2010 Annual Report for FNC09-755
Integrating Bats into Organic Pest Management
Summary
[EDITOR'S NOTE: See the attachment to see the full report with photos, charts, and graphs. The following report is the text only version.]
RESULTS
This project just finished year two of the three-year project. The first year was done without grant funds. Research continues on integrating bats into an organic pest management plan. Particularly, research is focused on the impact of bats on codling moth populations in organic apple orchards located in southern Michigan. The following objectives are being measured against the variables of proximity to the application of synthetic insecticides, an open water source, and a natural bat habitat in year one and two (2009 and 2010):
A. Determine whether the addition of bat houses to organic apple orchards increases bat activity
Twenty-eight bat houses were installed at the seven orchards. Each orchard has two bat houses at two separate locations. The two bat houses are painted black and placed back to back on a 20-foot long 4-inchx4-inch post (see photo, from Country Mill Orchard). The bat houses were designed and installed by the Organization for Bat Conservation in Michigan. All bat houses were installed by April 19th, 2010. A guano catcher was installed on each post to monitor for bat house occupancy. At the end of 2010, bat activity had not yet been observed in the twenty-eight bat houses. This is common with bat house establishment. In short, this potentially illustrates that the bats at the seven orchards currently have sufficient habitat. In some cases bat houses, are used once the bats’ current habitat is destroyed or disturbed.
B. Determine whether bats in apple orchards feed on key insect pests.
Several methods were utilized to determine that the bats present do in fact feed on key orchard pests. Much of this analysis is still ongoing.
A light trap was set up at a randomly selected location within the orchard during the nights of mist-netting. These traps are classified as attractant traps due to the interference of normal sensory orientation of the insects (Kunz, 1988) and have been used extensively in surveys of insect communities (Wolda, 1978). A car battery powered the light traps that were active during the time the bats were foraging (see photo below). After insects were trapped they fell through a funnel into a jar containing 70% alcohol. This allowed them to perish immediately and helped prevent damage to the individuals. After the survey, the container was labeled with the appropriate information for later identification and quantification (number and size).
A total of 37 trapping nights were in the organic apple orchards (13 during 2009 and 24 during 2010) yielding an average of 116.01 insects plus or minus 24.39 (SD) captured per night. A total of 38 trapping nights was recorded in the conventional apple orchards (14 during 2009 and 24 during 2010) yielding an average of 135.48 insects plus or minus 78.65 (SD) captured per night (Fig. 1). From both field seasons, a total of 9,412 insects was captured 4,179 insects captured in organic orchards and 5,233 insects captured in conventional orchards (synthetic chemicals present). Table 1 shows the number of insects distributed into orders that were captured within the two types of orchards.
Fig. 1: Displays the average number of insects captured per night between the two types of orchards along with standard deviation bars.
Lepidoptera is the family of codling moth and oriental fruit moth.
ORGANIC, CONVENTIONAL
Lepidoptera, 887, 605
Coleoptera, 1685, 1638
Diptera, 741, 1210
Hymenoptera, 15, 291
Hemip-Tera, 345, 271
Trichop-Tera, 500, 1145
Orthoptera, 1, 0
Table 1: Number of insects distributed into orders captured at each type of orchards from 2009- 2010.
Acoustic instruments (Anabat, Titley Electronics, Ballina, Australia) were used to identify and quantify the level of bat activity, based on high-frequency echolocation sounds that the bats produce (O’Farrell and Gannon, 1999). The monitoring units consisted of an ultrasonic detector and a ZCAIM (zero-crossing analysis interface module). The detector sensed ultrasound produced by each bat, transformed the sound into a digital signal, and then recorded the frequency-versus-time structure of the call as a file on a flash card that was installed in the ZCAIM.
Eight monitoring units were set up, one at each orchard, and each were programmed to record from around sunset to around sunrise each night they were set up. Data was downloaded every week for analysis. Each week, the monitoring units were moved to a new, randomly selected location in each orchard.
The echolocation calls of bats often differ in parameters such as the minimum and maximum frequency, duration of the call, and time between calls. This information was used to assign each call to a particular species or taxonomic group. Some species, such as red bats (Lasiurus borealis) and hoary bats (Lasiurus cinereus), are easily distinguished, but big brown bats (Eptesicus fuscus) and silver-haired bats (Lasionycteris noctivagans) are very similar and their calls were combined into one category, as will the different Myotis species. Since it is not possible to distinguish between individuals, bodies of water were avoided for the location of the monitoring unit, decreasing the likelihood of the recording multiple calls from the same individual.
