Changes in phenology and abundance of an at-risk butterfly

Bonoan, Rachael E.; Crone, Elizabeth E.; Edwards, Collin B.; Schultz, Cheryl B.

doi:10.1007/s10841-021-00318-7

Cited by 10 publications

(14 citation statements)

References 62 publications

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“…3 . As expected, given the correlation between the observable activity period and egg abundance [ 55 ], the number of the days when predicted mEggs w was > 1 decreased with increasing altitude, from ~ 220 days within the lowest range (0–200 m asl) to ~ 140 days within the highest range (801–1000 m asl). The time interval of 80EA, which had a mean of 74 days (± 3.5), did not show a clear decreasing trend with increasing altitude, since it is not correlated with egg abundance [ 57 ].…”

Section: Resultssupporting

confidence: 72%

“…The time interval within which 80% of the eggs (mEggs w ) were laid (80EA) was calculated as the number of days between the 10th and 90th percentiles. The observable activity period was calculated as the number of days when the predicted mEggs w was > 1 [ 55 ]. Furthermore, the first and last DOY of egg-laying activity were determined, respectively, as the day when mEggs w exceeded zero or dropped to zero, according to the predicted values from the Gaussian models.…”

Section: Methodsmentioning

confidence: 99%

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Aedes albopictus abundance and phenology along an altitudinal gradient in Lazio region (central Italy)

et al. 2022

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Background The Asian tiger mosquito Aedes albopictus (Skuse 1894), which is native to Southeast Asia, is among the top 100 invasive species worldwide and one of the most troubling vector species. It has become established in more than 20 European countries. Since its arrival in Italy in the 1990s, the species has colonized all the regions of the country, up to an altitude of 600 m. Nevertheless, no thorough investigation has ever been performed to confirm or extend its elevation limit (EL) in Italy. Methods To define the EL of Ae. albopictus and analyse its phenology along an altitudinal gradient, we carried out an investigation by means of ovitraps placed in Lazio region, central Italy. Sampling was performed on a weekly basis in 13 villages within five 200-m altitudinal ranges [0–1000 m above sea level (asl)], with the addition of higher localities to the species range whenever the species was recorded in the highest range. Results Aedes albopictus has colonized sites well beyond its known EL, with established populations at 900 m asl and positive ovitraps recorded at 1193 m asl. The relationship between egg abundance and elevation was described by an exponential decay regression, which predicted an EL for oviposition at 1015 m asl. In the active season, egg-laying started earlier at low altitude and ended earlier within the highest altitudinal range. Aedes albopictus abundance and activity period (number of days active) decreased, respectively, by 95% and 34% from the lowest to the highest altitudinal range. Conclusions Using data from the present study, the altitudinal limit of Ae. albopictus in central Italy was updated from 600 to 900 m asl. In addition, established populations were predicted to exist up to 1015 m asl. Considering that up to 99.5% of Lazio region’s inhabitants could potentially be affected by Aedes-borne virus outbreaks, the surveillance area for Ae. albopictus should be expanded accordingly. However, our results also indicate that Ae. albopictus surveillance programs need to be revised in order to harmonize the resources earmarked for these with the altitudinal changes in the phenology of this species. Graphical abstract

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Section: Resultssupporting

confidence: 72%

Section: Methodsmentioning

confidence: 99%

Aedes albopictus abundance and phenology along an altitudinal gradient in Lazio region (central Italy)

et al. 2022

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“…The 0.1 quantile (hereafter, the start of migration range) corresponds to the day when 10% of the migration curve has occurred; the 0.5 (hereafter, the migration midpoint) corresponds to the median day of the migration (which differed from the day of the peak if the migration was not symmetric); and the 0.9 quantile (hereafter, the end of migration range) corresponds to the day when 90% of the migration curve has occurred. These specific quantiles are similar to those used in other recent phenology studies (e.g., Bonoan et al, 2021;Jonzén et al, 2006;Newson et al, 2016).…”

