Going beyond the green: senesced vegetation material predicts basal area and biomass in remote sensing of tree cover conditions in an African tropical dry forest (miombo woodland) landscape

Mayes, Marc; Mustard, John F.; Melillo, Jerry M.; Neill, Christopher; Nyadzi, Gerson

doi:10.1088/1748-9326/aa7242

Cited by 10 publications

(8 citation statements)

References 33 publications

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“…The biomass and volume values found in Huambo province were similar to those found in other miombo forests in Angola [8,37]. The high biomass accumulation in this forest type implies a high C sequestration capacity, with values similar to those found by other authors in the region [51], though higher than values obtained in other degraded Miombo formations of Mozambique [2,38], Zambia and Zimbabwe [52], and Tanzania [53,54]. Further, the above-ground accumulated C in the most-degraded miombo forest of Huambo is higher than other Miombo forests in the central and southern region of Africa [10,55,56].…”

Section: Accumulated Carbon and Co 2 Equivalentsupporting

confidence: 82%

Deforestation and Biomass Production in Miombo Forest in Huambo (Angola): A Balance between Local and Global Needs

Miapia¹,

Ariza-Mateos

Lacerda-Quartín³

et al. 2021

Forests

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Miombo is one of the most widely distributed ecosystems in Angola, with a great social and environmental value. Thus, the rural population uses the biomass as fuel and miombo provides important ecosystem services, such as its carbon sequestration capacity. The objectives of this work were (i) to assess deforestation in miombo forest in Huambo province (Angola) during the last 20 years, (ii) to evaluate carbon storage capacity of miombo, and (iii) to calculate the charcoal productive capacity of those forests. From 2000 to 2019, 359,130 ha (12.96%) were deforested in Huambo province. Thirty-six woody species were identified as major components of miombo forest, the most frequent being Albizia anthunesiana, Brachystegia spiciformis, Julbernardia paniculata, Monote spp., Brachystegia boemii, Isoberlinea angolensis, Anisophyllea boehmii, Syzygium guineense, and Erythrophleum africanum. The total biomass estimated in miombo forest was 195.05 Mg ha−1 (55.02 Mg ha−1 radical and 140.04 Mg ha−1 area), with a total wood volume of 78.57 m3 ha−1. This represents values of 91.67 Mg ha−1 of accumulated carbon and 336.13 Mg ha−1 of CO2 equivalent. The potential charcoal productivity was 15,359.9 kg ha−1, corresponding to 24.78 trees ha−1. The Annual Allowable Cutting Volume was 10.77 m3 ha−1 year−1, 14.13 m3 ha−1 year−1, 21.17 m3 ha−1, and 32.85 m3 ha−1 year−1 for rotation lengths of 55, 40, 25, and 15 years, respectively, corresponding to a potential annual charcoal productivity of 2107.08 Kg ha−1 year−1, 2762.96 Kg ha−1 year−1, 4139.21 Kg ha−1, and 422.56 Kg ha−1 year−1. However, deforestation rates in the last 19 years and low charcoal productive capacity could compromise the sustainability of the Miombo ecosystem and its value as an ecosystem service provider in the province if appropriate management strategies are not developed.

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Section: Accumulated Carbon and Co 2 Equivalentsupporting

confidence: 82%

Deforestation and Biomass Production in Miombo Forest in Huambo (Angola): A Balance between Local and Global Needs

Miapia¹,

Ariza-Mateos

Lacerda-Quartín³

et al. 2021

Forests

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“…A key assumption in site selection was that the influences of past cultivation, fire, and grazing processes was “controlled” and that the main covariate among all was regrowth age. In effort to check farmer responses, all interviews were done with at least two people present, the current landowner and a village elder familiar with the region for at least 40 years or more, and sites having regrown since 1990 were cross‐checked with remote sensing analyses (Mayes et al, ; Mayes et al, ). We took pilot soil cores to a depth of 190 cm for basic soil property characterization as we searched for accessible regrowth chronosequence sites.…”

