Search

Context. Pasture dieback has emerged as a significant threat to the health and productivity of sown pastures in eastern Queensland and northern New South Wales, Australia. Aims. We aimed to address knowledge gaps on spatial spread patterns, recovery trajectories and floristic changes using remote sensing and ground surveys. Methods. We used a time series of high-resolution (12–25 cm) aerial imagery to quantify and compare pasture dieback spread over 7 years in three land-use areas: ungrazed pasture, grazed pasture and rehabilitation following mining. The green leaf index was applied using supervised random forest algorithms to classify areas affected between 2015 and 2021. Flora surveys were conducted to compare impacted and unimpacted areas for the three land uses and validate classifications. Key results. The first emergence of pasture dieback was in ungrazed pasture, and these areas recorded the highest rate of dieback spread at 1.88 ha month−1, compared with 0.54 and 0.19 ha month−1 in rehabilitated and grazed pastures respectively. Field validation showed that dieback-impacted pastures shifted from buffel grass (Cenchrus ciliaris L.), to forb-dominated communities with significantly different species mix, biomass and cover conditions. An analysis of local climate data showed that winter night-time temperatures and rainfall were notably higher than long-term means in the year preceding the first detection of pasture dieback. Conclusions. High resolution aerial imagery and ground surveys can be used to monitor pasture health by employing vegetation indices and random forest classifiers. Implications. Ungrazed pastures and roadside areas should be managed to protect the region from further outbreaks.

Context. Pasture dieback has emerged as a significant threat to the health and productivity of sown pastures in eastern Queensland and northern New South Wales, Australia. Aims. We aimed to address knowledge gaps on spatial spread patterns, recovery trajectories and floristic changes using remote sensing and ground surveys. Methods. We used a time series of high-resolution (12–25 cm) aerial imagery to quantify and compare pasture dieback spread over 7 years in three land-use areas: ungrazed pasture, grazed pasture and rehabilitation following mining. The green leaf index was applied using supervised random forest algorithms to classify areas affected between 2015 and 2021. Flora surveys were conducted to compare impacted and unimpacted areas for the three land uses and validate classifications. Key results. The first emergence of pasture dieback was in ungrazed pasture, and these areas recorded the highest rate of dieback spread at 1.88 ha month−1, compared with 0.54 and 0.19 ha month−1 in rehabilitated and grazed pastures respectively. Field validation showed that dieback-impacted pastures shifted from buffel grass (Cenchrus ciliaris L.), to forb-dominated communities with significantly different species mix, biomass and cover conditions. An analysis of local climate data showed that winter night-time temperatures and rainfall were notably higher than long-term means in the year preceding the first detection of pasture dieback. Conclusions. High resolution aerial imagery and ground surveys can be used to monitor pasture health by employing vegetation indices and random forest classifiers. Implications. Ungrazed pastures and roadside areas should be managed to protect the region from further outbreaks.

Manure generated from livestock production could represent an important source of plant nutrients in substitution of synthetic fertilizer. To evaluate the sustainability of partially substituting synthetic fertilizer with soil organic amendments (OAs) in horticulture, an economic and greenhouse gas (GHG) budget was developed. The boundary for analysis included manure processing (stockpiling vs. composting) and transport and spreading of manure and compost (feedlot and chicken) in intensively cultivated horticultural fields. The OA field application rates were calculated based on the nitrogen supplied by OAs. The GHG budget based on directly measured emissions indicates that the application of composted manure, in combination with reduced fertilizer rate, was always superior to stockpiled manures. Compost treatments showed from 9 to 90% less GHG emissions than stockpiled manure treatments. However, higher costs associated with the purchase and transport of composted manure (three times higher) generated a greater economic burden compared with stockpiled manure and synthetic fertilizer application. The plant nutrient replacement value of the OAs was considered only for the first year of application, and if long-term nutrient release from OAs is taken into account, additional savings are possible. Because the income from soil carbon sequestration initiatives in response to OA application is unlikely to bridge this financial gap, particularly in the short term, this study proposes that future policy should develop methodologies for avoided GHG emissions from OA application. The combined income from soil carbon sequestration and potentially avoided GHG initiatives could incentivize farmers to adopt OAs as a substitute for synthetic fertilizers, thereby promoting more sustainable farming practices.

