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[This corrects the article DOI: 10.1371/journal.pone.0288407.].

Varroa mites (Varroa destructor) are parasitic mites that, combined with other factors, are contributing to high levels of honey bee (Apis mellifera) colony losses. A Varroa-active dsRNA was recently developed to control Varroa mites within honey bee brood cells. This dsRNA has 372 base pairs that are homologous to a sequence region within the Varroa mite calmodulin gene (cam). The Varroa-active dsRNA also shares a 21-base pair match with monarch butterfly (Danaus plexippus) calmodulin mRNA, raising the possibility of non-target effects if there is environmental exposure. We chronically exposed the entire monarch larval stage to common (Asclepias syriaca) and tropical (Asclepias curassavica) milkweed leaves treated with concentrations of Varroa-active dsRNA that are one- and ten-fold higher than those used to treat honey bee hives. This corresponded to concentrations of 0.025-0.041 and 0.211-0.282 mg/g leaf, respectively. Potassium arsenate and a previously designed monarch-active dsRNA with a 100% base pair match to the monarch v-ATPase A mRNA (leaf concentration was 0.020-0.034 mg/g) were used as positive controls. The Varroa mite and monarch-active dsRNA's did not cause significant differences in larval mortality, larval or pupal development, pupal weights, or adult eclosion rates when compared to negative controls. Irrespective of control or dsRNA treatment, larvae that consumed approximately 7500 to 10,500-mg milkweed leaf within 10 to 12 days had the highest pupal weights. The lack of mortality and sublethal effects following dietary exposure to dsRNA with 21-base pair and 100% base pair match to mRNAs that correspond to regulatory genes suggest monarch mRNA may be refractory to silencing by dsRNA or monarch dsRNase may degrade dsRNA to a concentration that is insufficient to silence mRNA signaling.

Varroa mites (Varroa destructor) are parasitic mites that, combined with other factors, are contributing to high levels of honey bee (Apis mellifera) colony losses. A Varroa-active dsRNA was recently developed to control Varroa mites within honey bee brood cells. This dsRNA has 372 base pairs that are homologous to a sequence region within the Varroa mite calmodulin gene (cam). The Varroa-active dsRNA also shares a 21-base pair match with monarch butterfly (Danaus plexippus) calmodulin mRNA, raising the possibility of non-target effects if there is environmental exposure. We chronically exposed the entire monarch larval stage to common (Asclepias syriaca) and tropical (Asclepias curassavica) milkweed leaves treated with concentrations of Varroa-active dsRNA that are one- and ten-fold higher than those used to treat honey bee hives. This corresponded to concentrations of 0.025-0.041 and 0.211-0.282 mg/g leaf, respectively. Potassium arsenate and a previously designed monarch-active dsRNA with a 100% base pair match to the monarch v-ATPase A mRNA (leaf concentration was 0.020-0.034 mg/g) were used as positive controls. The Varroa mite and monarch-active dsRNA's did not cause significant differences in larval mortality, larval or pupal development, pupal weights, or adult eclosion rates when compared to negative controls. Irrespective of control or dsRNA treatment, larvae that consumed approximately 7500 to 10,500-mg milkweed leaf within 10 to 12 days had the highest pupal weights. The lack of mortality and sublethal effects following dietary exposure to dsRNA with 21-base pair and 100% base pair match to mRNAs that correspond to regulatory genes suggest monarch mRNA may be refractory to silencing by dsRNA or monarch dsRNase may degrade dsRNA to a concentration that is insufficient to silence mRNA signaling.

Convolutional neural networks have a broad spectrum of practical applications in computer vision. Currently, much of the data come from images, and it is crucial to have an efficient technique for processing these large amounts of data. Convolutional neural networks have proven to be very successful in tackling image processing tasks. However, the design of a network structure for a given problem entails a fine-tuning of the hyperparameters in order to achieve better accuracy. This process takes much time and requires effort and expertise from the domain. Designing convolutional neural networks’ architecture represents a typical NP-hard optimization problem, and some frameworks for generating network structures for a specific image classification tasks have been proposed. To address this issue, in this paper, we propose the hybridized monarch butterfly optimization algorithm. Based on the observed deficiencies of the original monarch butterfly optimization approach, we performed hybridization with two other state-of-the-art swarm intelligence algorithms. The proposed hybrid algorithm was firstly tested on a set of standard unconstrained benchmark instances, and later on, it was adapted for a convolutional neural network design problem. Comparative analysis with other state-of-the-art methods and algorithms, as well as with the original monarch butterfly optimization implementation was performed for both groups of simulations. Experimental results proved that our proposed method managed to obtain higher classification accuracy than other approaches, the results of which were published in the modern computer science literature.

We studied factors associated with survival, sex ratio, and seasonality of the tachinid fly Lespesia archippivora parasitizing monarch butterflies (Danaus plexippus). A total of 424 L. archippivora flies were collected from 124 parasitized monarch larvae in 2016 and 2017. The majority of flies emerged during the monarch's 5th larval instar. Both fly survival and brood size were higher for those emerging during the 5th instar relative to flies emerging during the 4th instar or pupal stage. Brood size ranged from 1 to 10 flies, and the proportion of each brood that successfully pupated lo emerge as adults increased with brood size. Adults emerging from larger broods were lighter and smaller, which likely impacts subsequent fecundity and survival. Overall sex ratio was skewed towards males, with 222 male and 129 female adults identified. L. archippivora were recovered from monarchs both early in the season and at the end of the season, with a gap from mid-June lo mid-July; a pattern consistent with a bivoltine life cycle.

