Monitoring beneficial insects with plant volatiles: a landscape approach

Progress report for GNE22-305

Project Type: Graduate Student
Funds awarded in 2022: $14,984.00
Projected End Date: 12/31/2024
Grant Recipient: Rutgers University
Region: Northeast
State: New Jersey
Graduate Student:
Faculty Advisor:
Dr. Cesar Rodriguez-Saona
Rutgers University
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Project Information


Monitoring insect abundance is essential for decision-making and thus a fundamental component of integrated pest management (IPM); however, these decisions are rarely based on the abundance of beneficial insects. To enhance IPM programs, monitoring tools for beneficial insects, such as pollinators and natural enemies of pests, need to be developed. While it is understood that beneficials are attracted to plant volatiles like methyl salicylate (MeSA), there are several considerations needed before volatiles can be used for monitoring. For instance, the composition of the landscape in which they live, such as the amount of non-crop habitats, can affect their response to plant volatiles. However, the combined effects of landscapes and local management practices on the response of beneficial insects to plant volatiles remains unknown. This research will determine how the landscape and local management of cranberry agroecosystems affect the beneficial insect community and subsequent ecosystem services in conjunction with the common and commercialized plant volatile MeSA. To achieve this, a trapping network will be established across 50 cranberry beds in the three largest cranberry farms in New Jersey. In each bed, sticky and pan traps baited with MeSA and unbaited traps will be used to monitor natural enemy and pollinator abundance throughout the season. In addition, sentinel eggs and exclusion cages will be placed to assess predation and pollination services. Results from these studies will help develop tools for monitoring beneficial insects that can be used in pest management decisions and conservation biocontrol.

Project Objectives:
  1. Investigate the effects of landscape (habitat composition) and local management practices (crop variety, pesticide usage, and weed abundance and diversity) on response of beneficial insects to plant volatiles.
  2. Investigate the effects of landscape and local management practices on the ecosystem services provided by beneficial insects: biological control (predation) and pollination.

The purpose of this study is to investigate the effects of landscape composition and local management practices on plant volatile recruitment of beneficial insects, which have practical implications in integrated pest management (IPM) decision-making and biocontrol. Making decisions in IPM relies heavily on monitoring to see what insect pests are present. While many monitoring approaches are directed at pests, beneficial insects such as pollinators and natural enemies of pests are rarely considered in decision-making, despite them being important. Many beneficials are known to utilize volatile organic compounds from the plants, for example predators and parasitoids, to locate their host or prey (Price et al. 1980). Since the 1980s, entomologists have been researching these volatiles and subsequently utilizing synthetic plant volatiles to attract these beneficial insects to crops (Rodriguez-Saona et al. 2011). One such plant volatile is methyl salicylate (MeSA) that is commonly released by flowers and other plant parts particularly after insect feeding damage (Vlot et al. 2009). The attraction of beneficial insects to MeSA has been studied in multiple crops, including cranberries, and is known to attract many beneficial insects, such as hoverflies, lady beetles, lacewings, among others (Rodriguez-Saona et al. 2011). Therefore, MeSA can potentially be used to monitor beneficial insects and conservation biological control in agricultural crops. In fact, a lure called PredaLure that contains MeSA is commercially available for this purpose. However, for these lures to be successful, beneficial insects need to be present in the agroecosystem, which means further studying of the agroecosystem in the context of landscape composition and local management practices is necessary.

There are many studies about how landscapes and management practices interact to affect beneficial insect abundance and diversity (Tscharntke et al. 2012). For instance, hoverflies, which are predators as larvae and pollinators as adults, are more diverse and abundant in areas with higher floral diversity, meaning that with higher floral diversity, there is likely to be more predation of pests and pollination (Gervais et al. 2018). Thus, one can theorize that agroecosystems with higher diversity will also have higher amounts of beneficial insects. Moreover, diverse agroecosystems and non-crop habitats provide refuge for beneficials that would otherwise be killed by the pesticide regimes and toxic sprays commonly applied by farmers (Pandey et al. 2022). To date, no studies have studied the correlation that landscape composition and management practices have on beneficial insect attraction to plant volatiles. Understanding the effects of landscape factors and local management practices on the response of beneficial insects to synthetic plant volatiles will help develop new and efficient monitoring techniques for them, which could play into sustainable IPM strategies like conservation and augmentation biocontrol. As such, this proposed research directly connects to the Northeast SARE Outcome Statement, of researching key issues in sustainable agriculture. Monitoring beneficial insects will allow growers to implement these biocontrols into decision-making in IPM programs, which could lead to a decreased reliance on pesticide applications and thus a more environmentally and possibly economically friendlier approach to pest management.


