ABSTRACT
Recent large hurricanes and earthquakes have demonstrated how vulnerable humanity is to natural disasters. In the United States, the 2017 hurricane season brought destruction to at least three major cities. While these events deserve attention, they can easily overshadow the more subtle events occurring within indigenous peoples-influenced landscapes of Amazonia that impact people and wildlife alike. Even though the magnitude of impacts of events occurring within Amazonia are not the same as hurricanes and earthquakes, droughts brought on by El Niño have created uncertainty and added pressure to indigenous peoples’ food production systems. The overarching goal of this chapter is to explore how freely available spatial data can be used to assess the impacts of natural disasters on the distribution of plant species from which indigenous peoples derive important ecosystem services. We examined the impacts of fire events, primarily triggered by El Niño, on the distribution of five plant species that have strong connections to the livelihoods of indigenous peoples in Guyana. Fire data were obtained from the MODIS sensor and presence data of plant species were obtained in situ from the Rupununi, Southern Guyana. Presence data for the plant species, four trees and one palm, were placed in a Maxent model to develop probabilistic distributions. Fire data were collected for the period 2007–2016 and included two El Niño events, 2009–2010 and 2015–2016, and were used to assess their impacts on the probabilistic distribution of plants. We found that the average probability of a species being impacted by fire did not exceed 20% in any given year, but the majority of fires that had probability of impacting a species distribution greater than 50% occurred in the 2015–2016 El Niño years. Our analysis showed that El Niño-related droughts could have negative implications for the distribution of plants that are critical to the livelihoods of indigenous peoples. The chapter shows that freely available data can be an important part of the toolkit in pre-disaster planning in settings where human populations may be vulnerable to larger global-level weather and climatic changes.
