Abstract:
Since their origins, human beings have transformed their surrounding environment. These transformations have varied in both spatial and temporal dimensions, being especially intensive as mankind invented the agriculture and established in settlements. However, despite the long history of human interactions with the physical space, the impact of these transformations in the human surroundings and particularly over the biodiversity have been studied only recently from a scientific perspective, and under the lens of landscape and community ecology. Community ecology is the branch of ecology that studies the distribution and abundance of assemblages (Morin 2011). Within this field, diversity patterns have been a main research interest (Maurer and MacGill 2011). Since the XIX century, naturalists like Alexander von Humboldt, Charles Darwin and Alfred Russel Wallace noted and described the differences in species number of the different places they visited and studied around the globe, starting to unveil some global diversity patterns. During the XX century, with ecology established and developed as a formal discipline, the study of the patterns and processes regarding the differences in distribution and abundance of species around the world started (Pianka 1966). During the second half of the XX century, several analytical tools were developed to account for and measure species diversity (Hubalek 2000). The English mathematician Alan Turing made great advances in information theory during the first half of the XX century, while decoding top German messages during the World War II, and therefore funding the basis of information theory (Chao and Jost 2012). Later, ecologists borrowed these informatic theoretical advances to express the diversity of ecological communities: for instance, they started to use the Shannon-Wiener entropy to quantify it. Since then, some popular and widely used diversity measures were species richness, entropies and Hill numbers or true diversity. Although they are mathematically distinct, all are calculated by using two basic community data: 1) Number of species and 2) Abundances (Gotelli 2008).
