Appetite for self-destruction: suicidal biting as a nest defense strategy in Trigona stingless bees

Self-sacrificial behavior represents an extreme and relatively uncommon form of altruism in worker insects. It can occur, however, when inclusive fitness benefits are high, such as when defending the nest. We studied nest defense behaviors in stingless bees, which live in eusocial colonies subject to predation. We introduced a target flag to nest entrances to elicit defensive responses and quantified four measures of defensivity in 12 stingless bee species in São Paulo State, Brazil. These included three Trigona species, which are locally known for their aggression. Species varied significantly in their attack probability (cross species range = 0–1, P < 0.001), attack latency (7.0–23.5 s, P = 0.002), biting duration of individual bees (3.5–508.7 s, P < 0.001), and number of attackers (1.0–10.8, P < 0.001). A “suicide” bioassay on the six most aggressive species determined the proportion of workers willing to suffer fatal damage rather than disengage from an intruder. All six species had at least some suicidal individuals (7–83 %, P < 0.001), reaching 83 % in Trigona hyalinata. Biting pain was positively correlated with an index of overall aggression (P = 0.002). Microscopic examination revealed that all three Trigona species had five sharp teeth per mandible, a possible defensive adaptation and cause of increased pain. Suicidal defense via biting is a new example of self-sacrificial altruism and has both parallels and differences with other self-sacrificial worker insects, such as the honey bee. Our results indicate that suicidal biting may be a widespread defense strategy in stingless bees, but it is not universal

Towards understanding interactions between Sustainable Development Goals: the role of environment–human linkages

Only 10 years remain to achieve all Sustainable Development Goals (SDGs) globally, so there is a growing need to increase the effectiveness and efficiency of action by targeting multiple SDGs. The SDGs were conceived as an ‘indivisible whole’, but interactions between SDGs need to be better understood. Several previous assessments have begun to explore interactions including synergies and possible conflicts between the SDGs, and differ widely in their conclusions. Although some highlight the role of the more environmentally-focused SDGs in underpinning sustainable development, none specifically focuses on environment-human linkages. Assessing interactions between SDGs, and the influence of environment on them, can make an important contribution to informing decisions in 2020 and beyond. Here, we review previous assessments of interactions among SDGs, apply an influence matrix to assess pairwise interactions between all SDGs, and show how viewing these from the perspective of environment-human linkages can influence the outcome. Environment, and environment-human linkages, influence most interactions between SDGs. Our action-focused assessment enables decision makers to focus environmental management to have the greatest impacts, and to identify opportunities to build on synergies and reduce trade-offs between particular SDGs. It may enable sectoral decision makers to seek support from environment managers for achieving their goals. We explore cross-cutting issues and the relevance and potential application of our approach in supporting decision making for progress to achieve the SDGs

British phenological records indicate high diversity and extinction rates among late-summer-flying pollinators

The long-term decline of wild and managed insect pollinators is a threat to both agricultural output and biodiversity, and has been linked to decreasing floral resources. Further insight into the temporal relationships of pollinators and their flowering partners is required to inform conservation efforts. Here we examined the phenology of British: (i) pollinator activity; (ii) insect-pollinated plant flowering; and (iii) extinct and endangered pollinator and plant species. Over 1 million records were collated from the historical databases of three British insect monitoring organisations, a global biodiversity database and an authoritative text covering the national flora. Almost two-thirds (62%) of pollinator species have peak flight observations during late-summer (July and August). This was the case across three of the groups studied: aculeate wasps (71% of species), bees (60%), and butterflies (72%), the exception being hoverflies (49%). When species geographical range (a proxy for abundance) was accounted for, a clear late-summer peak was clear across all groups. By contrast, there is marked temporal partitioning in the flowering of the major plant groups: insect-pollinated tree species blossoming predominantly during May (74%), shrubs in June (69%), and herbs in July (83%). There was a positive correlation between the number of pollinator species on the wing and the richness of both flowering insect-pollinated herbs and trees/shrubs species, per calendar month. In addition, significantly greater extinctions occurred in late-summer-flying pollinator species than expected (83% of extinct species vs. 62% of all species). This trend was driven primarily by bee extinctions (80% vs. 60%) and was not apparent in other groups. We contend that this is principally due to declines in late-summer resource supplies, which are almost entirely provisioned by herbs, a consequence of historical land-use change. We hypothesize that the seasonality of interspecific competition and the blooming of trees and mass-flowering crops may have partially buffered spring-flying pollinators from the impacts of historical change