Materials and methods:

1. Sites
1.1 Site location
There will be 50 selected geo-referenced sites (i.e., individual cranberry beds) spread out over three farms: Pine Island Cranberry, JJ White Cranberries, and Cutts Brothers Cranberry Farm (please see letters of support). These three cranberry farms are the largest in New Jersey and were chosen because each farm has its own unique pest management regime; thus, this decreases bias that can occur based on one farming method. Due to the varying sizes of the farms, there will be a different number of sites (i.e., beds) per farm (25 beds on Pine Island Cranberry, 15 beds on JJ White, and 10 beds on Cutts Brothers), with no two site beds bordering each other. The cultivars of cranberries at all the sites will be either Early Black (EB), Stevens (ST), Ben Lear (BL), Mullica Queen (MQ), or Crimson Queen (CQ), with a total of 10 sites per cultivar. EB, ST, and BL are older cultivars while MQ and CQ are newer cultivars. The locations were randomly chosen using a random number generator.

1.2 Site sampling
To monitor for natural enemies, each site will contain two yellow sticky traps that will be 10 meters apart and placed just above canopy level (Rodriguez-Saona et al. 2011). One of the traps will be baited with PredaLure (a commercial synthetic MeSA; AgBio Inc., Colorado, USA), and the other trap will be unbaited (since PredaLure is white, a square white paper will be used to account for visual cues). These traps will be collected after a week and replaced monthly between May through August for a total of 4 sampling times.

To monitor for pollinators, there will also be two white pan traps which will be deployed for a week after the sticky cards have been collected and will be placed in the same spot where the sticky traps were, one pan trap being baited with the previous PredaLure, and the other unbaited. Pan traps will be set during bloom (June and July) and will be out for 48 hours per sample.

The PredaLures will be replaced every month.

2. Data collection
2.1 Beneficial insect biodiversity
All the beneficial insects on the sticky cards (natural enemies) and in the pan traps (pollinators) will be identified at least to family level, and then a Shannon diversity index will be used to measure diversity.

3. Predation
3.1 Site location
The sites used are the same as the diversity study (1.1)

3.2 Site evaluation
Each site will contain 6 sentinel (frozen) fall armyworm (Spodoptera frugiperda) egg masses arranged in two circles of 3, one around the PredaLure and the other around an unbaited site. These egg masses will each be counted beforehand, and then left out for 48 hours, and then recounted to represent generalist predation. Fall armyworm egg masses are stuck to the surface on which they are laid, so a reduction of eggs from an egg mass would most likely be from generalist predation. Sentinel eggs masses will be deployed at each of the 50 sites monthly between May through August for a total of 4 times.

4. Pollination
4.1 Crop production
At 20 geo-referenced sites (beds) (10 on Pine Island Cranberry farm, 5 on J.J. White farm, and 5 on Cutts Brothers farm), there will be four types of cages. Two of the cages will have a fine mesh netting that is expected to exclude all pollinators, one of them will have a PredaLure inside and one without the PredaLure. The other two cages will be open to the sides to allow pollinators, and one will be baited with a PredaLure and the other without the PredaLure. Thus, the experimental design will be 2x2 factorial, with open or closed cages with and without PredaLures. All pollination studies will be conducted on the most common varieties among farms. The 20 sites will be selected randomly throughout the farm. The resulting fruit inside the cages will be counted, weighed, and seeds counted to estimate pollination levels. This will help determine if pollinators are attracted to MeSA and the ecosystem services they provide in relation to the landscape.

5. Data analyses
Every site (bed) will be geo-referenced with Global Positioning System (GPS), and the coordinates will be entered into high-resolution orthophoto imagery for all farms and surrounding areas downloaded from the New Jersey Department of Environmental Protection (NJDEP) Land Use/Land Cover information ( This information will be used to classify the land surrounding each farm into six main categories: 1. forest, 2. wetland , 3. cranberry cropland, 4. barren land, 5. bodies of water, and 6. urban within a 100, 250, 500, and 1500 m buffer area around each site to define the landscape composition and configuration. Landscape composition will be Shannon Diversity index of landscapes, and landscape configuration is area metrics, patch metrics, and edge metrics for each landscape class in each zone.

