Reliable tree height-diameter (H-D) allometric equations are a key tool for the estimation of forest productivity and Above Ground Biomass (AGB). Most existing H-D allometric equations developed for the tropical region are based on large-scale multi-species datasets, and their use to derive information on productivity and AGB at the species level is prone to uncertainties. The single-species H-D allometric equations available are mainly focused on monocultures or stands with simple tree species mixtures and did not account for the site effects. Here we measured the height and diameter of 2,288 trees of the emergent tree species Pericopsis elata (Harms) Meeuwen in the Democratic Republic of the Congo (DRC) and in Cameroon. We first examined how accurate multispecies H-D allometric equations are in predicting the total height of P. elata. We then tested whether single-species H-D allometric equations vary between sites. We developed the first H-D allometric equation of P. elata and tested whether and how stand-level and environmental variables induce changes in H-D allometric relationship of P. elata at the regional level. We additionally evaluated whether tree-level variables are important at the local level where climate and stand development stage are expected to be less variable. We found that pantropical, regional and local H-D allometric equations significantly underestimate the total height of P. elata. The local multi-species H-D allometric equation developed for Yangambi showed the highest underestimation in all the studied sites. This result supports the need for an H-D allometric equation specific for P. elata. The species-level H-D allometric equation developed showed significant underestimations for trees from the disturbed and undisturbed forests in DRC, while overestimations were observed for similar sites in Cameroon. Using a mixed-effect H-D allometric equation, we showed that even within a single species, a substantial variation exists between sites. This variation showed to be driven by the differences in the maximum asymptotic height (Hmax) between sites. We found that P. elata trees are taller and attain higher Hmax in DRC than in Cameroon. The basal area showed to be a significant covariate accounting for the site effects at the regional-scale where climate variables showed minor effects. However, at the local-scale, none of climate or stand variables showed to be significant. Local-scale variation showed to be associated with differences in light availability, highlighting the potential of management options that shape the local environment in driving species productivity.
Tag: Aboveground biomass
Allometric equations for estimating on-farm fuel production of Gliricidia sepium (Gliricidia) shrubs and Cajanus cajan (pigeon pea) plants in semi-arid Tanzania
Background: Fuelwood is considered to be the primary source of cooking energy in Tanzania and, due to ongoing deforestation, access to fuelwood is becoming more cumbersome. On-farm agroforestry systems can reduce dependency on off-farm fuel; however, the output of on-farm produced fuel is typically uncertain as production potentials are often not known. In this paper, we have developed allometric equations to model the above-ground woody biomass (AGWB) production from intercropped Gliricidia sepium (Jacq.) Kunth ex Walp (Gliricidia) shrubs and Cajanus cajan (L.) Millsp. (pigeon pea) plants. Methods: We used a destructive sampling approach, for measuring the dendrometric characteristics, such as the root collar diameter at a 20 cm stem height (RCD20) and the stem height to estimate the AGWB production. The models are based on 112 Gliricidia and 80 pigeon pea observations from annually pruned plants. Seven allometric equations were fitted to derive the best-fit models for the AGWB production. Results: We found that using a natural log-transformed linear model with RCD20 as a single predictor variable provides the highest explanatory value to estimate the AGWB production (Gliricidia: R2 = 95.7%, pigeon pea: R2 = 91.4%) while meeting Ordinary Least Square (OLS) estimator requirements. Adding stem height as an additional variable to predict the AGWB production does not improve model accuracy enough to justify the extra work for including it. Conclusions: While on-farm pigeon pea plants produced a stable amount of woody biomass per annum, annual fuelwood production from Gliricidia shrubs increased over the years. Compared to the annual fuelwood consumption data from the literature, our results show that on-farm produced fuelwood can substantially offset the demand for off-farm fuel, potentially resulting in household fuelwood autarky. © 2021, The Author(s).