Increasing demand for land-based climate mitigation requires more efficient management of agricultural landscapes for competing objectives. Here we develop methods for assessing trade-offs and synergies between intensification and carbon-sequestering conservation measures in annual crop production landscapes using the DayCent ecosystem model and the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) life-cycle assessment (LCA) model. We compiled county-scaled crop yields, fertilizer application rates, and tillage intensity for a corn–soybean farming case study landscape in the US state of Iowa. Using DayCent, we estimated a baseline soil organic carbon (SOC) accrual rate of 0.29 Mg C ha−1 y−1 driven by historical increases in crop productivity and reductions in tillage intensity. We then simulated the effects of management interventions targeted toward intensification (stover removal) and SOC sequestration (tillage intensity reduction and winter cover crop addition) individually and in combination. We propose a new multi-product landscape–LCA approach that analyzes marginal changes in corn grain, corn stover, and soybean production from the landscape in terms of their value for biofuel production (corn ethanol, soy biodiesel, and cellulosic ethanol from stover) and associated net displacement of conventional fossil-derived fuel use. This enables us to evaluate both intensification and sequestration effects in common CO2-equivalent mitigation units. We also used DayCent-simulated yields under the different land management scenarios to estimate farm-level costs and revenues. Our results show that intensification via collecting 30% of corn stover for biofuel production would increase the total greenhouse gas (GHG) mitigation potential of this landscape by 0.93 Mg CO2e ha−1 y−1 and provide $49 ha−1 y−1 of additional net revenue from biomass sales, but wo

The Forest Vegetation Simulator (FVS) growth and yield model is widely used throughout the United States, but recent studies have reported unexpectedly large bias for some regional model variants. Here we propose a general framework for model evaluation, designed to highlight model strengths and weaknesses and inform calibration efforts. We apply the framework to evaluate the Lodgepole Pine (LP) model of the FVS Central Rockies Variant (FVS-CR), which has rarely been evaluated in the literature despite its widespread use in the western US. We started with a qualitative verification of the structure and logic of the FVS-CR LP model against a modified Bakuzis matrix, determining that it adequately reproduces known patterns of stand dynamics. We then compared stand-level growth simulations to a chronosequence developed from 554 Forest Inventory and Analysis (FIA) plots measured in Colorado and Wyoming lodgepole pine forests. This quantitative validation exercise revealed that the default model settings substantially over-predict basal area and total stand carbon after 50 years for both pure lodgepole pine stands and mixed lodgepole pine stands containing a minor proportion of Engelmann spruce, subalpine fir, and quaking aspen. Using equivalence testing to validate the large-tree diameter increment model against a separate dataset of 3,790 remeasured trees on 124 lodgepole pine FIA plots, we found that the default FVS–CR LP model adequately predicts lodgepole diameter growth, though we observed large variation in model errors. Equivalence tests also revealed systematic under-estimation of spruce–fir and over-estimation of aspen productivity. Finally, we conducted a sensitivity analysis to identify the most important model parameters and data inputs driving simulated stand structure and carbon accumulation in both the short- (50 years) and long-term (200 years). The model shows the greatest sensitivity to initial species composition; a small proportion of aspen, spruc

