# Water beetle networks differences and migration between natural lakes and post-exploitation water bodies

## TL;DR

This study explores beetle community networks in natural lakes and post-exploitation water bodies to understand migration patterns and ecological stability.

## Contribution

The paper introduces a novel approach combining network analysis and machine learning to assess beetle migration and ecological network stability in different water bodies.

## Key findings

- Ecological networks in eutrophic lakes and clay ponds show the highest network density.
- Beetle species like argilophiles in gravel pits show a stronger affinity to dystrophic lakes.
- Rheophiles in clay pits primarily originate from mesotrophic lakes, contributing to functional connectivity.

## Abstract

Water deficits are a serious problem around the world, which also affects young landscapes, where lakes are most abundant. This poses a threat to many habitats and biological diversity found here. The relationships between species in the ecological networks of lakes at different stages of development and in nearby post-exploitation water bodies remain poorly understood. To better understand the functioning of beetle communities in different ecosystems, we created five network models that we subjected to graph analysis. By analysing the general attributes of the network (number of neighbours, shortest path, characteristic path length, clustering coefficient, network centralisation, network density and network heterogeneity) and those related to the nodes (NCC—Node Closeness Centrality, NBC—Node Betweenness Centrality, NDC—Node Degree Centrality) and to the edges (EBC—Edge Betweenness Centrality and correlations between the biomass of species as nodes), we were able to determine the role of each species in the networks and the relationships between the species. We then used the machine learning ensemble modelling XGBoost—SHAP to identify species that are particularly important in migrations between water bodies and to assess the direction and strength of migrations using Shapley values. Our analyses are based on faunal material from 25 lakes (mesotrophic, eutrophic, dystrophic) and 31—post-exploitation water bodies (clay pits and gravel pits) in northern Poland, in the Masurian Lake District. We found a total of 169 species representing different ecological and functional components. We have shown that the structures of the network between the biomass of species in the analysed five water types differ significantly. The highest value for network density was recorded in eutrophic lakes and clay ponds, the lowest in dystrophic lakes. In eutrophic lakes these are mainly eurybionts, in clay pits–rheophiles and in gravel pits–argilophiles and tyrphophiles. The relationship between the species with the highest NBC and EBC values is particularly important in order to maintain the stability of the network. The periphery of the network usually consists of larger predators that do not compete with each other. By analysing the migration directions of beetles between different ecosystems, we were able to demonstrate a greater affinity of the beetle fauna, especially the argilophiles (e.g. Scarodytes halensis and Laccobius minutus) inhabiting gravel pits, to dystrophic lakes. The beetles in clay pits originate mainly from mesotrophic lakes. These are mainly rheophiles, mostly weakly flying species, such as: Haliplus fluviatilis, Haliplus fulvus, Ilybius fenestratus, Hygrotus vericolor and Haliplus flavicollis. These species are important for the stability of ecological networks in the studied lake types. Their movements between the ecosystems studied in turn contribute to the functional connectivity between the individual lakes, which ensures the stabilisation of biotic relationships at the landscape level. At the same time, they generally also indicate the optimisation of environmental conditions in post-exploitation water bodies, which makes them potential substitute habitats for natural lakes.

The online version contains supplementary material available at 10.1038/s41598-025-00525-1.