The effect of long-term climatic variability on wild mammal populations in a tropical forest hotspot: A business intelligence framework

Abstract

Anthropogenic climate change has emerged as a new threat to biodiversity over the last decades. It affects climate systems such as El Niño Southern Oscillation (ENSO) with possible impacts on mammal populations due to changes in local climate. Since this issue had not been addressed in any previous work, the main contribution of this research was the development of a Business Intelligence (BI) system which significantly supports the analysis of patterns in the variation of the population of small mammals in the tropical forest and its response to ENSO phenomenon. In this sense, a Data Warehouse (DW) and Online Analytical Processing (OLAP) tool were built to support the analyses of the data amassed by a 22-year monitoring study of small mammal populations in a highly threatened biodiversity hotspot, the Atlantic Forest. The BI system was applied for three purposes: evaluating the population size trends throughout time, analyzing the relationship between ENSO events and local weather, and evaluating the effects of the most intense ENSO events on the population size of a small, endemic marsupial, Marmosops incanus. The data exploration started by the interactive and visual analyses of the BI dashboards, followed by a statistical analysis which confirmed some trends observed in the dashboards. Very strong and strong La Niña episodes reduced the average temperature and increased precipitation in the study area. These changes affected the population of M. incanus with a reduction in population size in short-term (4 and 6 months) as well as long-term (24 months), indicating the negative effects of reduced temperatures on the population dynamics. Since this BI system is available to the scientific community, we believe that it can stimulate further studies involving the relationship between the population dynamics of other Atlantic Forest species and changes in local and global climate.