The fifth assessment report of the intergovernmental panel on climate change (IPCC) estimated that by 2040 agroforestry would offer high potential of carbon (C) sequestration in developing countries. However, the role of tropical agroforestry in C sequestration and in climate change mitigation has only recently been recognized by United Nations Framework Convention on Climate Change (UNFCCC). This is partly due to the lack of reliable estimates on the sequestration potential in biomass and soil carbon pools over time. The aim of this study was to analyze the changes in the biomass and soil carbon pools of three indigenous agroforestry systems in south-eastern Rift Valley escrapment of Ethiopia using CO2FIX (v. 3.2) model. The agroforestry systems studied were Enset (Ensete ventricosum)-tree, Enset-coffee-tree, and Tree-coffee systems. To run the model, empirical data collected from 60 farms (20 farms for each agroforestry system) and literature were used as inputs to parameterize the model. Simulations were run over a period of 50 years. Average simulated total biomass C stocks was the highest for Tree-coffee system (122 Mg C ha1), followed by the Enset-coffee-tree (114 Mg C ha1) and Enset-tree system (76 Mg C ha1). The tree cohort accounted for 89–97% of the total biomass C stocks in all the studied systems, and the reminder was shared by Enset and coffee cohorts. The total average simulated total C stocks (biomass and soil) were 209, 286 and 301 Mg C ha1 for Enset-tree, Enset-coffee-tree and Tree-coffee systems, respectively. The soil organic carbon (SOC) stocks accounted for 60–64% of the total carbon in the studied systems. Model validation results showed that long-term (10–40 years) simulated biomass C stocks were within the range of measured biomass C stocks for Enset-tree and Enset-coffee-tree systems, but significantly differed for the Tree-coffee system. The simulated soil and total C stocks were within the range of measured values for all the three systems. The CO2FIX model accurately predicted the SOC and total C stocks in the studied indigenous agroforestry systems, but the prediction of the biomass C stocks could be improved by acquiring more accurate input parameter values for running the model.
Tag: Carbon sequestration
Microplastic contamination accelerates soil carbon loss through positive priming
The priming effect, i.e., the changes in soil organic matter (SOM) decomposition following fresh organic carbon (C) inputs is known to influence C storage in terrestrial ecosystems. Microplastics (particle size <5 mm) are ubiquitous in soils due to the increasing use and often inadequate end-of-life management of plastics. Conventional polyethylene and bio-degradable (PHBV) plastics contain large amounts of C within their molecular structure, which can be assimilated by microorganisms. However, the extent and direction of the potential priming effect induced by microplastics is unclear. As such, we added 14C-labeled glucose to investigate how background polyethylene and PHBV microplastics (1 %, w/w) affect SOM decomposition and its potential microbial mechanisms in a short-term. The cumulative CO2 emission in soil contaminated with PHBV was 42–53 % higher than under Polyethylene contaminated soil after 60-day incubation. Addition of glucose increased SOM decomposition and induced a positive priming effect, as a consequence, caused a negative net soil C balance (−59 to −132 μg C g−1 soil) regardless of microplastic types. K-strategists dominated in the PHBV-contaminated soils and induced 72 % higher positive priming effects as compared to Polyethylene-contaminated soils (160 vs. 92 μg C g−1 soil). This was attributed to the enhanced decomposition of recalcitrant SOM to acquire nitrogen. The stronger priming effect associated in PHBVs can be attributed to cooperative decomposition among fungi and bacteria, which metabolize more recalcitrant C in PHBV. Moreover, comparatively higher calorespirometric ratios, lower substrate use efficiency, and larger enzyme activity but shorter turnover time of enzymes indicated that soil contaminated with PHBV release more energy, and have a more efficient microbial catabolism and are more efficient in SOM decomposition and nutrient resource uptake. Overall, microplastics, (especially bio-degradable microplastics) can alter biogeochemical cycles with significant negative consequences for C sequestration via increasing SOM decomposition in agricultural soils and for regional and global C budgets.