Trapping and Fecal Sampling
A mist-net was erected in a random location within an orchard to capture the bats as they were foraging (see photo). Nets were extended approximately 7-m high and 12-m wide and were placed perpendicular to rows within the orchard to maximize capture success (Kunz and Kurta, 1988). After capture, each bat was identified to species, sexed and aged as adult or juvenile, depending on fusion of the epiphyseal plate (Anthony, 1988). Females were further identified as non-reproductive, pregnant, lactating, or post-lactating, based on body mass, nipple condition, and ability to express milk from nipples (Racey, 1988).
Fecal samples were taken from each individual by placing the bat in a 0.4-liter cup (McWilliams, 2005). Each cup was sealed with a perforated lid, to prevent the animal from escaping, and put in a safe area. The individual remained in the cup for up to 30 minutes until defecation occurred and then safely released. Fecal pellets were stored in plastic bags and frozen until later examination.
Dietary and DNA (PCR) Analysis
Diet of all bat species captured were analyzed including the presence of the pest species, the codling moth, the oriental fruit moth, or the plum curculio. Each fecal pellet was soaked in 95 percent ethanol and teased apart under a dissecting microscope, and the resulting insect fragments were classified to at least the level of the order and occasionally the family (Murray and Kurta, 2002), as well as the percent volume estimated (Kunz and Whitaker, 1983; Wilson and Barclay, 2006). It was not be possible to identify the pest species by visual examination of the tiny fragments. A polymerase chain reaction and sequence-based techniques were used to determine which insects were present (Clare et al., 2006). Fragments from the guano were identified, using the standard protocol of Whitaker (1988). Prey items were isolated from the fecal pellet and stored separately in 96-well plates containing ethanol (Clare et al., 2009).
For DNA analysis, ethanol was evaporated from the well plates before adding a lysis buffer to each well. The samples were incubated before the DNA was extracted. The target gene was a 648-bp region of the mitochondrial cytochrome oxidase c subunit I (COI) (Hebert et al., 2003) and amplified using specific primers following Hebert et al. (2004) The samples in the 96-well plates were sent to University of Michigan DNA Sequencing Core to be sequenced. The resulting sequences were then compared to approximately 127,000 reference sequences derived from North American arthropods that are present in the Barcode of Life Data System (BoLD) (Ratnasingham and Hebert, 2007), allowing me to determine whether the captured bats are consuming any of the pest species within the orchards. This procedure recently identified over 100 species of insect in the diet of red bats in Canada (Clare et al., 2009).
As of the writing of this report, the samples taken during the summer of 2010 are still being analyzed. This includes the guano samples and the acoustics. In 2009, however, there was a total of 174 nights that recorded with no malfunctions; 73 in the organic orchards and 101 in the conventional orchards. There were a total of 2,853 bat files recorded in the organic orchards and 5,657 bat files recorded in the conventional orchards (Fig. 2), yielding an average bat activity (number of files per night) of 39.28 number of files per night plus or minus 25.77 (SD) for the organic orchards and 59.64 number of files per night plus or minus 35.16 (SD) for the conventional orchards (Fig. 3). As for the composition of bat species that were recorded, there were 2,275 Eptesicus fuscus calls, 264 Lasiurus borealis calls, 1,342 Lasiurus cinereus calls, 6 Myotis calls (Fig. 4) while 4,733 were considered unknown (could not distinguish).
Fig. 2: Displays the total number of bat files recorded from 2009 between the two types of orchards.
Fig. 3: Displays the average activity (# files/night) between the two types of orchards along with the standard deviation bars.
Fig 4: Displays the composition of bat species of the files recorded from 2009 in both types of orchards.
Trapping and Fecal Sampling
A total of 136 bats were captured during 75 nights of both field seasons (see photo of Brenna Smith, EMU graduate student, mist-netting at an orchard to collect guano and identify bat species). A total of 37 nights in the organic apple orchards (13 during 2009 and 24 during 2010) and 38 nights in the conventional apple orchards (14 during 2009 and 24 during 2010) were mist-netted. There were a total of 54 bats captured in the organic apple orchards composed of 52 Eptesicus fuscus and 2 Lasiurus borealis (Fig. 5). There were a total of 82 bats captured in the conventional apple orchards composed of 79 E. fuscus and 3 L. borealis (Fig. 5). Type of orchard aside, there was a majority of E. fuscus captured and very few L. borealis, although there are nine species of bats found in Michigan. This would illustrate that the use of synthetic chemicals did not influence the population of these two species of bats.
