Estimating the global potential of forest and agroforest management practices to sequester carbon

Winjum, Jack K.; Dixon, Ross; Schroeder, Paul R.

doi:10.1007/bf00477103

Cited by 157 publications

(58 citation statements)

References 9 publications

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“…This may be due to the presence of trees which contribute more leaves, forage and branch litter as well as the amount of roots that decompose as compared to control plots with trees only. However, the SOC (Mg C ha -1 ) values obtained under a linear agroforestry system in Uganda are relatively higher than those reported by others (e.g., Dixon 1995;Montagnini and Nair 2004;Mutuo et al 2005;Winjum et al 1992). This may be due to the factors such as species used and tree density (Dixon 1995;Montagnini and Nair 2004) that influences the potential of an agroforestry system to sequester carbon.…”

Section: Discussioncontrasting

confidence: 73%

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Soil organic carbon under a linear simultaneous agroforestry system in Uganda

et al. 2011

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The objective of this study was to quantify and compare the amount and distribution of soil organic carbon (SOC) under a linear simultaneous agroforestry system with different tree species treatments. Field work was conducted at Kifu National Forestry Resources Research Institute in Mukono District, Central Uganda, in a linear agroforestry system established in 1995 with four different tree species and a crop only control treatment. Soil samples were collected in 2006 at three depths; 0-25, 25-50, and 50-100 cm, before planting and after harvesting a maize crop. The results indicate that an agroforestry system has significant potential to increase SOC as compared to the crop only control. There was no significant difference in the amount of SOC under exotic and indigenous tree species. Among the exotic species, Grevillea robusta had higher SOC than Casuarina equisetifolia across the entire depth sampled. There is significant difference in SOC among the indigenous species, where Maesopsis eminii has more SOC than Markhamia lutea. Distance from the tree row did not significantly influence SOC concentration under any of the tree species. In selecting a tree species to integrate with crops that will sequester reasonable quantities of carbon as well as boost the performance of the crops, a farmer can either plant an exotic species or an indigenous. In this study, the soil under Grevillea robusta and Maesopsis eminii have the highest potential to store organic carbon compared to soil under other tree species.

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Section: Discussioncontrasting

confidence: 73%

“…For example, estimates have shown that the combination of woody perennials and annual crops has the potential to store between 29 and 53 Mg above-ground C ha -1 in the humid highlands of Africa, between 39 and 195 Mg C ha -1 in South America, and between 12 and 228 Mg C ha -1 in Southeast Asia (Winjum et al 1992).…”

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confidence: 99%

Soil organic carbon under a linear simultaneous agroforestry system in Uganda

et al. 2011

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“…Forest vegetation and soils share almost 60% of the world's terrestrial carbon (Winjum et al 1992). Vegetation and soils are viable sinks of atmospheric carbon (C) and may significantly contribute to mitigation of global climate change (Bajracharya et al 1998;Phillips et al 1998;Lal 2004;Smith 2004).…”

Section: Introductionmentioning

confidence: 99%

Soil and vegetation carbon pools in a mountainous watershed of Nepal

Shrestha

Singh

2007

Nutr Cycl Agroecosyst

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Assessment of carbon stocks in vegetation and soil is a basic step in evaluating the carbon sequestration potential of an ecosystem. We collected soil (core and composite) samples from 0-10, 10-20, 20-40, and 40-70 cm depths, or down to the bed rock, in the soil profile of four types of forest (managed dense Shorea (DS), degraded forest (DF), pine mixed (PS), and Schima-Castanopsis (SC) forest) and two types of cultivated land (irrigated low land (Khet) and rain-fed upland (Bari)) in the Pokhare Khola watershed of Nepal. In addition to other essential properties, soil bulk density and carbon concentration were assessed. Fine roots were also collected from each sampling site. The biomass of standing trees and shrubs was estimated by using allometric relationships after measuring their diameter and height, while the biomass of grasses was estimated by a direct measurement of grass from a defined area. The carbon stocks in all forest vegetation (trees, shrubs, and ground grass) and in the soil profiles under different land uses were estimated. The vegetation carbon pool was largest in DS forest (219 ± 34 Mg ha -1 ) and least in SC forest (36 ± 5 Mg ha -1 ), while its order among forest types was DS [ DF [ PS [ SC. The soil organic carbon (SOC) pool was largest in Bari land (15.7 ± 1.5 kg C m -2 ) and least in PS forest (6.2 ± 0.5 kg C m -2 ) but the overall order among land uses was Bari [The total SOC stock in the whole watershed was 59 815 Mg, of which 36, 32, and 32% were in the 0-20, 20-40, and [40 cm soil depths, respectively. In the surface layer (0-10 cm), SOC stock was highest in Bari (36%) followed by DS (31%), and least was in PS forest (3%). This distribution pattern can primarily be assigned to SOC concentration and area covered by these land uses.

