The research and how to use it on SIR, netting and other tools to add to high pressure codling moth blocks. Presented by Betsy Beers, WSU Entomology at North Central Washington Tree Fruit Days January 2022.
Text Transcript and Description of Visuals
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| Thanks for joining this virtual session this morning. I retitled my talk a little bit because I had sort of a smorgasbord of tools, tactics, and ideas that I wanted to talk about. Things I’ve been thinking about for the past year or so based on some long philosophical discussions with some of the folks involved. | Title slide. Presentation title: Codling Moth Management: A Perspective. Presenter information: Elizabeth H. Beers. |
| I’d like to start with a few reflections on trapping and the codling moth model. And first I’m going to start with trapping. The pheromone trap has been with us for nearly a half century now, so it’s a pretty familiar technology. It’s changed and evolved over time, but for the most part, the basic principles and functions are unchanged. | Slide titled “Pheromone Traps” contains a photo of an orange, delta-style codling moth trap. |
| Trapping revolutionized our ability to monitor certain pests, including coddling moth, because instead of having to hunt them down in the orchard, we can have them come to us. I spent a lot of time in some pretty infested orchards. And here is a photo on the left of one of the few wild adults I’ve seen just flipping around in the canopy. They are most active at dawn and dusk when I am not. And they are usually in the upper canopy where I can’t reach. So you don’t just encounter them that often. What you do get to see is on the right, fruit damage, and that makes nobody happy. | Slide titled “Much Despised, Seldom Seen” contains a photo of an adult codling moth on the surface of a leaf, and of an apple with a hole from a burrowing codling moth larvae. |
| Traps changed all of that. The coddling moth comes to you and not vice versa. We lure them in with a pheromone, now usually with the addition of a kairomone, and trick them into landing on a sticky surface, and then count them at our leisure. And because the sex pheromone is species-specific, pretty much everything that looks like a codling moth in your trap is a codling moth. | Slide titled “If They Smell if, They Will Come…” contains a photo of moths stuck to the sticky card of a codling moth trap, and an image of a pheromone lure. |
| So ease of use has really promoted the adoption of traps as our primary monitoring method. It’s really our number one tool. But in many ways, we don’t truly understand what the numbers in the trap mean. | Slide titled “Traps: The Standard” contains two photos of delta traps placed within trees. |
| So here’s a list you’ve probably seen before, both from me and Vince, and well, probably a whole lot of other folks too. It’s all the factors that can or do influence trap capture. They’ve been studied in the lab in the field, and we have some quantitative information on some and qualitative information on others. But all in all, this is a pretty daunting list, especially when all you really want to do is measure the item at the bottom, codling moth density. | Slide titled “Factors Influencing Pheromone Trap Catch” contains a checklist of factors including temperature at dusk, rainfall, wind speed, wind direction, trap location, trap height, trap geometry, trap density, lure components, lure age, mating disruption, pesticides, and point in the emergence curve. At the bottom, a boxed phrase reads ‘Codling Moth Density”. |
| So I’d like to go over a couple of factors on this list that will illustrate this point a bit more clearly. Here’s another graph you’ve probably seen before. And one of the major takeaways is that the distribution of coddling moth in an orchard is really uneven. This patchy or aggregated distribution pattern is pretty common in insects. So it’s really not surprising to any extent. But what I’ve come to realize is that, in addition to this patchiness or hotspot type of a pattern, the other factors had far more of an influence than I realized. | Slide titled “Uneven Distribution” contains a depiction of the codling moth trap capture in a 12 acre block. Traps with high moth density are represented by large blue circles while traps with low density are represented by small blue circles. There is an uneven population distribution of moths throughout the block. |
| So we took a look at two of the biggest factors I think influenced trap capture. And we did a study with sterile moths. Admittedly, sterile codling moth may not be a perfect model for wild moths, especially during cool spring temperatures. which is why we do this in mid-summer. The block on the right was covered with partial nets, and the block on the left was open. The blank spot in the middle of the open block was still an orchard, but they were young grass that didn’t have the same canopy architecture as a larger or mature orchard. We set up a grid of traps, about one per acre, baited with a CM-DAA lure and released marked sterile codling moths weekly for six to 10 weeks from mid-June to mid-August. Importantly, not only were our traps in a grid, so were our release points. One release point for each trap, about the second row over and a little to the west. Literally, I could see the trap from where I was doing the release. We shook them out as high in the canopy as we could reach, collected the liners a week later, and then rinse and repeat through August. | Slide titled “Factors Influencing Pheromone Trap Catch” contains a depiction of two orchard blocks in which codling moth traps, represented by triangles, were evenly distributed. Text indicates that one orchard was netted and the other was open. |
