butterflies in ohio

Severe insect declines make headlines, but they are rarely based on systematic monitoring outside of Europe. We estimate the rate of change in total butterfly abundance and the population trends for 81 species using 21 years of systematic monitoring in Ohio, USA. Total abundance is declining at 2% per year, resulting in a cumulative 33% reduction in butterfly abundance. Three times as many species have negative population trends compared to positive trends. The rate of total decline and the proportion of species in decline mirror those documented in three comparable long-term European monitoring programs. Multiple environmental changes such as climate change, habitat degradation, and agricultural practices may contribute to these declines in Ohio and shift the makeup of the butterfly community by benefiting some species over others. Our analysis of life-history traits associated with population trends shows an impact of climate change, as species with northern distributions and fewer annual generations declined more rapidly. However, even common and invasive species associated with human-dominated landscapes are declining, suggesting widespread environmental causes for these trends. Declines in common species, although they may not be close to extinction, will have an outsized impact on the ecosystem services provided by insects. These results from the most extensive, systematic insect monitoring program in North America demonstrate an ongoing defaunation in butterflies that on an annual scale might be imperceptible, but cumulatively has reduced butterfly numbers by a third over 20 years.

Citation: Wepprich T, Adrion JR, Ries L, Wiedmann J, Haddad NM (2019) Butterfly abundance declines over 20 years of systematic monitoring in Ohio, USA. PLoS ONE 14(7): e0216270. https://doi.org/10.1371/journal.pone.0216270

Copyright: © 2019 Wepprich et al. This is an open access article 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.

Data Availability: Data and code to reproduce the analysis are available from Dryad (https://doi.org/10.5061/dryad.cf78420). Raw data from the monitoring program are available from the North American Butterfly Monitoring Network (www.thebutterflynetwork.org) upon request.

Defaunation, or the drastic loss of animal species and declines in abundance, threatens to destabilize ecosystem functioning globally [1]. In comparison to studies of vertebrate populations, monitoring of changes in insect diversity is more difficult and far less prevalent [2,3]. Despite this, a global analysis of long-term population trends across 452 species estimated that insect abundance had declined 45% over 40 years [1]. Recently, more extreme declines in insect biomass have been observed upon resampling after 2–4 decades [4,5]. Losses of total biomass or total abundance across all species may be more consequential than local declines in species diversity, as common insect species contribute the most to ecosystem services, such as pollination [6]. However, our knowledge of insect declines is skewed towards European monitoring programs, including in global analyses [1]. In this study, we analyze long-term, region-wide trends in abundance across a diversity of species for an entire insect group in North America to examine the scope of insect defaunation.

The best source of data to assess insect defaunation comes from large-scale, systematic monitoring programs of multiple species [3]. Through these efforts, trained volunteers or citizen scientists have contributed much of the evidence for biotic responses to anthropogenic climate warming such as changes in insect phenology and range distributions [7,8]. Unlike citizen science reporting of opportunistic observations or species checklists, many insect monitoring programs use a systematic protocol developed specifically to track butterfly abundances through time, both within and between seasons, and over large spatial scales [9]. Pollard-based monitoring programs, modeled after the first nationwide Butterfly Monitoring Scheme launched in the United Kingdom in 1977 (UKBMS), use weekly standardized counts on fixed transects [10]. Their widespread adoption enables regional comparisons of insect responses to environmental change or defaunation [11,12]. We compare our analysis with exemplary long-term monitoring schemes from Europe to test if the rate of insect declines generalizes across continents.

The best source of abundance data for assessment of chronic insect decline, and the most prominent source of data in [1], is within the butterflies. Due to the relative ease and popularity of monitoring butterflies, environmental assessments use them as an indicator taxa for the general trajectory of biodiversity, assuming that they experience comparable pressures from land-use change, climate change, and habitat degradation as other insect taxa [13–15]. Intensive long-term monitoring of individual butterfly species has provided rigorous, quantitative estimates of declines. Most prominently, the Eastern North American Monarch has declined by over 85% [16] and the Western North American Monarch by over 95% [17] over the past two decades. Severe declines have also been observed in some of the rarest butterflies [18,19]. These data from individual species of conservation concern may not represent a broader trend across butterflies, which is what we aim to document in this study.