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“…For example, it appears a quite interesting tool for biodiversity related analysis, such as habitat type classification (Vierling et al 2008, Collin et al 2010, Bassler et al 2011) and species diversity modeling (Gillespie et al 2004, Vierling et al 2008. Concerning with carbon sequestration, forests can sequester and store more carbon than all other terrestrial ecosystems (IPCC 2001) and exchange 90% of total carbon flow between the atmosphere and biosphere (Winjum et al 1992). Thus, the integration of data from inventories with remote sensing techniques is crucial for an accurate quantification of carbon stocks in forest ecosystems and to monitor the influence of human activities (i.e., forest management, afforestation, deforestation) on these stocks (Kotchenova et al 2004, Garcia et al 2010, Beets et al 2011, Saatchi et al 2011.…”

Section: Introductionmentioning

confidence: 99%

A LiDAR-based approach for a multi-purpose characterization of Alpine forests: an Italian case study

Alberti¹,

Boscutti²,

Pirotti³

et al. 2013

iForest

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Several studies have verified the suitability of LiDAR for the estimation of forest metrics over large areas. In the present study we used LiDAR as support for the characterization of structure, volume, biomass and naturalistic value in mixed-coniferous forests of the Alpine region. Stem density, height and structure in the test plots were derived using a mathematical morphology function applied directly on the LiDAR point cloud. From these data, digital maps describing the horizontal and vertical forest structure were derived. Volume and biomass were then computed using regression models. A strong agreement (accuracy of the map = 97%, Kappa Cohen = 94%) between LiDAR land cover map (i.e., bare soil, forest, shrubs) and ground data was found, while a moderate agreement between coniferous/broadleaf map derived from LiDAR data and ground surveys was detected (accuracy = 73%, Kappa Cohen = 60%). An analysis of the forest structure map derived from LiDAR data revealed a prevalence of even-age stands (66%) in comparison to the multilayered and uneven-aged forests (20%). In particular, the even-age stands, whether adult or mature, were overwhelming (33%). A moderate agreement was then detected between this map and ground data (accuracy = 68%, Kappa Cohen = 58%). Moreover, strong correlations between LiDAR-estimated and ground-measured volume and aboveground carbon stocks were detected. Related observations also showed that stem density can be rightly estimated for adult and mature forests, but not for younger categories, because of the low LiDAR posting density (2.8 points m-2). Regarding environmental issues, this study allowed us to discriminate the different contribution of LiDAR-derived forest structure to biodiversity and ecological stability. In fact, a significant difference in floristic diversity indexes (species richness - R, Shannon index - H’) was found among structural classes, particularly between pole wood (R=15 and H’=2.8; P <0.01) and multilayer forest (R=31 and H’=3.4) or thicket (R=28 and H’=3.4) where both indexes reached their maximum values

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Estimating the global potential of forest and agroforest management practices to sequester carbon

Cited by 157 publications

References 9 publications

Soil organic carbon under a linear simultaneous agroforestry system in Uganda

Soil organic carbon under a linear simultaneous agroforestry system in Uganda

Soil and vegetation carbon pools in a mountainous watershed of Nepal

A LiDAR-based approach for a multi-purpose characterization of Alpine forests: an Italian case study

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