Fig 5: Displays the total bat captures between both types of orchards from 2009-2010 including the difference bat species.
Dietary and PCR Analysis
This project is still in the early stages of the dietary analysis with both techniques: standard fecal analysis and molecular techniques. Thus far, 544 samples have been isolated using 4 intact insect fragments per individual. After using PCR to amplify to COI gene, 47 samples have been sent on to be sequenced. Of these 47 samples, 13 of them have successfully matched a reference sequence in BoLD (greater than or equal to 98 percent) (Fig 6). This work will continue during the winter and early spring.
Fig 6: Displays the 13 samples that have matched greater than or equal to 98 percent as the reference sequence in BoLD.
C. Determine the impact of bat activity in apple orchards on codling moth presence and associated damage.
Due to late spring freezes in 2010, the Michigan apple crop was significantly reduced. As a result some orchards had less than 5 percent of a crop while others had 67 percent of a crop. This variability made scientific research of this objective not possible since the number of insects was not reduced by the frost, but the number of apples was. This caused higher insect damage per fruit than normal and too much variability among sites. During 2011, researchers will work to achieve this objective.
Male codling moth were monitored at all seven study orchards using pherocone VI pheromone traps baited with L2 (Trécé Inc. Stillwell, OK) lures. Traps were laid out in a grid pattern around the two bat houses at each site. At some of the sites two separate grids were maintained while at others a single grid encompassed both bat houses. Grid design as well as trap spacing and density varied greatly among orchards, depending on the size of the orchard, orchard geometry and overall landscape. Table 2 presents total codling moth captures per grid per site as well as a Pearson’s correlation coefficient for total trap captures by distance of traps from bat houses.
Codling moth captures were much higher at organic versus conventional orchards and for the most part only weak positive or negative correlations between trapping numbers and distance from the bat houses was found (Table 2). The two exceptions to this were around one of the bat houses at the Country Mill (0.7160) and one of the bat houses as the Swindeman orchard (0.9010). However, the latter correlation is suspect due to the extremely low moth capture (2 per trap). The lack of strong positive correlations was not surprising as none of the bat houses showed evidence of inhabitation by the end of the 2010 study period
Table 2. Average codling moth captures per trap and correlations with distance of trap from bat houses at the seven study sites. *
Site, Bat House, CM Captured # Traps per grid, Correlation
AlMar, A, 27.1 (n=13), 0.003
AlMar, B, 27.1 (n=13), 0.012
Appleschram, A, 33 (n=7), -0.2789
Appleschram, B, 33 (n=7), 0.2121
Country Mill, A, 37.9 (n=12), 0.2889
Country Mill, B, 37.9 (n=12), 0.7160
County Line, A, 3.25 (n=12), 0.3407
County Line, B, 3.25 (n=12), 0.4431
Spicer’s, A, 2.16 (n=6), 0.6563
Spicer’s, B, 3.75 (n=4), 0.4259
Swindeman, A, 4.6 (n=5), -0.4388
Swindeman, B, 2 (n=6), 0.9010
Erwin, A, 1.2 (n=5), 0.4685
Erwin, B, 20.83 (n=12), 0.3766
* Sites in bold are organic (no synthetic chemicals). Pearson’s correlation numbers indicate the intensity of a positive or negative relationship between trap captures and distance from the bat house. A value of 1 indicates a perfect positive relationship while a value of negative 1 indicates a perfect inverse relationship.
D. Deliver science-based information to apple growers on the importance of bats to codling moth management and how to maximize their impact.
This objective will be accomplished during year three once all research is complete.
SUMMARY
The four main objectives are being evaluated against application of synthetic insecticides, an open water source, and a natural bat habitat. Research during year two showed no correlation between the level of bat activity and the application of synthetic insecticides as seen in the above graphs. This was from the total activity at organic verses conventional orchards. This will still be evaluated in year three. The distance from an open water source and natural bat habitat will be evaluated once after year three in which more random sampling locations are chosen within the orchards. Currently, the 2010 DNA (PCR) analysis of the insects is not yet completed. All other activities are going according to the project timeline.
WORK PLAN FOR 2011
In the third and final year of this project, this research team plans on answering all four objectives and conducting a field day in accordance with the original grant proposal.
Proposed Timeline:
May-September 2011- Conduct bat and insect monitoring
November 2011- Submit final project report.
November 2011- Conduct field day at Project Manager’s Orchard
December 2011- Present final findings.
OUTREACH
Since the research is ongoing the outreach portion of this grant has not yet been conducted.
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