| And here’s what we found. This is the sum of all moths caught in a given trap during the study period. In the net plot, there was a 2.6-fold difference between the highest and the lowest trap. In the open plot, or really two plots, the differences were more extreme. We found a 7.6-fold difference between the highest and lowest traps. So this is an example of what we would call the effect of trap location. Now, normally when we think of location as being a factor, we relate it to topography, but this orchard was dead flat. We think location has to do with outside sources, not in this case. All the sources were inside the orchard, and they were all marked moths. So all we’re left with is wind direction and just random error. And as you can see, just those two factors alone can be pretty substantial. | Slide titled “Trap Placement Influences Capture” contains a depiction of the two orchard blocks used in the study, with blue circles of varying sizes indicating moth density in traps across the netted and un-netted trial. |
| Here is the exact same data set, but using trap averages instead of sums and plotted over time instead of space. Looks like an emergence curve in the second generation, right? Nope. This is the exact same number of factory-produced moths released every week in the exact same spot going about their business as best they could. So this is the influence of weather. And as you can see, it is not trivial either. There was about a 20-fold difference between the high and the low catch during a time when generally temperature isn’t limiting for codling moth flight and reproduction. | Slide titled “Weather Influences Trap Captures” contains a plot of the moths per trap per week from June to September. This data is shown for both the netted and un-netted trials. The trap capture for the un-netted trial is generally lower, with less extreme spikes. |
| So you’re thinking, should I even be using traps? Just the opposite. And with apologies, it comes down to statistics. There is a basic principle in statistics that dictates that the more you sample or the more traps you put out, the more confident you are in the results that you get. This has to do with the average number per trap. Let’s say you have five traps with an average of eight moths per trap. You are 95% confident that the true average is between 4 and 12. But if you only have two traps, you are only confident that it is somewhere between 1 and 14. Now, I know this seems a little too obvious, but you can’t calculate an average of a single trap. And this is part of the basis for a longstanding recommendation to put at least a trap in every two and a half acres. It’s all about confidence. | Slide titled “How Confident are you? Contains a graph of moths per trap versus the number of traps. For the low trap numbers, the observed range of data is more variable. The more samples that are taken, the more consistent the data is. |
| You might be thinking that, well, that’s just statistics and they’re all made up anyways. So here’s the real data. The gray bars represent the actual range of what we caught in a given trap over 10 weeks. And the range was 0 to 18 up to 0 to 32. So if you only had one trap out, it’s sort of a dice roll as to what you’ll catch in any given week. | A graph appears on screen of the moth captures per trap per week versus the number of traps. The confidence intervals are narrower for the higher numbers of traps. |
| So I’d like to segue now to the codling moth model. The concept of degree days is 100 years old now. The basic model was developed in Michigan in the 1970s and implemented in earnest in Washington after the arrival of Jay Brunner sometime in the 1980s. I think the title of this early extension bulletin says it all, a new tool for timing sprays. There’s a couple of nuances to that title that I’d like to go over because after 100 years, some folks seem to think that the model is somehow broken. I don’t think it is, and I’d like to try to explain why. | Slide titled “Codling Moth Model” contains the title and author information of the mentioned study, as well as an image of an extension publication announcing the model. |
| The first is that the model is based on temperature-driven development. Typically, we do a series of lab experiments at different temperatures and calculate a daily developmental rate and the amount of time, measured in degree days, that it takes to complete each stage. Here are two examples of such studies, one from 1922 and one from 2000. I don’t think codling moth have changed their physiological requirements since the 1980s, but if anybody wants to redo these experiments, I’m willing to listen. | Slide titled “Codling Moth: Physiological Time” contains the degree day timing charts from the two mentioned papers outlining the lifecycle timing of codling moths. |