Improved management practices should be implemented in croplands in sub-Saharan Africa to enhance soil organic carbon (SOC) storage and/or reduce losses associated with land-use change, thereby addressing the challenge of ongoing soil degradation. DayCent, a process-based biogeochemical model, provides a useful tool for evaluating which management practices are most effective for SOC sequestration. Here, we used the DayCent model to simulate SOC using experimental data from two long-term field sites in western Kenya comprising of two widely promoted sustainable agricultural management practices: integrated nutrient management (i.e. mineral fertilizer and crop residues/farmyard manure incorporation) and conservation agriculture (i.e. minimum tillage and crop residue retention). At both sites, correlations between measured and simulated SOC were low to moderate (R2 of 0.25−0.55), and in most cases, the model produced fairly accurate prediction of the SOC trends with a low relative root mean squared error (RRMSE < 7%). Consistent with field measurements, simulated SOC declined under all improved management practices. The model projected annual SOC loss rates of between 0.32 to 0.35 Mg C ha-1 yr-1 in continuously tilled maize (Zea mays) systems without fertilizer or organic matter application over the period 2003–2050. The most effective practices in reducing the losses were the combined application of 4 Mg ha-1 of farmyard manure and 2 Mg ha-1 of maize residue retention (reducing losses up to 0.22 Mg C ha-1 yr-1), minimum tillage in combination with maize residue retention (0.21 Mg C ha-1 yr-1), and rotation of maize with soybean (Glycine max) under minimum tillage (0.17 Mg C ha-1 yr-1). Model results suggest that response of the passive SOC pool to the different management practices is a key driver of the long-term SOC trends at the two study sit

This study aims to fill a gap in the literature by examining the impacts of an emissions trading scheme (ETS) in Vietnam, as the policy has been discussed for a decade in the country but the likely impacts on the economy and different sectors are still unidentified. The simulations are carried out in a global energy computable general equilibrium (CGE) model, an extension of the GTAP-E model, which treats Vietnam as a country region. Results show that restricting the number of industrial sectors in the emissions trading market substantially affects the country's economy with a decline in real GDP by 4.57%. However, the country experiences much smaller adverse impacts (e.g., real GDP declines by 1.78%) when all industries participate in the emissions trading market. In either case of the ETS design, the coal mining, manufacturing, transportation, and electricity sectors are highly adversely affected; however, the crude oil and natural gas extraction sectors would experience expansion in their production levels due to substitutions for coal. In general, under the policy the emission levels from burning fossil fuels decline at significant rates, particularly from the electricity generation sector.

Energy security has been a major concern in developing countries because of rapid economic development and population growth, low power generation capacity, and unwell-developed transmission infrastructure. Vietnam in this context has been under energy security threats for more than a decade and is currently having a new power policy to strongly develop power generation and distribution networks. It is expected that the country's economy is able to develop substantially due to massively additional energy supply once completing the plants and distribution networks but the likely impacts are still undefined. This paper extends an economic electricity-detailed model to examine the potential impacts of such a new power policy in Vietnam. We find that the policy will decrease the prices of both fossil-based and renewable-based electricity significantly by 40%–78% under a 2030 target scenario, benefiting all sectors in the economy to substitute for fossil fuels. Households are particularly benefited as evidenced by 5.64%–19.19% increases in per-capita utility. Overall, the Vietnamese economy is significantly advantaged with real GDP increasing by 5.44%–24.83% over different scenarios, which are much higher than the findings in other countries. More importantly, the policy moves the country to a low-carbon energy structure in the near future.

Vietnam's forests have experienced a notable transformation over the past 20 years from net deforestation to reforestation and expanding forests. Continued reforestation that aims to achieve further economic and environmental benefits remains a national priority and strategy. We explore the current status of plantation forests and highlight possible means to facilitate their expansion in the uplands of Vietnam. We employ mixed method triangulation to empirically explore plantation forests and their economic role in household livelihood, to quantify trade-offs between plantation forests and shifting cultivation, and to assess the constraints on plantation forest expansion in Nghe An province, north-central Vietnam. Results show that forest in the study area expanded by 406,000 ha (71.1%) between 1990 and 2016. Plantation forests increased by nearly 500% (from 32,000 ha to 190,000 ha), while natural forests expanded by 48.1% (from 538,000 ha to 797,000 ha). Plantation forests contributed an average of 35.1 percent of total household income in wealthier households and 27.9 percent of income in poor households. Switching from shifting cultivation to plantation forests would increase total household income and average carbon stock but decrease food provision. Total Economic Value would be higher for plantation forest scenarios if increased carbon stocks in plantations can be monetized. This carbon income might drive conversion of shifting cultivation to plantation forests. Constraints on further expansion of plantation forest are low external cooperation, education, market stability, and agroforestry extension services. Our empirical results inform national plantation forest development, sustainable upland livelihood development, and climate change mitigation programs to ultimately facilitate forest transition and improve the resilience and sustainability of socio-ecological systems.

