Denys Yemshanov

Pest Risk Maps for Invasive Alien Species: A Roadmap for Improvement

Pest risk maps are powerful visual communication tools to describe where invasive alien species might arrive, establish, spread, or cause harmful impacts. These maps inform strategic and tactical pest management decisions, such as potential restrictions on international trade or the design of pest surveys and domestic quarantines. Diverse methods are available to create pest risk maps, and can potentially yield different depictions of risk for the same species. Inherent uncertainties about the biology of the invader, future climate conditions, and species interactions further complicate map interpretation. If multiple maps are available, risk managers must choose how to incorporate the various representations of risk into their decisionmaking process, and may make significant errors if they misunderstand what each map portrays. This article describes the need for pest risk maps, compares pest risk mapping methods, and recommends future research to improve such important decision-support tools.

Mapping Invasive Species Risks with Stochastic Models: A Cross-Border United States-Canada Application for Sirex noctilio Fabricius

Nonindigenous species have caused significant impacts to North American forests despite past and present international phytosanitary efforts. Though broadly acknowledged, the risks of pest invasions are difficult to quantify as they involve interactions between many factors that operate across a range of spatial and temporal scales: the transmission of invading organisms via various pathways, their spread and establishment in new environments. Our study presents a stochastic simulation approach to quantify these risks and associated uncertainties through time in a unified fashion. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. We simulate new potential entries of S. noctilio as a stochastic process, based on recent volumes of marine shipments of commodities from countries where S. noctilio is established, as well as the broad dynamics of foreign marine imports. The results are then linked with a spatial model that simulates the spread of S. noctilio within the geographical distribution of its hosts (pines) while incorporating existing knowledge about its behavior in North American landscapes. Through replications, this approach yields a spatial representation of S. noctilio risks and uncertainties in a single integrated product. The approach should also be appealing to decisionmakers, since it accounts for projected flows of commodities that may serve as conduits for pest entry. Our 30-year forecasts indicate high establishment probability in Ontario, Quebec, and the northeastern United States, but further southward expansion of S. noctilio is uncertain, ultimately depending on the impact of recent international treatment standards for wood packing materials.

A bioeconomic approach to assess the impact of an alien invasive insect on timber supply and harvesting: a case study with Sirex noctilio in eastern Canada

This study presents a model that assesses the potential impact of a new alien insect species, Sirex noctilio Fabri- cius, on pine timber supply and harvest activities in eastern Canada. We integrate the spread of S. noctilio with a broad-scale growth and harvest allocation model. Projections of pine mortality range between 25 � 10 6 and 115 � 10 6 m 3 over 20 years depending on S. noctilio spread and impact assumptions. Our model suggests Ontario could experience the highest, most im- mediate losses (78% of the potential losses across eastern Canada), with Quebec sustaining most of the rest of the losses over the next 20 years. Potential losses of

Trade-associated pathways of alien forest insect entries in Canada.

86 to

Robustness of risk maps and survey networks to knowledge gaps about a new invasive pest.

254 million per year are simulated after 20 years. The net present value of total harvest losses after 28 years of outbreak ranges between

Detection capacity, information gaps and the design of surveillance programs for invasive forest pests.

0.7 to

Towards an integrated approach to modelling the risks and impacts of invasive forest species

2.1 billion. Adaptation policies decrease short- term losses by 46%-55% and delay larger harvest failures by 9-11 years. Without harvest adaptation, failures to maintain annual allowable cut levels may occur once the total area infested exceeds 15 � 10 6 ha. While better understanding and rep- resenting S. noctilio behaviour will involve a significant effort, there is a strong demand by policy makers for this kind of in- formation.

Modelling the Arrival of Invasive Organisms via the International Marine Shipping Network: A Khapra Beetle Study

Long-distance introductions of new invasive species have often been driven by socioeconomic factors, such that traditional “biological” invasion models may not be capable of estimating spread fully and reliably. In this study we present a new methodology to characterize and predict pathways of human-assisted entries of alien forest insects. We have developed a stochastic quantitative model of how these species may be moved with commodity flow through a network of international marine ports and major transportation corridors in Canada. The study makes use of a Canadian roadside survey database and data on Canadian marine imports, complemented with geo-referenced information on ports of entry, populated places and empirical observations of historical spread rates for invasive pests. The model is formulated as a probabilistic pathway matrix, and allows for quantitative characterization of likelihoods and vectors of new pest introductions from already or likely-to-be infested locations. We applied the pathway model to estimate the rates of human-assisted entry of alien forest insect species across Canada as well as cross-border transport to locations in the US. Results suggest a relatively low nationwide entry rate for Canada when compared to the US (0.338 new forest insect species per year vs. 1.89). Among Canadian urban areas, Greater Toronto and Greater Vancouver appear to have the highest alien forest insect entry potential, exhibiting species entry rates that are comparable with estimated rates at mid-size US urban metropolises.

Using a Network Model to Assess Risk of Forest Pest Spread via Recreational Travel

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads to risk-ignorant decisions and miscalculation of expected impacts as well as the costs required to minimize these impacts. Here we use the information gap concept to evaluate the robustness of risk maps to uncertainties in key assumptions about an invading organism. We generate risk maps with a spatial model of invasion that simulates potential entries of an invasive pest via international marine shipments, their spread through a landscape, and establishment on a susceptible host. In particular, we focus on the question of how much uncertainty in risk model assumptions can be tolerated before the risk map loses its value. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. The results provide a spatial representation of the robustness of predictions of S. noctilio invasion risk to uncertainty and show major geographic hotspots where the consideration of uncertainty in model parameters may change management decisions about a new invasive pest. We then illustrate how the dependency between the extent of uncertainties and the degree of robustness of a risk map can be used to select a surveillance network design that is most robust to knowledge gaps about the pest.

Mapping forest composition from the Canadian National Forest Inventory and land cover classification maps

Integrated pest risk maps and their underlying assessments provide broad guidance for establishing surveillance programs for invasive species, but they rarely account for knowledge gaps regarding the pest of interest or how these can be reduced. In this study we demonstrate how the somewhat competing notions of robustness to uncertainty and potential knowledge gains could be used in prioritizing large-scale surveillance activities. We illustrate this approach with the example of an invasive pest recently detected in North America, Sirex noctilio Fabricius. First, we formulate existing knowledge about the pest into a stochastic model and use the model to estimate the expected utility of surveillance efforts across the landscape. The expected utility accounts for the distribution, abundance and susceptibility of the host resource as well as the value of timely S. noctilio detections. Next, we make use of the info-gap decision theory framework to explore two alternative pest surveillance strategies. The first strategy aims for timely, certain detections and attempts to maximize the robustness to uncertainty about S. noctilio behavior; the second strategy aims to maximize the potential knowledge gain about the pest via unanticipated (i.e., opportune) detections. The results include a set of spatial outputs for each strategy that can be used independently to prioritize surveillance efforts. However, we demonstrate an alternative approach in which these outputs are combined via the Pareto ranking technique into a single priority map that outlines the survey regions with the best trade-offs between both surveillance strategies.