Landscape models can predict the distribution of aquatic insects across agricultural areas

Gerber, Rémi; Piscart, Christophe; Roussel, Jean-Marc; Georges, Romain; Houet, Thomas; Royer, Justine; Bergerot, Benjamin

doi:10.1007/s10980-023-01761-4

Cited by 4 publications

(1 citation statement)

References 56 publications

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“…Temperature, precipitation, altitude, and other environmental variables have direct and indirect impacts on insect survival [ 36 , 37 ]. Temperature is an important environmental and survival factor for insects, including P. fuscipes .…”

Section: Discussionmentioning

confidence: 99%

Predicting the Impact of Climate Change on the Future Distribution of Paederus fuscipes Curtis, 1826, in China Based on the MaxEnt Model

Gao,

Wei,

Peng

et al. 2024

Insects

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Paederus fuscipes Curtis, 1826, belongs to the Coleoptera order, Staphylinidae family, and Paederus genus (Fabricius, 1775). It has a wide distribution and strong invasive and environmental adaptation capabilities. As a predatory natural enemy of agricultural and forestry pests, understanding its suitable habitat is crucial for the control of other pests. This study, for the first time, uses the MaxEnt model and ArcGIS software, combining known distribution information of P. fuscipes and climate environmental factors to predict the current and future suitable habitat distribution of this insect. The key environmental variables affecting the distribution of P. fuscipes have been identified as mean diurnal range (mean of monthly (max temp-min temp)) (bio2), isothermality (Bio2/Bio7) (*100) (bio3), minimum temperature of the coldest month (bio6), temperature annual range (bio5-bio6) (bio7), mean temperature of the driest quarter (bio9), mean temperature of the coldest quarter (bio11), precipitation of the wettest month (bio13), precipitation of the driest month (bio14), and precipitation seasonality (coefficient of variation) (bio15). The highly suitable areas for P. fuscipes in China are mainly distributed in the hilly regions of Shandong, the North China Plain, and the middle and lower reaches of the Yangtze River Plain, with a total suitable area of 118.96 × 104 km2, accounting for 12.35% of China’s total area. According to future climate change scenarios, it is predicted that the area of highly and lowly suitable regions will significantly decrease, while moderately suitable regions will increase (except for the 2090s, SSP2-4.5 scenario). These research findings provide important theoretical support for pest control and ecological conservation applications.

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Section: Discussionmentioning

confidence: 99%

Predicting the Impact of Climate Change on the Future Distribution of Paederus fuscipes Curtis, 1826, in China Based on the MaxEnt Model

Gao,

Wei,

Peng

et al. 2024

Insects

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Principal determinants of aquatic macroinvertebrate communities in small shallow lakes and ponds

Labat,

Thiébaut,

Piscart

2024

Biodivers Conserv

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Soil cover heterogeneity associated with biocrusts predicts patch-level plant diversity patterns

Havrilla,

Villarreal

2024

Landsc Ecol

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Context Soil resource heterogeneity drives plant species diversity patterns at local and landscape scales. In drylands, biocrusts are patchily distributed and contribute to soil resource heterogeneity important for plant establishment and growth. Yet, we have a limited understanding of how such heterogeneity may relate to patterns of plant diversity and community structure. Objectives We explored relationships between biocrust-associated soil cover heterogeneity and plant diversity patterns in a cool desert ecosystem. We asked: (1) does biocrust-associated soil cover heterogeneity predict plant diversity and community composition? and (2) can we use high-resolution remote sensing data to calculate soil cover heterogeneity metrics that could be used to extrapolate these patterns across landscapes? Methods We tested associations among field-based measures of plant diversity and soil cover heterogeneity. We then used a Support Vector Machine classification to map soil, plant and biocrust cover from sub-centimeter resolution Unoccupied Aerial System (UAS) imagery and compared the mapped results to field-based measures. Results Field-based soil cover heterogeneity and biocrust cover were positively associated with plant diversity and predicted community composition. The accuracy of UAS-mapped soil cover classes varied across sites due to variation in timing and quality of image collections, but the overall results suggest that UAS are a promising data source for generating detailed, spatially explicit soil cover heterogeneity metrics. Conclusions Results improve understanding of relationships between biocrust-associated soil cover heterogeneity and plant diversity and highlight the promise of high-resolution UAS data to extrapolate these patterns over larger landscapes which could improve conservation planning and predictions of dryland responses to soil degradation under global change.

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Landscape models can predict the distribution of aquatic insects across agricultural areas

Cited by 4 publications

References 56 publications

Predicting the Impact of Climate Change on the Future Distribution of Paederus fuscipes Curtis, 1826, in China Based on the MaxEnt Model

Predicting the Impact of Climate Change on the Future Distribution of Paederus fuscipes Curtis, 1826, in China Based on the MaxEnt Model

Principal determinants of aquatic macroinvertebrate communities in small shallow lakes and ponds

Soil cover heterogeneity associated with biocrusts predicts patch-level plant diversity patterns

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