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DocumentInternational Workshop of the Knowledge Action Group of the Global Alliance for Climate-Smart Agriculture. Workshop Report
Montpellier, France, March 15, 2015
2015Also available in:
No results found.This report summarizes the proceedings of the “International Workshop of the Knowledge Action Group,” held in Montpellier, March 15th, 2015, organized by CCAFS, FAO, and CIRAD. The workshop brought together participants from Governments, research institutions, farmer organizations, civil society organizations, and the private sector to determine the knowledge priorities for Climate-Smart Agriculture and partnerships to make these priorities possible. The priorities and outputs identified at the workshop formed inputs into the Knowledge Action Group’s work plan for its inception year. The workshop provided background on the role that the Global Alliance for Climate-Smart Agriculture plays in developing a knowledge base for Climate-Smart Agriculture, and provided participants insights into how the Knowledge Action Group of the Alliance is governed and its activities to date. Discussions at workshop focused on the five priority work areas of the Knowledge Action Group (1. technical interv entions and practices in CSA; 2. evidence base of CSA; 3. support, services and extension for CSA; 4. inclusive knowledge systems for CSA, and 5. integrated planning and monitoring for CSA). Participants identified the priority outputs for the inception year and partnerships to achieve these outputs. The workshop provided a platform for participants to share ideas, knowledge, approaches and resources, fostering stronger partnerships between organizations. -
Book (stand-alone)International Workshop on Socio-economic Impacts of Genetically Modified Crops co-organised by JRC-IPTS and FAO: Workshop proceedings 2012
Also available in:
No results found.The report provides proceedings of the “International workshop on socio-economic impacts of genetically modified (GM) crops”, which was co-organized by FAO and the European Commission's in-house science service, the Joint Research Centre (JRC), in Seville, Spain on 23-24 November 2011. The objective of the workshop was to review for policy makers the main findings of scientists who are active world-wide in the field of socio-economic assessment of the impacts of GMOs in the EU. -
DocumentThe effects of ignoring clustered data structure in allometric biomass models on large forest area biomass estimation
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.The aim of this study was to assess the effects of ignoring the clustered data structure on large area biomass estimation, when model uncertainty is included or not in the biomass prediction process. We used a Monte Carlo error propagation procedure to combine the uncertainty from allometric model predictions with the uncertainty from plot-to-plot variation, to produce estimates of mean AGB per hectare and standard error of the mean. An alternative procedure that ignores model prediction uncertainty was also used, therefore, showing only uncertainty due to differences between plots. Ignoring the clustered data structure, (i.e., fitting allometric models using ordinary least squares), the estimates of mean biomass per hectare were approximately 11% less than the estimates based on mixed effects models (that accounted for the clustered data structure), regardless of including or not the model prediction uncertainty. The estimates of uncertainty were also affected by ignoring the clustered data structure. When including model prediction uncertainty, ignoring the clustered data structure resulted in underestimation of standard error by 30%, whereas when model uncertainty was not included, the underestimation was 13%. Therefore, ignoring the clustered data structure, may affect both, the accuracy and the precision of biomass estimations over large forest areas. Keywords: Monitoring and data collection, Climate change ID: 3616826
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