Effect of elevation and aspect on carbon stock of bamboo stands (Bambusa nutans subsp. Cupulata) outside the forest area in Eastern Nepal
Bamboo has emerged as a promising option for climate change mitigation due to its rapid growth, versatility, and renewability. However, in Nepal, there exists a substantial knowledge gap on carbon (C) stock and the influence of aspect and elevation on C stock of bamboo species, particularly in areas outside forests where bamboo is dominant. Therefore, this research was conducted to quantify C stock and aspect-elevation influence on the C stock of Bambusa nutans subsp. cupulata outside the forest area. For this study, three elevation zones (0–400 m, 400–800 m, 800–1200 m) and two aspects (East and West) were considered. A total of 30 square plots having a 100 m2 area were established utilizing purposive sampling due to the scattered distribution of bamboo. Non-destructive methods were applied to measure bamboo culm diameters, while composite soil samples were systematically collected from 30 cm depth using soil augers and core samplers. Clump density (400 ha⁻¹), culm density (42,480 ha⁻¹) and culm diameter (6.82 ± 0.41 cm) were highest at middle elevations (p 0.05). The total mean C stock potential of B. nutans was 148.73 ± 3.43 Mg ha⁻¹. Our results indicated a significant difference in C stock among elevation zones, with middle elevation zones (161.77 ± 6.74 Mg ha-1) exhibiting notably higher C stock compared to both lower (150.26 ± 2.69 Mg ha-1) and higher (134.17 ± 4.26 Mg ha-1) elevation zones. Furthermore, East aspect was found to have significantly (p < 0.05) higher soil organic C stock (18.52 ± 1.32 Mg ha-1) compared to West aspect (11.4 ± 1.01 Mg ha-1). Further research is needed to explore other complex environmental interactions with C stock potential for better climate change strategies. Incorporating bamboo C into Nepal's REDD+ initiative can be crucial for optimizing opportunities to earn C credits.
Enhancing climate action
This chapter discusses how peatlands can be integrated in domestic climate commitments and measures
Evaluation and improvement of the E3SM land model for simulating energy and carbon fluxes in an Amazonian peatland
Tropical peatlands are one of the largest natural sources of atmospheric methane (CH4) and play a significant role in regional and global carbon budgets. However, large uncertainties persist regarding their feedbacks to climate variations. The Energy Exascale Earth System Model (E3SM) Land Model (ELM) is an ongoing state-of-the-science model, which has developed new representations of soil hydrology and biogeochemistry and includes a new microbial-functional-group-based CH4 module. This model has been tested in boreal forest peatlands, but has not yet been evaluated for simulating energy and carbon exchange for tropical peatlands. Here, we evaluated the ELM performance in simulating energy, carbon dioxide (CO2) and CH4 fluxes of an Amazonian palm swamp peatland in Iquitos, Peru. ELM simulations using default parameter values resulted in poor performance of seasonal carbon dynamics. Several algorithms were improved according to site-specific characteristics and key parameters were optimized using an objective surrogate-assisted Bayesian approach. The modified algorithms included the soil water retention curve, a water coverage scalar function for CH4 processes, and a seasonally varying leaf carbon-to-nitrogen ratio function. The revised tropics-specific model better simulated the diel and seasonal patterns of energy and carbon fluxes of the palm swamp peatland. Global sensitivity analyses indicated that the strong controls on energy and carbon fluxes were mainly attributed to the parameters associated with vegetation activities, such as plant carbon distribution, stomatal regulation, photosynthetic capacity, and leaf phenology. Parameter relative importance depended on biogeochemical processes and shifted significantly between wet and dry seasons. This modeling study advanced the understanding of biotic controls on the energy and carbon exchange in Amazonian palm swamp peatlands and identified knowledge gaps that need to be addressed for better prediction of carbon cycle processes and budgets for tropical peatlands.