Section: Methodsmentioning

confidence: 99%

Nitrogen Cycle Patterns During Forest Regrowth in an African Miombo woodland Landscape

et al. 2019

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Tropical dry forests in eastern and southern Africa cover 2.5 × 106 km2, support wildlife habitat and livelihoods of more than 150 million people, and face threats from land use and climate change. To inform conservation, we need better understanding of ecosystem processes like nutrient cycling that regulate forest productivity and biomass accumulation. Here we report on patterns in nitrogen (N) cycling across a 100‐year forest regrowth chronosequence in the Tanzanian Miombo woodlands. Soil and vegetation indicators showed that low ecosystem N availability for trees persisted across young to mature forests. Ammonium dominated soil mineral N pools from 0‐ to 15‐cm depth. Laboratory‐measured soil N mineralization rates across 3‐ to 40‐year regrowth sites showed no significant trends and were lower than mature forest rates. Aboveground tree N pools increased at 6 to 7 kg N·ha−1·yr−1, accounting for the majority of ecosystem N accumulation. Foliar δ15N <0‰ in an N‐fixing canopy tree across all sites suggested that N fixation may contribute to ecosystem N cycle recovery. These results contrast N cycling in wetter tropical and Neotropical dry forests, where indicators of N scarcity diminish after several decades of regrowth. Our findings suggest that minimizing woody biomass removal, litter layer, and topsoil disturbance may be important to promote N cycle recovery and natural regeneration in Miombo woodlands. Higher rates of N mineralization in the wet season indicated a potential that climate change‐altered rainfall leading to extended dry periods may lower N availability through soil moisture‐dependent N mineralization pathways, particularly for mature forests.

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“…If the green vegetation cover on the land surface is uneven in the area, it is easy to be destroyed or removed due to private occupation. The use of reliable data sets to classify and identify the green vegetation cover on the land surface and explore its spatial distribution can provide important reference for the work of regional ecosystem managers and urban planners [7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Effective Screening and Texture Segmentation of Green Vegetation Cover Based on UAV Images

Zhao¹,

Huang²,

Wang³

et al. 2022

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As an important part of the ecosystem, green vegetation coverage is crucial to people’s sensory and mental health. Using reliable data sets to classify and identify the green vegetation cover on the land surface and explore its spatial distribution law can provide important reference for the work of regional ecosystem managers and urban planners. The optimization of effective screening methods for green vegetation coverage areas is an important requirement to measure the surface vegetation status. UAV aerial images feature high definition, large scale, small area and high up-to-dateness. However, at present, there are few studies based on the reliable UAV aerial image system to identify green vegetation cover and further explore its spatial changes. In this study, 701 residential neighborhoods in Beijing were taken as the research objects, and the green vegetation of 7,695 sample points was identified by UAV. The green vegetation coverage was measured, and the spatial distribution pattern of green vegetation in different land surface areas was quantitatively compared. The results show that the image processing method proposed in this paper can effectively detect the boundary of green vegetation cover area from UAV aerial images, the correlation of texture segmentation is good, and the segmentation performance is better than other methods. The distribution of green vegetation cover in the research target area is uneven, with 63.79% of the research area having relatively low (Level 2) and medium (Level 3) green vegetation coverage, which indicates that the green vegetation coverage area in the research area is insufficient to meet the needs of regional ecosystem development. The characteristics of green vegetation cover in 16 districts in the study area are different, showing different spatial distribution patterns; except Xicheng District, there are 211 points without landscape in the area covered by green vegetation in 15 districts. The results can provide support for urban land surface planning and management.

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Going beyond the green: senesced vegetation material predicts basal area and biomass in remote sensing of tree cover conditions in an African tropical dry forest (miombo woodland) landscape

Cited by 10 publications

References 33 publications

Deforestation and Biomass Production in Miombo Forest in Huambo (Angola): A Balance between Local and Global Needs

Deforestation and Biomass Production in Miombo Forest in Huambo (Angola): A Balance between Local and Global Needs

Nitrogen Cycle Patterns During Forest Regrowth in an African Miombo woodland Landscape

Effective Screening and Texture Segmentation of Green Vegetation Cover Based on UAV Images

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