Research Article |
Corresponding author: Timothy Ebert ( tebert@ufl.edu ) Academic editor: Donald Lafontaine
© 2014 Roger Downer, Timothy Ebert.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Downer R, Ebert T (2014) Macrolepidoptera biodiversity in Wooster, Ohio from 2001 through 2009. ZooKeys 452: 79-105. https://doi.org/10.3897/zookeys.452.8009
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A Skinner mercury vapor light trap was operated from 2001 through 2009 in a residential backyard to document biodiversity within the moth families Thyatiridae, Drepanidae, Geometridae, Mimallonidae, Apatelodidae, Lasiocampidae, Saturniidae, Sphingidae, Erebidae (including Lymantriinae and Arctiinae), Euteliidae, Nolidae, and Noctuidae. When making comparisons to older literature, we recalculated our results to conform to the older classification of the Noctuoidea. Moths were released after identification. There were 501 species documented in 77581 captures from 1290 sampling dates. There was a perceived risk that released moths would fly back into the trap the following evening. This should result in an abnormal number of rare moths that are caught multiple times. The number of species caught twice versus the number caught once was no different than a similar ratio for surveys that used more traditional sampling methods. Therefore this concern does not seem to be valid for these data. These data are provided in a supplementary file available for download.
There were three previous surveys conducted in nearby natural areas. They documented fewer species than were documented here. To understand this better, we examined several specialized groups of moths that tend to use host plants not typically found in an urban residential yard. More species in Schinia Hübner, Catocala Schrank, Acronicta Ochsenheimer, and Herminiinae Leech were found in this survey than the other local surveys. Only in the Papaipema Smith did we recover fewer species, though it was still above 70% of what was expected. This diversity could be a result of sampling effort, but it shows that this urban location has a very diverse moth fauna. We suggest that this diversity is partly due to the planting of native plant species in the area about the light trap. Therefore we would concur with others that urban landscapes can be planned to increase biodiversity relevant to more natural ecosystems.
In this study we looked at the ratio of the number of species of Geometridae divided by the number of species of Noctuidae as one approach to evaluating the level of disturbance in the moth assemblage. Although the yearly average was nearly constant, the seasonal ratio ranged from 0.09 to 0.91 depending on the sampling date. We also calculated alpha diversity and found that seasonal change in alpha diversity greatly exceeded yearly differences. This strong seasonal component means that a comparison between two studies requires a correction for seasonality and similar sampling intervals. In this study, a shift of two weeks would be sufficient to result in a significant difference in alpha diversity. This is the equivalent of increasing temperature by 1.53 °C. Seasonal shifts limit the usefulness of this methodology for environmental assessment because the within season change exceeds the between season change. This problem is compounded when sampling designs interact with this seasonality.
In describing our data, we made use of a growing degree day (GDD) model. This approach corrects for simple temperature dependent shifts in moth biology. Consequently, some of the variability in the data was removed, which should improve the power of statistical tests involving survey data. If sampling protocols were based on growing degree days rather than calendar dates, the bias caused by temperature induced shifts in seasonal cycles could be reduced.
Organismal biological diversity, survey, seasonality, phenology, moth
Moths play an important role in ecosystems. Adults pollinate flowers, and their larvae play a variety of roles as herbivores, detritivores, omnivores, or carnivores (
The largest family of moths is the Noctuidae (
Urbanization results in a large number of environmental changes. Physical changes from urbanization include elevated pollution levels in air and soil, elevated temperatures, increased soil compaction, and increased soil alkalinity (
Biodiversity is one measure of the effect of environmental impact, but it can be distorted by an influx of new generalist species better adapted to disturbed environments. It has been suggested that the ratio of the number of geometrid moths to the number of noctuid moths is a better measure of environmental disturbance (
Moth surveys are often justified as tools to document ecological processes like climate change (
To put this survey in perspective, we compiled a table of several moth surveys from the last 70 years (Table
Overview of moth surveys including number of moths sampled (no.), number of species recorded (spp.), and the number of species of Noctuidae (Noct.) and Geometridae (Geo.). The main focus was surveys from the United States.
