Influence of sample size and frequency of observations on the relationship between phenological patterns and climate

• Grant number: 13/11978-1
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: August 01, 2013
• End date: July 31, 2014
• Field of knowledge: Biological Sciences - Ecology - Ecosystems Ecology
• Principal Investigator: Leonor Patricia Cerdeira Morellato
• Grantee: Nathalia Bonani
• Host Institution: Instituto de Biociências (IB). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil

Abstract

Phenology is the study of the occurrence of recurrent biological events in a given species or group of species and their relationship to biotic and abiotic factors. Phenological studies have been conducted to improve the understanding of ecosystem dynamics. In the context of current climate change, phenology has gained importance as a tool for monitoring and detect these changes, and as an important indicator, since changes in phenology have far-reaching consequences for ecological systems. However, the lack of standardization of methods to carry out the phenological research hampers accurate comparisons among studies and their interpretation. Phenological cycles of tropical plants are complex, and many irregular patterns are difficult to recognize. Therefore, it is crucial to conduct studies that address the methos to collect and analyse phenological data. The present study aims to investigate how the sample size and frequency of observations affect the definition of seasonal patterns, the relationship with climatic factors and their interpretation in plant phenology. We analyze the phenological patterns of three species of trees planted on the campus of UNESP, Rio Claro, SP, for changes in vegetative and reproductive phenology over eight years. Observations are weekly and we phenological evaluatinon takes into account the intensity index Fournier and activity index or percentage of individuals. The analysis will be made using correlation tests, regression and circular statistics.