Modelling the multi-scaled nature of pest outbreaks

Addressing a century-old hypothesis - do pioneer beetles of Ips typographus use volatile cues to find suitable host trees?

Global warming and more frequent climate extremes have caused bark beetle outbreaks of unprecedented scale of these insects in many conifer forests world-wide. Conifers that have been weakened by drought and heat or damaged by storms are highly susceptible to bark beetle infestation. A large proportion of trees with impaired defences provides good conditions for beetle population build-up of beetles, but mechanisms driving host search of pioneer beetles are still uncertain in several species, including the Eurasian spruce bark beetle Ips typographus. Despite a two-century-long history of bark beetle research, we still lack a sufficient understanding of interactions between I. typographus and its host Norway spruce (Picea abies) to forecast future disturbance regimes and forest dynamics. Depending on the scale (habitat or patch) and beetle population state (endemic or epidemic), host selection is likely driven by a combination of pre and postlanding cues, including visual selection or olfactory detection (kairomones). Here, we discuss primary attraction mechanisms and how volatile emission profiles of Norway spruce may provide cues on tree vitality and suitability for attacks by I. typographus, in particular during the endemic phase. We identify several crucial knowledge gaps and provide a research agenda addressing the experimental challenges of such investigations.

Inference for epidemic models with time-varying infection rates: Tracking the dynamics of oak processionary moth in the UK

Invasive pests pose a great threat to forest, woodland, and urban tree ecosystems. The oak processionary moth (OPM) is a destructive pest of oak trees, first reported in the UK in 2006. Despite great efforts to contain the outbreak within the original infested area of South‐East England, OPM continues to spread.

Here, we analyze data consisting of the numbers of OPM nests removed each year from two parks in London between 2013 and 2020. Using a state‐of‐the‐art Bayesian inference scheme, we estimate the parameters for a stochastic compartmental SIR (susceptible, infested, and removed) model with a time‐varying infestation rate to describe the spread of OPM.

We find that the infestation rate and subsequent basic reproduction number have remained constant since 2013 (with R0 between one and two). This shows further controls must be taken to reduce R0 below one and stop the advance of OPM into other areas of England.

Synthesis. Our findings demonstrate the applicability of the SIR model to describing OPM spread and show that further controls are needed to reduce the infestation rate. The proposed statistical methodology is a powerful tool to explore the nature of a time‐varying infestation rate, applicable to other partially observed time series epidemic data.

Refuge distributions and landscape connectivity affect host-parasitoid dynamics: Motivations for biological control in agroecosystems

Species distributions are affected by landscape structure at different spatial scales. Here we study how the interplay between dispersal at different spatial scales and landscape connectivity and composition affect local species dynamics. Using a host-parasitoid model, we assessed host density and host occupancy on the landscape, under different parasitoid dispersal ranges and three local distributions of non-crop habitats, areas where hosts are unable to grow but parasitoids are provided with alternative hosts and food resources. Our results show distinct responses of host density to increases in non-crop area, measured by differences in slopes for different distributions of non-crop habitats, and that the effect of local landscape composition on species dynamics depends on the landscape connectivity at the regional scale. Moreover, we show how host density and occupancy are affected by increasing parasitoid dispersal ranges depending on landscape structure. Our results demonstrate the role of local and regional scales on species distributions and the importance of the combined effects of species biological parameters and landscape structure on species dynamics. Finally, we highlight the relevance of these aspects for the development of better strategies of biological control.

Impact of Stand and Landscape Management on Forest Pest Damage

One promising approach to mitigate the negative impacts of insect pests in forests is to adapt forestry practices to create ecosystems that are more resistant and resilient to biotic disturbances. At the stand scale, local stand management practices often cause idiosyncratic effects on forest pests depending on the environmental context and the focal pest species. However, increasing tree diversity appears to be a general strategy for reducing pest damage across several forest types. At the landscape scale, increasing forest heterogeneity (e.g., intermixing different forest types and/or age classes) represents a promising frontier for improving forest resistance and resilience and for avoiding large-scale outbreaks. In addition to their greater resilience, heterogeneous forest landscapes frequently support a wide range of ecosystem functions and services. A challenge will be to develop cooperation and coordination among multiple actors at spatial scales that transcend historical practices in forest management.