Cite | State | Location | No. | Spp. |
Noct. | Geo. |
---|---|---|---|---|---|---|
A | OR | Blue Mtns | 20322 | 383 | 212 | 93 |
B | WV | Cooper’s Rock State Forest | 29983 | 400 | 220 | 102 |
C | WV | Turkey Run and Great Falls National Pks |
Unk | 480 | 278 |
107 |
C1 | WV | Camp Dawson Collective Training Area | 3666 | 235 | 101 | 73 |
C2 | WV | Southern West Virginia |
Unk | 751 | 418 | 191 |
D | FL | Blue Spring State Park |
Unk | 275 | 171 | 67 |
E | NJ | Hutcheson Memorial Forest | 22880 | 410 | 253 | 98 |
F | LA | West Feliciana Parish | 3155 | 314 | 122 | 68 |
G | LA | Long-leaf pine Savanna | 1182 | 208 | 84 | 42 |
H | IN | Morgan-Monroe State Forest | 14537 | 324 | 110 | 72 |
I | IA | Neal Smith National Wildlife Refuge | 9416 | 508 | 136 | 69 |
J | OH | Wilderness Center |
Unk | 413 | 233 | 94 |
K | OH | Funk Bottoms |
Unk | 262 | 159 | 46 |
L | OH | Atwood Lake State Park |
Unk | 376 | 221 | 93 |
-- | OH | Wooster (current study) | 77581 | 501 | 314 |
104 |
M | TN,NC | Great Smoky Mountains National Park |
Unk | 914 | 528 | 225 |
N | AR | Ozark mtns | 8720 | 314 | 57 |
33 |
O | Hungry | Aggtelek National Park | 127035 | 994 | 512 | 326 |
P | Canada | Ministik Hills, Alberta | 24578 | 264 | 151 | 66 |
Q | Canada | Acadia Research Forest, New Brunswick | 31634 | 539 | 270 | 169 |
R | ME | Orono | 43435 | 337 | 258 | 27 |
There have been three Lepidoptera surveys in our local area. These took place at Funk Bottoms, The Wilderness Center, and Atwood Lake Park. Funk Bottoms Wildlife Area consists of periodically flooded moist meadows, bottomland hardwoods, and 80 ha of permanent marsh. However, thousands of hectares may be flooded for up to several months each year (
Temperature plays a critical role in biological processes. A “growing degree day” (GDD) model is typically used where accumulated thermal units are explanatory variables for the biological process of interest (
It would be useful to define the area being sampled when conducting any sampling activity. Defining the sampling radius about a light trap is not simple in part because it is a probability function where the probability of capture decreases exponentially with increasing distance. The probability of capture also declines rapidly if the moth starts its movement outside the radius where the light is strong enough to be attractive. Anything that affects background light levels (moon phase, light pollution, cloud cover) will alter capture probabilities (
The above paragraph contains considerable uncertainty about the exact attraction radius. This is caused by differences in the methodology of the cited works. We provide two cases to illustrate the point.
Our goals were to; 1) Document biodiversity in an urban setting to compare to three previous surveys in natural settings. 2) A quantification of the effect of seasonal changes in moth diversity. 3) Document the utility of a phenological model in understanding biological survey results.
The trap was located in an urban (as defined by US Census Bureau (
Moths were collected using a Skinner mercury vapor light trap with a 125 Watt mercury vapor bulb (model 7591 from Watkins and Doncaster (www.watdon.co.uk)) with the filament 33 cm above ground level. The performance of this trap relative to others was recently evaluated (
We suggest using the GPS coordinates provided earlier and Google Earth® (http://www.google.com/earth/index.html) for a detailed view of the environment about the moth trap. Botanical composition of nearby parks (1 km distant) is largely irrelevant due to the short attraction radii of black light trapping methods (<520 m). Furthermore, the light was close to the ground, so buildings, trees, and tall shrubs all block light and serve to further restrict this radius.
Moths were identified and catalogued using an older classification system (
A lower developmental threshold of 10 °C was used to estimate growing degree days (GDD) (
We used the various approaches to estimating species richness implemented in EstimateS (
We used the proportion of species represented by a single capture as an indication of the effectiveness of the sampling protocol (
The study site had bats, birds, and wasps that preyed on moths attracted to the light. There may also have been other vertebrate and invertebrate predators. Moths were released in different locations in the yard to reduce such predation. However, we could not quantify the level of predation or the effectiveness of any effort at reducing predation. Sometimes moths were too worn to be properly identified, and these individuals were ignored.
