A Landscape-Based Habitat Suitability Model (LHS Model) for Oriental Migratory Locust Area Extraction at Large Scales: A Case Study along the Middle and Lower Reaches of the Yellow River

Geng, Yun; Zhao, Longlong; Huang, Wenjiang; Dong, Yingying; Ma, Huiqin; Guo, Anting; Ren, Yu; Xing, Naichen; Huang, Yanru; Sun, Ruiqi; Wang, Jing

doi:10.3390/rs14051058

Remote Sensing

2022

DOI: 10.3390/rs14051058

|View full text |Cite

A Landscape-Based Habitat Suitability Model (LHS Model) for Oriental Migratory Locust Area Extraction at Large Scales: A Case Study along the Middle and Lower Reaches of the Yellow River

Yun Geng

Longlong Zhao

Wenjiang Huang

et al.

Abstract: The Oriental migratory locust is a destructive agricultural pest in China. Large-scale locust area (the area possessing suitable breeding habitat for locusts and has locust infestation) extraction and its evolution analysis are essential for locust ecological control. Existing methods seldom consider the spatial differences in the locust development and habitat landscape structures in large areas. To analyze these effects, our study proposed a landscape-based habitat suitability model (LHS model) for large-sca… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

2024

Publication Types

Select...

Article3

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Spatiotemporal Distribution and Main Influencing Factors of Grasshopper Potential Habitats in Two Steppe Types of Inner Mongolia, China

Guo

Dong

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

Grasshoppers can greatly interfere with agriculture and husbandry, and they will breed and grow rapidly in suitable habitats. Therefore, it is necessary to extract the distribution of the grasshopper potential habitat (GPH), analyze the spatial-temporal characteristics of the GPH, and detect the different effects of key environmental factors in the meadow and typical steppe. To achieve the goal, this study took the two steppe types of Xilingol (the Inner Mongolia Autonomous Region of China) as the research object and coupled them with the MaxEnt and multisource remote sensing data to establish a model. First, the environmental factors, including meteorological, vegetation, topographic, and soil factors, that affect the developmental stages of grasshoppers were obtained. Secondly, the GPH associated with meadow and typical steppes from 2018 to 2022 were extracted based on the MaxEnt model. Then, the spatial-temporal characteristics of the GPHs were analyzed. Finally, the effects of the habitat factors in two steppe types were explored. The results demonstrated that the most suitable and moderately suitable areas were distributed mainly in the southern part of the meadow steppe and the eastern and southern parts of the typical steppe. Additionally, most areas in the town of Gaorihan, Honggeergaole, Jirengaole, as well as the border of Wulanhalage and Haoretugaole became more suitable for grasshoppers from 2018 to 2022. This paper also found that the soil temperature in the egg stage, the vegetation type, the soil type, and the precipitation amount in the nymph stage were significant factors both in the meadow and typical steppes. The slope and precipitation in the egg stage played more important roles in the typical steppe, whereas the aspect had a greater contribution to the meadow steppe. These findings can provide a methodical guide for grasshopper control and management and for further ensuring the security of agriculture and husbandry.

show abstract

Spatiotemporal Distribution and Main Influencing Factors of Grasshopper Potential Habitats in Two Steppe Types of Inner Mongolia, China

Guo

Dong

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

show abstract

Outbreak Mechanism of Locust Plagues under Dynamic Drought and Flood Environments Based on Time Series Remote Sensing Data: Implication for Identifying Potential High-Risk Locust Areas

Zhao,

Li,

Huang

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

Locust plagues inflict severe agricultural damage. Climate change-induced extreme events like rainfall and droughts have expanded locust habitats. These new areas, often beyond routine monitoring, could become potential high-risk locust areas (PHRLA). Quantitatively understanding the outbreak mechanism driving drought and flood dynamics is crucial for identifying PHRLA, but such studies are scarce. To address this gap, we conducted a case study on locust outbreaks in Xiashan Reservoir, the largest reservoir in Shandong Province, China, in 2017 and 2018. Using time series satellite imagery and meteorological products, we quantitatively analyzed how drought–flood dynamics and temperature affect locust habitats, reproduction, and aggregation. Employing an object-oriented random forest classifier, we generated locust habitat classification maps with 93.77% average overall accuracy and Kappa coefficient of 0.90. Combined with meteorological analysis, we found that three consecutive drought years from 2014 to 2016 reduced the water surface area by 75%, expanding suitable habitats (primarily reeds and weeds) to cover 60% of the reservoir. Warm winters and high temperatures during locust key growth periods, coupled with expanding suitable habitats, promoted multi-generational locust reproduction. However, substantial flooding events in 2017 and 2018, driven by plentiful rainfall during key growth periods, reduced suitable habitats by approximately 54% and 29%, respectively. This compression led to high locust density, causing the locust plague and high-density spots of locusts (HDSL). Our study elucidates locust plague outbreak mechanisms under dynamic drought and flood environments. Based on this, we propose an approach to identify PHRLA by monitoring changes in drought and flood patterns around water bodies and variations in suitable habitat size and distribution, as well as surrounding topography. These findings hold significant implications for enhancing locust monitoring and early warning capabilities, reducing pesticide usage, and ensuring food and ecological security and sustainable agriculture.

show abstract

Global perspectives and transdisciplinary opportunities for locust and grasshopper pest management and research

Word Ries,

Adriaansen,

Aldobai

et al. 2024

JOR

View full text Add to dashboard Cite

Locusts and other migratory grasshoppers are transboundary pests. Monitoring and control, therefore, involve a complex system made up of social, ecological, and technological factors. Researchers and those involved in active management are calling for more integration between these siloed but often interrelated sectors. In this paper, we bring together 38 coauthors from six continents and 34 unique organizations, representing much of the social-ecological-technological system (SETS) related to grasshopper and locust management and research around the globe, to introduce current topics of interest and review recent advancements. Together, the paper explores the relationships, strengths, and weaknesses of the organizations responsible for the management of major locust-affected regions. The authors cover topics spanning humanities, social science, and the history of locust biological research and offer insights and approaches for the future of collaborative sustainable locust management. These perspectives will help support sustainable locust management, which still faces immense challenges such as fluctuations in funding, focus, isolated agendas, trust, communication, transparency, pesticide use, and environmental and human health standards. Arizona State University launched the Global Locust Initiative (GLI) in 2018 as a response to some of these challenges. The GLI welcomes individuals with interests in locusts and grasshoppers, transboundary pests, integrated pest management, landscape-level processes, food security, and/or cross-sectoral initiatives.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

A Landscape-Based Habitat Suitability Model (LHS Model) for Oriental Migratory Locust Area Extraction at Large Scales: A Case Study along the Middle and Lower Reaches of the Yellow River

Cited by 3 publications

References 52 publications

Spatiotemporal Distribution and Main Influencing Factors of Grasshopper Potential Habitats in Two Steppe Types of Inner Mongolia, China

Spatiotemporal Distribution and Main Influencing Factors of Grasshopper Potential Habitats in Two Steppe Types of Inner Mongolia, China

Outbreak Mechanism of Locust Plagues under Dynamic Drought and Flood Environments Based on Time Series Remote Sensing Data: Implication for Identifying Potential High-Risk Locust Areas

Global perspectives and transdisciplinary opportunities for locust and grasshopper pest management and research

Contact Info

Product

Resources

About