A lot of progress has been made in root research during the last decade in tropical agroforestry that contributes to better understanding of the interactions of roots and below-ground resource use in sequential and simultaneous systems. New tools have been developed that allow in situ measurements of root growth and interactions in woody and herbaceous species associations. There was much increase in information on root architecture, root behavior and functions of potential tree and shrub species grown in associations with crops. Root behavior is influenced by genetic, site and management factors. The information can be utilized for minimizing competition for nutrients and moisture in agroforestry systems, especially under stress conditions, as often observed in dry zones or on acidic soils. Research is needed for more efficient utilization of below-ground growth resources by crops and/or woody species to optimize returns in various agroforestry systems. Research is also needed on the morphophysiological relationships of various root classes, on the contribution from root turn-over to soil organic matter and nutrient status, and on the need for indices for measuring root competition in agroforestry systems. Despite progress on knowledge of soil biota and faunal activities in agroforestry systems, research is needed to quantify the effects on the sustainability of agroforestry systems.
Tag: belowground biomass
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.
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.
Allometric Equations for the Biomass Estimation of Calophyllum inophyllum L. in Java, Indonesia
Reliable data on CO2 quantification is increasingly important to quantify the climate benefits of forest landscape restoration and international commitments, such as the Warsaw REDD+ Framework and Nationally Determined Contributions under the Paris Agreement. Calophyllum inophyllum L. (nyamplung as a local name or tamanu tree for the commercial name) is an increasingly popular tree species in forest landscape restoration and bioenergy production for a variety of reasons. In this paper, we present allometric equations for aboveground biomass (AGB), belowground biomass (BGB), and total above- and belowground biomass (TABGB) predictions of C. inophyllum L. Data collection was carried out twice (2017 and 2021) from 40 trees in Java, Indonesia. Allometric equations using the natural logarithm of diameter at breast height (lnDBH) and ln height (lnH) for biomass prediction qualified the model’s fit with statistical significance at 95% of the confidence interval for AGB, BGB, and TABGB predictions. The results showed that the linear models using both lnDBH and lnH were well fit and accurate. However, the model with lnDBH is more precise than the model using lnH. Using lnDBH as a predictor, the R2 values were 0.923, 0.945, and 0.932, and MAPE were 24.7, 37.0, and 25.8 for AGB, BGB, and TABGB, respectively. Using lnH as a predictor, the R2 values were 0.887, 0.918, and 0.898 and MAPE were 37.4, 49.0, and 39.8 for AGB, BGB, and TABGB, respectively. Consequently, the driven allometric equations can help accurate biomass quantification for carbon-trading schemes of C. inophyllum L.