We expect that three traps run six times per year for one year (
Quantitative assessment of the effect of multiple captures was made by examining the number of moth species captured once per year versus the number represented by two captures per year. A methodology that increased the probability of recapturing moths should have a disproportionate number of rare species captured twice. The average doubleton÷singleton ratio for each year was 0.574 (standard deviation [SD] of 0.211). We also look at this ratio for each sampling date because in this case doubletons cannot be recaptures of the same individual. The doubleton÷singleton ratio for each night where there were both singletons and doubletons was 0.382 (SD 0.336). The yearly average was not significantly greater than the daily average (F=2.91; df=1, 980; P=0.09). Obviously, a failure to detect a significant difference is not the same as proving that there was no effect.
The raw data are included as supplemental data. The data file is in Excel format. We recommend that users read the “Introduction”, which is the first page (left-to-right) in the file. The next page to the right in the file includes the weather data. Farther to the right are nine pages with yearly capture data. These pages include the number of growing degree days accumulated by each collection date. Cells are blank if no individuals of a given species were captured on a specific date. Next is a page “Condensed List” that contains total number of each species, and the number of years each species was collected. This page contains the species as they were identified and the equivalent under the system by
In 1290 sampling dates from 1 January 2001 through 31 December 2009, a total of 77,581 moths were captured and identified. This averages to 60 moths/night. However this number has little value because it includes early and late season samples that have few moths. In 2001 the range was from 1 to 496 moths per night with an average of 96. Within this nine year sampling effort were 501 species, of which 122 were found in all nine years.
The numbers of species within a family that were represented by a single capture has been used as a metric for evaluating the effectiveness of a sampling methodology.
Genera, species, and abundance compositions for 12 Families of macrolepidoptera in Wooster Ohio. Total percentage singletons is the number of species represented by a single capture in the nine years of the survey divided by the number of species. Average percentage singletons is the average of the number of singletons caught each year divided by the number of species caught that year.
Family | Individuals captured | Number of genera | Number of species | Total percentage singletons | Average percentage singletons |
---|---|---|---|---|---|
Thyatiridae | 16 | 3 | 3 | 33 | 50 |
Drepanidae | 31 | 2 | 2 | 0 | 43 |
Geometridae | 8578 | 70 | 104 | 13 | 20 |
Mimallonidae | 3 | 1 | 1 | 0 | 100 |
Apatelodidae | 8 | 2 | 2 | 0 | 63 |
Lasiocampidae | 229 | 3 | 5 | 0 | 3 |
Saturniidae | 42 | 8 | 8 | 25 | 50 |
Sphingidae | 184 | 9 | 13 | 7 | 41 |
Notodontidae | 2755 | 18 | 32 | 16 | 22 |
Erebidae | 17197 | 11 | 112 | 15 | 23 |
Euteliidae | 112 | 3 | 5 | 0 | 34 |
Nolidae | 340 | 3 | 6 | 0 | 21 |
Noctuidae | 48086 | 122 | 208 | 11 | 22 |
Statistic | Mean | Lower 95% CI | Upper 95% CI |
---|---|---|---|
Chao 1 Mean | 553.69 | 529.61 | 598.78 |
Chao 2 Mean | 560.43 | 533.43 | 609.52 |
Standard Deviation | |||
Jacknife 1 | 568.95 | 8.33 | |
Jacknife 2 | 598.97 | 1.18 | |
Bootstrap | 533.27 | 0.49 |
The number of species only present in a single year was greatest in 2001 (Table
Summary by year, and over the nine year study period for macrolepidoptera in Wooster Ohio. We list the number of days sampled (Days), number of individuals captured (Captured), number of genera (Genera), number of species (Species), the species that had never been captured prior to that year (Never Before), the species captured only in the given year (Only Once), percentage of species represented by only one capture (Only One), Fisher’s alpha (Alpha), and the standard deviation of Fishers alpha (SD).