Each fall, Eastern North American monarch butterflies (Danaus plexippus) leave their northern range and migrate to their overwintering sites high atop mountains in central Mexico. Although monarchs primarily rely on the use of a bidirectional time-compensated sun compass to maintain southwards directionality en route to Mexico, on overcast sky days when directional daylight cues are unavailable, monarchs can use an inclination-based magnetic compass to maintain correct directionality. As compass cues can only be used to determine direction, monarchs must use other mechanisms for recognizing, locating, and ultimately stopping at their overwintering sites. Although previous work found no evidence of monarchs using a fine-scale magnetic map for locating their specific overwintering sites, monarchs might still use magnetic cues in a general sense, such as when recognizing that they have overshot their destination or have gone off course. Here, using righting response orientation trials, we show that fall monarchs maintain equatorward (southward) orientation even when tested under artificially generated magnetic field conditions consistent with either their overwintering sites or magnetic conditions geographically south of these sites. We also found that fall migrants exposed to overwintering-like coldness reverse their orientation poleward (northward). This result indicates that the monarch's magnetic compass is also recalibrated by the cold temperature microenvironment at the overwintering sites, as has been shown previously with its time-compensated sun compass. Our results indicate that migratory monarchs must use other cues for locating and stopping at their migratory destination. Our discovery that coldness recalibrates multiple compass mechanisms in a long-distance migratory species underscores the threat of climate change and corresponding increasing temperatures on animal migration.

In nature, the eastern North American monarch population is known for its southward migration during the late summer/autumn from the northern USA and southern Canada to Mexico, covering thousands of miles. By simplifying and idealizing the migration of monarch butterflies, a new kind of nature-inspired metaheuristic algorithm, called monarch butterfly optimization (MBO), a first of its kind, is proposed in this paper. In MBO, all the monarch butterfly individuals are located in two distinct lands, viz. southern Canada and the northern USA (Land 1) and Mexico (Land 2). Accordingly, the positions of the monarch butterflies are updated in two ways. Firstly, the offsprings are generated (position updating) by migration operator, which can be adjusted by the migration ratio. It is followed by tuning the positions for other butterflies by means of butterfly adjusting operator. In order to keep the population unchanged and minimize fitness evaluations, the sum of the newly generated butterflies in these two ways remains equal to the original population. In order to demonstrate the superior performance of the MBO algorithm, a comparative study with five other metaheuristic algorithms through thirty-eight benchmark problems is carried out. The results clearly exhibit the capability of the MBO method toward finding the enhanced function values on most of the benchmark problems with respect to the other five algorithms. Note that the source codes of the proposed MBO algorithm are publicly available at GitHub ( https://github.com/ggw0122/Monarch-Butterfly-Optimization , C++/MATLAB) and MATLAB Central ( http://www.mathworks.com/matlabcentral/fileexchange/50828-monarch-butterfly-optimization , MATLAB).

What makes a flagship species effective in engaging conservation donors? Large, charismatic mammals are typically selected as ambassadors, but a few studies suggest butterflies—and monarchs in particular—may be even more appealing. To gather more information about people’s responses to monarchs, we conducted an empirical study of member submissions to a successful conservation campaign, the Monarch Story Campaign, conducted by the Environmental Defense Fund (EDF). The set of 691 stories along with their associated demographic and donation data was analyzed in a mixed-methods study using qualitative analysis and tests of association. The results showed that people often described encounters with monarchs in childhood and as adults. They expressed strong, positive emotions, and lauded the monarch’s beauty and other “awe-inspiring” qualities and expressed wonder at their lifecycle (i.e., metamorphosis and migration). They also raised conservation themes of distress at monarch loss, calls for action, and caretaking, such as being “fragile” and “in need.” Sharing personal encounters was associated with current efforts to save the species and more past financial donations, while a second pattern tied more donations to awe at the monarch’s mass migration. These results imply that conservation campaigns built around species people encounter may build lifelong awareness, concern, and actions towards conservation.

North American monarch (Danaus plexippus) populations have experienced sharp declines. Loss of milkweed is among the major drivers of this decline. Our objective is to identify factors that influence milkweed habitat quality for monarchs to inform habitat reconstruction efforts. We measured the response of monarch egg abundance to milkweed patch characteristics (milkweed species identity and co-occurring insects) and features of the surrounding landscape (wildflower nectar plants and land use context). From May through September 2019 and 2021, we assessed the abundance of naturally occurring monarch eggs, lady beetles (predators), and aphids (competitors) on swamp milkweed (Asclepias incarnata) and common milkweed (A. syriaca) plants established in a diverse matrix of wildflower nectar plants or monoculture of fescue grass and located in open row crop habitats or abutting wooded edges. We found that local patch characteristics had the largest effects on monarch egg abundance. Egg abundance differed across milkweed species, but the milkweed species with the highest monarch egg abundance switched from common milkweed in 2019 to swamp milkweed in 2021. We also found that monarch egg abundance was positively associated with oleander aphid (Aphis nerii) abundance on both milkweed species, despite significantly higher aphid abundance on swamp milkweed than common milkweed. Lady beetles exhibited a numerical response to oleander aphid prey, but there was no evidence that greater numbers of these generalist predators negatively affected monarch eggs. Landscape features also influenced monarch egg abundance, but the effects varied across milkweed species and years. In 2019, egg abundance was higher on swamp milkweed near trees than in open crop fields, while proximity to wildflower nectar plants increased egg abundance on common milkweed; landscape features did not directly affect egg abundance in 2021. Our results highlight the important role of environmental context in mediating the conservation value of milkweed plantings for monarchs.