Thermally moderated firefly activity is delayed by precipitation extremes

Abstract

The timing of events in the life history of temperate insects is most typically primarily cued by one of two drivers: photoperiod or temperature accumulation over the growing season. However, an insect's phenology can also be moderated by other drivers like rainfall or the phenology of its host plants. When multiple drivers of phenology interact, there is greater potential for phenological asynchronies to arise between an organism and those with which it interacts. We examined the phenological patterns of a highly seasonal group of fireflies (Photinus spp., predominantly P. pyralis) over a 12-year period (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) across 10 plant communities to determine whether interacting drivers could explain the variability observed in the adult flight activity density (i.e. mating season) of this species. We found that temperature accumulation was the primary driver of phenology, with activity peaks usually occurring at a temperature accumulation of approximately 800 degree days (base 10°C); however, our model found this peak varied by nearly 180 degree-day units among years. This variation could be explained by a quadratic relationship with the accumulation of precipitation in the growing season; in years with either high or low precipitation extremes at our study site, flight activity was delayed. More fireflies were captured in general in herbaceous plant communities with minimal soil disturbance (alfalfa and no-till field crop rotations), but only weak interactions occurred between within-season responses to climatic variables and plant community.

Why are there so many bee‐orchid species? Adaptive radiation by intra‐specific competition for mnesic pollinators

“…Moreover, holometabolous insects can delay their emergence according to ambient weather conditions for days or even weeks (e.g. Hermann et al ., 2016). Finally, historic data of both the flowering dates of Ophrys sphegodes and the flight periods of its pollinator ( Andrena nigroaenea ) over more than 350 years provide interesting and rare evidence that Ophrys flowering periods have become increasingly imperfectly matched to the phenology of their pollinators under the effects of global warming (Hutchings et al ., 2018).…”

The Broken Window: An algorithm for quantifying and characterizing misleading trajectories in ecological processes

“…These data on firefly (beetles in the family Lampyridae, with those captured primarily thought to belong to Photinus pyralis) captures on insect sticky traps were collected 2004-2015 across 10 plant communities in southwestern Michigan. Complete sampling design and treatments descriptions are provided in Hermann et al (2016). For the purpose of this demonstration, we used the data collected at the perennial early secessional community plots, where fireflies were relatively abundant and complete data were available.…”

“…We demonstrate the utility of the bad-breakup algorithm using the firefly study which inspired its development [20]. These data on firefly (beetles in the family Lampyridae, with those captured primarily .70) and low R 2 value (0.002) suggesting there is unlikely a linear trend with time in these data (or, more accurately, we fail to reject the null hypothesis that there is no linear relationship between our response and time) (Figure 3).…”

“…A fundamental problem arises when shorter term studies apply statistical tools at time scales that are not matched with the underlying processes to make inferences about trajectory: not only may spurious trends be observed, but because only a portion of the underlying process variability is captured, a higher degree of statistical confidence in the result will be found. This concept is best illustrated with an example: in recent work, Bahlai and students examined a 12-year time series of fireflies at Kellogg Biological Station in southwestern Michigan [20] with two questions in mind:…”

“…A vexing problem arises when shorter term studies apply statistical tools at time scales that are not matched with the underlying processes to make inferences about trajectory: not only may spurious trends be observed, but because only a portion of the underlying process variability is captured, a higher degree of statistical confidence in the result will be found. For example, Bahlai and students examined a 12-year time series of firefly captures from Michigan (Hermann et al, 2016). Concerns had been raised about the status of fireflies in eastern North America (Chow et al, 2014), however, for that population, the authors found no evidence of decline over the 12 years (Fig.…”