Habitat selection ecology of the aquatic beetle community using explainable machine learning

被引：0
作者：
Kruk, Marek [1 ]
Pakulnicka, Joanna [2 ]
机构：
[1] Univ Warmia & Mazury, Chair Appl Comp Sci & Math Modelling, Sloneczna 54, PL-10719 Olsztyn, Poland
[2] Univ Warmia & Mazury, Dept Zool, Lodzki Sq 3, PL-10727 Olsztyn, Poland
来源：
SCIENTIFIC REPORTS | 2024年 / 14卷 / 01期
关键词：
WATER BEETLES; BODY-SIZE; BEHAVIORAL ECOLOGY; ABUNDANCE; INSECTS; FAUNA; SPECIALISTS; POPULATION; PREDICTION; COLEOPTERA;
D O I：
10.1038/s41598-024-80083-0
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
The aim of our work is to determine the importance of habitat features for the selection of the aquatic beetle community. Insects are represented by their general ecological traits such as body size, ecological element and trophic type, which are categorised into four body size ranges, four ecological groups and four trophic types. To determine the importance of habitat selection of the studied insects, we analysed the relationships between the above categories and the set of habitat features of the lake and its surroundings. Ensemble machine learning modelling (XGBoost-SHAP) revealed the mechanism of habitat feature selection in relation to the general ecological traits. We found strong interactions between the body size, ecological element and trophic type of beetles, suggesting that these general traits control the structure and functioning of the beetle community studied. The area of the lake and the features of beetle occurrence in the aquatic environment play an important but secondary role, and the importance of the characteristics of the lake's riparian zone was minimised. We found several categories of beetles as they select the number of the same habitat features. The study can provide valuable information for the practical conservation and management of lake ecosystems.
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页数：16
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