| Abstract Detail
Biodiversity Informatics & Herbarium Digitization Meek, Jared [1], Eaton, Deren [2]. `mountaineer`: a Python package to explore mountain plant biodiversity using open-source and remotely-sensed data. Mountain regions are among the most biodiverse hotspots on earth, harboring endemic plant species, novel evolutionary insights, and natural resources. Although most mountain systems remain relatively undeveloped, human activities - such as resource extraction, livestock grazing, habitat destruction, and climate change - heavily influence these ecosystems. Mountain plant species are especially susceptible to these disturbances because they have limited space to escape increasing temperatures and loss of habitat. However, the rate and scale of ecological change in mountain plant communities is outpacing our ability to study these processes with traditional methods. Fortunately, large, open-source databases are revolutionizing the scale at which ecological and evolutionary research is done. `mountaineer` is a new software package that applies the power of the Global Biodiversity Information Facility, Google Earth Engine, and other climate and geospatial databases to visually explore and compare biodiversity, ecology, and evolutionary processes in mountains across the world. With this package, users can select a mountain region of interest, download occurrence records within the region for any taxonomic rank, extract environmental data, and produce interactive maps with remotely-sensed geospatial variables. By combining these open-source databases, `mountaineer` allows researchers to explore and quantify the effects of climate, topography, and land-use change on mountain biodiversity with greater urgency.
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1 - Columbia University, 1200 Amsterdam Ave, New York, NY, 10025, United States
2 - Columbia University, Ecology, Evolution, And Environmental Biology, 1200 Amsterdam Ave. , Schermerhorn Ext. Office 1007, New York, NY, 10027, United States
Keywords:
alpine
Montane
remote sensing
landscape analysis
spatial analysis
climate change.
Presentation Type: Poster
Session: P1, Biodiversity Informatics & Herbarium Digitization Posters
Location: Virtual/Virtual
Date: Monday, July 19th, 2021
Time: 5:00 PM(EDT)
Number: P1BI009
Abstract ID:1018
Candidate for Awards:None Canceled |
