Posted on ثلاثاء, 25 سبتمبر 2018, 09:38
Deadline on خميس, 06 ديسمبر 2018, 23:00
The International Plant Protection Convention (IPPC) Secretariat is calling for Trade Cases on pest risk management to improve negotiations over market access. Selected Trade Cases will receive support in implementing pest risk management decision support tools for export commodities, as part of the project “Rolling out Systems Approach Globally", which is funded by the Standards and Trade Development Facility (STDF) and implemented by the IPPC Secretariat, in collaboration with the Centre for Environmental Policy, Imperial College London (ICL). Trade Cases involving pest risk management for imports, and pathways, will also be considered.
Deadline: 7 December 2018
Who can apply?
National Plant Protection Organizations (NPPOs), Regional Plant Protection Organizations (RPPOs) and regional plant health entities wishing to strengthen pest risk management capacities of developing countries to improve market access in specific high-priority trade cases.
While guidance and support in implementing the pest risk management decision support tools will be provided, applicants will be expected to provide human resources to carry out the actual work.
How to apply
Applicants should complete the Trade Cases template available (in English) at: https://www.ippc.int/en/publications/86476/
The complete Trade Cases should be submitted to:
• Ms Ketevan Lomsadze, IPPC Secretariat Implementation Facilitation Officer ([email protected])
• With copy to : Ms Megan Quinlan, ICL ([email protected])
The deadline is 7 December 2018.
The nominations will be reviewed by the project steering committee and selections will be made based on:
• the characteristics of the Trade Case (e.g. complexity, disagreement between trade partners, use of Systems Approach, need for equivalent measures);
• the commitment of the applicant group to progressing the trade proposal through to negotiation, in an evidence-based and systematic manner;
• written evidence that the applicant understands and commits to provide the human resources (staff time) needed to carry out the in-country work required as part of this trade case, in collaboration with external partners providing guidance and support to this project;
• diversity of countries covered (geographic area, development status) and type of Trade Cases.
Only the representatives of the selected Trade Cases will be contacted by the IPPC Secretariat once the nomination has been confirmed. Your submissions are welcome and we look forward to having a fruitful exchange of experiences in disseminating the Beyond Compliance tools.
The selected Trade Cases will become part of the project “Rolling out Systems Approach Globally", which is funded by the Standards and Trade Development Facility (STDF) and implemented by the IPPC Secretariat, in collaboration with the Centre for Environmental Policy, Imperial College London (ICL).
This project aims at adapting and introducing a series of decision support tools. The tools can be used by NPPOs to design and evaluating risk management plans for trade in agricultural products that may be associated with pests, and are thus considered a source of pest risk.
The Beyond Compliance tools, developed under another STDF-funded project (STDF/PG/328), provide practical support to improve pest risk management for plant health needs in trade. The tools range from a set of questions to consider when meeting stakeholders, to advanced probabilistic modelling and Bayesian Networks, which will allow the participants to:
• Organise existing knowledge and data
• Better understand the value of each measure in a system, in particular for Systems Approach (ISPM 14), and where redundancy is valid or restrictive
• Estimate the impacts of risk management measures on pest risk, even when empirical data may be lacking
• Enhance the competency and confidence of NPPOs in market access negotiations
An eBook about the development and use of these tools can be found at: www.standardsfacility.org/sites/default/files/Beyond_Compliance_eBook.pdf