Design Implications for Surveys to Monitor Monarch Butterfly Population Trends

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2019-05-01
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Kinkead, Karen
Harms, Tyler
Dinsmore, Stephen
Frese, Paul
Murphy, Kevin
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Dinsmore, Stephen
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Natural Resource Ecology and Management
The Department of Natural Resource Ecology and Management is dedicated to the understanding, effective management, and sustainable use of our renewable natural resources through the land-grant missions of teaching, research, and extension.
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Natural Resource Ecology and ManagementCenter for Survey Statistics and Methodology (CSSM)
Abstract

The Iowa Multiple Species Inventory and Monitoring (MSIM) Program includes a protocol for monitoring butterfly density on conservation lands using transects. Most data are collected from sites chosen randomly; additional sites are chosen non-randomly for other reasons. We analyzed a 12-year dataset for monarchs to address how density (per 50 m2 transect section) responded to site selection (random vs. non-random), latitude, and measures of the amount of milkweed and canopy cover on survey transects. Between 2006 and 2017, we conducted 2,328 surveys on 420 sites and detected a total of 2,757 adult monarchs. Monarch densities peaked in 2010 for random sites and 2012 for non-random sites, but densities were lowest in 2013 for both site types. The density of monarchs at non-random transects (0.047, 95% CI = 0.031, 0.062) was higher than that at random transects (0.029, 95% CI = 0.019, 0.044) and the temporal trends of density for random and non-random sites were significantly different. Monarch density was positively correlated with UTM northing, suggesting that monarch density increases from south to north in Iowa. The percent of plots containing milkweed was positively correlated with monarch density whereas percent tree canopy cover was negatively correlated with monarch density. Our results show that non-random transects had more monarchs, which may be a concern when interpreting findings from some citizen science efforts that used non-probabilistic sampling designs. Collectively, the MSIM program data provide a comprehensive assessment of monarch densities statewide as well as the first empirically-derived density estimates for monarchs on the breeding grounds and may prove helpful when refining future monitoring efforts.

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This article is published as Kinkead, Karen E., Tyler M. Harms, Stephen J. Dinsmore, Paul W. Frese, and Kevin T. Murphy. "Design implications for surveys to monitor monarch butterfly population trends." Frontiers in Ecology and Evolution 7 (2019): 195. doi: 10.3389/fevo.2019.00195.

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Tue Jan 01 00:00:00 UTC 2019
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