In a field study, long-term application of compost to a tropical Aeric Endoaquept under continuous rice growing in a rice–rice–fallow sequence resulted in the stimulation of microbial biomass and ...select soil enzyme activities. Mean seasonal soil microbial biomass-C (C
mic) increased by 42%, 39% and 89% in inorganic fertilizer, compost and compost+inorganic fertilizer treatments, respectively, over the unamended control. C
mic content was also influenced by the rice crop growth stage and was highest at maximum tillering stage irrespective of treatments and declined thereafter. Soil organic C (C
org) content showed highly significant positive correlation with dehydrogenase, urease, cellulase,
β-glucosidase and fluorescein di-acetate (FDA) hydrolysis activity, and a positive but not significant correlation with invertase and amidase activity. C/N ratio which was lowest in unamended control plots showed a significant positive relationship with only the enzymes involved in C cycle. Stepwise regression analysis revealed that for prediction of both total organic C and total N, FDA hydrolysis activity contributed significantly for the variance and explained up to 85–96% variability. Results demonstrated that microbial biomass and soil enzyme activity is sensitive in discriminating between long-term organic residue amendment practices.
Community-led watershed development activities, including the establishment of exclosures (areas where both livestock and farming activities are excluded) on degraded communal grazing land, have ...become a common practice in Ethiopia since the 1990s. However, it is not yet fully understood how these exclosures change soil organic carbon and total soil nitrogen in different soil types and under different agroecologies. A meta-analysis using data gathered from the most relevant peer reviewed articles from Ethiopian exclosure systems was conducted to assess the variation in the effects of exclosures on soil carbon and nitrogen and to investigate the factors controlling change. The results demonstrate that after 16 years, exclosures can increase soil organic carbon and total soil nitrogen up to an effect size greater than two. This is moderated by soil type, exclosure age, landscape position and agroecology. More effective restoration of soil carbon was observed in less developed Leptosols and Cambisols than in more developed Luvisols, and in drier than more humid agroecologies. The results suggest that soil type and agroecology should be taken into consideration when planning and implementing exclosures on degraded communal grazing land. The findings of this study provide base line information for the future expansion of exclosures, and guide where to focus implementation. They also provide criteria to be used when planning and establishing exclosures to restore soil carbon and nitrogen. In addition, the results generated through this meta-analysis provide better understanding of the spatial and temporal variation of the effectiveness of exclosures to restore soil carbon and nitrogen.
This dataset represents long-term marginal abatement cost (MAC) curves of all major emission sources of non-CO2 greenhouse gases (GHGs); methane (CH4), nitrous oxide (N2O) and fluorinated gases ...(HFCs, PFCs and SF6). The work is based on existing short-term MAC curve datasets and recent literature on individual mitigation measures. The data represent a comprehensive set of MAC curves, covering all major non-CO2 emission sources for 26 aggregated world regions. They are suitable for long-term global mitigation scenario development, as dynamical elements (technological progress, removal of implementation barriers) are included. The data is related to the research article: “Long-term marginal abatement cost curves of non-CO2greenhouse gases” 1.
Systems approaches in global change and biogeochemistry research Smith, Pete; Albanito, Fabrizio; Bell, Madeleine ...
Philosophical transactions of the Royal Society of London. Series B. Biological sciences,
01/2012, Letnik:
367, Številka:
1586
Journal Article
Recenzirano
Odprti dostop
Systems approaches have great potential for application in predictive ecology. In this paper, we present a range of examples, where systems approaches are being developed and applied at a range of ...scales in the field of global change and biogeochemical cycling. Systems approaches range from Bayesian calibration techniques at plot scale, through data assimilation methods at regional to continental scales, to multi-disciplinary numerical model applications at country to global scales. We provide examples from a range of studies and show how these approaches are being used to address current topics in global change and biogeochemical research, such as the interaction between carbon and nitrogen cycles, terrestrial carbon feedbacks to climate change and the attribution of observed global changes to various drivers of change. We examine how transferable the methods and techniques might be to other areas of ecosystem science and ecology.
•Long-term non-CO2 MAC curves developed based on most recent literature.•Includes all major non-CO2 emission sources and mitigation measures for 26 world regions.•Maximum reduction potential of ...nitrous oxide estimated higher, of methane lower.•Overall non-CO2 mitigation estimated at 58% in 2050 and 71% in 2100.•Delayed climate action can lower mitigation potentials.