| So the model is built on these physiological parameters and then validated by observing what actually occurs in the field. This has been done and redone a number of times, and we still come up with pretty much the same answer. But, and this is important, most of that original work was done in highly infested orchards that were not under mating disruption. And by highly infested, I mean they caught between 200 and 500 moths per trap per year on the average. If, in your managed orchard, you catch four moths per trap per year, describe to me the peaks of three generations. You just can’t do it. It’s not possible. | Slide titled “Codling Moth Model” contains a plot of the codling moth cumulative proportion in stage versus the degree day in Sunrise Orchard in 2011. Data is shown for all 4 life stages of the moths. Three generational peaks are seen for each of the life stages. |
| So the take-home is this. In a well-managed, low-pressure orchard, trapping is not, repeat, not model validation. Not even close. The model is a phenology model, not a population abundance model. And because they sort of look alike, we’ve been confusing the two. In fact, every management tactic you use, mating disruption, SIR, or pesticides, are expressly designed to disrupt the relationship between trap abundance and a normal undisturbed population development. If your trap catch follows the model perfectly, you probably aren’t spraying enough. | Slide titled “Trap Catch does not equal Model Validation” contains a bullet point list of reminders for model validation, as outlined in the audio. |
| This is the output from Vince’s spray effects calculator, and it really illustrates the point perfectly. When you take a chunk out of one or more stages in one generation, that disturbance ripples through to the next generation. And that’s one reason why you may end up with those weird trap counts. The spray effects calculator helps you forecast how those missing chunks will play out in your orchard. But I hope also the information on trapping variability will also give you some insight as to why you end up with more or less moths in any given trap in any given week. | Slide titled “Spray Record Evaluator/Pesticide Effects” contains two plots of the relative number of crawlers versus the degree days since January 1. Blue sections are used to indicate the spray effects. |
| So I do want to spend a little bit of time on new tools and tactics. You’ve heard me go over most of these before, so I’ll just hit the highlights. First, they all have one thing in common. They’re expensive. These are whole orchard driving cages, and over several years of study, we’ve looked at how good they are at keeping wild moths out. And they’re pretty effective. Not quite 100%, but pretty close. Having your orchard or your tree surrounded by nets resets your baseline codling moth pressure to a lower level, just like mating disruption does. | Slide titled “New Tools for CM: Nets and Cages” contains several photos of different types of drape netting in orchards as well as photos of codling moths sitting on the netting. |
| The second is solid set canopy delivery system. Jay Brunner and Keith Granger did a study on this a few years back. Actually, it’s been about 10 years now. And I’ve never forgotten about that study and what a great idea it was and is. This work has continued in Prosser with Lav Khot and his students and Gwen Hoheisel, and they are still working on an optimization of the system. While coverage may not be perfect, it’s improving and may be sufficient for our purposes. Being able to spray your orchard in a fraction of the time by flipping a valve instead of getting on a tractor and hitting your degree day targets on the nose instead of within a week or 10 days, this could be a game changer. But someday in that high-tech automated orchard of the future, we need to get pickers off of ladders and pesticide applicators off of tractors. | Slide titled “SSCDS: Solid Set Canopy Delivery System” contains a diagram of the system within the field, as well as water sensitive paper showing gaps in spray coverage for the underside of leaves. |
| And lastly, SIR. I can’t believe I’m saying this, but this is actually the least expensive option of the three I’ve mentioned and also the most flexible. You can move it around from block to block or year to year as need and pressure dictates, which is pretty hard to do with an irrigation system or nets. | Slide titled “SIR: Sterile Insect Release” contains a photo of a drone flying above an orchard for sterile insect releases, as well as photos of adult codling moths gathered on fruit and leaves. |
| While that was probably a little more pie in the sky than you were looking for, we may not be able to afford some of these options today, but we also can’t afford to stay in the same place forever. Thank you. | Thank you slide containing the logos of funding sources. |
Link to YouTube video: Codling Moth Management Tools
