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Assessments of fisheries by‐catch on marine megafauna are important for developing effective management strategies. For sea turtles, impacts may be evident in nesting population trends, but generally only after a lag, as turtles are slow to mature. We examined 850 loggerhead turtle (Caretta caretta) by‐catch samples collected over 14 years throughout the western North Atlantic to identify source nesting populations. We identified proportions of turtles from 19 distinct management units (MUs), using mitochondrial DNA and mixed stock analysis, considering population size. We found a significant split in the distribution of small versus large loggerheads to the north and south of Cape Hatteras, North Carolina (latitude 35°N). North of Cape Hatteras, large turtles came from south‐east Florida (SEFL; 44% ± 15%) and the northern United States (33% ± 16%) MUs, while south of Cape Hatteras, the major contributors were Central East Florida (52% ± 20%) and south‐east Florida (SEFL; 41% ± 20%). Small turtles in the north came from Central East Florida (64% ± 14%), and in the south, south‐east Florida had the highest representation (56% ± 25%). There was little contribution from Mediterranean and Cape Verde populations, indicating low risk from western North Atlantic by‐catch to MUs in the Mediterranean. Understanding where threats may impact source populations is important, particularly for larger size turtles, as these individuals have the highest reproductive value. These findings allow more informed threat assessments to be conducted for loggerhead turtles considering spatial and demographic structure.

To further develop and finalize the Fishery Performance Indicators (FPIs) for scaling up to the Bank's entire fisheries portfolio, a number of specific pilots and case studies have been conducted. This report provides an overview of the FPIs, and a summary of two case studies in its application, the blue swimming crab (BSC) fisheries in Indonesia and the Philippines. A comparative analysis with an Icelandic lobster fishery is conducted as a benchmark, as the Icelandic lobster fishery is also export oriented and has been recognized as a well-managed fishery. The study is organized as follows: chapter two provides a brief introduction of FPIs and the blue swimming fisheries in Indonesia and the Philippines. Chapter three presents the results for FPIs that measure the success ('outputs') in achieving the 'triple bottom line' of environmental, social, and economic sustainability and provides a critical evaluation of strengths, weaknesses, and omissions of the current FPIs design. Chapter four presents the results for FPIs that measure factors ('inputs') that enable (or undermine) the likelihood that the triple bottom line will be achieved and provides a critical evaluation of strengths, weaknesses, and omissions of the current FPIs design chapter five summarizes the results and draws conclusions about the applicability of FPIs and next steps. Five appendices provide supplementary information. Appendix A provides detailed explanation of the rationale and measurement for each indicator. Appendix B lists additional suggested indicators based on the case studies. Appendix C lists the participants who have attended the workshops in London and Hawaii. Appendixes D and E illustrate the FPIs' output and input results for the studied fisheries, respectively.

Floods are a major source of risk for the agricultural sector. Flood risk in the agricultural sector primarily arises from river flooding, flash floods, and coastal flooding. The impacts of floods can result in sizable agricultural damages at the local level. Floods in agricultural zones expose agricultural producers, agricultural supply chains, rural financial institutions (such as agricultural banks), and governments to financial risks due to the loss of crops, delinquency on seasonal production loans, damage to infrastructure and loss of public revenues. The costs associated with these damages are often absorbed by households directly or governments that provide compensation to agricultural producers in the aftermath of catastrophic flood events. Rural financial institutions also absorb the cost of floods through loan rescheduling or, in catastrophic cases, loan cancellation. In many developing countries, floods are dealt with in a reactive, rather than proactive, manner and little is done to be financially prepared for a catastrophic outcome of floods. Going forward, government and donors can play an important role to facilitate the development of risk spreading mechanisms in general and agricultural flood insurance in particular. First, this includes investment in the generation of public goods to support disaster risk reduction and recovery, risk management, and ultimately insurance applications. Second, awareness building and risk education are essential for better risk management and insurance. In that vein, identifying and assessing flood risk is critical first steps. Third, many of the technologies described here have applications beyond insurance, including for better planning, risk reduction, early warning, and disaster response. Insurance can complement such activities, but is only viable if carried out jointly as part of a broader risk management framework. Fourth, more research and technical assistance is needed to develop simple and financially viable products for flood risk transfer at aggregate levels; there is increasing demand expressed for such products from flood-prone countries. Finally, donors and government can support international and regional centers involved in flood modeling and facilitate a platform that convenes the technical expertise required for flood risk insurance development. Several of such centers and core expertises were identified through this work.