Page History

...

1. Scope - other carbon sinks (e.g. trees), GHGs emissions (e.g. emissions from livestock) and opportunities for avoided carbon loss
2. Mitigation co-benefits (e.g. water and biodiversity conservation)
3. Accuracy needs and tolerance for uncertainty
4. Risk of impermanence (e.g. adoption of practices or events that may reduce soil C stocks) and non
5. Non-performance (e.g. unexpected practice effect) 
6. Scalability
7. Reporting requirements - given the timing to detect changes (e.g. usually > 5 years) and make payments.
8. Verification needs (e.g. 1^stfirst, 2^nd and 3^rd Partysecond and third-party)
9. Costs (e.g. acceptable % of the total project budget)
10. Ensure benefits to farmers 

...

1. Developing practice-based indicators (e.g. scientific literature review and experts consultation)
2. Using models - chosing choosing a model, technical requirements, caveats, assumptions and uncertainties  
3. Hybrid approach: direct measurements with modeling/remote sensing. 
   1. Optimal measurement strategy based on project/region characteristics and resources available (e.g. how to focus on few high-quality measurements)
      1. prioritization if needed (e.g. sampling design; soil C or bulk density; soil C determination using routine analysis or dry-combustion; use of pedotransfer functions)
   2. Dealing with data gaps (e.g. scietific scientific literature, experts consultation, global databases) 
   3. Chosing Choosing a model, model calibration, technical requirements and acceptable uncertainties
   4. Co-benefits assessment (e.g. generating water/biodiversity indicators from/in conjunction with soil C measurements)
4. Aggregation aspects across larger scales to reduce project-level variation effects 
5. Setting up baselines (e.g. Baseline v. base year)

...