Driving factors and their interactions of carabid beetle distribution based on the geographical detector method
The decline of insect diversity has received widespread attention as a serious ecosystem problem worldwide. Accurately learning the driving factors of insect decline is difficult because of the complex multitrophic and environmental interactions involved. The scientific interpretation of the factors...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-12-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X2101058X |
| _version_ | 1798026694712360960 |
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| author | Xueqin Liu Hui Wang Xinpu Wang Ming Bai Dahan He |
| author_facet | Xueqin Liu Hui Wang Xinpu Wang Ming Bai Dahan He |
| author_sort | Xueqin Liu |
| collection | DOAJ |
| description | The decline of insect diversity has received widespread attention as a serious ecosystem problem worldwide. Accurately learning the driving factors of insect decline is difficult because of the complex multitrophic and environmental interactions involved. The scientific interpretation of the factors driving insect distribution is essential to understanding biological systems and the effects of changed environment. Generally, insect distributions result from the interactions of different factors, therefore, understanding how multi-factor interactions effect of carabid distribution is beneficial. Carabid beetles are indicator species in the steppes of northwestern China. Previous studies have focused on the main driving factors of carabid beetle occurrence separately, ignoring the interactions between drivers. Using the Geographical Detector method, a new method of spatial statistics, the interactive influences of 15 variables on carabid beetle distribution were quantified at three steppes in the Ningxia Hui Autonomous region, of northwestern China. The results showed that carabid beetle distribution in the steppes was primarily driven by annual average precipitation (q=0.55). Among the interactions of factors, precipitation ∩ Altitude (q=0.719) was the strongest, followed by precipitation ∩ plant biomass (q=0.677 ), and precipitation ∩ pH value (q=0.677). The areas with the greatest risk of carabid beetle decline are the desert steppe and northern parts of the meadow steppe. This study shows that the Geographical Detector approach was successful for analyzing the driving forces of carabid beetle distribution. Our study also offers a new method for understanding the interactions between different drivers of other animal distributions more broadly. |
| first_indexed | 2024-04-11T18:39:33Z |
| format | Article |
| id | doaj.art-3cb1e7c8cd5d466b94631d09dd518980 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-04-11T18:39:33Z |
| publishDate | 2021-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-3cb1e7c8cd5d466b94631d09dd5189802022-12-22T04:09:02ZengElsevierEcological Indicators1470-160X2021-12-01133108393Driving factors and their interactions of carabid beetle distribution based on the geographical detector methodXueqin Liu0Hui Wang1Xinpu Wang2Ming Bai3Dahan He4School of Agriculture, Ningxia University, Yinchuan 750021, ChinaInstitute of Green Manure, Yan’an Academy of Agricultural Sciences, Yan’an 716000, ChinaSchool of Agriculture, Ningxia University, Yinchuan 750021, China; Corresponding authors : School of Agriculture, Ningxia University, Yinchuan, 750021, China (XP. Wang) ;Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China (M. Bai).School of Agriculture, Ningxia University, Yinchuan 750021, China; Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Corresponding authors : School of Agriculture, Ningxia University, Yinchuan, 750021, China (XP. Wang) ;Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China (M. Bai).School of Agriculture, Ningxia University, Yinchuan 750021, ChinaThe decline of insect diversity has received widespread attention as a serious ecosystem problem worldwide. Accurately learning the driving factors of insect decline is difficult because of the complex multitrophic and environmental interactions involved. The scientific interpretation of the factors driving insect distribution is essential to understanding biological systems and the effects of changed environment. Generally, insect distributions result from the interactions of different factors, therefore, understanding how multi-factor interactions effect of carabid distribution is beneficial. Carabid beetles are indicator species in the steppes of northwestern China. Previous studies have focused on the main driving factors of carabid beetle occurrence separately, ignoring the interactions between drivers. Using the Geographical Detector method, a new method of spatial statistics, the interactive influences of 15 variables on carabid beetle distribution were quantified at three steppes in the Ningxia Hui Autonomous region, of northwestern China. The results showed that carabid beetle distribution in the steppes was primarily driven by annual average precipitation (q=0.55). Among the interactions of factors, precipitation ∩ Altitude (q=0.719) was the strongest, followed by precipitation ∩ plant biomass (q=0.677 ), and precipitation ∩ pH value (q=0.677). The areas with the greatest risk of carabid beetle decline are the desert steppe and northern parts of the meadow steppe. This study shows that the Geographical Detector approach was successful for analyzing the driving forces of carabid beetle distribution. Our study also offers a new method for understanding the interactions between different drivers of other animal distributions more broadly.http://www.sciencedirect.com/science/article/pii/S1470160X2101058XCarabid beetleGeographical detector modelInteractionSpatial heterogeneityHigh risk area |
| spellingShingle | Xueqin Liu Hui Wang Xinpu Wang Ming Bai Dahan He Driving factors and their interactions of carabid beetle distribution based on the geographical detector method Ecological Indicators Carabid beetle Geographical detector model Interaction Spatial heterogeneity High risk area |
| title | Driving factors and their interactions of carabid beetle distribution based on the geographical detector method |
| title_full | Driving factors and their interactions of carabid beetle distribution based on the geographical detector method |
| title_fullStr | Driving factors and their interactions of carabid beetle distribution based on the geographical detector method |
| title_full_unstemmed | Driving factors and their interactions of carabid beetle distribution based on the geographical detector method |
| title_short | Driving factors and their interactions of carabid beetle distribution based on the geographical detector method |
| title_sort | driving factors and their interactions of carabid beetle distribution based on the geographical detector method |
| topic | Carabid beetle Geographical detector model Interaction Spatial heterogeneity High risk area |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X2101058X |
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