Section: Southbound Migrationsupporting

confidence: 67%

“…However, such measures are subject to individual variation and population size biases (Edwards & Crone, 2021 ; Tryjanowski & Sparks, 2001 ) and do not describe the population‐level phenomenon of migration phenology (Carter et al, 2018 ; Goodenough et al, 2015 ; Inouye et al, 2019 ). One solution is to use quantiles (or percentiles) representing proportions of a population's phenological distribution, as they are unbiased analogs for describing relative timing within the distribution (Bonoan et al, 2021 ). For example, the 0.05 or 0.1 quantile are phenological landmarks (i.e., identifiable points within the migration distribution) representing initial or early activity, while the 0.9 or 0.95 quantile similarly represents late activity (Jonzén et al, 2006 ; Newson et al, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Quantifying phenological landmarks of migration shows nonuniform use of the Caribbean by shorebirds

Cañizares

Edwards

Reed

2023

Ecology and Evolution

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Of the boreal-and Arctic-breeding North American shorebirds that migrate south through the Caribbean, most individuals continue farther south. However, for many species, some individuals remain beyond the southbound migration period (i.e., throughout the temperate winter and/or summer). This variation among individuals adds complexity to observation data, obscures migration patterns, and could prevent the examination of the use of different Caribbean regions by various shorebird species during migration and in the nonmigratory seasons. Here, we present a novel method that leverages a well-established statistical approach (generalized additive models) to systematically identify migration phenology even for complex passage migrant species with individuals that remain beyond migration. Our method identifies the active migration period using derivatives of a fitted GAM and then calculates phenology metrics based on quantiles of that migration period. We also developed indices to quantify oversummering and overwintering patterns with respect to migration. We analyzed eBird data for 16 North American shorebird species as they traveled South through the insular Caribbean, identifying separate migratory patterns for Cuba,

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“…Second, many North American solitary bee species are in decline (Bartomeus et al, 2013; LeCroy et al, 2020), and we want to understand the causes of these declines. Changes in phenology can have positive impacts on insect populations (Duchenne, Thébault, Michez, Gérard, et al, 2020; Macgregor et al, 2019; Michielini et al, 2021), including matching of life cycles to new environmental conditions (Bonoan et al, 2021) and the possibility for additional generations in multivoltine species (Kerr et al, 2020). However, there are also notable examples of shifts having negative impacts on population viability, due to mismatches between altered phenology and interacting species (Kudo & Ida, 2013) or environmental cues for different life cycle events (Van Dyck et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Ecological traits explain long‐term phenological trends in solitary bees

Dorian

McCarthy

Crone

2022

Journal of Animal Ecology

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Across taxa, the timing of life‐history events (phenology) is changing in response to warming temperatures. However, little is known about drivers of variation in phenological trends among species. We analysed 168 years of museum specimen and sighting data to evaluate the patterns of phenological change in 70 species of solitary bees that varied in three ecological traits: diet breadth (generalist or specialist), seasonality (spring, summer or fall) and nesting location (above‐ground or below‐ground). We estimated changes in onset, median, end and duration of each bee species' annual activity (flight duration) using quantile regression. To determine whether ecological traits could explain phenological trends, we compared average trends across species groups that differed in a single trait. We expected that specialist bees would be constrained by their host plants' phenology and would show weaker phenological change than generalist species. We expected phenological advances in spring and delays in summer and fall. Lastly, we expected stronger shifts in above‐ground versus below‐ground nesters. Across all species, solitary bees have advanced their phenology by 0.43 days/decade. Since 1970, this advancement has increased fourfold to 1.62 days/decade. Solitary bees have also lengthened their flight period by 0.44 days/decade. Seasonality and nesting location explained variation in trends among species. Spring‐ and summer‐active bees tended to advance their phenology, whereas fall‐active bees tended to delay. Above‐ground nesting species experienced stronger advances than below‐ground nesting bees in spring; however, the opposite was true in summer. Diet breadth was not associated with patterns of phenological change. Our study has two key implications. First, an increasing activity period of bees across the flight season means that bee communities will potentially provide pollination services for a longer period of time during the year. And, since phenological trends in solitary bees can be explained by some ecological traits, our study provides insight into mechanisms underpinning population viability of insect pollinators in a changing world.

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Changes in phenology and abundance of an at-risk butterfly

Cited by 10 publications

References 62 publications

Aedes albopictus abundance and phenology along an altitudinal gradient in Lazio region (central Italy)

Aedes albopictus abundance and phenology along an altitudinal gradient in Lazio region (central Italy)

Quantifying phenological landmarks of migration shows nonuniform use of the Caribbean by shorebirds

Ecological traits explain long‐term phenological trends in solitary bees

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