Vietnam's forests have experienced a notable transformation over the past 20 years from net deforestation to reforestation and expanding forests. Continued reforestation that aims to achieve further economic and environmental benefits remains a national priority and strategy. We explore the current status of plantation forests and highlight possible means to facilitate their expansion in the uplands of Vietnam. We employ mixed method triangulation to empirically explore plantation forests and their economic role in household livelihood, to quantify trade-offs between plantation forests and shifting cultivation, and to assess the constraints on plantation forest expansion in Nghe An province, north-central Vietnam. Results show that forest in the study area expanded by 406,000 ha (71.1%) between 1990 and 2016. Plantation forests increased by nearly 500% (from 32,000 ha to 190,000 ha), while natural forests expanded by 48.1% (from 538,000 ha to 797,000 ha). Plantation forests contributed an average of 35.1 percent of total household income in wealthier households and 27.9 percent of income in poor households. Switching from shifting cultivation to plantation forests would increase total household income and average carbon stock but decrease food provision. Total Economic Value would be higher for plantation forest scenarios if increased carbon stocks in plantations can be monetized. This carbon income might drive conversion of shifting cultivation to plantation forests. Constraints on further expansion of plantation forest are low external cooperation, education, market stability, and agroforestry extension services. Our empirical results inform national plantation forest development, sustainable upland livelihood development, and climate change mitigation programs to ultimately facilitate forest transition and improve the resilience and sustainability of socio-ecological systems. © 2020 by the authors.

We demonstrate the use of a surrogate-based optimization framework for large-scale and high-resolution landscape management optimization, using irrigated corn production systems in eastern Colorado, USA as a case study. An artificial neural network was employed to create a surrogate of the DayCent biogeochemical simulation model. Our optimization considered trade-offs among seven different objectives at different scales, including farm profits, irrigation water use, corn grain, corn stover, soil organic carbon (SOC), greenhouse gas (GHG) emissions, and nitrogen leaching. The results show that the surrogate captured greater than 99% of the variations in the DayCent's simulated outputs and was 6.2 million times faster than the DayCent model for our analysis. Farm-level optimization increased farm profits by 83%–150%, SOC by 16%–53%, grain yield by 10.1–11.3%, and reduced GHG emissions by 19%–55% compared to the ‘business-as-usual’ scenario.

Biofuels have been proposed as a potential solution for climate change mitigation. However, there exist several barriers, such as “food vs fuel” issues and technological constraints, restricting the sustainable commercialization of both first- and second-generation biofuels. Combining arable crops and their residues for hybrid first- and second-generation biofuel production provides opportunities to overcome these barriers. This study presents a high-resolution quantitative tool to support decision-making in feedstock production and sourcing for hybrid biofuel supply chains. We demonstrate this work with a case study on optimizing feedstock landscape design for a hybrid corn grain- and stover-based ethanol production system at Front Range Energy biorefinery, Windsor, Colorado, USA using a coupled simulation modeling and life-cycle assessment approach. The case study considered three competing design objectives including the minimization of feedstock-delivered costs, farm-to-refinery greenhouse gas emissions (GHG), and nitrogen (N) leaching, subject to constraints in land use and biofuel feedstock demand. Social costs of carbon (SC-CO2) and nitrogen leaching (SC-NL) were used as weighting factors for GHG and N leaching in the objective function. Our results showed that marginal decreases of feedstock-delivered costs (below $0.31 L−1), N leaching (below 0.44 g N L−1), and GHG emissions (below 125 g CO2e L−1) resulted in extreme trade-offs among the design objectives. Changes in feedstock landscape design were most sensitive to the variations of the SC-CO2 between $400 and $800 per Mg CO2e, SC-NL between $0 and $50 per kg N leaching, and their ratio between 0 and 350, respectively.

