The economic vulnerability of fishing households to climate change in the south Pacific region of Colombia.

Climate change's direct and indirect effects on marine ecosystems and coastal areas mainly impact small-scale fishers, especially in developing countries, which present extreme poverty and high dependency on marine ecosystems as a source of food and sustenance for households. Understanding the vulnerability of fishing households and considering the associated socio-economic-political complexities is essential for preserving their livelihoods and maintaining their well-being. This study proposes a measure of economic vulnerability based on the capacity of fishing households in Tumaco, located on the southern Pacific coast of Colombia, to diversify their livelihoods. Different statistical procedures have been conducted to identify the most relevant strategies in reducing the economic vulnerability of households. The results indicate that reducing the vulnerability of fishing households depends on adaptation strategies such as occupational mobility, some elements of social capital, and reduced dependence on the fisheries resource. This study could constitute an input for creating public policy that guides efforts to achieve strategies for the generation of other livelihoods and the sustainability of fishing households that continue to choose fishing as their main economic activity.

Projecting future changes in distributions of small-scale pelagic fisheries of the southern Colombian Pacific Ocean.

Small-scale fisheries (SSF) contribute to nearly half of global landings and provide multiple socioeconomic benefits to coastal communities. The Pacific coast SSF represents 37% of the total fisheries landings in Colombia. Scientific literature continually shows that tropical marine habitats are most vulnerable to oceanic changes associated with climate change. This study prioritized three pelagic species (Euthynnus lineatus, Scomberomorus sierra, and Cynoscion albus) based on their landing statistics to develop potential current and future species distributions using five ensembled machine learning models including Artificial Neural Network (ANN), Maximum Entropy (MaxEnt), Boosted Regression Tree (BRT), Random Forest (RF), and Classification Tree (CT). Future distributions of these species in the medium-term (2050s) and long-term (2080s) were modeled using the Representative Concentration Pathways (RCP) 2.6 and 8.5 emission scenarios for four ensembled General Circulation Models (GCMs) obtained from the Coupled Model Intercomparison Project Phase 5 (CMIP5). In addition, change detections were calculated to identify contraction and expansion of areas, and the distributional core shift was determined to estimate the spatial movements. Results indicate that E. lineatus and S. sierra will potentially move to deeper waters away from the coastline. Alternatively, C. albus could be a species to potentially gain more importance for the fishing sector due to potential variations in climate. These results constitute a critical scientific basis for evaluating the climate change vulnerability of the fishing sector and the decision-making process in the future of small-scale fishery management in the southern Colombian Pacific Ocean.