Tag: carbon
Seasonal and spatial patterns of surface water quality in large-scale treatment wetlands with different vegetation communities
The Everglades Stormwater Treatment Areas (STAs), a network of large, constructed wetlands, were built to reduce phosphorus (P) in water discharged into downstream oligotrophic Everglades ecosystem. These wetlands are colonized by two main types of macrophyte communities: emergent aquatic vegetation (EAV) and submerged aquatic vegetation (SAV). The objective of this study was to compare the seasonal and spatial patterns of surface water quality within two flow-ways (FWs) in STA-2 (FW1 dominated by EAV and FW3 a mixed marsh with both EAV and SAV) and assess how surface water quality was affected by extreme storm events. Surface water samples were collected from three stations (near the inflow, middle of the FW, and near the outflow) along the flowpath of each FW four times from 2016 to 2018. Total P and its fractions generally decreased along the flowpath in both FWs while other elements did not show a consistent trend between seasons. Surface water quality in FW1 had more evident seasonal patterns and was less affected by 2017 storm events compared to that of FW3. The changes and patterns of water quality indicate that the processes (e.g., plant nutrient uptake, microbial assimilation, detritus decomposition and particle settling, etc.), which take the primary role of removing nutrients from the water column in FW1, vary not only due to the differences in plant growth but also to variations of hydraulic and nutrient loadings over wet and dry seasons. In FW3, on the contrary, our results indicate that the occlusion process facilitated by underwater photosynthesis of SAV likely enhanced the capacity of removing P and associated elements from water column and attenuated the seasonal differences. The SAV in FW3 also was susceptible to extreme events, with both short- and long-term adverse effects of storm events on surface water quality.
Effects of diverse mangrove management practices on forest structure, carbon dynamics and sedimentation in North Sumatra, Indonesia
For decades, mangrove forests have been under tremendous pressure due to deforestation and conversion. To sustainably manage the mangroves that remain, an ecosystem approach to management is essential. Two different management regimes – conservation and restoration – were assessed, looking at their respective effects on forest structure and carbon cycling capacity, when compared with degraded mangrove. We found that mangrove restoration enhanced tree density, while mangrove conservation was able to maintain species diversity. In terms of carbon budgets, aboveground carbon was lower in restored mangrove (79.40 ± 37.41 Mg C ha−1) when compared with conserved mangrove (92.26 ± 22.65 Mg C ha−1), but was almost double that found in degraded mangrove (39.89 ± 27.49 Mg C ha−1). Although conserved mangrove had higher aboveground carbon, lower amounts of soil carbon were found in conserved mangrove (127.49 ± 33.21 Mg C ha−1) than in restored and degraded mangrove (236.26 ± 20.33 Mg C ha−1 and 139.17 ± 25.44 Mg C ha−1, respectively). The elevation change was highest in degraded mangrove (41.7 ± 24.0 mm yr−1), followed by restored (20.7 ± 14.6 mm yr−1) and conserved mangrove (12.2 ± 3.9 mm yr−1). Carbon burial in conserved mangrove (1.20 ± 1.90 Mg C ha−2 yr−1) was double that of degraded mangrove (0.63 ± 0.60 Mg C ha−2 yr−1). Ultimately, we conclude that although a conserved mangrove is not always the end result of mangrove restoration and sustainable management, finding balance between structural development and ecosystem function is essential to serve different objectives, including biodiversity maintenance.
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.
Blue carbon assessments of seagrass and mangrove ecosystems in South and Southeast Asia: Current progress and knowledge gaps
Coastal blue carbon ecosystems can be an important nature-based solution for mitigating climate change, when emphasis is given to their protection, management, and restoration. Globally, there has been a rapid increase in blue carbon research in the last few decades, with substantial investments on national scales by the European Union, the USA, Australia, Seychelles, and Belize. Blue carbon ecosystems in South and Southeast Asia are globally diverse, highly productive and could represent a global hotspot for carbon sequestration and storage. To guide future efforts, we conducted a systematic review of the available literature on two primary blue carbon ecosystems—seagrasses and mangroves—across 13 countries in South and Southeast Asia to assess existing national inventories, review current research trends and methodologies, and identify existing knowledge gaps. Information related to various aspects of seagrass and mangrove ecosystems was extracted from 432 research articles from 1967 to 2022. We find that: (1) blue carbon estimates in several countries have limited data, especially for seagrass meadows compared to mangrove ecosystems, although the highest reported carbon stocks were in Indonesia and the Philippines with 4,515 and 707 Tg within mangrove forest and 60.9 and 63.3 Tg within seagrass meadows, respectively; (2) there is a high difference in the quantity and quality of data between mangrove and seagrass ecosystems, and the methodologies used for blue carbon estimates are highly variable across countries; and (3) most studies on blue carbon stocks are spatially biased towards more familiar study areas of individual countries, than several lesser-known suspected blue carbon hotspots. In sum, our review demonstrates the paucity and variability in current research in the region, and highlights research frontiers that should be addressed by future research before the robust implementation of these ecosystems into national climate strategies.
