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Rapidly detecting and responding to new invasive species and the spread of those that are already established is essential for reducing their potential threat to food production, the economy, and the environment. We describe a new spatial modeling platform that integrates mapping of phenology and climatic suitability in real-time to provide timely and comprehensive guidance for stakeholders needing to know both where and when invasive insect species could potentially invade the conterminous United States. The Degree-Days, Risk, and Phenological event mapping (DDRP) platform serves as an open-source and relatively easy-to-parameterize decision support tool to help detect new invasive threats, schedule monitoring and management actions, optimize biological control, and predict potential impacts on agricultural production. DDRP uses a process-based modeling approach in which degree-days and temperature stress are calculated daily and accumulate over time to model phenology and climatic suitability, respectively. Outputs include predictions of the number of completed generations, life stages present, dates of phenological events, and climatically suitable areas based on two levels of climate stress. Species parameter values can be derived from laboratory and field studies or estimated through an additional modeling step. DDRP is written entirely in R, making it flexible and extensible, and capitalizes on multiple R packages to generate gridded and graphical outputs. We illustrate the DDRP modeling platform and the process of model parameterization using two invasive insect species as example threats to United States agriculture: the light brown apple moth, Epiphyas postvittana, and the small tomato borer, Neoleucinodes elegantalis. We then discuss example applications of DDRP as a decision support tool, review its potential limitations and sources of model error, and outline some ideas for future improvements to the platform., Competing Interests: The authors have declared that no competing interests exist.

Simple Summary: Knowledge of where invasive species could potentially establish (potential distribution) is critical to prioritizing and addressing biological invasion threats. In this study, we predicted the potential distribution of Calonectriapseudonaviculata (Cps), an invasive fungal pathogen that blights boxwood, an iconic landscape plant, major evergreen nursery crop, and keystone forest species. We used climate data, presence records from Europe and western Asia, and multiple modeling approaches to predict the potential distribution of Cps at regional and global scales and to explore the roles of temperature and moisture in shaping its distribution. Model predictions were validated using an independent presence record dataset. A consensus map of model predictions revealed that Cps could potentially spread and establish well beyond its currently invaded range in Europe, western Asia, New Zealand, United States and Canada. These include a number of not-yet-invaded areas in eastern and southern Europe, North America, and many regions of the world where boxwood is native. This knowledge informs policymakers and other stakeholders in these areas on the need for implementing a strict phytosanitary protocol for risk mitigation of accidental introduction, having an effective surveillance for early detection, and developing a recovery plan for the pathogen when accidental introductions occur. Boxwood blight caused by Cps is an emerging disease that has had devastating impacts on Buxus spp. in the horticultural sector, landscapes, and native ecosystems. In this study, we produced a process-based climatic suitability model in the CLIMEX program and combined outputs of four different correlative modeling algorithms to generate an ensemble correlative model. All models were fit and validated using a presence record dataset comprised of Cps detections across its entire known invaded range. Evaluations of model performance provided validation of good model fit for all models. A consensus map of CLIMEX and ensemble correlative model predictions indicated that not-yet-invaded areas in eastern and southern Europe and in the southeastern, midwestern, and Pacific coast regions of North America are climatically suitable for Cps establishment. Most regions of the world where Buxus and its congeners are native are also at risk of establishment. These findings provide the first insights into Cps global invasion threat, suggesting that this invasive pathogen has the potential to significantly expand its range. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]