Type: User
Company: Chicago Botanic Garden
Bio: I use data science to make scientifically informed land management decisions by synthesizing field surveys, remote sensing, museums specimens, & genetics data.
Location: Western North America and Chicago
Blog: https://sagesteppe.github.io/
sagesteppe's Projects
Using Species Distribution Modelling and connectivity analysis to inform restoration germplasm developement endeavors in Western North America.
Tools for estimating the mass required to achieve an operational Seeds of Success collection.
Estimating the initiation of flower, peak flower, fruit maturation, and fruit dispersal using herbarium specimens to inform wildland seed collection in the Western United States.
Scripts for informed scouting of native populations for restoration
One hour talk for Seeds of Success Great Basin Ecoregional Training
R4DS Spatial Lecture materials for Northwestern University
Github repository for code and lecture notes associated with the RMBL 2020 Spatial Data Science Webinar Series
this is the presentation for my masters thesis defense
Palettes, plots templates, and some css for UFO RMP followup report.
Scripts to help create tables for humans to classify large amounts of ESDs retroactively
Interim reporting throughout the life of the sample design, and analysis of nearly all indicators without weight
This repository contains the code to assemble all Chapters of the AIM project into a final document. It also contains a loose guide to the R scripts and data we used for ths project.
This script serves to compare the NOC values of bareground from a terradat summary to the benchmarks from the Reference Sheet of an ESD. These values are present in all completed reference sheets, and provide a minimial vegetation benchmark reference which may be implemented by all.
Compare expected vegetation cover between ESGs and ESDs
calculating SPDI, and SPEI using R
Track and report the status of ESD completion in a field office.
Indentifying common noxious weeds, impacted ecological sites, and trends in their distributions from AIM data
Scripts for estimating natural variation of Plant Diversity, mostly alpha - species richness, from Ecological Sites
Analysing soil surface pedon stability, and contextualizing information regarding canopy cover and biocrusts
These two scripts 1) perform a k-means clustering, and follow up manual assignment of field data to classify vegetation plots into 4 strata. A second script utilizes Random Forest and an 12 band raster to classify the area of study.
All of the inferential statistics for the 5 year write up are carried out in this repository and written to be used for different chapters of writing.
This helps one recover the weights for an AIM analysis
Making slides, mostly maps, for Seeds of Success talk for the CBG USFS interns 2023