Year | Days | Captured | Genera | Species | Never before | Only once | Only one | Alpha | SD |
---|---|---|---|---|---|---|---|---|---|
2001 | 133 | 12,819 | 219 | 339 | 339 | 19 | 87(26%) | 64.12 | 1.54 |
2002 | 115 | 6,688 | 176 | 257 | 37 | 6 | 68(26%) | 53.05 | 1.56 |
2003 | 146 | 8,094 | 193 | 288 | 36 | 6 | 63(22%) | 58.29 | 1.60 |
2004 | 121 | 6,754 | 175 | 278 | 29 | 13 | 66(24%) | 58.42 | 1.67 |
2005 | 127 | 6,950 | 182 | 274 | 14 | 5 | 39(14%) | 56.93 | 1.63 |
2006 | 126 | 7,067 | 192 | 278 | 11 | 5 | 64(23%) | 57.73 | 1.64 |
2007 | 164 | 9,837 | 199 | 317 | 15 | 8 | 79(25%) | 60.17 | 1.67 |
2008 | 142 | 7,476 | 172 | 263 | 5 | 4 | 60(23%) | 53.11 | 1.52 |
2009 | 216 | 11,892 | 209 | 333 | 15 | 15 | 74(22%) | 63.59 | 1.56 |
All | 1290 | 77,581 | 2934 | 501 | 64(13%) | 71.86 | 1.17 |
Given that we documented 501 species at this one location, one might suggest that this urban environment had greater macrolepidopteran diversity than 15 of the 19 North American sites in Table
There have been three moth surveys near this survey. The Wilderness Center had the fewest number of shared species with our study (Table
Similarity between our results and those from other surveys in Ohio in numbers of species in each family or subfamily. Arct = Arctiinae, Geo = Geometridae, Noc = Noctuidae, Noto = Notodontinae, Sat = Saturniidae, Sphing = Sphingidae.
Location | Arct | Geo | Noc | Noto | Sat | Sphing |
---|---|---|---|---|---|---|
Funk Bottoms | ||||||
In Common | 14 | 40 | 100 | 18 | 6 | 4 |
Unique to cited | 2 | 6 | 25 | 1 | 1 | 1 |
Unique to ours | 6 | 64 | 161 | 15 | 2 | 9 |
Wilderness Center | ||||||
In Common | 16 | 64 | 191 | 28 | 6 | 10 |
Unique to cited | 3 | 32 | 51 | 8 | 0 | 4 |
Unique to ours | 3 | 40 | 117 | 5 | 2 | 3 |
Atwood Lake Park | ||||||
In Common | 14 | 74 | 135 | 22 | 5 | 9 |
Unique to cited | 1 | 19 | 37 | 5 | 2 | 2 |
Unique to ours | 6 | 30 | 126 | 11 | 3 | 4 |
An alternative strategy to assess the value of this urban moth assemblage is to examine specific genera within the Noctuoidea that are not associated with typical urban vegetation. Larvae from moths in the Noctuid genus Schinia are mostly associated with plants in the Asteraceae and Fabaceae. Species in the genus Catocala are specialists on plants in the Fabaceae, Fagaceae, Rosaceae, Juglandaceae, Myricaceae, and Salicaceae. The genus Acronicta larvae feed on woody shrubs and trees, some are specialists. Larvae of moths in the genus Papaipema are borers in stems of plants in the Asteraceae and other weedy species. The tribe Psaphidini primarily feed on members of the Juglandaceae and Fagaceae with the exception of Copivaleria grotei (Morrison), which feeds on ash. The subfamily Herminiinae is a member of the family Erebidae, with larvae that primarily feed on senescent plant material (http://www.eeb.uconn.edu/people/wagner/USDA Noctuid Guide Most Current.doc). Table
Number of species collected from specific groups for several faunal surveys. These groups contain a large proportion of specialists that could be adversely impacted by urbanization.
Source | Schinia | Catocala | Acronicta | Papaipema | Psaphidini | Herminiinae |
---|---|---|---|---|---|---|
A | 3 | 26 | 23 | 10 | 2 | 25 |
B | 1 | 16 | 14 | 12 | 2 | 18 |
C | 2 | 19 | 19 | 8 | 2 | 11 |
D | 2 | 11 | 5 | 13 | 2 | 11 |
E | 2 | 12 | 19 | 6 | 2 | 31 |
F | 0 | 15 | 20 | 6 | 2 | 25 |
A Whittaker plot showed no obvious difference in ranked abundance between any of the years (Fig.
