The context dependency of pollinator interference: How environmental conditions and co-foraging species impact floral visitation

Robustness and Complexity of Directed and Weighted Metabolic Hypergraphs

Metabolic networks are probably among the most challenging and important biological networks. Their study provides insight into how biological pathways work and how robust a specific organism is against an environment or therapy. Here, we propose a directed hypergraph with edge-dependent vertex weight as a novel framework to represent metabolic networks. This hypergraph-based representation captures higher-order interactions among metabolites and reactions, as well as the directionalities of reactions and stoichiometric weights, preserving all essential information. Within this framework, we propose the communicability and the search information as metrics to quantify the robustness and complexity of directed hypergraphs. We explore the implications of network directionality on these measures and illustrate a practical example by applying them to a small-scale E. coli core model. Additionally, we compare the robustness and the complexity of 30 different models of metabolism, connecting structural and biological properties. Our findings show that antibiotic resistance is associated with high structural robustness, while the complexity can distinguish between eukaryotic and prokaryotic organisms.

Honey bees (Apis mellifera) modify plant-pollinator network structure, but do not alter wild species' interactions

Honey bees (Apis mellifera) are widely used for honey production and crop pollination, raising concern for wild pollinators, as honey bees may compete with wild pollinators for floral resources. The first sign of competition, before changes appear in wild pollinator abundance or diversity, may be changes to wild pollinator interactions with plants. Such changes for a community can be measured by looking at changes to metrics of resource use overlap in plant-pollinator interaction networks. Studies of honey bee effects on plant-pollinator networks have usually not distinguished whether honey bees alter wild pollinator interactions, or if they merely alter total network structure by adding their own interactions. To test this question, we experimentally introduced honey bees to a Canadian grassland and measured plant-pollinator interactions at varying distances from the introduced hives. We found that honey bees increased the network metrics of pollinator and plant functional complementarity and decreased interaction evenness. However, in networks constructed from just wild pollinator interactions, honey bee abundance did not affect any of the metrics calculated. Thus, all network structural changes to the full network (including honey bee interactions) were due only to honey bee-plant interactions, and not to honey bees causing changes in wild pollinator-plant interactions. Given widespread and increasing use of honey bees, it is important to establish whether they affect wild pollinator communities. Our results suggest that honey bees did not alter wild pollinator foraging patterns in this system, even in a year that was drier than the 20-year average.

Effects of habitat disturbance on the reproductive ecology of Arum pictum ssp. sagittifolium: from pollination to seedling recruitment

BACKGROUND AND AIMS

The loss of natural habitats may strongly affect the fitness of plants that depend on animals for reproduction. However, very little is known regarding the differential effects of habitat disturbance on the distinct phases of the reproductive cycle of plants, especially in non-rewarding species.

METHODS

We assessed the effects of habitat disturbance on the entire reproductive cycle of Arum pictum ssp. sagittifolium, a species with deceptive pollination that is endemic to the western Mediterranean Basin. For this, we performed hand-pollination and bagging experiments, evaluated the role of pollinators and dispersers on reproduction, and estimated seedling recruitment in three natural and three disturbed populations (according to their surrounding natural habitat) in Mallorca Island.

KEY RESULTS

Pollinators were sphaerocerid flies (mainly Coproica, with ~50 % of visits) and staphylinid beetles, and were required for sexual reproduction. Habitat disturbance differently affected the reproductive phases of A. pictum ssp. sagittifolium. Habitat disturbance had a positive effect on Shannon pollinator diversity (but not on pollinator richness), and total pollinator and Coproica abundance were three times higher in disturbed habitats, where overall seed production was also ~30 % higher in natural habitats. Seed production increased with Coproica abundance, but only in natural habitats. Seed dispersers of A. pictum ssp. sagittifolium were birds, mainly Sylvia atricapilla. Although habitat disturbance did not influence disperser diversity or abundance, the majority of seedlings appeared under adult plants and in natural habitats.

