4th UF Water Institute Symposium Abstract

   
Submitter's Name Geraldine Klarenberg
Session Name Poster Session: Impact of changing drivers on water resources
Poster Number 7
 
Author(s) Geraldine Klarenberg,  University of Florida (Presenting Author)
  Rafael Muñoz-Carpena,  University of Florida
  Miguel Campo-Bescos, University of Navarra
  Jane Southworth, University of Florida
  Stephen Perz, University of Florida
   
  A spatial and temporal analysis of the relationship between vegetation and hydrology in an area subject to Inter-Oceanic Highway road paving in the SW Amazon
   
  Infrastructure projects such as road paving have proven to bring a variety of (mainly) socio-economic advantages to countries and populations. However, many studies have also highlighted the negative socio-economic and biophysical effects that these developments have at local, regional and even larger scales. The MAP area (Madre de Dios in Peru, Acre in Brazil, and Pando in Bolivia) is a biodiversity hotspot where sections of South America’s Inter-Oceanic Highway were paved between 2006 and 2010. The area has been subject to flooding in 1997 and 2012, and droughts in 2005 and 2010. An exploratory data analysis was conducted in this “MAP” area in order to start understanding the complex socio-ecological dynamics associated with the road construction, particularly from the perspective of ecosystem services provision. The analysis focused on vegetation dynamics as an indicator of ecosystem services, and included data on socio-economic and hydrological variables. Time series of 10 years for vegetation (Enhanced Vegetation Index, EVI) were obtained for 100 communities in the area as the response variable. In addition, 34 socio-economic and physical time series were considered as candidate explanatory variables. Dynamic Factor Analysis (DFA) was applied to disentangle the spatial and temporal links between the explanatory variables and the response variable. DFA is a multivariate time series reduction technique which aims at decomposing the EVI spatio-temporal variance between unexplained variability represented by one (or more) common trend(s), and explained variability represented by the explanatory variables. The outcome of the analysis provides insight into driving socio-economic and/or physical factors of vegetation dynamics in an area subject to road paving. For the purpose of this poster presentation, the vegetation-hydrology linkages and dynamics will be outlined. Overall however, this exploratory research provides a conceptual framework to start linking social and ecological processes mechanistically, contributing to an ongoing NSF-CNH funded project.