Locusts are grasshoppers (Orthoptera: Acrididae) that are characterised by their capacity for extreme population density-dependent polyphenism, transforming between a cryptic solitarious phase that avoids other locusts, and a swarming gregarious phase that aggregates and undergoes collective migration. The two phases differ in many aspects of behaviour, physiology and ecology, making locusts a useful model through which to investigate the phenotypic interface of molecular processes and environmental cues. This review summarises recent progress in understanding the mechanisms and consequences of locust phase change, from differential gene expression and epigenetic regulation through to neuronal plasticity and altered behaviour. The impact of techniques such as RNA interference (RNAi), and the sequencing of the first locust genome is discussed, and we consider the evidence from comparative analyses between related locust species for the possible evolution of locust-like phenotypic plasticity. Collective movement, and new ways of measuring the behaviour of both migrating bands in the field and individuals in the laboratory, are analysed. We also examine the environmental factors that affect phase change, along with the wider impact of land use and management strategies that may unwittingly create environments conducive to outbreaks. Finally, we consider the human costs of locust swarming behaviour, and use combined social, economic and environmental approaches to suggest potential ways forward for locust monitoring and management.

The Central American locust (CAL) Schistocerca piceifrons piceifrons Walker is one of the most harmful plant pests in the Yucatan Peninsula, where an important gregarious zone is located. The olfactory response and host plant acceptance by the CAL have not been studied in detail thus far. In this work, the olfactory response of the CAL to odor of various plant species was evaluated using an olfactometer test system. In addition, the host plant acceptance was assessed by the consumption of leaf area. Results showed that the CAL was highly attracted to odor of Pisonia aculeata. Evaluation of host plant acceptance showed that the CAL fed on Leucaena glauca and Waltheria americana, but not on P. aculeata or Guazuma ulmifolia. Analysis of leaf thickness, and leaf content of nitrogen (N) and carbon (C) showed that the CAL was attracted to plant species with low leaf C content.

Abstract:The Central American Locust Schistocerca piceifrons piceifrons is one of the most damaging plant pest in Mexico and Central America. The present work was carried out to evaluate the seasonal population fluctuation of S. p. piceifrons and vegetation diversity and their association with weather factors and edaphic conditions in the gregarious zone of the Yucatán Península. The study was performed in seven sites during three seasons: North-wind (December 2013), rainy (June 2014) and dry (April 2014). The locust density was sampled in transect of 100 m 2 , as well as the vegetation in 16 m 2 : plant species richness (PSR) and relative species density (RSD), and analyzed by generalized linear models. Additionally, soil samples were obtained at 10 cm depth into a 4 × 6 m quadrat, land use in the sites was classified and temperature, precipitation and evaporation of each site were obtained from the database and they were analyzed with multiple factor analysis. The population density of S. p. piceifrons was higher in the sites Panaba, Tizimin, Tunkas and Cenotillo (F= 74.3, P < 0.0001). Characterization of vegetation showed that PSR and RSD were higher during the rainy season relative to those in the dry season (F= 50.4, P < 0.0001). RSD was identified as the most important group associated with locust density (0.86), followed by isotherm/isohyets (0.63), maximum precipitation and temperature (0.60), as well as the land use (0.65); no correlation between locust density and soil characteristics was found. Locust density was positively correlated with the abundance of the grass Panicum maximum (Sr 2 = 0.85, PC5= 0.87). This work shows that the population of S. p. piceifrons is high in the rainy season and influenced primarily by the abundance of the grass P. maximum and the precipitation. The results indicate that surveys for early detection and control of the locust on the Yucatán Península can focus on areas with the grass P. maximum to predict risk areas and target survey efforts. Rev. Biol. Trop. 66(1): 403-414. Epub 2018 March 01.

From ancient times to the present, infestations of the Central American locust (CAL) [Schistocerca piceifrons piceifrons (Walker, 1870)] have occurred periodically and with varying intensities in the Yucatan Peninsula (YP), Mexico. Despite efforts to survey the recession zone, an upsurge is still difficult to predict and prevent, and high economic costs are incurred in controlling this pest. For this study, two models were developed to determine the probability of an upsurge in the YP. The first was the Markov chain (MC) with transition probability matrix, which estimates probability by determining the proportion of times that the system moved from one state to another (n2) over 71, 33, and 24 years in Yucatan, Campeche, and the Quintana Roo States, respectively, divided into different periods; a correlation of the matrix and probability (n2) of the next period was performed to evaluate the accuracy of the estimation. The other method is the classic probabilistic (CP) model, which uses the number of times the upsurge could happen and the number of possible events. In the MC model, great variation was found in CAL upsurge probabilities between periods, with a similar number of upsurges from the past to the present but with varying intensity. In recent years, the treated area with insecticides has been less than that of the past. The CP model revealed that the locust population reached its maximum peak every four years, with the migration of swarms to neighboring states at the end/start of the year. Validation of the MC and CP models was performed considering information on areas treated in 2019 and 2020, and good accuracy was obtained. Both models provide information on the probability of an upsurge in the YP. This information can be incorporated into economic models to improve management decisions, such as when to announce early warnings, and to implement preventive control strategies.

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