Major carbon losses from degradation of Mauritia flexuosa peat swamp forests in western Amazonia
Tropical peat swamp forests are major global carbon (C) stores highly vulnerable to human intervention. In Peruvian Amazonia, palm swamps, the prevalent peat ecosystem, have been severely degraded through recurrent cutting of Mauritia flexuosa palms for fruit harvesting. While this can transform these C sinks into significant sources, the magnitude of C fluxes in natural and disturbed conditions remains unknown. Here, we estimated emissions from degradation along a gradient comprising undegraded (Intact), moderately degraded (mDeg) and heavily degraded (hDeg) palm swamps. C stock changes above- and below-ground were calculated from biomass inventories and peat C budgets resulting from the balance of C outputs (heterotrophic soil respiration (Rh), dissolved C exports), C inputs (litterfall, root mortality) and soil CH4 emissions. Fluxes spatiotemporal dynamics were monitored (bi)monthly over 1–3 years. The peat budgets (Mg C ha−1 year−1) revealed that medium degradation reduced by 88% the soil sink capacity (from − 1.6 ± 1.3 to − 0.2 ± 0.8 at the Intact and mDeg sites) while high degradation turned the soil into a high source (6.2 ± 0.7 at the hDeg site). Differences stemmed from degradation-induced increased Rh (5.9 ± 0.3, 6.2 ± 0.3, and 9.0 ± 0.3 Mg C ha−1 year−1 at the Intact, mDeg, and hDeg sites) and decreased C inputs (8.3 ± 1.3, 7.1 ± 0.8, and 3.6 ± 0.7 Mg C ha−1 year−1 at the same sites). The large total loss rates (6.4 ± 3.8, 15.7 ± 3.8 Mg C ha−1 year−1 under medium and high degradation), originating predominantly from biomass changes call for sustainable management of these peatlands.
Agroforestry’s contribution to livelihoods and carbon sequestration in East Africa: A systematic review
Agroforestry is a powerful practice for sustainable and regenerative intensification because it promotes multifunctional landscapes that deliver ecological functions that contribute to livelihoods, land productivity, biodiversity conservation, and other ecosystem services. Despite a large body of literature on agroforestry in East Africa, a systematic understanding of its livelihood benefits and contribution to carbon sequestration is still lacking. A systematic review was used to provide a quantitative and qualitative synthesis of available evidence and knowledge gap from 185 publications that met the selection criteria regarding the contribution of agroforestry to livelihoods (n = 152) and carbon sequestration (n = 43) in East Africa. The main livelihood benefits include fodder, food, firewood and income, reported in over 70, 63, 56 and 40 publications, respectively. These and other benefits diversify livelihoods of rural communities and act as safety nets in times of climate shocks. Agroforestry systems in East Africa stock an average of 24.2 ± 2.8 Mg C ha−1 in biomass and 98.8 ± 12.2 Mg C ha−1 in the soil. Much of the aboveground carbon is held in homegardens (34.3 ± 7.9 Mg C ha−1), perennial tree-crop systems (29.9 ± 12.7 Mg C ha−1) and trees on boundaries (26.7 ± 14.1 Mg C ha−1). Empirical studies are needed for better understanding of belowground carbon in agroforestry and emission of greenhouse gases in different agroforestry practices. A smaller number of studies reported income from sale of carbon credits, suggesting a gap in the development of science regarding carbon rights, land tenure, tree tenure rights, and the potential impact of climate change on the growing niches of tree species in the region. The results show that agroforestry is a powerful climate adaptation and mitigation solution as it can increase household resilience and sequesters significant amounts of carbon dioxide from the atmosphere.
Mapping and monitoring peatland conditions from global to field scale
Peatlands cover only 3–4% of the Earth’s surface, but they store nearly 30% of global soil carbon stock. This significant carbon store is under threat as peatlands continue to be degraded at alarming rates around the world. It has prompted countries worldwide to establish regulations to conserve and reduce emissions from this carbon rich ecosystem. For example, the EU has implemented new rules that mandate sustainable management of peatlands, critical to reaching the goal of carbon neutrality by 2050. However, a lack of information on the extent and condition of peatlands has hindered the development of national policies and restoration efforts. This paper reviews the current state of knowledge on mapping and monitoring peatlands from field sites to the globe and identifies areas where further research is needed. It presents an overview of the different methodologies used to map peatlands in nine countries, which vary in definition of peat soil and peatland, mapping coverage, and mapping detail. Whereas mapping peatlands across the world with only one approach is hardly possible, the paper highlights the need for more consistent approaches within regions having comparable peatland types and climates to inform their protection and urgent restoration. The review further summarises various approaches used for monitoring peatland conditions and functions. These include monitoring at the plot scale for degree of humification and stoichiometric ratio, and proximal sensing such as gamma radiometrics and electromagnetic induction at the field to landscape scale for mapping peat thickness and identifying hotspots for greenhouse gas (GHG) emissions. Remote sensing techniques with passive and active sensors at regional to national scale can help in monitoring subsidence rate, water table, peat moisture, landslides, and GHG emissions. Although the use of water table depth as a proxy for interannual GHG emissions from peatlands has been well established, there is no single remote sensing method or data product yet that has been verified beyond local or regional scales. Broader land-use change and fire monitoring at a global scale may further assist national GHG inventory reporting. Monitoring of peatland conditions to evaluate the success of individual restoration schemes still requires field work to assess local proxies combined with remote sensing and modeling. Long-term monitoring is necessary to draw valid conclusions on revegetation outcomes and associated GHG emissions in rewetted peatlands, as their dynamics are not fully understood at the site level. Monitoring vegetation development and hydrology of restored peatlands is needed as a proxy to assess the return of water and changes in nutrient cycling and biodiversity.
