Analytical Framework for Forest Gap Gradient Effects on Tropical Species Abundance

Problem

Forest gaps alter microhabitat structure and resource availability, potentially affecting the abundance of tropical species. Understanding these changes requires a robust statistical approach capable of testing abundance responses along a continuous gradient.

Goal: Develop an analytical framework using generalised linear models (GLMs) to quantify abundance changes for tropical species across forest gap gradients.

Approach

• Collaborated with field ecologists to integrate survey data from multiple forest sites spanning gap size and position.
• Applied GLMs with appropriate error structures to model species abundance as a function of gap-related covariates (e.g., gap size, distance to edge).
• Assessed significance of trends, controlled for site-level variability, and validated models through residual diagnostics.

Stack

• Statistical modelling: GLMs for abundance–gradient relationships.
• Data workflows: data cleaning, exploratory analysis, model validation.
• Implementation: performed entirely in R, with reproducible scripts for all analytical steps.

Results

• Quantified abundance responses for multiple species, revealing both positive and negative trends along gap gradients.
• Provided effect size estimates and confidence intervals to guide ecological interpretation.

Impact

• Supplied a reproducible analytical framework for assessing habitat gradient effects on species abundance.
• Results contributed directly to the publication and interpretation of forest gap ecology in tropical systems.

Links & Resources

• 📄 Paper: Ecologica Montenegrina article

Role

• Designed and implemented the analytical framework.
• Conducted all GLM analyses and model validation.
• Interpreted statistical outputs in ecological context.
• Contributed to manuscript preparation.