Agricultural land management often involves trade-offs between ecosystem services (ES) and disservices (EDS). Balancing these trade-offs to achieve low-impact production of agricultural commodities requires rigorous approaches for quantifying and optimizing ES and EDS, reconciling biophysical constraints and different management objectives. In this study, we demonstrate a high-resolution spatially-explicit analysis of ES and EDS trade-offs for irrigated corn production systems in the South Platte River Basin, Colorado, USA, as a case study. The analysis integrated a biogeochemical model (DayCent) with optimization algorithms to assess trade-offs between multiple ES and EDS indicators, including net primary production, soil organic carbon, water use, nitrogen leaching, and greenhouse gas emissions. Our results show a large fraction of total potential system productivity (up to 21 Mg ha−1 year−1) can be realized at minimal ecosystem impacts through careful land management decisions. Our analysis also explores how different land management objectives imply different landscape configurations.

Cassava-based ethanol has been promoted in China and Southeast Asia as an effective means to reduce greenhouse gas (GHG) emissions and promote energy security. However, existing life cycle assessments of the environmental impacts of cassava ethanol have used highly-aggregated empirical methods to estimate ecosystem C stock changes, which do not capture finer-scale characteristics of different cassava growing regions within a country. We investigated carbon debts, GHG emissions, and payback periods for cassava-based ethanol in Vietnam using a life cycle assessment approach coupled with the widely-used ecosystem biogeochemical CENTURY model. The model simulated regionally-specific carbon stock changes associated with cassava cultivation for biofuel feedstock under different land use change, cassava yield and fertilization scenarios. We found that switching land use to cassava production for biofuel substantially reduced soil organic carbon in all major cassava growing regions in Vietnam. GHG emissions, carbon debts, and payback periods of Vietnam's cassava ethanol were strongly dependent on cassava yield. The mean carbon debt due to direct land use change to cassava production for ethanol ranged from 66 to 97 Mg of CO2 per hectare, and the net carbon dioxide equivalent emission of cassava-based ethanol ranged from 36 to 95 g MJ−1, depending on the range of cassava fresh weight yield (from 18 to 60 Mg ha−1). To repay a carbon debt from direct land use change within 25 years, the average fresh weight yield of cassava used as feedstock for ethanol production must be above 33 Mg ha−1.

Infrared optical switching devices based on closed-tube-vapor- transport grown single crystals of group IV metal dichalcogenides were investigated. Reversible infrared reflectance modulation was identified in alkali metal intercalated HfS2 and ZrS2. A reflectance driven transmittance modulation of 0.0 1 % to 50% from 2-16 microns was observed with LixHfS2 single crystals chemically lithiated and delithiated. Similar, although less dramatic, modulation was obtained with AgxHfS2 crystals. Efforts to develop practical optical switching devices based on this IR modulation focused on the incorporation of electroactive and photoactive electron donor-acceptor complexes in the van der Waals' gaps of the crystals. Electron donor (e.g., Li or Ag) intercalation is readily achieved because of coulombic stabilization of the intercalated crystal through intercalation of the chalcogens (e.g., S) and the donor cation. Intercalation of electron acceptors (e.g., I and Br) into reduced (donor intercalated) dichalcogenides was found energetically unfavorable and resulted in deintercalation of the donor. Mixed-metal (group IV and V) dichalcogenide crystals, that are intrinsically n-type, were also used as hosts for acceptor intercalation. The as-grown mixed-metal crystals had higher electrical conductivities and were more IR reflective than pure HfS2 or ZrS2. Attempts to intercalate I and Br into the mixed-metal crystals resulted in extensive exfoliation. The use of metallocenes, principally chromocene, to create a 5A c-axis expansion was successful and led to the preparation Of I2 'intercalated' chromocene-HfS2. The nature of the bonding between the intercalated I2 and both the chromocene and HfS2 remains unknown. Optical hardening Crystal growth, Dichalcogenides, Intercalation.