Ants Sleep, Plants do not: The Variation in Species’ Activity Influences the Topology of Interaction Networks

The emergence of graph theory allowed using the complex network approach to aggregate detailed information about interactions between species. Although the use of the complex network approach has improved the understanding about community structuring, few aspects such as the temporal variation in the species’ activity pattern in the networks’ topology were explored so far. The current study used the ecological network approach to investigate ants interacting in the extrafloral nectary (EFN) of plants in order to test the hypothesis that the temporal variation in the foraging behavior of these animals affects the networks’ topology. In order to assess the temporal effect on the interaction networks, 24-hour collections divided in two 12-hour shifts (day and night) were performed in 20 plots, thus totaling 288 collection hours over 6 months. The ant-plant interaction networks presented similarity among the topological metrics assessed throughout the day. Different ant species presented distinct foraging times. Thus, two modules referring to the day and night shifts emerged from the network and presented specific species at each foraging shift. On the other hand, the plants kept on providing the resource (active EFNs) throughout the day. The results found in the current study have shown that ecological networks keep their structures constant; however, the ecological processes ruling these networks can better respond to the effects caused, for example, by the temporal variation in species’ activity. Therefore, it is worth always taking into consideration the importance of ecological processes at the time to analyze interactions in the nature

Bringing Innovations to Set Up a Better Scientific Journal for Publication of Your Research

The journal Sociobiology announces the adoption of a series of editorial innovations that aim to speed up review and publication time, to select high quality articles for publication, to adopt transparent and ethical editorial standards and to reinforce the culture of open acess scientific publishing

Food niche of solitary and social bees (Hymenoptera: Apoidea) in a Neotropical Savanna

In this study we investigated the group of floral resources that support bee populations from a bee assemblage in a savanna, and the way in which bee species use these food resources, with an emphasis on the breadth and overlap of trophic niches. The interactions between 75 species of bees and 62 species of plants visited to obtain floral resources were recorded on a Brazilian savanna site. The bee species explored a diverse set of plant species, but concentrated the collection of resources in a few plant species. The distribution of the samples over a long period favored a robust characterization of the food niche of the bee populations. Byrsonima sericea, Serjania faveolata, and Stigmaphyllon paralias were the plant species with the highest number of links with bees. In general, the trophic niche overlap was low, with 75% of pairs of bee species having a niche overlap (NO) less than 0.33. Only four pairs showed high overlap (NO>0.70) and all cases were related to the exploitation of floral resources provided by B. sericea, a key resource for the maintenance of the local bee fauna, an oil and pollen provider

The Similar Usage of a Common Key Resource Does Not Determine Similar Responses by Species in A Community of Oil-collecting Bees

Variations in abundance and species richness among communities are often determined by interactions between biotic and abiotic factors. However, for communities composed of species that share a common specialization (such as similar foraging adaptations) it may be a key ecological factor involved in the common specialization that affects community variations. To evaluate this possibility, we characterized the guild of oil-collecting bees of a Neotropical savanna in Brazil and tested whether differences in Byrsonima abundance and availability of floral oil explain differences in species richness and abundance of oil-collecting bees of different tribes. Both the number of species and total abundance of Centridini species increased with the abundance of Byrsonima. One plausible explanation for the stronger adjustment between the abundance of Centridini and Byrsonima is that the abundance of these plants affects not only the availability of floral oil, but also of pollen. These findings indicate that the existence of a common specialization among different species does not homogenize their response to variations in a common explored resource

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

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