Volunteers, organized and trained by The Ohio Lepidopterists, have assembled the most extensive dataset of systematic butterfly counts that stands alone in North America in terms of the spatial extent and sampling frequency of Pollard walks [9]. Three other monitoring programs in the United States have documented long-term, multi-species population trends. In Massachusetts, based on species lists from field trips, climate-driven community shifts explain how the relative likelihood of species observations change over 18 years [20]. Shapiro and colleagues have made biweekly presence/absence observations and Pollard-based counts on 11 fixed transects along an elevational gradient in California over more than 45 years to document species richness changes in response to climate and land-use, increasing abundance at a high elevation site, and impacts of agricultural practices on abundance at low elevation sites [21,22]. Several teams have monitored declines in specialist butterflies restricted to native prairie patches in the Midwestern states with transect or timed survey methods over 26 years [23,24]. The growing number of Pollard-based monitoring programs in the United States [9] has the potential to track how widespread and consistent butterfly trends are across regions.

Here, we used 21 years of weekly butterfly surveys across 104 sites to assess abundance trends for butterflies in Ohio. We estimate population trends for 81 species and test for their association with life-history traits and phylogenetic relatedness. We review findings from European butterfly monitoring schemes for quantitative comparison with the rate of abundance changes in Ohio. This analysis provides evidence of widespread insect defaunation and species’ declines from the most extensive, systematic monitoring program in North America.

We studied butterfly population trends across the state of Ohio in the Midwestern USA. Over its 116,100 km2 land area, Ohio has a mosaic of habitat types due to its partially glaciated history and its place at the confluence of Midwestern prairies, the Appalachian Mountains, and the boreal forest [25]. Only remnants of wetland and prairie habitat remain in the state due to human modification of the landscape. Some rare butterflies have declined due to forest succession following suppression of disturbances [26]. Agriculture and pastures (50%), forest (30%), and urban development (10%) are the predominant land-use/land cover classes [27].

Monitoring sites have a Northeast to Southwest gradient in their mean annual temperatures (mean 18.8°C, range from 14.0°C to 23.6°C) from interpolated daily temperatures from Daymet over 1996–2016 [28]. Mean annual temperatures at these sites grew at a linear trend of 0.3°C per decade and growing season length has increased by 60 degree-days (base 5°C) per decade from 1980–2016. Monitoring sites span the state but are concentrated near cities (Fig 1). On average, within a radius of 2 kilometers, monitoring sites have 24% cropland and pasture, 34% forest, and 30% urban land-use based on the National Land Cover Dataset [29]. Although not considered in this study, impervious surfaces from urban development influence temperature-dependent butterfly phenology in Ohio through the urban heat island effect, which may not be fully captured in these gridded temperature interpolations [30]. Download:

Of the 147 sites, this analysis used the 104 sites monitored for three or more years.

Trained volunteers contributed 24,405 butterfly surveys from 1996 to 2016 as part of the Ohio Lepidopterists Long-term Monitoring of Butterflies program. Volunteers surveyed on fixed paths at approximately weekly intervals during the entire growing season from April through October (median 23 of 30 weeks surveyed per year per site) and count every species within an approximate 5-meter buffer around the observer [10]. Surveys are constrained to times of good weather to increase the detectability of butterflies and last a mean 85 minutes in duration. The annual number of monitored sites ranged from 13 in 1996 to a maximum of 80 in 2012. We limited our analysis of abundance trends to the 104 sites with three or more years of monitoring data and 10 or more surveys per year at each site (Fig 1). We included observations of all sites with at least 5 surveys per year in phenology models that we used to interpolate missing counts before estimating abundance [31].

All 102 species with population indices estimated by phenology models contributed to the total abundance analysis. We limited species-specific analysis to 81 species with sufficient population indices for estimating trends (present at five or more sites and for 10 or more years). Species naming conventions in the monitoring program follow those used in [25,32] except for combining all observations of Celastrina ladon (Spring Azure) and Celastrina neglecta (Summer Azure) as an unresolved species complex.

We estimated population indices for each site x year x species by adapting methods established for the UKBMS that account for missing surveys and butterfly phenology over the season [31,33]. We used generalized additive models for each species to estimate variation in counts in order to interpolate missing surveys with model predictions [31,34]. To account for seasonal, spatial, and interannual variation in species phenology, we extended the regional generalized additive model approach (12, Supplement 1) by including spatially-explicit site locations and converting calendar dates of observations to degree-days [35], which can improve butterfly phenology predictions [36]. We calculated the population index by integrating over the weekly counts and missing survey interpolations using the trapezoid method [31].

