Predicting the impacts of climate change on the distribution and conservation of endemic forest land snails of Madeira Island

Climate change is emerging as one of the major threats to natural communities of the world’s ecosystems; and biodiversity hotspots, such as Madeira Island, might face a challenging future in the conservation of endangered land snails’ species. With this thesis, progresses have been made in order to properly understand the impact of climate on these vulnerable taxa; and species distribution models coupled with GIS and climate change scenarios have become crucial to understand the relations between species distribution and environmental conditions, identifying threats and determining biodiversity vulnerability. With the use of MaxEnt, important changes in the species suitable areas were obtained. Laurel forest species, highly dependent on precipitation and relative humidity, may face major losses on their future suitable areas, leading to the possible extinction of several endangered species, such as Leiostyla heterodon. Despite the complexity of the biological systems, the intrinsic uncertainty of species distribution models and the lack of information about land snails’ functional traits, this analysis contributed to a pioneer study on the impacts of climate change on endemic species of Madeira Island. The future inclusion of predictions of the effect of climate change on species distribution as part of IUCN assessments could contribute to species prioritizing, promoting specific management actions and maximizing conservation investment.

A model to screen and improve business potential of micro and small enterprises in developing countries: Evidence from the Island of Mozambique

Programmes supporting micro and small enterprises in developing countries have been showing that capital is not enough to allow business success: survival and growth. Literature does not provide comprehensive and practical tool to support business development in this context, but allowed the collection of forty-nine success variables that were studied in a sample of successful and unsuccessful businesses in the Island of Mozambique to discover what were the key factors affecting those businesses’ performance. Empirical data gave the insights for the development of a model to screen and improve business potential of micro and small enterprises in this context.