studies based on remote-sensing images.

Aboveground biomass allocation and additive allometric models of fifteen tree species in northeast China based on improved investigation methods

Tree allometric models are crucial to accurate forest biomass assessment, but the acquisition of biomass data is one of the most important limitations in establishing biomass models. This study aims to propose an improved investigation method to quickly and practically obtain biomass data, establish species-specific allometric equations and evaluate the biomass allocation pattern for various tree species in a broad-leaved Korean pine forest in northeast China. Based on the non-destructive measurement and sampling of 390 trees from 15 tree species, partial and aggregate biomass models with DBH and DBH2 × H as predictors were established. Results indicated that all allometric models could effectively estimate the dependent variables, and almost no antilog correction was required. Specifically, for the stem and bark components of most tree species, using the DBH2 × H predictor improved the prediction performance of the model. However, DBH was the best predictor for branch and leaf biomass models. The biomass allocation of trees was affected by tree diameter. Small-diameter trees (DBH < 8) had more leaf investment than other size trees, medium-diameter trees (8 < DBH < 20) increased the allocation of resources to stems, and large-diameter trees (DBH > 20) paid more attention to the growth and accumulation of branches. Our allometric model and biomass allocation research based on the non-destructive measurement and sampling will help improve the accuracy of biomass assessment in broad-leaved Korean pine forests and advance our understanding of woody plant development and survival strategies.

Allometric equation for aboveground biomass estimation of Galiniera saxifraga (Hochst.) Bridson in Gesha-Sayilem forest, southwestern Ethiopia

Abstract. Bareke T, Addi A. 2021. Allometric equation for aboveground biomass estimation of Galiniera saxifraga (Hochst.) Bridson in Gesha-Sayilem forest, southwestern Ethiopia. Asian J For 5: 76-82. There is limited information about the precise quantification of Aboveground Biomass (AGB) of species-specific allometric equations for shrubs and small trees. Thirty Galiniera saxifraga plants were selected to develop species-specific allometric biomass equations. Biometric parameters, including the diameter at the Breast Height (DBH), height and crown area were predictive variables that were measured for each individual plant. AGB was measured through a destructive method. The AGB was correlated to biometric variables using regression analysis. The species-specific allometric models, with DBH and crown area as predictors (DBH-crown area models), accounted for 90% of the variation in the AGB of G. saxifraga. The DBH-crown area model was adequate for predicting the AGB for G. saxifraga with the adjusted R2 value 0.9 and AIC values was 47.37. The specific allometric equation developed for the Gesha-Sayilem Afromontane forest can be used in similar moist forests in Ethiopia to implement Reduced Emission from Deforestation and Degradation (REDD+) activities to benefit the local communities from carbon trade.

FIELD: A Software Tool That Integrates Harvester Data and Allometric Equations for a Dynamic Estimation of Forest Harvesting Residues

On an international comparison basis, Australia’s utilisation of forest residues remains very low. While there are numerous factors contributing to this low utilisation, this is greatly explained by the limited timely and accurate data on availability, quality, and location of residues generated during harvesting operations. This manuscript reports on the development and testing of a new freeware tool called FIELD (Forest Inventory Electronic Live Data), which supports the real-time monitoring and estimation of forestry harvesting residues. As inputs, FIELD uses StanForD pri files and geo-location data extracted from the harvester’s onboard computer in combination with locally developed species-specific allometric equations. Using a case study, this paper describes how FIELD works operationally and illustrates the range of support features that the tool can provide to decision-makers by producing real-time data on the availability, quality, and location of harvesting residues. In addition, it is discussed how the tool can contribute to supporting decisions during forest operations associated with the feasibility of residue utilisation in specific site conditions. Our results show that it is possible to estimate the availability of harvesting residues at geo-located sites dynamically, although further testing of the tool is required for a more accurate estimation and monitoring of harvesting residues.

The Benefits of Combining Global and Local Data—A Showcase for Valuation and Mapping of Mangrove Climate Regulation and Food Provisioning Services within a Protected Area in Pará, North Brazil

Mangrove forests provide a large variety of ecosystem services (ES) to coastal societies. Using a case study focusing on the Ajuruteua peninsula in Northern Brazil and two ES, food provisioning (ES1) and global climate regulation (ES2), this paper proposes a new framework for quantifying and valuing mangrove ES and allow for their small-scale mapping. We modelled and spatialised the two ES from different perspectives, the demand (ES1) and the supply (ES2) side respectively. This was performed by combining worldwide databases related to the global human population (ES1) or mangrove distribution and canopy height (ES2) with locally derived parameters, such as crab catches (ES1) or species-specific allometric equations based on local estimates of tree structural parameters (ES2). Based on this approach, we could estimate that the area delivers the basic nutrition of about 1400 households, which equals 2.7 million USD, and that the mangrove biomass in the area contains 2.1 million Mg C, amounting to 50.9 million USD, if it were paid as certificates. In addition to those figures, we provide high-resolution maps showing which areas are more valuable for the two respective ES, information that could help inform management strategies in the future.

Assessment of carbon stock potential of parkland agroforestry practice: the case of Minjar Shenkora; North Shewa, Ethiopia

BackgroundThe anthropogenic global climate change has negative impacts on various sectors and communities who particularly rely on rain-fed agriculture. Parkland agroforestry practice can contribute to mitigate and adapt to the forthcoming climate change through carbon sequestration. However, empirical studies on carbon stocks potential of parklands agroforestry practices .MethodologyBy using two-stage stratified random sampling technique, 4 kebeles from two agro ecology were selected and 8 farms/plots/ of 40 m*40 m sample size were selected from each kebele for the vegetation inventory. Tree species-specific allometric equations were used to determine carbon stock potential of parkland agroforestry practice.ResultsThe result reveal that, AGC, BGC, SOC and Total Carbon have significant variation (p < 0.05) across kebeles. The mean total carbon stock of Bolo Giorgis, Bolo Slase, Agirat and Korma Agere is 48.87 Mg C ha− 1, 58.21 Mg C ha− 1, 57.81 Mg C ha− 1and 73.71 Mg C ha− 1; respectively. On average, carbon stock of parklands practice in Minjar shenkora was 59.65 Mg C ha− 1.ConclusionsThe parkland agroforestry practice has a large potential to deliver regulating ecosystem services like opportunities to mitigate the impending climate-changing through carbon sequestration and increasing the resilience of the agricultural system at Minjar shenkora woreda. To enhance the multiple ecosystem services of the parkland agroforestry practices in sustainable way: local by-laws should be strengthened to avoid illegal tree cutting and free grazing.