A unified model explaining the unimodal relationship between productivity and species richness in fish communities

Understanding the productivity–diversity relationship is central in ecology. While hypotheses exist for explaining positive and negative monotonic trends, they never have been combined into one model to account for hump-shaped patterns. Here, we propose a unified model integrating the more-individuals, biomass-driven competition, and environmental filtering hypotheses. Analyzing fish communities along a eutrophication gradient, we reconstructed the observed hump-shaped curve between productivity and species richness. Two productivity-related variables explained richness: community size (positive effect) and zooplanktivorous fish biomass (negative effect). Zooplanktivores, overly favored by high productivity, likely competed with juvenile stages of other species for zooplankton, leading to species exclusions. This offers rare evidence for intensified species interactions along a productivity gradient in animal communities. Competition-driven loss thus precedes stress-induced losses (e.g...., , # A unified model explaining the unimodal relationship between productivity and species richness in fish communities

Dataset DOI: [10.5061/dryad.pg4f4qs1r](10.5061/dryad.pg4f4qs1r)

## Description of the data and file structure

**README — Unimodal, JBE, Covariance Analyses (Figures 3–5)**

This repository contains scripts and data required to reproduce Figures 3–5 from the manuscript. The analyses cover:

1. Unimodal and linear regression of fish community metrics versus environmental and productivity predictors (Figure 3).
2. Nested regression modeling of productivity–richness relationships (Figure 4).
3. Covariance tests across biomass gradients for different fish functional groups (Figure 5).

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**1. Figure 3 — Unimodal and Linear Regression**

**Script:** unimodal and linear regression-Figure3.R

**Description:**\
Generates Figure 3 and supporting appendix figures, exploring linear vs. quadratic (unimodal) relationships between fish community metrics and predictors.

**Input:**...,