Showing papers by "Robert C. Venette published in 2020"

Temperature and prey assessment on the performance of the mealybug predator Tenuisvalvae notata (Coleoptera: Coccinellidae)

Abstract: Tenuisvalvae notata preys upon several mealybug species (Hemiptera: Pseudococcidae), a group of worldwide pests including Planococcus citri and Ferrisia dasyrilii. Although the consequences of variation in temperaturefor the development and reproduction of insects are generally appreciated, the consequences of potential interactions between temperature and prey for predatory insects are not. Thermal requirements and predation rates were determined for T. notata at different constant temperatures with both prey species. T. notata larvae developed to adults in experimental conditions > 18 to <38 °C. The upper thermal limit for egg hatch was 34 °C and for pupation was 33 °C. Adults reared at ≥32 °C did not lay eggs and survived less than 1 week. Prey species did not affect lower temperature thresholds or thermal constants for development from egg to adult. Furthermore, prey did not affect a number of reproductive traits, but the interaction between temperature and prey affected changes in developmental times and oviposition rate with age. Predation rate of T. notata increased as a function of temperature, and T. notata adults generally consumed more nymphs of P. citri than F. dasyrilii. These findings indicate that T. notata is well adapted to the tropical and sub-tropical temperatures and may prove useful for the biological control of some native and non-native mealybugs.

Minimizing Risk and Maximizing Spatial Transferability: Challenges in Constructing a Useful Model of Potential Suitability for an Invasive Insect

Abstract: Forecasting the spread and potential impacts of invasive, alien species is vital to relevant management and policy decisions. Models that estimate areas of potential suitability are useful to guide early detection and eradication, inform effective budget allocations, and justify quarantine regulations. Machine-learning is a rapidly emerging technology with myriad applications, including the analysis of factors that govern species’ distributions. However, forecasts for invasive species often require extrapolation into novel spaces, which may severely erode model reliability. Using the popular machine-learning platform, MaxEnt, we integrate numerous tools and recommendations to demonstrate a method of rigorous model development that emphasizes assessment of model transferability. Our models use Lymantria dispar dispar (L.) (Lepidoptera: Erebidae), an insect brought to the United States in the late 1860s from Europe and subsequently well monitored in spread. Recent genetic analyses provide evidence that the eastern North American population originated in Germany, France, and northern Italy. We demonstrate that models built and assessed using typical methodology for invasive species (e.g., using records from the full native geographic range) showed the smallest extent of extrapolation, but the worst transferability when validated with independent data. Conversely, models based on the purported genetic source of the eastern North American populations (i.e., a subset of the native range) showed the greatest transferability, but the largest extent of extrapolation. Overall, the model that yielded high transferability to North America and low extrapolation was built following current recommendations of spatial thinning and parameter optimization with records from both the genetic source in Europe and early North American invasion.

Optimal invasive species surveillance in the real world: practical advances from research.

Abstract: When alien species make incursions into novel environments, early detection through surveillance is critical to minimizing their impacts and preserving the possibility of timely eradication. However, incipient populations can be difficult to detect, and usually, there are limited resources for surveillance or other response activities. Modern optimization techniques enable surveillance planning that accounts for the biology and expected behavior of an invasive species while exploring multiple scenarios to identify the most cost-effective options. Nevertheless, most optimization models omit some real-world limitations faced by practitioners during multi-day surveillance campaigns, such as daily working time constraints, the time and cost to access survey sites and personnel work schedules. Consequently, surveillance managers must rely on their own judgments to handle these logistical details, and default to their experience during implementation. This is sensible, but their decisions may fail to address all relevant factors and may not be cost-effective. A better planning strategy is to determine optimal routing to survey sites while accounting for common daily logistical constraints. Adding site access and other logistical constraints imposes restrictions on the scope and extent of the surveillance effort, yielding costlier but more realistic expectations of the surveillance outcomes than in a theoretical planning case.

Allopatric populations of the invasive larch casebearer differ in cold tolerance and phenology

Abstract: 1. Traits of non-native insect herbivores may vary spatially due to local genetic differences, rapid post-introduction evolution, and/or novel host plant associations. 2. Populations of larch casebearer, Coleophora laricella Hubner, originally from Europe have likely been isolated for >60 years in North America on eastern larch, Larix laricina (Du Roi) K. Koch, and western larch, Larix occidentalis Nutt. 3. This study investigated cold tolerance and phenology of larvae collected from eastern larch in Minnesota, and western larch in Oregon, Idaho, and Montana, U.S.A. 4. Mean supercooling points of larvae from Minnesota were up to 10 ∘C lower than supercooling points of larvae from Oregon, Idaho, and Montana. 5. At ambient environmental conditions in spring, overwintering larvae from Minnesota required a mean (±SE) of 172±19 degree-days above 5 ∘C to break winter quiescence and actively wander, significantly more than required by larvae from Oregon (66±4), Idaho (64±1), and Montana (60±2). 6. Across all assays and despite substantial latitudinal and elevational variation among western larch sites, no significant differences in any traits were detected among larvae collected from western larch. 7. Spatial variation in cold tolerance and phenological traits of larch casebearer may be attributable to insect genetic differences and/or host plant effects, but exact mechanisms remain unknown. Differences in thermal biology between regions may result in disparate effects of climate change on insect populations and should be accounted for when forecasting insect dynamics across large spatial scales.

Optimal planning of multi‐day invasive species surveillance campaigns

Abstract: 1. Multi-day survey campaigns are critical for timely detection of biological invasions. We propose a new modelling approach that helps allocate survey inspections in a multi-day campaign aimed at detecting the presence of an invasive organism. 2. We adopt a team orienteering problem to plan daily inspections and use an acceptance sampling approach to find an optimal surveillance strategy for emerald ash borer in Winnipeg, Manitoba, Canada. The manager's problem is to select daily routes and determine the optimal number of host trees to inspect with a particular inspection method in each survey location, subject to upper bounds on the survey budget, daily inspection time, and total survey time span. 3. We compare optimal survey strategies computed with two different management objectives. The first problem minimizes the expected number of survey sites (or area) with undetected infestations. The second problem minimizes slippage – the expected number of undetected infested trees in sites that were not surveyed or where the surveys did not find infestation. 4. We also explore the impact of uncertainty about site infestation rates and detection probabilities on the surveillance strategy. Accounting for uncertainty helps address temporal and spatial variation in infestation rates and yields a more robust surveillance strategy. The approach is generalizable and can support delimiting survey programs for biological invasions at various spatial scales.