Currently, the Galapagos sea lion (GSL, Zalophus wollebaeki) and Galapagos fur seal (GFS, Arctocephalus galapagoensis) are among the most important endemic species for conservation in the Galapagos Archipelago. Both are classified as “Endangered” since their populations have undergone drastic declines over the last several decades. In this study we estimated the abundance of both otariids, and their population trends based using counts conducted between 2014 and 2018 in all their rookeries, and we analyzed the influence of environmental variability on pup production. The GSL population size in 2018 in the archipelago was estimated to be between 17,000 to 24,000 individuals and has increased at an average annual rate of 1% over the last five years after applying correction factors. The highest number of GSL counted in the archipelago was in 2014 followed by a population decline of 23.8% in 2015 that was associated with the El Niño event that occurred during that year. Following this event, the population increased mainly in the northern, central and southeastern rookeries. The GSL pup abundance showed a decreasing trend with the increase in intensity of the El Niño. The GFS population in 2018 was counted in 3,093 individuals and has increased at an annual rate of 3% from 2014 to 2018. A high number of GFS counted in 2014 was followed by a population decrease of 38% in 2015, mainly in the western rookeries. There was interannual population fluctuations and different growth trends among regions of the archipelago. GSL and GFS pup abundance has a strong decreasing tendency with the increase in the subthermocline temperature (ST) and the El Niño 1 + 2 index. Our results provide evidence that both species are highly vulnerable to periodic oceanographic-atmospheric events in the Galapagos Archipelago which impact prey abundance and the flow of energy in the unique Galapagos ecosystem.
A complex learning process (CLP) is understood as the result of the dynamic and unanticipated integration of diverse pedagogical approaches in a learning process, based on the collaboration between instructors and learners. Educational modeling languages are used to specify and design learning processes that can be adaptable to the demands of a particular pedagogical context. Based upon IMS service-oriented architectural principles, a framework for learning process composition and execution is presented. The objective of that framework is to enable the dynamic and unanticipated composition of distributed learning services. This is guided by a case study of how this framework can be implemented in a complex learning scenario.
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