Past Research

I worked on the development of biodiversity assessments in the context of biodiversity offsets to meet BBOP and IFC standards. I developed preliminary analysis for the Donoso District in Panama, and the Dominican Republic. For these assessments, I modeled the distribution of different species of concern and evaluated land cover change in the region to assess potential biodiversity impact of BAU scenarios of deforestation, as well as potential benefits of new protected areas (Sangermano et al. 2015a, Sangermano et al. 2015b). 

Land cover change is one of the most important threats to global biodiversity and ecosystems services. This area of research has grown immensely in the past few decades, in order to understand how landscapes are changing and how these changes may affect the provisioning of ecosystems services for future generations. Much of my work has been the analysis and modeling of land cover changes, and the evaluation of biodiversity impacts. 

I participated as a research assistant in the Southern Yucatan Peninsula Region Project (SYPR), which main objective was to understand human- environment interactions such as land cover change in the southern Yucatan. A main component of this research was the development of a detailed land cover map of the region through remote sensing (Schmook et al. 2011), and the analysis of the impacts of land cover change on habitat and biodiversity (Vester et al. 2007). 

I have also been involved in the development of the Land Change Modeler for Ecological Sustainability (LCM), a project in partnership with Conservation International. Resulting tools facilitate the analysis of land cover change and biodiversity impacts, and are currently included in the IDRISI GIS software. These tools are currently being used globally for the analysis of land cover change and for the assessment of REDD projects (Reduced Emissions from Deforestation and Forest Degradation.

Included in LCM, and as part of a project funded by the Gordon and Betty Moore Foundation (GBMF) and Google.org, I developed a new algorithm (called SimWeight) to relate historical land cover changes to driver variables of change, in order to produce land cover change vulnerability maps (Sangermano et al. 2010). These maps of changes are  essential components in REDD projects. 

I have also investigated the potential of “win-win” REDD projects in the Bolivian Amazon region, where both Carbon sequestration and biodiversity protection could be maximized (Sangermano et al. 2012). In this work I evaluated historic land cover changes in the Bolivian Amazon and projected land cover change scenarios to the year 2050, in order to evaluate how these changes will affect carbon emissions, and the distribution of endemic mammals, amphibians and birds. Current network of protected areas were then assessed to evaluate the potential for simultaneous protection of biodiversity and Carbon in the region. This work highlighted the importance of evaluating biodiversity when generating REDD projects, as otherwise biodiversity protection would not be guaranteed by this offset mechanism. 

Global environmental change also includes changes in other aspects of the earth system, such as climate change. Related to this, I have participated in the development of a set of tools within IDRISI - called the Earth Trends Modeler- for the analysis of image time series (eg satellite images), aimed to the  understanding and monitoring of changes in the earth system.  In particular I was involved in the development of a novel method to evaluate phenological changes (Eastman et al. 2009). Phenology is the study of biological periodic events (such as the emergence of flowers, migration of birds or egg hatching), climate change may cause changes in these cycles, disrupting ecological cycles and ecosystems functioning. 

My research also focuses on species distribution modeling (SDM) to study the impacts of climate change on biodiversity.

As part of my Ph.D. dissertation I developed a framework for inferential monitoring of the impact of global change on biodiversity. I used remotely sensed climate and environmental data, and species distribution modeling techniques, to map species vulnerability to climate change.

For this research I generated a methodology to refine species geographic ranges (Sangermano and Eastman, 2012), which allowed the refinement of 6500 species ranges of mammals, amphibians and birds  throughout  South America. The refined species distribution maps were used to study the importance of climate variables in the delimitation of the range of species, and to generate maps of species vulnerability to climate change in South America.

I have also applied GIS and remote sensing technologies to study invasive species and infectious diseases, which are in rapid increase due to globalization and climate changes. I have collaborated in with the Biology department at Clark University, and the Bermuda Ministry of Health to evaluate the use of species distribution models for the prediction of mosquito infestations in Bermuda Island, in the context of prevention of infectious diseases such as Malaria and Dengue fever (Khatchikian et al. 2010). I also participated in a project in conjunction with the USDA – APHIS program where we developed an infestation risk map of Gypsy Moth (Lippitt et al. 2008). This research helped USDA in the planning and management of monitoring sites for Gypsy Moth across the United States.