This study presents a new comprehensive set of long-term Marginal Abatement Cost (MAC) curves of all major non-CO2 greenhouse gas emission sources. The work builds on existing short-term MAC curve datasets and recent literature on individual mitigation measures. The new MAC curves include current technology and costs information as well as estimates of technology development and removal of implementation barriers to capture long-term dynamics. Compared to earlier work, we find a higher projected maximum reduction potential (MRP) of nitrous oxide (N2O) and a lower MRP of methane (CH4). The combined MRP for all non-CO2 gases is similar but has been extended to also capture mitigation measures that can be realized at higher implementation costs. When applying the new MAC curves in a cost-optimal, integrated assessment model-based 2.6 W/m2 scenario, the total non-CO2 mitigation is projected to be 10.9 Mt CO2 equivalents in 2050 (i.e. 58% reduction compared to baseline emissions) and 15.6 Mt CO2equivalents in 2100 (i.e. a 71% reduction). In applying the new MAC curves, we account for inertia in thline implementation speed of mitigation measures. Although this does not strongly impact results in an optimal strategy, it means that the contribution of non-CO2 mitigation could be more limited if ambitious climate policy is delayed.
This dataset represents long-term marginal abatement cost (MAC) curves of all major emission sources of non-CO
greenhouse gases (GHGs); methane (CH
), nitrous oxide (N
O) and fluorinated gases (HFCs, ...PFCs and SF
). The work is based on existing short-term MAC curve datasets and recent literature on individual mitigation measures. The data represent a comprehensive set of MAC curves, covering all major non-CO
emission sources for 26 aggregated world regions. They are suitable for long-term global mitigation scenario development, as dynamical elements (technological progress, removal of implementation barriers) are included. The data is related to the research article: "
" 1.
To predict the response of C-rich soils to external change, models are needed that accurately reflect the conditions of these soils. Estimation of Carbon in Organic Soils—Sequestration and Emissions ...(ECOSSE) is a model that allows simulations of soil C and N turnover in both mineral and organic soils using only the limited meteorological, land-use and soil data that is available at the national scale. Because it is able to function at field as well as national scales if appropriate input data are used, field-scale evaluations can be used to determine uncertainty in national simulations. Here we present an evaluation of the uncertainty expected in national-scale simulations of Scotland, using data from the National Soil Inventory of Scotland. This data set provides measurements of C change for the range of soils, climates and land-use types found across Scotland. The simulated values show a high degree of association with the measurements in both total C and change in C content of the soil. Over all sites where land-use change occurred, the average deviation between the simulated and measured values of percentage change in soil C was less than the experimental error (11% simulation error, 53% measurement error). This suggests that the uncertainty in the national-scale simulations will be ~11%. Only a small bias in the simulations was observed compared to the measured values, suggesting that a small underestimate of the change in soil C should be expected at the national scale (–4%).
In order to predict the response of carbon (C)-rich soils to external change, models are needed that accurately reflect the conditions of these soils. Here we present an example application of the ...new Estimation of Carbon in Organic Soils – Sequestration and Emissions (ECOSSE) model to estimate net change in soil C in response to changes in land use in Scotland. The ECOSSE estimate of annual change in soil C stocks for Scotland between 2000 and 2009 is −810 ± 89 kt yr⁻¹, equivalent to 0.037 ± 0.004% yr⁻¹. Increasing the area of land-use change from arable to grass has the greatest potential to sequester soil C, and reducing the area of change from grass to arable has the greatest potential to reduce losses of soil C. Across Scotland, simulated changes in soil C from C-rich soils (C content >6%) between 1950 and 2009 is −63 Mt, compared with −35 Mt from non-C-rich mineral soils; losses from C-rich soils between 2000 and 2009 make up 64% of the total soil C losses. One mitigation option that could be used in upland soils to achieve zero net loss of C from Scottish soils is to stop conversion of semi-natural land to grassland and increase conversion of grassland to seminatural land by 125% relative to the present rate. Mitigation options involving forestry are not included here because the data available to calculate losses of soil C do not account for losses of soil C on drainage of semi-natural land.
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