Results from the Summer 2022 Undergraduate Forestry Data Science Program
Date:
Product demonstration of an RShiny website we developed as part of the Harvard Undergraduate Forestry Data Science program in collaboration with our stakeholder NCASI. Here we combine CMIP5 and CMIP6 large ensemble climate data with forestry data to model how changes in climate are expected to impact tree species distributions. We particularly focus on user experience and interactivity alongside developing graphics that contain measures of uncertainty while still being accessible to an audience with a wide range of statistical acumen.
Presentation
Maxwell Vanlandschoot and I present results from our 6-person research group at the US Forest Inventory and Analysis Fall meeting in November 2022. We presented a demonstration of an application we produced with NCASI (see portfolio) and highlighted the other 4 projects that the team tackled. A short slide deck we will use for this presentation can be found here.
Abstract
Over the last 4 years, the Undergraduate Forestry Data Science effort has proved to be a very effective way to engage diverse and talented undergraduate students from multiple universities in forest inventory applications. Each summer students in this growing program conduct research motivated by FIA researchers and data users. In this presentation, we will summarize the summer 2022 projects. These projects include a comparative study of various model-assisted estimators, an exploration of zero-inflation models for estimating forest parameters over small regions, the creation of a watersheds estimation dashboard to inform new precision targets for FIA small area estimates, the enhancement of a climate projection analysis tool, and the construction of a tool to share carbon accounting estimates and their standard errors.