# Ecological Drivers of Vertebrate Richness and Implications for Inland Wetland Survey in Korea

## TL;DR

This study examines how environmental factors influence vertebrate species richness in Korean wetlands and highlights the need for standardized data collection to improve conservation efforts.

## Contribution

The study compiles and analyzes long-term wetland survey data to identify ecological drivers of vertebrate richness and advocates for standardized data protocols.

## Key findings

- Species richness is higher in larger wetlands with healthier vegetation.
- Standardized reporting formats and metadata are needed to enable effective long-term analysis.
- Wetland area and NDVI positively correlate with species richness across all vertebrate groups.

## Abstract

The Republic of Korea has conducted inland wetland surveys for more than 20 years. However, much of the information is available mainly in report documents, which makes cross-site comparison and long-term analysis difficult. We compiled 134 survey reports published between 2000 and 2021, calculated species richness for amphibians/reptiles, birds, and mammals in each wetland, and tested how richness relates to climate, topography, land use, and water quality. Species richness was generally higher in larger wetlands and where vegetation was healthier, and these patterns remained after accounting for spatial structure. Yet the report-based data is not sufficiently standardized, limiting reuse and the ability to track change over time. These results support the need for standardized survey records and an integrated, analysis-ready national wetland database.

Wetlands have been recognized as nature-based solutions to the climate crisis. This study evaluates the state of standardization in nationwide inland wetland survey datasets and analyzes terrestrial vertebrate patterns by integrating datasets with public environmental data. Species richness data for amphibians/reptiles (432 wetlands), birds (1183 wetlands), and mammals (72 wetlands) were compiled from 134 reports published between 2000 and 2021. Using generalized linear models (GLMs) and generalized additive models (GAMs), we assessed how 15 explanatory variables (climate, topography, wetland information, land use, and water quality) relate to species richness. Model families were chosen for each taxonomic group, and variables were selected using the Akaike information criterion (AIC) and ecological plausibility. Deviance explained was 55.5% for amphibians/reptiles, 60.1% for birds, and 52.4% for mammals. Wetland area and Normalized Difference Vegetation Index (NDVI) were positively associated with species richness across all groups. Despite the large volume of survey data, inconsistent reporting formats and limited metadata constrain longitudinal and time series analyses. Standardized protocols and metadata management are therefore needed to build a systematic national database that can support wetland ecological modeling and conservation policy.