Shade tree identity rather than diversity influences soil macrofauna in cacao-based agroforestry systems
Humanity is facing a rapid decline in global biodiversity, caused mainly by tropical deforestation through industrial and smallholder agriculture. However, smallholder agriculture landscapes host areas containing home gardens and other agroforestry systems (AFS) proved highly relevant for soil and biodiversity conservation. The positive interactions between aboveground and belowground biodiversity probably constitute a key element to promote the efficiency of these agro-ecosystems. To determine whether a relationship exists between tree and soil macrofauna diversity and composition, we compared cacao AFS with contrasted tree diversity along a topography and forest cover gradient in Talamanca, Costa Rica. To determine which components of the shade tree species, community structure (density, richness, Shannon, Pielou), and agroforest floor best explain the macrofauna community composition and structure, we constructed the “best models” based on the tree composition, tree structure, and agroforest floor as explanatory matrices in redundancy analyses. Macrofauna composition was best explained by a mix of tree species and litter attributes (R2=26.5 %), whereas macrofauna and vegetation co-vary significantly with topography (R2=12 %). Macrofauna structure is best explained by a selection of seven tree species (R2=41.2 %). The co-variation with topography remained low (R2=10.9 %). Tree evenness (Pielou index) explained only 7 % of macrofauna community structure while other diversity indices were not correlated with macrofauna composition or structure. The soil macrofauna was therefore more influenced by tree identity and litter composition than by the overall diversity of the tree community. This information is important for designing the optimal combinations of species for the intensification of production and provision of ecosystem services in cacao-based AFS.
High aboveground carbon stock of African tropical montane forests
Tropical forests store 40–50 per cent of terrestrial vegetation carbon1. However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests2. Owing to climatic and soil changes with increasing elevation3, AGC stocks are lower in tropical montane forests compared with lowland forests2. Here we assemble and analyse a dataset of structurally intact old-growth forests (AfriMont) spanning 44 montane sites in 12 African countries. We find that montane sites in the AfriMont plot network have a mean AGC stock of 149.4 megagrams of carbon per hectare (95% confidence interval 137.1–164.2), which is comparable to lowland forests in the African Tropical Rainforest Observation Network4 and about 70 per cent and 32 per cent higher than averages from plot networks in montane2,5,6 and lowland7 forests in the Neotropics, respectively. Notably, our results are two-thirds higher than the Intergovernmental Panel on Climate Change default values for these forests in Africa8. We find that the low stem density and high abundance of large trees of African lowland forests4 is mirrored in the montane forests sampled. This carbon store is endangered: we estimate that 0.8 million hectares of old-growth African montane forest have been lost since 2000. We provide country-specific montane forest AGC stock estimates modelled from our plot network to help to guide forest conservation and reforestation interventions. Our findings highlight the need for conserving these biodiverse9,10 and carbon-rich ecosystems.
Carbon stocks of Geramo forest, the western escarpment of the rift valley of Ethiopia
Forests play a vital role in the global carbon balance and combating global climate change by sequestering and retaining carbon from the atmosphere in their biomass and soil. Thus, this study aims to estimate the carbon stocks in the biomass and soil along with various environmental factors in the Geramo forest in southern Ethiopia. Ninety-six plots (20 × 20 m2) were laid at a distance of 250 m along 16 line transects that were laid 300 m apart. Five 1 × 1 m2 subplots (4 at the corner and 1 at the center) were laid inside each main plot for LHG and soil data collection. The results revealed that the estimated total carbon stocks and mean carbon stock densities of the study forest were 57994 Mg h−1and 604 ± 344 Mg h−1, respectively, with a mean CO2 equivalent of 2217 ± 1262 Mg h−1. This result indicates the remarkable role of the Geramo forest in carbon stock and sequestration potential compared with other remnant forests in Ethiopia. Thus, the Geramo forest plays a crucial role in climate change mitigation through carbon sequestration, and hence, this forest can generate carbon credits as financial benefits to the nearby population in the future. The results also revealed that anthropogenic disturbances were negatively associated with the carbon stocks of the forest. Therefore, sustainable forest conservation activities are needed to conserve forest resources, protect the forest from growing anthropogenic disturbances, and sustain its current global climate change mitigation and adaptation benefits.