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.
Combined application of the EM-DEA and EX-ACT approaches for integrated assessment of resource use efficiency, sustainability and carbon footprint of smallholder maize production practices in sub-Saharan Africa
The goal to improve food security in sub-Saharan Africa (SSA) through domestic, resource efficient and low carbon agriculture is importance. Interventions to produce more food could impact the resource-base and lead to increase in greenhouse gas (GHG) emissions from agroecosystems. Unfortunately, existing methods are limited in analyzing small-scale agricultural systems, and this situation is an obstacle to decision making which aims at sustainable agriculture. In this paper, we showcase the recently developed Emergy-Data Envelopment Analysis (EM-DEA) approach to assess the resource use efficiency (RUE) and sustainability in maize production systems in Ghana, SSA. Using the Agricultural Production Systems sIMulator (APSIM), five land use and resource management scenarios were modeled to represent practices as decision making units (DMUs) in small-scale maize systems. The carbon footprint of the systems was assessed using an approach, which we adapted from the FAO Ex-Ante Carbon balance Tool (EX-ACT). The overall trend of the results showed that the yield, total emergy, GHG emissions and carbon footprint all increased with increase in urea application intensity. However, the relationship between the yield and urea intensity was not always linear. A system that used more renewable or fewer resources to produce a yield equal to that of its peer was considered more efficient and sustainable in relative terms. In particular, the business-as-usual scenario (12 kg/ha/yr NPK input to rainfed maize system, i.e. Extensive12) was inefficient when compared to the four contrasting scenarios. The ecological intensive scenario (20 kg/ha/yr urea input to rainfed maize-legume intercropping system, i.e. Intercrop20) achieved the greatest marginal yield, better RUE and sustainability. The high input scenario (100 kg/ha/yr urea input plus supplemental irrigation to maize monoculture, i.e. Intensive100) produced the greatest yield, but the demand for purchased inputs as well as GHG emissions and carbon footprint were greatest. The no external input scenario (0 kg/ha/yr urea input to rainfed maize system, i.e. Extensive0), and the moderate input scenario (50 kg/ha/yr urea input plus supplemental irrigation to maize monoculture, i.e. Intensive50) showed the greatest and least yield gaps relative to Intensive100, respectively. Based on these results and trade-off analysis, it was evident that Intercrop20 and Intensive50 were the two best case scenarios. As such, land use policy that aims at sustainable agriculture could recommend Intercrop20 and Intensive50 for implementation in low and high input maize production systems, respectively. Comparison between our results and other existing empirical studies revealed similarities that confirm our results. We conclude that the information derived using the EM-DEA and EX-ACT approaches could be useful when making informed decisions that aim at sustainable agriculture. Despite the limitation caused by scarcity of data, the use of the EM-DEA approach led to inclusive information on RUE and sustainability of the DMUs. Hence, the EM-DEA approach represents a way forward to better assess energy footprint in agricultural land use as a whole.
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.
Aspectos financieros de las acciones nacionales de mitigación apropiada (NAMA) para los sistemas ganaderos en la región de América Latina y El Caribe [Financial aspects of National Appropriate Mitigation actions (NAMAs) for livestock systems in the Latin America and Caribbean region]
This document summarizes the results of the analysis on the financing issues related to business models proposed by existing NAMAs or emission reduction initiatives in nine LAC countries (Mexico, the Dominican Republic, Guatemala, Honduras, Costa Rica, Colombia, Argentina, Uruguay and Paraguay), developed between November 2018 and February 2019 by reviewing and analyzing secondary information and consulting (remotely) with key informants from each country evaluated. Financial and non financial barriers were evaluated, along with financial instruments proposed by livestock NAMAs. As a result, the implementation of a financing mechanism in countries developing NAMAs or livestock programs is recommended, as well as a few general recommendations to guide the financial aspects of these initiatives, in order to increase their long-term sustainability.
Gobernanza de las Acciones Nacionales Apropiadas de Mitigación (NAMA) para los sistemas ganaderos en la región de América Latina y el Caribe [Governance of National Appropriate Mitigation Actions (NAMAs) for livestock systems in Latin America and the Caribbean]
This document summarizes the governance analysis of bovine livestock NAMAs, or low-emission cattle farming initiatives, that are either underway or in formulation in LAC. It focuses on the legal and institutional frameworks and the key aspects related to stakeholder framework structure and design, associated with an effective and sustainable governance model.