Seasonal time series forewarning model for population dynamics of mango hopper (Hemiptera: Cicadellidae) in humid agro-climatic conditions

Bana, JK; Choudhary, Jaipal Singh; Kumar, Sushil; Ghoghari, PD; Kalaria, G. B.; Desai, H. R.; Patil, S. J.; Patil, Prakash

doi:10.1080/09670874.2021.2019349

Cited by 3 publications

(1 citation statement)

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“…In temperate climates, the deterministic component is often a sinusoid over a one-year period defined by the annual mean temperature, annual temperature amplitude, and a phase shift parameter that reflects seasonal lag. Noise is generally characterized by parameters defining autocorrelation and variability magnitude (Ali et al, 2013;Bana et al, 2021;Mudelsee, 2014). Climate change has influenced both the deterministic and stochastic components of temperature.…”

Section: Introductionmentioning

confidence: 99%

Quantifying population resistance to climatic variability: The invasive spotted lanternfly grape pest is buffered against temperature extremes in California

Lewkiewicz,

Seibold,

Helmus

2023

Preprint

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Temperature time series data are a composition of average trends and stochastic variability that together shape population dynamics. However, models of temperature-dependent species often overlook variability, focusing solely on growth rate under average conditions. When models omit variability, they can inaccurately predict the dynamics that underlie the establishment of invasive pests sensitive to temperature fluctuations. Here, we conduct a stochastic modeling study of spotted lanternfly (Lycorma delicatula), a univoltine grape pest, which has invaded grape growing regions of the eastern U.S. due to human transport leading to frequent establishment of populations in urban and suburban areas. As spotted lanternfly continues to be transported to new grape growing regions and climate change alters variability, it is vital to predict its establishment potential. Although it overwinters as diapausing eggs, experiments suggest that diapause is plastic and not necessary for survival. We developed a deterministic stage-age-structured partial differential equation model of diapausing and non-diapausing populations. We derived a new metric quantifying population resistance to climatic variability defined as the level of stochasticity that leads to negative growth compared to average conditions. We simulated growth rate and resistance to variability across a range of average temperature conditions and stochasticity. We then analyzed how variability and diapause interact with survival, fecundity, and development to affect population dynamics. Finally, we estimated establishment potential across all U.S. cities. Diapausing populations were typically more resistant than non-diapausing populations because diapause enhances overwintering egg survival during winter cold waves, while allowing accelerated development and increased fecundity during summer and fall heat waves. Establishment potential is especially underestimated in important grape growing regions of California if models of diapausing populations omit variability. By quantifying population resistance to climatic variability, we gain a fuller understanding of invasive species establishment in today’s stochastic and changing climate.

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Section: Introductionmentioning

confidence: 99%