Implementation of multispecies ecological networks at the regional scale: analysis and multi-temporal assessment

Today, major landscape changes affect ecological connectivity exerting adverse effects on ecosystems. Connectivity is a critical element of landscape structure and supports ecosystem functionality. Landscape connectivity can be efficiently increased in landscape ecology by building ecological networks (EN) through models mimicking the interaction between animal and vegetal species and their environment. ENs are important in sustainable landscape planning, where they need to be studied both by applying landscape metrics and by performing multi-temporal analyses. This paper presents theoretical and practical evidence of an analysis of a multispecies ecological network in Calabria (Italy) and its changes over three decades. Landscape connectivity was modeled basing on 66 focal faunal species' requirements. Human disturbance (HD) was defined and assessed according to distance from different disturbance sources. This allowed for the definition of overall habitat quality (oHQ). Landscape permeability to the animal movement was focused as the main concept to measure landscape fragmentation. Landscape graph theory was applied to perform a spatial comparison of the ENs robustness. Many binary and probabilistic indices and landscape morphological spatial pattern analysis (MSPA) were used in this perspective. We obtained a set of ecological networks, including nodes, patches (i.e., habitat patches), linkages, and corridors, all intertwined in one giant component. The multi-temporal analysis showed many indices' stationary values, while MSPA yielded an increase of habitat quality and habitat patches in core areas. This methodological approach allowed for assessing the regional EN's robustness in the time-span considered, thus providing a reliable tool for landscape planners and communities.

The Vision of Managing for Pest-Resistant Landscapes: Realistic or Utopic?

PURPOSE OF REVIEW

Forest managers have long suggested that forests can be made more resilient to insect pests by reducing the abundance of hosts, yet this has rarely been done. The goal of our paper is to review whether recent scientific evidence supports forest manipulation to decrease vulnerability. To achieve this goal, we first ask if outbreaks of forest insect pests have been more severe in recent decades. Next, we assess the relative importance of climate change and forest management-induced changes in forest composition/structure in driving these changes in severity.

RECENT FINDINGS

Forest structure and composition continue to be implicated in pest outbreak severity. Mechanisms, however, remain elusive. Recent research elucidates how forest compositional and structural diversity at neighbourhood, stand, and landscape scales can increase forest resistance to outbreaks. Many recent outbreaks of herbivorous forest insects have been unprecedented in terms of duration and spatial extent. Climate change may be a contributing factor, but forest structure and composition have been clearly identified as contributing to these unprecedented outbreaks.

SUMMARY

Current research supports using silviculture to create pest-resistant forest landscapes. However, the precise mechanisms by which silviculture can increase resistance remains uncertain. Further, humans tend to more often create pest-prone forests due to political, economic, and human resistance to change and a short-sighted risk management perspective that focuses on reactive rather than proactive responses to insect outbreak threats. Future research efforts need to focus on social, political, cultural, and educational mechanisms to motivate implementation of proven ecological solutions if pest-resistant forests are to be favoured by management.

A Review on Prediction Models for Pesticide Use, Transmission, and Its Impacts

The lure of increased productivity and crop yield has caused the imprudent use of pesticides in great quantity that has unfavorably affected environmental health. Pesticides are chemicals intended for avoiding, eliminating, and mitigating any pests that affect the crop. Lack of awareness, improper management, and negligent disposal of pesticide containers have led to the permeation of pesticide residues into the food chain and other environmental pathways, leading to environmental degradation. Sufficient steps must be undertaken at various levels to monitor and ensure judicious use of pesticides. Development of prediction models for optimum use of pesticides, pesticide management, and their impact would be of great help in monitoring and controlling the ill effects of excessive use of pesticides. This paper aims to present an exhaustive review of the prediction models developed and modeling strategies used to optimize the use of pesticides.

Assessing the multi-pathway threat from an invasive agricultural pest: Tuta absoluta in Asia

Modern food systems facilitate rapid dispersal of pests and pathogens through multiple pathways. The complexity of spread dynamics and data inadequacy make it challenging to model the phenomenon and also to prepare for emerging invasions. We present a generic framework to study the spatio-temporal spread of invasive species as a multi-scale propagation process over a time-varying network accounting for climate, biology, seasonal production, trade and demographic information. Machine learning techniques are used in a novel manner to capture model variability and analyse parameter sensitivity. We applied the framework to understand the spread of a devastating pest of tomato, Tuta absoluta, in South and Southeast Asia, a region at the frontier of its current range. Analysis with respect to historical invasion records suggests that even with modest self-mediated spread capabilities, the pest can quickly expand its range through domestic city-to-city vegetable trade. Our models forecast that within 5-7 years, Tuta absoluta will invade all major vegetable growing areas of mainland Southeast Asia assuming unmitigated spread. Monitoring high-consumption areas can help in early detection, and targeted interventions at major production areas can effectively reduce the rate of spread.