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Using Open Source Data to Identify Conservation Priorities at Large Spatial Scales

Data can be downloaded in a variety of formats (the GBIF data is in .csv and needs to be modified and the NASA data is HDF4) and can be used by any software package that can analyze spatial data (such as ArcMap, R, Python, etc.)
Date created
We are in the middle of the sixth mass extinction, due in part to the intensification of human land use. Therefore it is vital to quickly and effectively identify species at risk of extinction if we are to save them. The effects of human land use can extend beyond habitat loss by severing gene flow between subpopulations, making them more susceptible to inbreeding depression. These genetic effects have a negative impact on species viability and need to be considered in long-term conservation planning. One way to address this is by assessing the vulnerability of populations that are unable to reproduce with one another due to habitat fragmentation. In this study we used open source satellite imagery and species occurrence data to create a method for assessing the vulnerability of subpopulations of species. We selected ten focal species of Quercus found in Japan to develop this methodology and were able to identify four subpopulations that are likely threatened. With these data, we were able to identify local gardens and protected areas best situated to aid these subpopulations. Our methods use open source data and do not require costly field expeditions. Thus, this methodology can aid conservationists, who are often limited by cost or location, in quickly assessing the state of a species and the viability of its subpopulations.
Subject - keywords and LC headings
Conservation of natural resources
Related Entities
Casmey, Mariah (is local contact/expert)
Carrero, Christina (is local contact/expert)
Beckman Bruns, Emily (is local contact/expert)
Westwood, Murphy (is local contact/expert)
Global Biodiversity Information Facility (is related to)
National Aeronautics and Space Administration (NASA) (is related to)
Spatial Coverage