Search

A wide variety of organisms use the regular seasonal changes in photoperiod as a cue to align their life cycles with favorable conditions. Yet the phenological consequences of photoperiodism for organisms exposed to new climates are often overlooked. We present a conceptual approach and phenology model that maps voltinism (generations per year) and the degree of phenological mismatch that can arise when organisms with a short-day diapause response are introduced to new regions or are otherwise exposed to new climates. Our degree-day-based model combines continent-wide spatialized daily climate data, calculated date-specific and latitude-specific day lengths, and experimentally determined developmental responses to both photoperiod and temperature. Using the case of the knotweed psyllid Aphalara itadori, a new biological control agent being introduced from Japan to North America and Europe to control an invasive weed, we show how incorporating a short-day diapause response will result in geographic patterns of attempted voltinism that are strikingly different from the potential number of generations based on degree-days alone. The difference between the attempted and potential generations represents a quantitative measure of phenological mismatch between diapause timing and the end of the growing season. We conclude that insects moved from lower to higher latitudes (or to cooler climates) will tend to diapause too late, potentially resulting in high mortality from inclement weather, and those moved from higher to lower latitude (to warmer climates) may be prone to diapausing too early, therefore not fully exploiting the growing season and/or suffering from insufficient reserves for the longer duration in diapause. Mapped output reveals a central region with good phenology match that shifts north or south depending on the geographic source of the insect and its corresponding critical photoperiod for diapause. These results have direct relevance for efforts to establish populations of classical biocontrol agents. More generally, our approach and model could be applied to a wide variety of photoperiod- and temperature-sensitive organisms that are exposed to changes in climate, including resident and invasive agricultural pests and species of conservation concern., (© 2022 The Ecological Society of America.)

A change in climate is known to affect seasonal timing (phenology) of the life stages of poikilothermic organisms whose development depends on temperature. Less understood is the potential for even greater disruption to the life cycle when a phenology shift exposes photoperiod-sensitive life stages to new day lengths. We present a conceptual framework and model to investigate the ways that photoperiod-cued diapause can interact with a change in climate or latitude to influence voltinism in poikilothermic organisms. Our degree-day phenology model combines detailed spatial climate data, latitude- and date-specific photoperiods, and development and photoperiod response parameters. As an example, we model the biological control beetle Galerucella calmariensis and map the number of generations expected following its introduction into diverse climates throughout the continental United States. Incorporation of photoperiodism results in a complex geography of voltinism that differs markedly from predictions of traditional phenology models. Facultative multivoltine species will be prone to univoltism when transported to either warmer or southern climates due to exposure of the sensitive stage to shorter day lengths. When moved to more northern locations, they may attempt too many generations for the season duration thereby exposing vulnerable life stages to harsh weather in the fall. We further show that even small changes in temperature can result in large and unexpected shifts in voltinism. Analogous effects may be expected for organisms from wide variety of taxa that use photoperiod as a seasonal cue during some stage of their life cycle. Our approach is useful for understanding the performance and impacts of introduced pests and beneficial organisms as well as for predicting responses of resident species to climate change and climate variability.