63 research outputs found

    Dynamic model development of enteric methane emission from goats based on energy balance measured in indirect open circuit respiration calorimeter

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    [EN] A dynamic model of methane (CH4) emission in goats was proposed and parameterized from energy balance experimental data. The model focused on dry matter intake and fat content of the diet as explanatory variables for CH4 emission. Experimental and literature data were used to develop the model. Then, data (n = 123) from five energy balance experiments were used to evaluate the model. The model was adequate to represent energy in milk, heat production and CH4 emissions. Residual analysis showed that most of the prediction errors were due to unexplained variations with small mean and slope bias (around zero with exception of CH4; <6%). The model tends to over-predict energy in CH4 at higher energy intake and, energy in milk and heat production at lower energy intake. Random bias was greater than 90%, signifying than more than 90% of the error was non-systematic indicating the mechanism in the model are properly represented. The model is a first step towards a mechanistic description of nutrient use by goats and, useful as a research tool for investigating energy partition in dairy goat systems. The model described in this study should be considered for preparation of enteric CH4 emissions inventories for goats. (c) 2018 The Author. Published by Elsevier B.V.This study was supported by LOW CARBON FEED Project reference LIFE2016/CCM/ES/000088.Fernández Martínez, CJ. (2018). Dynamic model development of enteric methane emission from goats based on energy balance measured in indirect open circuit respiration calorimeter. Global Ecology and Conservation. 15:1-14. https://doi.org/10.1016/j.gecco.2018.e00439S1141

    Challenges towards renewable energy : an exploratory study from the Arabian Gulf region

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    Considering the importance of energy for social and economic development, access to clean, affordable and reliable energy has been adopted as one of the United Nations sustainable development goals that all countries aim to achieve by 2030. However, much of the world's energy is still produced from fossil fuels and thus the progress towards clean and renewable energy is slow. This paper explores the key challenges towards renewable energy in Gulf Cooperation Council countries blessed with plenty of oil and gas reserves. The key challenges identified through literature review were ranked using a quantitative approach through the data collected from a selective sample across the six countries. These challenges in order of importance were found to be policies and regulations, manpower experience and competencies, renewable energy education, public awareness, costs and incentives for renewable energy and government commitment. The findings could be helpful to decision makers and government organisations in the region to develop strategies to overcome these identified challenges

    Toward REDD+ Implementation

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    Models meet data: Challenges and opportunities inimplementing land management in Earth system models

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    As the applications of Earth system models (ESMs) move from general climate projections toward questions of mitigation and adaptation, the inclusion of land management practices in these models becomes crucial. We carried out a survey among modeling groups to show an evolution from models able only to deal with land‐cover change to more sophisticated approaches that allow also for the partial integration of land management changes. For the longer term a comprehensive land management representation can be anticipated for all major models. To guide the prioritization of implementation, we evaluate ten land management practices—forestry harvest, tree species selection, grazing and mowing harvest, crop harvest, crop species selection, irrigation, wetland drainage, fertilization, tillage, and fire—for (1) their importance on the Earth system, (2) the possibility of implementing them in state‐of‐the‐art ESMs, and (3) availability of required input data. Matching these criteria, we identify “low‐hanging fruits” for the inclusion in ESMs, such as basic implementations of crop and forestry harvest and fertilization. We also identify research requirements for specific communities to address the remaining land management practices. Data availability severely hampers modeling the most extensive land management practice, grazing and mowing harvest, and is a limiting factor for a comprehensive implementation of most other practices. Inadequate process understanding hampers even a basic assessment of crop species selection and tillage effects. The need for multiple advanced model structures will be the challenge for a comprehensive implementation of most practices but considerable synergy can be gained using the same structures for different practices. A continuous and closer collaboration of the modeling, Earth observation, and land system science communities is thus required to achieve the inclusion of land management in ESMs
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