Ecological Research

This project centers on the analyses of ecological patterns, particularly on biotic interactions, spatial distribution patterns, environmental factors, and habitat relationships. By applying comprehensive statistical analyses in R, I gain deep insights into ecological dynamics, demonstrating a strong capacity for data science applications, such as predictive modeling and pattern recognition.

Introduction

The study focused on ecological systems, specifically examining invertebrate behavior and interactions within their ecosystems. The goal was to uncover significant patterns that reveal insights into species behavior, population dynamics, and environmental responses. My approach combined field data collection with rigorous statistical analyses, transforming observational findings into impactful scientific knowledge.

This ecological project highlights the power of data-driven techniques to advance our understanding of complex biological systems. By integrating fieldwork and robust statistical analysis, I was able to derive valuable ecological insights that demonstrate skills applicable to a variety of data science fields, including environmental modeling, predictive analytics, and systems analyses.

Data Acquisition

Data collection was conducted in both field and laboratory settings. My field work is heavily based on scientific SCUBA diving. I primarily utilized the following methods:

Data Analyses

A majority of the data I work with is used to test hypotheses, where I apply statistical tests to find differences between groups. I also use statistical tests in complex models to identify trends and patterns in large datasets, such as behavioral and environmental data. I analyze the relationships between ecological parameters using statistical methods and then model them to find the best solutions. Some of the key statistical methods I use include:

Descriptive Statistics

Inferential Statistics

Publications

Journals

Conference Contributions

Other Contributions