Controlling for confounding factors

We accounted for differences in sampling across sites and years so that our modeled trends would capture changes in abundance rather than changes in detection probability [37]. True abundance is confounded with detection probability when using counts from Pollard walks [38]. Butterfly monitoring protocols that account for detection probability like distance sampling are commonly used for single-species studies [39], but untenable for scaling up to a regional program. Most analyses of Pollard walks assume no systematic change in detectability (but see [40]) because counts correlate closely with true abundance estimates from distance sampling [41,42]. We used two covariates to account for variation in sampling and its influence on population indices for each site x year [20,37,43]. We tracked the mean number of species reported in each survey, or list-length, which is a synthetic measure of factors influencing detectability such as weather conditions, site quality, and observer effort [20,44,45]. We treated the total duration of surveys in minutes as an offset in the models of population trends. Because we interpolated missing surveys for the population indices, we projected what the total duration would be if all 30 weeks had been surveyed at the mean duration reported for that site x year.

Sampling across the state is nonrandom because participants choose transect locations, a common practice in volunteer-based monitoring programs. Since sites generally cluster near human population centers with a greater proportion of developed land-use and a lesser proportion of agriculture, we assumed that population trends at the 104 sites across the state sufficiently capture the broader statewide trends [37]. Comparisons between the UKBMS volunteer-placed transects and a broader survey with stratified, random sampling show congruence between species trends estimated from each monitoring strategy [46].

We used generalized linear mixed models to estimate temporal trends in relative abundance for 81 species from their population indices [47]. We modeled population indices at each site and year as an over-dispersed Poisson random variable with covariates on the log-link scale. (1)

We included the numeric year and mean list length for each population index as covariates, which were centered to aid in model fitting and interpretation [48]. We used the coefficient for year (β2) as the annual trend in population indices as our main result. We controlled for changes in sampling by using the total duration of surveys as a model offset, converting the dependent variable to a rate of butterflies counted per minute. Random effects of individual sites and years account for spatial and temporal variation in population counts deviating from the statewide trend. We accounted for over-dispersion in the Poisson-distributed counts with the random effect siteyearID for each unique observation [49]. We modeled trends in total abundance using the same modeling approach, but summed across 102 species’ population indices for each site x year observation. We interpreted trends as an annual rate by taking the geometric mean rate of change between the predicted abundance between two points in time after setting the list-length covariate to its mean and excluding the random effects [47]. For comparisons with other monitoring programs, we used a p-value threshold of 0.05 to classify trends as positive, negative, or stable.

Our approach is similar to that used by the UKBMS and other European monitoring programs which use generalized linear models in TRIM software [50]. One key difference is that our site and annual fluctuations from the temporal trend were derived from random effects rather than fixed effects, which reduces spurious detection of trends [43]. Another key difference is that TRIM does not allow for continuous covariates, which we used to account for sampling variation instead of assuming no confounding pattern in sampling effort. To validate that our modeling choices did not unreasonably influence the results, we used three alternative approaches: (1) a Poisson-based generalized linear model (Eq 1 without the random effect siteyearID); (2) a nonlinear generalized additive mixed model with a smoothing spline replacing the linear temporal trend [43]; and (3) a TRIM model with over-dispersion and serial temporal correlation but no sampling covariates or offsets [50]. We compared similarity in the total abundance trends, the correlation of species’ trends between model alternatives, and the classification of species’ trends as positive, stable, or negative.

Habitat loss and fragmentation

In Ohio, habitat loss and fragmentation plateaued well before butterfly monitoring started, with human population growth slowing by 1970. In common with other Midwestern states, Ohio had already lost tallgrass prairie species, such as the Regal Fritillary (Speyeria idalia), due to habitat conversion to agriculture [25,26]. Land-use has changed slowly over the course of the monitoring program; fewer than 10% of monitoring sites have had more than 2.5% change in the surrounding (2-km radius) developed, agriculture, or forest land cover from 2001–2011 [29]. The persistence of butterfly populations in a landscape of habitat fragments are mediated by species’ traits that permit them to either move between more isolated resources or persist in smaller, localized populations [85,87]. Wing size is one life history trait associated with dispersal ability, but it had no association with species’ population trends (Tables A and B in S1 Appendix). However, defining habitat patches by land-use classes overlooks how mobile insect populations are bound by resources, varying across the lifecycle, rather than area [88,89]. Although there has been little wholesale habitat conversion around our study transects, degradation of the remaining habitat could be a cause of the general decline in butterfly abundance.

Species trends are associated with two life-history traits, voltinism and range distribution, which suggest that the butterfly community is changing with the warming climate. Species that only complete one annual generation, or univoltine species, had more negative abundance trends. This aligns with obligate univoltine species becoming less common in Massachusetts [20], but is the opposite of the findings in Spain where multivoltine species are in steeper declines with exposure to increasingly dry summers [40]. Multivoltine species may be more adaptive to annual and spatial variation in growing season length as many have plasticity in the voltinism observed within Ohio [25]. For many species with flexible voltinism in Ohio, adding an extra generation in warmer summers increases their annual population growth rates [55]. Northern-distributed species have more negative population trends compared to widely distributed or southern species. This corresponds with findings from Massachusetts and Europe that warm-adapted species are replacing cool-adapted species as range distributions shift [20,90]. Even though these two traits should increase abundance for some species as the climate warms, it has not been enough to prevent the overall decline in butterfly abundance.

