Aug 16, 2024
USDA LTAR Common Experiment measurement: Butterfly diversity and abundance
- Nick M. Haddad1,2,
- Jamie D. Smith1
- 1W.K. Kellogg Biological Station, Michigan State University, Hickory Corners, MI;
- 2Department of Integrative Biology, Michigan State University, East Lansing, MI
External link: https://ltar.ars.usda.gov
Protocol Citation: Nick M. Haddad, Jamie D. Smith 2024. USDA LTAR Common Experiment measurement: Butterfly diversity and abundance. protocols.io https://dx.doi.org/10.17504/protocols.io.14egn6bnpl5d/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: February 12, 2024
Last Modified: August 16, 2024
Protocol Integer ID: 97103
Keywords: Long-Term Agroecosystem Research, LTAR, USDA LTAR, Common Experiment, butterflies, citizen scientists, pollinators, insect abundance, surveys
Funders Acknowledgements:
United States Department of Agriculture
Grant ID: -
Abstract
We will use a measure of butterfly abundance and diversity collected using a method standard across the US and the globe (Wepprich, et al. 2019). This method is used in regional studies, for example, the states of Ohio, Illinois, and Michigan in the US and the countries of the UK, the Netherlands, and Spain. Within these regions across hundreds of sites, data collection is performed by scientists and citizen scientists. Butterflies are the easiest-to-measure indicator of pollinator and insect abundance; metrics from large-scale butterfly surveys have proven consistent with long-term responses of pollinators and other insects across the globe (Van Klink, et al. 2020). The recommended method is easily employed by people not trained with insects and is not burdensome in terms of time. For every replicate, it involves walking a 1 km line transect at least once a month and recording the number and species of butterflies within a set distance of the transect.
Materials
- Stopwatch
- Watch
- Clipboard
- Site map
- Pencil
- Butterfly net
- Binoculars
- Datasheets
- Butterfly ID guide
Before start
This protocol has been altered from https://faculty.jmcl.wwu.edu/Wildlife/bfly_walk.pdf and https://ukbms.org/methods. The presence and abundance of butterflies are sampled using transect counts, modified from Pollard (1977).
Pollard walks
Pollard walks
1h 30m
1h 30m
Transect routes are established as appropriate for each site.
The recommended transect length is 1 km and the walking duration is 1 hour and 30 minutes.
Note
If areas, such as prevailing and alternative treatments in LTAR, do not allow 1 km transects, these values are scaled proportionally. For example, at the LTAR Kellogg Biological Station, some treatments permit 100 m transects that are walked for 8 min.
Transects are marked before surveys commence, and the same transect is sampled throughout the research effort.
Sampling transects are surveyed by walking from one end to the other without doubling back. Walk at a steady pace.
Observers record butterflies seen within a 5 m radius on both sides and above them while walking a transect at a slow and steady pace (see the figure embedded below).
Credit: Elizabeth Schultheis
Credit: Elizabeth Schultheis
To avoid double-counting, butterflies behind the observer are not counted.
Species identifications are made visually, using binoculars when needed.
Note
Occasionally, identification may require a photograph or capture with nets, after which the insects are released unharmed.
Record species or higher taxa using common names and keep a tally per butterfly taxon.
Record each individual once only. If the survey pauses to capture, identify, photograph, or take notes on a butterfly, stop the timer.
Transects are walked during midday hours (10:00 am − 4:00 pm) when it is warm and insects are flying.
Sampling is restricted to relatively calm conditions and times when air temperature exceeds 11 °C in sunny weather or 17 °C in cloudy weather.
Ideally, treatments are sampled weekly, and LTAR Sites should aspire to this frequency of sampling.
Note
However, they can be sampled at least monthly (at most daily, with any rate more than weekly aggregating to a weekly average).
Samples will occur during the growing season, with samples beginning 14 days after the first butterflies are observed.
The rate at which plots or fields are sampled within an LTAR Site will be consistent across all treatments and replicates.
The rate may vary across LTAR Sites for multiple reasons (e.g., staffing or the nature of additional questions being addressed).