Biomass estimation models for Acacia saligna trees in restored landscapes
Acacia saligna, originating from Australia, is a naturalized multipurpose tree species widely grown to restore degraded lands of Africa. The contribution of A. saligna in biomass restoration can be quantified using a precise estimation of tree biomass carbon. This study developed species-specific allometric models and evaluated the spatial variation of tree biomass across restored areas in exclosures and open grazing landscapes. These models could play a considerable role in the monitoring of carbon dynamics across A. saligna planation dominated areas. We harvested, excavated, and weighed twenty-one sample trees representing different size classes to develop allometric models for the estimation of aboveground (AGB), belowground (BGB) and total tree (TB) biomass. The average dry-to-fresh mass ratio and the root-to-shoot ratio was 0.47 (±0.13) and 0.28 (±0.14), respectively. Tree biomass significantly correlated with diameter at breast height (r = 0.93; P < 0.001), diameter at stump height (r = 0.88, P < 0.001) and tree height (r = 0.56, P < 0.05). Our best biomass estimation models explained 86%, 82% and 87% of variations in AGB, BGB, and TB, respectively. Models using DSH and DSH & H explained 70%–78% of the variation in AGB, BGB, and TB. Estimated C-stock showed a significant relationship with stem density (R2= 0.91, P < 0.01). Estimated TB varied between 1.5–18 Mg ha−1 on grazed land and exclosures. Estimated C-stocks in the exclosure exceeded the estimated C-stock in the open grazing land by ∼60%. This implies that with proper management practices and enrichment planting A. saligna significantly contributes to increasing carbon accumulation on degraded landscapes, playing a key role in climate change mitigation efforts while improving land productivity.
Allometric equations, wood density and partitioning of aboveground biomass in the arboretum of Ruhande, Rwanda
There is growing interest in plantation forests throughout Africa because of their role in environment, economy and people’s livelihoods. However, the contribution of planted forests to climate mitigation is poorly understood, partly due to lack of allometric equations for biomass estimation. This study aimed to determine wood density and biomass fractions in aboveground components, and to develop biomass estimation equations for multispecies plantation forests in the arboretum of Ruhande in Rwanda. Allometric equations were developed by regressing diameter at breast height (DBH) alone or in combination with height or wood density or age of trees against the biomass of 45 trees harvested from a 200-ha site. Biomass estimates obtained from destructively sampled trees were up-scaled to estimate the amount of carbon stocked in the arboretum of Ruhande, assuming a stem density of 250 stems per ha. Wood density varied among the species but not tree size. The greatest fraction of aboveground biomass was allocated to stems (71–77%) compared to branches (19–27%) and leaves (1–8%) and varied by species. Equations developed fit the data well with DBH explaining over 90% of the observed variation in aboveground and stem biomass. Including height or wood density as supporting parameters reduced the relative error for aboveground biomass by 6.4 and 8.0% and improved model fit by 2.1 and 2.9%, respectively. Akaike information criterion (AIC) showed that wood density (AIC=63.6) and height (AIC=48.2) were the most suitable parameters to support DBH as a proxy for aboveground and stem biomass, respectively. Allometric equations developed in this study are useful tool for estimating carbon stocks of plantation forests in Rwanda and can enhance the accuracy of biomass predictions where site-specific equations rather than generalized models are recommended. Further studies focusing on development of allometric equations on belowground biomass in such systems are recommended.