Cropland and pasture make up half of Ohio’s land area, so we would expect agricultural practices to affect statewide insect abundance. One assessment of pollinator habitat suitability based on land-use, conservation reserve program acreage, and crop type estimated an increase in resources in Ohio from 1982 through 2002, followed by a stable trend [91]. However, agricultural practices can decrease insect abundance with systemic insecticides, herbicide use on host plants or nectar resources, and nitrogen fertilization that alters the composition of surrounding plant communities.

In Ohio, the use of neonicotinoids rapidly increased after 2004 when they became widely used on corn and soybeans [92,93]. The mechanistic link between neonicotinoid insecticides and insect declines is established and observational studies have shown widespread impacts of their use [94–96]. Even though seed-coatings with neonicotinoids reduce broadcast spraying, the mechanical planting of these seeds exposes widespread areas around farms to contaminated dust that exposes non-target plants and insects to biologically-relevant concentrations [97,98]. In the United Kingdom and California, neonicotinoids are associated with butterfly declines [22,99] and hinder butterfly larval development on host plants [100]. We did not design this study to test whether neonicotinoids affect butterfly abundance in Ohio. However, the observed declines across common and generalist species, which we otherwise would expect to exploit an agricultural or human-altered landscape, would be consistent with widespread exposure to insecticides.

Species that eat forbs as larvae have negative population trends (Fig 5). Both herbicide use and nitrogen deposition may alter plant communities to favor grasses over forbs [101]. In Ohio, glyphosate use has increased linearly, and is now applied at 6 times the rate it was in 1996 [92,93]. Milkweed losses, attributed to increased glyphosate use in the Midwest, contribute to declines in Monarch butterfly abundance [79,80]. Nitrogen increases, which may come from fertilization or atmospheric deposition, have been linked to declines in grassland butterfly species adapted to low-nitrogen environments [102–104] and to higher mortality during larval development on enriched host plants [105].

Systematic, long-term surveys of butterflies provide the most rigorous estimate for the rate of insect declines. This study demonstrates that defaunation is happening in North America similarly to Europe. In landscapes comprising natural areas amid heavy human land-use, butterfly total abundance is declining at 2% per year and 2–3 times more species have population trends declining rather than increasing. Additional Pollard-based monitoring programs in North America, listed in [9], will enable tracking insect trends over larger spatial extents as will efforts to integrate data across European monitoring schemes [11]. The rates for other insect groups may deviate from this baseline and were previously estimated to be declining more rapidly than Lepidoptera [1]. Expanded monitoring and support for taxonomists are imperative for other taxa and under sampled regions, like the Tropics where most insect diversity resides. Besides the evaluation if butterfly trends generalize to other insects, the most urgent research needs are understanding the causes of decline and testing mitigation strategies. As butterflies are the best-monitored insect taxa, they are the best indicator of the baseline threat to the 5.5 million insect species, the most diverse group of animals on earth.

The Butterflies of Adams County, Ohio

FAQ

What is the most common butterfly in Ohio?

• 6 Most Common Butterflies In Ohio.
• Viceroy. Nectar Plants: Asters, Joe-Pye Weed, Golden Rod, Phlox. …
• Painted Lady. Nectar Plants: Joe-Pye Weed, Liatris (Blazing Star), Bee Balm, Goldenrod, Phlox, Asters. …
• Spice Bush Swallowtail. …
• Eastern Black Swallowtail. …
• Eastern Tiger Swallowtail. …
• Monarch. …
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Is it good to have butterflies in your yard?

Butterflies are great for your garden as they are attracted to bright flowers and need to feed on nectar. When they do this their bodies collect pollen and carry it to other plants. This helps fruits, vegetables and flowers to produce new seeds.

What time of year are monarchs in Ohio?

Many arrive in Ohio in the early summer. Here, they eat and reproduce. The fourth generation flies back to Mexico in the late summer/early fall.

What are the rare butterflies in Ohio?

Four butterflies are endangered in Ohio. Three of these, Erynnis persius (Scudder), Incisalia irus (Godart), and Lycaeides melissa samuelis Nabokov, are restricted to the Oak Openings and use Lupinus perennis L. as the larval host.