The ZHU Lab

The ZHU Lab is based in Department of Entomology at Washington State University, Pullman, Washington State.

We combine statistical analysis, mathematical modeling, and field surveys, to examine basic and applied questions in (invasive) pest management, functional insect biodiversity and conservation, and global change biology. We utilize diverse data sources, including field sampling, community science initiatives, and existing databases, and employ multiple cutting-edging models, including statistical model, machine learning, and AI, to address various pest management questions, e.g., how insects respond to climate change, the timing and location of pest occurrences, invasive insects potential distribution patterns, and strategies for conserving natural enemies for biological control purposes.

Our work contributes to the early detection of invasive species and enhances both classical and conservation biological control approaches. Current research interests include microclimate and biophysical modeling, niche and distribution modeling, and phenology modeling, and insect thermal imaging:

1. Landscape Ecology– ecological niche and distributional modeling

Predicting the distribution of emerging invasive species is crucial for early detection and eradication. While ecological niche models are often used to forecast invasions, such models are limited when invasive populations of a species have realized niches that differ from native populations, or when invasive populations are not at equilibrium. One technique to potentially overcome these challenges is to incorporate physiological responses of invaders to abiotic factors into ecological niche models, although few studies have assessed whether such approaches are effective. We addressed this by determining whether incorporating physiological data from life table analyses of an invasive insect, Drosophila suzukii, improved predictions of ecological niche models (Zhu et al. 2021). We show that incorporating physiological responses of D. suzukii to temperature into our ecological niche models increased transferability of predictions from the native to the invasive range, while also reducing uncertainty of predictions. Moreover, physiological combined models performed best when equilibrium assumptions were violated. Our study suggests ecological niche models that incorporate data on physiological responses of invaders to abiotic factors provides a means to develop more effective and timely invasive pest distributional models.

Schematic illustration of incorporation insect life table data into regular ecological niche models (regular-ENM, top right). Developmental and survival rates (bottom left) derived from insect life table (top left) served as a prior for Bayesian GLM (bottom right) (Zhu et al. 2021).

The mild climate in the Pacific Northwest (i.e., warm but not hot, cool but not cold, with lots of moisture) has provided suitable conditions for many invasive species, where intense human activity in the coastal areas (e.g., Seattle, Portland) have facilitated their arrival, resulting in ever-increasing establishments of invasive species every year in this area, and great economic loss. Developing approaches to successfully detect, predict, and mitigate invasive species is a necessary step to advance effective management as early detection and rapid response practices are the most cost-effective and efficient method. We aim to employ state-of-the-art niche and distribution techniques to estimate potential distribution and dispersal of these invasive species, to facilitate their early detection and eradication. Here is an example of habitat suitability prediction of Northern Giant Hornet (Zhu et al. 2021), the establishment of this hornet in Washington State is of great concern to bee industry.

Ensemble forecast of global habitat suitability for Northern Giant Hornet (Zhu et al. 2021). Increasing intensities of yellow represent increasing climate suitability, and increasing blue represent increasing severity of invasions due to human activity.

2. Functional insects conservation (i.e., nature insect enemy, bee, pollinator) and biological control assessment

Bee biodiversity and conservation were well noticed, whereas the nature enemy is often overlooked, they provide important function in suppressing invasive populations. Releasing natural enemies or parasites of an exotic insect is a successfully proven method to reduce pest populations. These functional insects (i.e., nature insect enemy, bee, pollinator) are very important in our heath ecosystem. In this section, (1) we are leveraging large scale data to assess biological control for Brown marmorated stink bug and Spotted wing drosophila. Specifically, we are identifying the suitable habitat and phenology congruence between insect invaders and their nature enemies, for Brown marmorated stink bug (Zhu et al. 2024) and Spotted wing drosophila (see below early emergence time prediction). We are also assessing the effectiveness of widely used protected areas (USGS) and climate resilient sites (The Nature Conservancy) in safeguarding these functional insects.

Early emergence time of Spotted wing drosophila after overwintering in mainland US, will be compared with the seasonal activity of its two nature enemies, Ganaspis kimorum and Leptopilina japonica for assessing their phenological congruence (unpublished data).

3. Thermal imaging — Microclimate and biophysical modeling

This is a new research area that we are exploring in potato pest system. Most phenology and habitat suitability models were developed using air temperatures, which were measured at >1 m above the ground at weather stations, without considering the real temperature experienced by (insect) species, together with non-temperature conditions (e.g., precipitation, soil conditions, photoperiod, and wind). The concept of microclimate in biodiversity modeling is well recognized but has often been overlooked in insect phenology or habitat models. Current microclimate models allow us to translate air temperatures from weather stations into the environmental conditions (i.e., microclimate) experienced by insects, and to further predict insect body temperatures. In addition, infrared images provides a unique opportunity to observe biophysical properties in real time, enabling the visualization of the heat transfer processes of organisms within their environment. Through the examination of thermal images captured above and below ground around live insect using FLIR cameras, we can extract microclimate temperature conditions from these captured images, we are comparing air temperature, microclimate models based temperatures, thermal images of insect temperature for fields.

Thermographic image of grasshopper (T_host = 27.7° F, T_environment = 58.8F, from TrEnCh Project)