Global observation gaps of peatland greenhouse gas balances: needs and obstacles
Greenhouse gas (GHGs) emissions from peatlands contribute significantly to ongoing climate change because of human land use. To develop reliable and comprehensive estimates and predictions of GHG emissions from peatlands, it is necessary to have GHG observations, including carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), that cover different peatland types globally. We synthesize published peatland studies with field GHG flux measurements to identify gaps in observations and suggest directions for future research. Although GHG flux measurements have been conducted at numerous sites globally, substantial gaps remain in current observations, encompassing various peatland types, regions and GHGs. Generally, there is a pressing need for additional GHG observations in Africa, Latin America and the Caribbean regions. Despite widespread measurements of CO2 and CH4, studies quantifying N2O emissions from peatlands are scarce, particularly in natural ecosystems. To expand the global coverage of peatland data, it is crucial to conduct more eddy covariance observations for long-term monitoring. Automated chambers are preferable for plot-scale observations to produce high temporal resolution data; however, traditional field campaigns with manual chamber measurements remain necessary, particularly in remote areas. To ensure that the data can be further used for modeling purposes, we suggest that chamber campaigns should be conducted at least monthly for a minimum duration of one year with no fewer than three replicates and measure key environmental variables. In addition, further studies are needed in restored peatlands, focusing on identifying the most effective restoration approaches for different ecosystem types, conditions, climates, and land use histories.
Proximal remote sensing and gross primary productivity in a temperate salt marsh
Salt marshes are highly productive ecosystems relevant for Blue Carbon assessments, but information for estimating gross primary productivity (GPP) from proximal remote sensing (PRS) is limited. Temperate salt marshes have seasonal canopy structure and metabolism changes, defining different canopy phenological phases, GPP rates, and spectral reflectance. We combined multi-annual PRS data (i.e., PhenoCam, discrete hyperspectral measurements, and automated spectral reflectance sensors) with GPP derived from eddy covariance. We tested the performance of empirical models to predict GPP from 12 common vegetation indices (VIs; e.g., NDVI, EVI, PSRI, GCC), Sun-Induced Fluorescence (SIF), and reflectance from different areas of the electromagnetic spectrum (i.e., VIS-IR, RedEdge, IR, and SIF) across the annual cycle and canopy phenological phases (i.e., Greenup, Maturity, Senescence, and Dormancy). Plant Senescence Reflectance Index (PSRI) from hyperspectral data and the Greenness Index (GCC) from PhenoCam, showed the strongest relationship with daily GPP across the annual cycle and within phenological phases (r2=0.30–0.92). Information from the visible-infrared electromagnetic region (VIS-IR) coupled with a partial least square approach (PLSR) showed the highest data-model agreement with GPP, mainly because of its relevance to respond to physiological and structural changes in the canopy, compared with indices (e.g., GCC) that particularly react to changes in the greenness of the canopy. The most relevant electromagnetic regions to model GPP were ∼550 nm and ∼710 nm. Canopy phenological phases impose challenges for modeling GPP with VIs and the PLSR approach, particularly during Maturity, Senescence, and Dormancy. As more eddy covariance sites are established in salt marshes, the application of PRS can be widely tested. Our results highlight the potential to use canopy reflectance from the visible spectrum region for modeling annual GPP in salt marshes as an example of advances within the AmeriFlux network.