This project addresses the ecological challenge of invasive species throughout Vermont, initially focusing on Niquette Bay State Park before expanding to the entire state. Using multiple data sources and advanced analytical techniques, including Species Distribution Modeling (SDM) and spatial clustering, the study maps current distribution and predicts future spread under different environmental conditions. Comprehensive analysis and visualization will identify areas at risk and provide information for strategic conservation planning. The project emphasizes the value of adaptive research frameworks in ecological studies and provides insights critical to effective management and decision making in Vermont's ecosystems.

This project addresses the ecological challenge of invasive species throughout Vermont, initially focusing on Niquette Bay State Park before expanding to the entire state. Using multiple data sources and advanced analytical techniques, including Species Distribution Modeling (SDM) and spatial clustering, the study maps current distribution and predicts future spread under different environmental conditions. Comprehensive analysis and visualization will identify areas at risk and provide information for strategic conservation planning. The project emphasizes the value of adaptive research frameworks in ecological studies and provides insights critical to effective management and decision making in Vermont's ecosystems.

This comprehensive study embarks on a spatial analysis to delineate the distribution and ecological impact of invasive species across Vermont. Starting with a focus on Niquette Bay State Park, the scope expanded statewide due to data constraints. Utilizing iNaturalist Vermont data, along with environmental variables from WorldClim and OpenWeather, this project employs Species Distribution Modeling (SDM) to predict the spread of key invasive species under current environmental conditions. This analysis integrates RStudio and GIS techniques to identify hotspots, perform cluster analyses, and visualize the geographic distribution of invasive threats like the Emerald Ash Borer and Hemlock Woolly Adelgid. Keywords: Invasive Species, Vermont, Species Distribution Modeling, Spatial Analysis, GIS, RStudio

This R Markdown document provides a comprehensive guide for the development and implementation of Species Distribution Models (SDMs) specifically tailored to address invasive species in Vermont. Utilizing a combination of environmental data and recorded occurrences, this study aims to predict and understand the potential distribution of these species under various climatic conditions, supporting strategic conservation and management efforts.

This Rmarkdown document provides a comprehensive analysis of invasive species across Vermont, emphasizing the spatial dynamics and ecological impacts of these species. The document begins with an overview of the data sources and methodologies used, including the integration of species occurrence data with climatic and environmental variables from WorldClim and OpenWeather. It details the steps involved in data preparation and analysis using R packages, and the use of GIS for spatial analysis. The core of the document focuses on the spatial distribution of key invasive species like the Emerald Ash Borer and Hemlock Woolly Adelgid. It explores the current distribution patterns, identifies hotspots, and predicts future spreads. Various figures illustrate the geographic spread and density of invasive species across Vermont, highlighting areas requiring targeted management interventions. The analysis employs advanced spatial and statistical techniques, including clustering algorithms like DBSCAN and K-means, to uncover underlying spatial patterns and inform conservation strategies. The document concludes with a transition to Species Distribution Modeling (SDM), anticipating the integration of more detailed environmental data to refine predictions and aid in ecological management.

rough draft proposes) This study investigates the potential distribution of invasive species, specifically the emerald ash borer and the hemlock woolly adelgid, within Vermont’s Niquette Bay State Park, focusing on the impact of environmental variables such as temperature and precipitation on their spread. By analyzing spatial patterns and the interaction between these invasive species and key native flora, the research aims to identify high-risk areas for invasion and assess the ecological effects on the park’s biodiversity. Utilizing data from various sources, including iNaturalist Vermont and environmental databases, and employing tools like GIS and RStudio, the study seeks to create visual aids that facilitate a deeper understanding of the ecological dynamics at play. These efforts are directed towards developing targeted conservation strategies to enhance the ecological resilience of Niquette Bay State Park and the broader Lake Champlain Basin. The study acknowledges potential limitations such as data quality and model accuracy, emphasizing the need for adaptability in conservation efforts.

Exploring Education and Economy in West Virginia West Virginia, situated in the heart of Appalachia, presents a compelling case study for examining the interplay between educational attainment and economic prosperity. In this analysis, I will look into the patterns and disparities that inform policy decisions. Utilizing data from the American Community Survey (ACS), I seek to identify opportunities and barriers shaping the state's trajectory.

A workflow demonstrating how to create a leaflet map with emergency services as point data; presents an interactive visualization of emergency water supplies and services. By using leaflet, sf and other R packages we create informative maps that can be crucial for emergency planning and response.

Exploration of tornado paths in the United States. This project aims to create a detailed visualization of tornado events from 2016 to 2021 by using a combination of tornado paths and point maps to illustrate the impact of these natural events. Then, tornado density was summarized by county and year and visualized through faceted charts from 2016 to 2021. Finally, choropleth maps were created to visualize tornado density using quantile breaks, with variations in the number of classes revealing different interpretations of the spatial distribution of the data. Overall, the project explored different techniques for spatial analysis and visualization of tornado data and demonstrated the capabilities of R in processing spatial datasets.

This R script outlines a comprehensive analysis workflow focused on understanding patterns of invasive species observations in relation to environmental factors such as climate. By integrating, transforming, and visualizing the data, the script aims to uncover insights into how the abundance and distribution of invasive species are influenced by climate variables and temporal changes. Storyline: The overarching story revolves around the investigation of invasive species dynamics over time and across various locations, with a particular focus on how climatic factors such as temperature and precipitation influence these patterns. This analysis seeks to provide ecological insights into the resilience and spread of invasive species in response to environmental conditions, aiding in conservation efforts and the development of strategies for managing invasive populations.