Macroecological patterns of forest structure and allometric scaling in mangrove forests
Mangrove wetlands span broad geographical gradients, resulting in functionally diverse tree communities. We asked whether latitudinal variation, allometric scaling relationships and species composition influence mangrove forest structure and biomass allocation across biogeographical regions and distinct coastal morphologies. We built the largest field‐based dataset on mangrove forest structure and biomass to date (c. 2,800 plots from 67 countries) to address macroecological questions pertaining to structural and functional diversity of mangroves spanning biogeographical and coastal morphology gradients. We used frequentist inference statistics and machine learning models to determine environmental drivers that control biomass allocation within and across mangrove communities globally. Allometric scaling relationships and forest structural complexity were consistent across biogeographical and coastal morphology gradients, suggesting that mangrove biomass is controlled by regional forcings rather than by latitude or species composition. For instance, nearly 40% of the global variation in biomass was explained by regional climate and hydroperiod, revealing nonlinear thresholds that control biomass accumulation across broad geographical gradients. Furthermore, we found that ecosystem‐level carbon stocks (average 401 ± 48 MgC/ha, covering biomass and the top 1 m of soil) varied little across diverse coastal morphologies, reflecting regional bottom‐up geomorphic controls that shape global patterns in mangrove biomass apportioning. Our findings reconcile views of wetland and terrestrial forest macroecology. Similarities in stand structural complexity and cross‐site size–density relationships across multiscale environmental gradients show that resource allocation in mangrove ecosystems is independent of tree size and invariant to species composition or latitude. Mangroves follow a universal fractal‐based scaling relationship that describes biomass allocation for several other terrestrial tree‐dominated communities. Understanding how mangroves adhere to these universal allometric rules can improve our ability to account for biomass apportioning and carbon stocks in response to broad geographical gradients.
Carbon stocks in Miombo Woodlands: Evidence from over 50 years
Miombo woodlands are extensive dry forest ecosystems in central and southern Africa covering ≈2.7 million km2. Despite their vast expanse and global importance for carbon storage, the long-term carbon stocks and dynamics have been poorly researched. The objective of this paper is to present and summarize the evidence gathered on above- and belowground (root and soil) carbon stocks of miombo woodlands from the 1960s to mid-2018 through a review. We analyzed data to answer: (1) What is the range of aboveground and belowground carbon stocks found in miombo woodlands over the last six decades? (2) Are there differences in carbon stocks based on land-management categories? (3) Does precipitation influence aboveground carbon stocks in old-growth miombo? (4) Do differences in cover type, age and region influence carbon stocks? (5) How does previous land-use affect carbon stocks in re-growth miombo? A literature review protocol was used to identify 56 publications from which quantitative data on aboveground and soil carbon pools were extracted. We found that the mean aboveground carbon stock in old-growth miombo was 30.83±16.76 Mg C ha-1 (range 1.48—107.24 Mg ha-1). Old-growth miombo had an average calculated root carbon stock of 16.49±9.18 Mg C ha-1 (range 0.8—57.81 Mg ha-1). Soil carbon stocks in old-growth miombo varied widely, between 8.75 and 134.6 Mg C ha-1 while in re-growth miombo they varied between 10.73 and 52.2 Mg C ha-1. It must be noted these soil data are given only for information; they inconsistently refer to varying soil depths and are thus difficult to interpret. The wide range reported suggests a need for further studies, much more systematic in methods and reporting. Other limitations of the dataset include the lack of systematic sampling and lack of data in some countries, viz. Angola and Democratic Republic of the Congo.
Carbon Storage Potential of Silvopastoral Systems of Colombia
Nine Latin American countries plan to use silvopastoral practices—incorporating trees into grazing lands—to mitigate climate change. However, the cumulative potential of scaling up silvopastoral systems at national levels is not well quantified. Here, we combined previously published tree cover data based on 250 m resolution MODIS satellite remote sensing imagery for 2000–2017 with ecofloristic zone carbon stock estimates to calculate historical and potential future tree biomass carbon storage in Colombian grasslands. Between 2000 and 2017, tree cover across all Colombian grasslands increased from 15% to 18%, with total biomass carbon (TBC) stocks increasing from 0.41 to 0.48 Pg. The range in 2017 carbon stock values in grasslands based on ecofloristic zones (5 to 122 Mg ha−1) suggests a potential for further increase. Increasing all carbon stocks to the current median and 75th percentile levels for the respective eco-floristic zone would increase TBC stocks by about 0.06 and 0.15 Pg, respectively. Incorporated into national C accounting, such Tier 2 estimates can set realistic targets for silvopastoral systems in nationally determined contributions (NDCs) and nationally appropriate mitigation actions (NAMAs) implementation plans in Colombia and other Latin American countries with similar contexts.