Mechanism of the wing colouration in the dragonfly Zenithoptera lanei (Odonata: Libellulidae) and its role in intraspecific communication

AbstractZenithoptera dragonflies are known for their remarkable bluish colouration on their wings and unique male behaviour of folding and unfolding their wings while perching. However, nothing is known about the optical properties of such colouration and its structural and functional background. In this paper, we aimed to study the relationship between the wing membrane ultrastructure, surface microstructure and colour spectra of male wings in Zenithoptera lanei and test the hypothesis that colouration functions as a signal in territorial fights between males. The results show that the specific wing colouration derives from interference in alternating layers of melanized and unmelanized cuticle in the wing membrane, combined with diffuse scattering in two different layers of wax crystals on the dorsal wing surface, one lower layer of long filaments, and one upper layer of leaf-shaped crystals. The results also show that the thicker wax coverage of the dorsal surface of the wings results in increased brightness and reduced chroma. In the field experiments, we have demonstrated that there is a reduction of aggressive reactions of rivals towards individuals with experimentally reduced amount of blue wing colouration

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

FIGURE 1 in Description of the larva of Mnesarete pudica (Hagen in Selys, 1853) (Odonata: Calopterygidae) and notes on known genera of South American Calopterygidae larvae

FIGURE 1. Mnesarete pudica, final instar larva. (A) head, dorsal view; (B) antenna; (C) labium, dorsal view; (D) labial palp; (E) laccinia, ventral and lateral views; (F) left mandible, inner view; (G) right mandible, inner view; (H) pronotum, dorsal view; (I) lateral view of abdominal segments 4–10; (J) tibia