Multivariate statistics (generalized mixed models) will be employed to determine the interactive effects of PredaLure and landscape (e.g., percent of forest around each site) and local management (e.g. pesticide use, weed cover, variety) variables on the abundance and diversity of natural enemies and pollinators as well as predation and pollination (dependent variables). The goal of this analysis will be to determine the importance of landscape and pest management practices on the response (abundance and diversity) of natural enemies and pollinators to PredaLure and on the effects of PredaLure on ecosystem services (predation and pollination).

2023 Update

I ran all four experiments (sticky traps, pan traps, egg masses, and cages) this year on the sites chosen. I collected pesticide records from the growers at each site. I am currently still looking through all my traps and collecting data. The New Jersey Department of Environmental Protection released a newer land use/cover map, so I redid my landscape analysis, this time looking at 100 m, 250 m, 500 m, and 1500 m buffer zones using ArcGIS Pro. The metrics I  measured for each buffer zone was percent zone for each class (like percent of 100 m zone that is water, percent wetland, agriculture, forest, etc.), number of patches of each class, largest patch index, total edge length, edge density, and Shannon diversity index. 

Research results and discussion:

No results yet. All of the sampling is finished and is in the process of being analyzed. The only thing completely analyzed is the landscape (both composition and configuration). Preliminary analysis on the pollination study (method 4) is suggesting that PredaLure does not have any affect, but it still is not completely clear yet.

Participation Summary
3 Farmers participating in research

Education & Outreach Activities and Participation Summary

1 Curricula, factsheets or educational tools
1 Journal articles
1 On-farm demonstrations
4 Webinars / talks / presentations
1 Workshop field days

Participation Summary:

25 Farmers participated
Education/outreach description:

The ideas in this proposed research are novel and applicable to cranberry growers in New Jersey and the USA, my target audience. Since all the research will be done at commercial farms, there will be an opportunity for regular communication with growers. All the farms on which the research will be conducted have a long history in New Jersey, with the youngest one being over a century old and one of them being amongst the biggest cranberry producers in the world. Thus, this research will likely have profound impact on the whole cranberry industry in New Jersey and the USA.

By working directly with growers, I will be providing them with information on my research progress. Information on biological control and pollination services in cranberries will be provided to growers through various media sources. Factsheets will be written on how to identify and conserve natural enemies of herbivores and pollinators. Another factsheet was already written on New Jersey cranberry pests. This information will be given to growers also through bogs published in the Rutgers Plant & Pest Advisory.

Another important method of outreach is by attending and presenting at grower meetings and scientific conferences. I presented findings from this research at the American Cranberry Growers Association winter meeting, the North American Cranberry Research and Extension Workers conference, and at the Entomological Society of America branch and national meetings. I also plan on writing scientific articles including a meta-analysis about how and what synthetic herbivore-induced plant volatiles are used to attract natural enemies of cultivated crops as well as a synthesis literature review of the past thirty years of integrated pest management practices against insect pests of cranberries (which was published in 2023). These publications will be directed at both scientists and farmers, who can hopefully learn how to utilize plant volatiles and see the history of cranberry pest management.

2023 Update

I wrote and published a literature review on cranberry pest management from the past thirty years as well as a factsheet on cranberry pests of New Jersey, which was distributed at the American Cranberry Growers Association in January 2024. I also attended and presented at the North American Cranberry Research and Extension Workers meeting in August 2023 and the International Society of Chemical Ecology meeting in July 2023.

Advances in cranberry insect pest management: A literature synthesis

Major Insect Pests of Cranberries in New Jersey

Project Outcomes

Project outcomes:

My research will theoretically help farmers be more sustainable. Results from my research will suggest to farmers methods to consider their landscape when managing their land, allowing for greater conservation of beneficial insects. Furthermore, since I am also looking at ecosystem services, I will be able to inform the farmers on how much the beneficial insects are actually providing.

Knowledge Gained:

During the course of this project so far I learned how to talk and work with farmer and how to use ArcGISPro. These two skills helped me realize how unique landscape ecology is and how important it is to approach problems from a large scale, since surrounding habitats may have some strong impacts on sustainability and integrated pest and pollinator management.

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.