# Diversity and Spatiotemporal Distribution of Fish in a Highland Lake in China Based on Environmental DNA Metabarcoding

## TL;DR

This study used eDNA metabarcoding to assess fish diversity and distribution in Erhai Lake, China, finding it effective for monitoring aquatic biodiversity.

## Contribution

The study demonstrates the effectiveness of eDNA metabarcoding for fine-scale fish monitoring in highland lakes.

## Key findings

- Thirty-six fish taxa, including 5 native and 31 non-native species, were detected in Erhai Lake.
- Seasonal and spatial variations in fish communities were influenced by water temperature, nutrients, and depth.
- Shoreline sampling proved to be a cost-effective method for detecting most fish species in the lake.

## Abstract

Local fish diversity in lakes has severely declined in the last century under the effects of climate change and human activities. Thus, examining the underlying factors and implementing appropriate measures are crucial for preventing further aquatic biodiversity losses. Environmental DNA (eDNA) metabarcoding represents a promising tool for improving fish population monitoring. While spatiotemporal variations of fish eDNA in lentic ecosystems have become a research focus, effective monitoring techniques remain limited. Therefore, this study used eDNA metabarcoding to monitor the diversity and spatiotemporal distribution of fish in Erhai Lake, China. Water samples from the shore, nearshore, and midline were collected from 2020 to 2021 during summer and autumn. Thirty‐six taxa, including 5 native (one endangered species, Schizothorax taliensis) and 31 non‐native taxa, were detected. Seasonal and spatial differences in fish community structure were observed. The seasonal distribution was primarily influenced by water temperature and nutrient status, while the spatial distribution was affected by water depth. Most fish species found in the lake were detected in shoreline samples, suggesting that shoreline sampling is a cost‐effective strategy for monitoring fish diversity. These findings confirmed that fine‐scale spatial sampling and eDNA metabarcoding represent effective tools for monitoring fish diversity and spatiotemporal distribution in lakes.

We analyzed water samples from different seasons and locations in Erhai Lake to determine whether eDNA barcoding can effectively show the diversity of fish in such lakes. In the manuscript, we discuss our findings regarding the range of species found, their spatiotemporal distribution, and whether eDNA barcoding gave similar results to traditional diversity surveying.