CONCLUSIONS

Overall recruitment was higher in natural habitats, but this effect could have been masked by only assessing pollinator and disperser numbers, as processes related to the quality of these interactions might be influencing fitness. Our study highlights the need to study different reproductive phases and their multiple components and processes to properly understand the effects of habitat disturbance on the regeneration of plant populations.

Mounting evidence that managed and introduced bees have negative impacts on wild bees: an updated review

Worldwide, the use of managed bees for crop pollination and honey production has increased dramatically. Concerns about the pressures of these increases on native ecosystems has resulted in a recent expansion in the literature on this subject. To collate and update current knowledge, we performed a systematic review of the literature on the effects of managed and introduced bees on native ecosystems, focusing on the effects on wild bees. To enable comparison over time, we used the same search terms and focused on the same impacts as earlier reviews. This review covers: (a) interference and resource competition between introduced or managed bees and native bees; (b) effects of introduced or managed bees on pollination of native plants and weeds; and (c) transmission and infectivity of pathogens; and classifies effects into positive, negative, or neutral. Compared to a 2017 review, we found that the number of papers on this issue has increased by 47%. The highest increase was seen in papers on pathogen spill-over, but in the last five years considerable additional information about competition between managed and wild bees has also become available. Records of negative effects have increased from 53% of papers reporting negative effects in 2017 to 66% at present. The majority of these studies investigated effects on visitation and foraging behaviour. While only a few studies experimentally assessed impacts on wild bee reproductive output, 78% of these demonstrated negative effects. Plant composition and pollination was negatively affected in 7% of studies, and 79% of studies on pathogens reported potential negative effects of managed or introduced bees on wild bees. Taken together, the evidence increasingly suggests that managed and introduced bees negatively affect wild bees, and this knowledge should inform actions to prevent further harm to native ecosystems.

Analysis of Hypergraph Signals via High-Order Total Variation

Beyond pairwise relationships, interactions among groups of agents do exist in many real-world applications, but they are difficult to capture by conventional graph models. Generalized from graphs, hypergraphs have been introduced to describe such high-order group interactions. Inspired by graph signal processing (GSP) theory, an existing hypergraph signal processing (HGSP) method presented a spectral analysis framework relying on the orthogonal CP decomposition of adjacency tensors. However, such decomposition may not exist even for supersymmetric tensors. In this paper, we propose a high-order total variation (HOTV) form of a hypergraph signal (HGS) as its smoothness measure, which is a hyperedge-wise measure aggregating all signal values in each hyperedge instead of a pairwise one in most existing work. Further, we propose an HGS analysis framework based on the Tucker decomposition of the hypergraph Laplacian induced by the aforementioned HOTV. We construct an orthonormal basis from the HOTV, by which a new spectral transformation of the HGS is introduced. Then, we design hypergraph filters in both vertex and spectral domains correspondingly. Finally, we illustrate the advantages of the proposed framework by applications in label learning.

Predator interference and complexity-stability in food webs

It is predicted that ecological communities will become unstable with increasing species numbers and subsequent interspecific interactions; however, this is contrary to how natural ecosystems with diverse species respond to changes in species numbers. This contradiction has steered ecologists toward exploring what underlying processes allow complex communities to stabilize even through varying pressures. In this study, a food web model is used to show an overlooked role of interference among multiple predator species in solving this complexity–stability problem. Predator interference in large communities weakens species interactions due to a reduction in consumption rates by prey-sharing species in the presence of predators in response to territorial and aggressive behavior, thereby playing a key stabilizing role in communities. Especially when interspecific interference is strong and a community has diverse species and dense species interactions, stabilization is likely to work and creates a positive complexity–stability relationship within a community. The clear positive effect of complexity on community stability is not reflected by/intraspecific interference, emphasizing the key role of interspecific interference among multiple predator species in maintaining larger systems.