An integrative phenology and climatic suitability model for emerald ash borer.

Introduction: Decision support models that predict both when and where to expect emerald ash borer (EAB), Fairmaire (Coleoptera: Buprestidae), are needed for the development and implementation of effective management strategies against this major invasive pest of ash ( species) in North America and other regions such as Europe. We present a spatialized model of phenology and climatic suitability for EAB for use in the Degree-Days, Risk, and Phenological event mapping (DDRP) platform, which is an open-source decision support tool to help detect, monitor, and manage invasive threats.

Methods: We evaluated the model using presence records from three geographic regions (China, North America, and Europe) and a phenological dataset consisting primarily of observations from the northeastern and midwestern United States.

Phenological Mapping of Invasive Insects: Decision Support for Surveillance and Management.

Readily accessible and easily understood forecasts of the phenology of invasive insects have the potential to support and improve strategic and tactical decisions for insect surveillance and management. However, most phenological modeling tools developed to date are site-based, meaning that they use data from a weather station to produce forecasts for that single site. Spatial forecasts of phenology, or phenological maps, are more useful for decision-making at area-wide scales, such as counties, states, or entire nations.

Potential Distribution of Invasive Boxwood Blight Pathogen () as Predicted by Process-Based and Correlative Models.

Boxwood blight caused by is an emerging disease that has had devastating impacts on 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.

Combining photoperiod and thermal responses to predict phenological mismatch for introduced insects.

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.

DDRP: Real-time phenology and climatic suitability modeling of invasive insects.

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.

The consequences of photoperiodism for organisms in new climates.

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.