We calculated the number of species that went missing from one year to the next expressed as a proportion of the number of species originally present (e.g., 100* number of species in 2001 not collected in 2002 divided by the total number of species collected in 2001). We also calculated the number of immigrants expressed as a proportion of the number of species present in the year of collection (e.g., 100* number of species in 2002 not collected in 2001 divided by the total number of species in 2002). The missing rate averaged 24.0% (standard deviation 0.0701) while the immigration rate averaged 23.9% (standard deviation 0.0632) from 2001 through 2009. This would suggest that the biodiversity in this area was relatively stable over this nine year period.
The Noctuidae had three peak abundances in the year, with the first peak ending at about 722 GDD (late June), a second peak from 722 to 1056 (early August), and the third peak from 1056 GDD onwards (Fig.
The presence of seasonal patterns has been documented previously, though the specific pattern may be unique to a specific location (
A long term trapping effort is managed as the Hungarian Plant Protection and Forestry Light Trap Network (
We were interested in the difference between using a growing degree day model versus a calendar date. We selected 37 individuals with 350 or more captures in the nine year study, and calculated the average day of capture. For each species we divided the mean by the standard deviation, and used a paired t-test for a significant difference between using Julian day versus GDD (df 36; t=7.12; Pr>|t|<0.001). On average there was a 57% reduction in this ratio for GDD relative to using Julian Day (95% CI: 51.7 to 61.3%). Therefore, the GDD approach should significantly increase the statistical power of tests for treatment differences relative to using calendar date.
Looking at the number of Catocola, Acronicta, and species in the Herminiinae that we collected relative to surveys from less disturbed environments, we would conclude that our sample from an urban environment was not inflated by a large number of generalists attracted to the mix of exotics in the urban landscape. Therefore we would concur with others that urban landscapes can be planned to increase biodiversity relevant to more natural ecosystems (
There is no end point to general surveys. No matter how many years of sampling, there will always be an additional species that can be added to the list if sufficient effort is expended. One reason for making such lists is that they provide quantifiable justification for maintaining a natural area to preserve biodiversity. In some cases a threatened local population is being preserved, and those individuals may be locally abundant. More commonly we are preserving rare species associated with a specific habitat. In this case, there is no end to the survey because it is not possible to identify all the species present at an instant in time nor is it possible to identify all the potential species that could live in that habitat. Partly this is a function of forces like climate change, but there are also changes in the spatial distribution of all plant communities. An end point might be reached if the survey goal is to identify those species visitors to the park are likely to encounter and ask “what is this?” In this survey there were 122 species encountered every year. Five species stop flying in May. Five only start flying in August, and three start flying in September. So one could ask how many years it would take to get all 122 species by sampling once per month from May through October. Sampling the first day of these six months will result in recovering an average of 63.2 of these 122 species in any one year. This sampling protocol will only recover 117 of these species in the nine years sampling took place. How does this answer change if we took two or three samples each month? What if we shifted the sampling dates by a few days? Another simple option is to choose the date with the most number of species for the year. In this study that date would fall between 24 July and September 1. The maximum number of species recovered on a single night averaged 51.1. Thus a simple sampling design has difficulty recovering species that we know are present every year. The required sampling effort increases greatly if one desires to go beyond a species list to an understanding of the underlying relationships between these ecologically important organisms.
We thank J. Donald Lafontaine for help in updating our species list to the modern classification of the Noctuoidea. We thank Ian Woiwod for access to the data from trap 336 from the Rothamsted Insect Survey. We thank the Pennsylvania Natural Heritage Program for access to data from Annville, Pennsylvania. We also thank Jerry Powell for data from Inverness Ridge in California, and Keith Summerville for data from his researches on moth biodiversity in other parts of Ohio. We thank two anonymous reviewers whose comments greatly improved this manuscript. We thank Michael Rogers from University of Florida for helping with page charges.
Nightly moth captures in Wooster, Ohio and summaries of these data
Data type: Excel workbook with multiple worksheets
Explanation note: The first worksheet on the left is the “Introduction”. The next page to the right in the file includes the weather data. Then there are nine pages with yearly capture data. These pages include the number of growing degree days accumulated by each collection date. Cells are blank if no individuals of a given species were captured on a specific date. Next is a “Condensed List” that contains total number of each species, and the number of years each species was collected. This page contains the species as they were identified and the equivalent under the system by