Using Remote Sensing data to understand drivers of genetic and functional diversity in the Atlantic Forest of Brazil

Maria Strangas, City College of New York, mariastrangas@gmail.com (Presenter)
Kyle McDonald, The City College of New York, kmcdonald2@ccny.cuny.edu
Thiago Silva, UNESP, Rio Claro, Brazil, tscanada@gmail.com
Ana Carnaval, City College of New York, acarnaval@ccny.cuny.edu

In this study, we apply satellite-derived data to address hypotheses on the the spatial and environmental drivers of genetic and functional diversity in a montane, tropical lizard. We employ a landscape-genetics framework by generating effective distances between individuals through various present-day dispersal resistance surfaces and assessing the correlation of effective distance with genetic, morphological, and physiological distance across the species' range. We find an important role of landscape heterogeneity in shaping patterns of gene flow over time, and thus structuring genetic diversity within the species. However, landscape features poorly predict spatial patterns of functional diversity. To better incorporate thermal variables into these analyses, we are also generating layers of ground temperatures throughout the study region. For this, we are integrating temperatures from dataloggers on the ground with MODIS Terra MOD11A2 surface temperature data. Our approach exemplifies the utility of remote sensing data in identifying important drivers of biodiversity in the tropics, particularly at fine spatial scales.

Presentation Type:  Poster

Session:  Theme 1: Tracking habitat change through new integrative approaches and products   (Mon 1:30 PM)

Associated Project(s): 

• McDonald, Kyle: Vegetation Phenology Assessment Using Satellite Radar Remote Sensing: Global Monitoring of Daily and Seasonal Changes in Canopy Structure and Water Status ...details

Poster Location ID: 52