Measures will still be comparable across sites using standard meta-analytic approaches.
Pollard walks - Covariate metrics
Pollard walks - Covariate metrics
Immediately before surveying each transect, record the date, plot (treatment, replicate), surveyor initials, and estimated cloud cover (%).
Obtain temperature from weather station records recorded on-site or nearby.
Record the time of day and start the stopwatch at the beginning of each survey.
Collect data needed on plant diversity using the USDA LTAR Common Experiment measurement: Cropland plant diversity protocol.
Pollard walks - Location
Pollard walks - Location
All replicates of prevailing and alternative treatments.
Pollard walks - Species identification
Pollard walks - Species identification
Butterflies are a strong indicator for other insects because they are readily identified on the wing.
Data collectors are trained in one survey day by a lead investigator knowledgeable about butterfly species of the region.
Most species can be identified and learned quickly using a field guide. Some species, especially skippers, can be identified on the wing but with some difficulty. For these species, individuals can be captured and released or can be photographed.
Calculations
Calculations
An index of abundance is calculated by:
- Calculating the mean count per transect each week, and then
- Summing the mean weekly counts (Pollard 1977).
Quality assessment and quality control
Quality assessment and quality control
People conducting surveys will be trained in butterfly identification.
This training will occur through field guides and focus on the most common butterflies in a site’s experiment. Then, a new investigator will accompany a trained investigator on at least one day of butterfly surveys until the trained investigator knows the new person can identify butterflies.
Datasheets will be checked for completeness when submitted at the end of a survey day and then entered into a database.
A different person will conduct a second review, checking the entered data against the datasheet.
Finally, data will be reviewed for accuracy. This review includes any necessary adjustments to species/taxa identifications based on spelling errors, the likelihood of species occurrence in a given habitat or geographic location, and difficult identification scenarios, such as species challenging to distinguish morphologically or known to hybridize. This review also includes a check for possible miscounts or typos. For example, if a species typically occurring at low abundance has a very high count in a survey, the reviewer should check the count against the original datasheet.
Recommendations for data collection
Recommendations for data collection
Table 1. Summary of recommendations for measuring butterfly abundance and diversity.
| A | B | C | |
| Attribute | Preferred | Minimum | |
| Spatial scale | All prevailing and alternative treatments | ||
| Frequency | Once per week | Once per month | |
| Covariate metrics | Temperature, cloud cover, plant diversity, plant abundance by species |
Protocol references
The key papers describing the method
1. Pollard, E. (1977). A method for assessing changes in the abundance of butterflies. Biological conservation, 12(2), 115-134.
2. Pollard, E, and TJ Yates. 1993. Monitoring Butterflies for Ecology and Conservation. Chapman & Hall, London, UK.
On the appropriateness of the Pollard index for determining population size
Haddad, N. M., Hudgens, B., Damiani, C., Gross, K., Kuefler, D., & Pollock, K. (2008). Determining optimal population monitoring for rare butterflies. Conservation Biology, 22(4), 929-940.
Examples of the use of the method for assessing decades-long trends in butterfly abundance
Wepprich, T., Adrion, J. R., Ries, L., Wiedmann, J., & Haddad, N. M. (2019). Butterfly abundance declines over 20 years of systematic monitoring in Ohio, USA. PLoS One, 14(7), e0216270.
On why butterflies are strong indicators for other insects globally
Van Klink, R., Bowler, D. E., Gongalsky, K. B., Swengel, A. B., Gentile, A., & Chase, J. M. (2020). Meta-analysis reveals declines in terrestrial but increases in freshwater insect abundances. Science 368:417-420.
Acknowledgements
This research is a contribution from the Long-Term Agroecosystem Research (LTAR) network. LTAR is supported by the United States Department of Agriculture. The use of trade, firm, or corporation names in this publication is for the information and convenience of the reader. Such use does not constitute an official endorsement or approval by the United States Department of Agriculture or the Agricultural Research Service of any product or service to the exclusion of others that may be suitable. USDA is an equal opportunity provider and employer.