Effects of Altered Seasonality of Precipitation on Grass Production and Grasshopper Performance in a Northern Mixed Prairie

Analysis of Spatiotemporal Variation in Habitat Suitability for Oedaleus decorus asiaticus Bei-Bienko on the Mongolian Plateau Using Maxent and Multi-Source Remote Sensing Data

O. decorus asiaticus is a major grasshopper species that harms the development of agriculture on the Mongolian Plateau. Therefore, it is important to enhance the monitoring of O. decorus asiaticus. In this study, the spatiotemporal variation in the habitat suitability for O. decorus asiaticus on the Mongolian Plateau was assessed using maximum entropy (Maxent) modeling along with multi-source remote sensing data (meteorology, vegetation, soil, and topography). The predictions of the Maxent model were accurate (AUC = 0.910). The key environmental variables affecting the distribution of grasshoppers and their contribution were grass type (51.3%), accumulated precipitation (24.9%), altitude (13.0%), vegetation coverage (6.6%), and land surface temperature (4.2%). Based on the assessment results of suitability by Maxent model, the model threshold settings, and the formula for calculating the inhabitability index, the 2000s, 2010s, and 2020s inhabitable areas were calculated. The results show that the distribution of suitable habitat for O. decorus asiaticus in 2000 was similar to that in 2010. From 2010 to 2020, the suitability of the habitat for O. decorus asiaticus in the central region of the Mongolian Plateau changed from moderate to high. The main factor contributing to this change was accumulated precipitation. Few changes in the areas of the habitat with low suitability were observed across the study period. The results of this study enhance our understanding of the vulnerability of different regions on the Mongolian Plateau to plagues of O. decorus asiaticus and will aid the monitoring of grasshopper plagues in this region.

Application of Remote Sensing Data for Locust Research and Management-A Review

Simple Summary

Locust outbreaks around the world regularly affect vast areas and millions of people. Mapping and monitoring locust habitats, as well as prediction of locust outbreaks is essential to minimize the damage on crops and pasture. In this context, remote sensing has become one of the most important data sources for effective locust management. This review paper summarizes remote sensing-based studies for locust management and research over the past four decades and reveals progress made and gaps for further research. We quantify which locust species, regions of interest, sensor data and variables were mainly used and which thematic foci were of interest. Our review shows that most studies were conducted for the desert locust, the migratory locust and Australian plague locust and corresponding areas of interest. Remote sensing studies for other destructive locust species are rather rare. Most studies utilized data from optical sensors to derive NDVI and land cover for mapping and monitoring the locust habitats. Furthermore, temperature, precipitation and soil moisture are derived from thermal infrared, passive and active radar sensors. Applications of the European Sentinel fleet, entire Landsat archive or very-high-spatial-resolution data are rare. Implementing new methods (e.g., data fusion) and additional data sources could provide new insights for locust research and management.

Abstract

Recently, locust outbreaks around the world have destroyed agricultural and natural vegetation and caused massive damage endangering food security. Unusual heavy rainfalls in habitats of the desert locust (Schistocerca gregaria) and lack of monitoring due to political conflicts or inaccessibility of those habitats lead to massive desert locust outbreaks and swarms migrating over the Arabian Peninsula, East Africa, India and Pakistan. At the same time, swarms of the Moroccan locust (Dociostaurus maroccanus) in some Central Asian countries and swarms of the Italian locust (Calliptamus italicus) in Russia and China destroyed crops despite developed and ongoing monitoring and control measurements. These recent events underline that the risk and damage caused by locust pests is as present as ever and affects 100 million of human lives despite technical progress in locust monitoring, prediction and control approaches. Remote sensing has become one of the most important data sources in locust management. Since the 1980s, remote sensing data and applications have accompanied many locust management activities and contributed to an improved and more effective control of locust outbreaks and plagues. Recently, open-access remote sensing data archives as well as progress in cloud computing provide unprecedented opportunity for remote sensing-based locust management and research. Additionally, unmanned aerial vehicle (UAV) systems bring up new prospects for a more effective and faster locust control. Nevertheless, the full capacity of available remote sensing applications and possibilities have not been exploited yet. This review paper provides a comprehensive and quantitative overview of international research articles focusing on remote sensing application for locust management and research. We reviewed 110 articles published over the last four decades, and categorized them into different aspects and main research topics to summarize achievements and gaps for further research and application development. The results reveal a strong focus on three species—the desert locust, the migratory locust (Locusta migratoria), and the Australian plague locust (Chortoicetes terminifera)—and corresponding regions of interest. There is still a lack of international studies for other pest species such as the Italian locust, the Moroccan locust, the Central American locust (Schistocerca piceifrons), the South American locust (Schistocerca cancellata), the brown locust (Locustana pardalina) and the red locust (Nomadacris septemfasciata). In terms of applied sensors, most studies utilized Advanced Very-High-Resolution Radiometer (AVHRR), Satellite Pour l’Observation de la Terre VEGETATION (SPOT-VGT), Moderate-Resolution Imaging Spectroradiometer (MODIS) as well as Landsat data focusing mainly on vegetation monitoring or land cover mapping. Application of geomorphological metrics as well as radar-based soil moisture data is comparably rare despite previous acknowledgement of their importance for locust outbreaks. Despite great advance and usage of available remote sensing resources, we identify several gaps and potential for future research to further improve the understanding and capacities of the use of remote sensing in supporting locust outbreak- research and management.

A review of historical and recent locust outbreaks: Links to global warming, food security and mitigation strategies

Locusts differ from ordinary grasshoppers in their ability to swarm over long distances and are among the oldest migratory pests. The ecology and biology of locusts make them among the most devastating pests worldwide and hence the calls for actions to prevent the next outbreaks. The most destructive of all locust species is the desert locust (Schistocerca gregaria). Here, we review the current locust epidemic 2020 outbreak and its causes and prevention including the green technologies that may provide a reference for future directions of locust control and food security. Massive locust outbreaks threaten the terrestrial environments and crop production in around 100 countries of which Ethiopia, Somalia and Kenya are the most affected. Six large locust outbreaks are reported for the period from 1912 to 1989 all being closely related to long-term droughts and warm winters coupled with occurrence of high precipitation in spring and summer. The outbreaks in East Africa, India and Pakistan are the most pronounced with locusts migrating more than 150 km/day during which the locusts consume food equivalent to their own body weight on a daily basis. The plague heavily affects the agricultural sectors, which is the foundation of national economies and social stability. Global warming is likely the main cause of locust plague outbreak in recent decades driving egg spawning of up to 2-400,000 eggs per square meter. Biological control techniques such as microorganisms, insects and birds help to reduce the outbreaks while reducing ecosystem and agricultural impacts. In addition, green technologies such as light and sound stimulation seem to work, however, these are challenging and need further technological development incorporating remote sensing and modelling before they are applicable on large-scales. According to the Food and Agriculture Organization (FAO) of the United Nations, the 2020 locust outbreak is the worst in 70 years probably triggered by climate change, hurricanes and heavy rain and has affected a total of 70,000 ha in Somalia and Ethiopia. There is a need for shifting towards soybean, rape, and watermelon which seems to help to prevent locust outbreaks and obtain food security. Furthermore, locusts have a very high protein content and is an excellent protein source for meat production and as an alternative human protein source, which should be used to mitigate food security. In addition, forestation of arable land improves local climate conditions towards less precipitation and lower temperatures while simultaneously attracting a larger number of birds thereby increasing the locust predation rates.