Rapid evolution of a floral trait following acquisition of novel pollinators

Changes in the pollinator assemblage visiting a plant can have consequences for reproductive success and floral evolution. We studied a recent plant trans‐continental range expansion to test whether the acquisition of new pollinator functional groups can lead to rapid adaptive evolution of flowers. In Digitalis purpurea, we compared flower visitors, floral traits and natural selection between native European populations and those in two Neotropical regions, naturalised after independent introductions. Bumblebees are the main pollinators in native populations while both bumblebees and hummingbirds are important visitors in the new range. We confirmed that the birds are effective pollinators and deposit more pollen grains on stigmas than bumblebees. We found convergent changes in the two new regions towards larger proximal corolla tubes, a floral trait that restricts access to nectar to visitors with long mouthparts. There was a strong positive linear selection for this trait in the introduced populations, particularly on the length of the proximal corolla tube, consistent with the addition of hummingbirds as pollinators. Synthesis. The addition of new pollinators is likely to happen often as humans influence the ranges of plants and pollinators but it is also a common feature in the long‐term evolution of the angiosperms. We show how novel selection followed by very rapid evolutionary change can be an important force behind the extraordinary diversity of flower

Global goals mapping: the environment-human landscape

The UK Natural Environment Research Council (NERC), The Rockefeller Foundation (RF), and the UK Economic and Social Research Council (ESRC) recognise that the development challenges of the 21st century require both a shift in thinking and actions that prepare us for the future, while enabling more effective development interventions today. These organisations are establishing a new initiative: 'Towards a Sustainable Earth: Environment-human Systems and the UN Global Goals' (TaSE) as part of their commitment to seeing the 17 Sustainable Development Goals (also known as Global Goals) become a reality. The core premise of the TaSE initiative is that environment-human interactions must be central to all development. The TaSE initiative is convening a meeting at The Rockefeller Foundation Bellagio Centre (7-11 November 2016) to identify the major research and innovation questions relevant to the achievement of the overarching ambition of this initiative. To help focus discussions during this meeting, NERC commissioned the Sussex Sustainability Research Programme (SSRP) at the University of Sussex and the UN Environment World Conservation Monitoring Centre (UNEP-WCMC) to produce a “synthesis of past and current research and innovation relating to the policy landscape surrounding the environment-human relationships and systems that interact across the UN Global Goals”. The commissioned work is encapsulated in this report, Global Goals mapping: the environment-human landscape. For each Goal, the first part of this report summarises the role of environment-human interactions and synthesises relevant research evidence, key innovations and policies, and knowledge and research gaps. The syntheses of research evidence, key innovations and policies presented for individual Global Goals show that environment-human interactions are important for the achievement of all of the Goals. However, the number of environment-human interactions, and the extent to which these interactions need to be considered for achieving each Goal, varies among Global Goals. Although research, innovation and policy have advanced substantially since the Millennium Ecosystem Assessment, knowledge and research gaps related to environment-human interactions remain for all Goals. The Global Goals were conceived as an 'indivisible whole'. The Goals relate to and depend on each other, but relationships between Goals need to be better understood. Previous analyses have begun to explore relationships including synergies and possible conflicts between the Goals from a number of different perspectives and differ widely in their conclusions. While many highlight the role of the more environmentally-focused Goals in underpinning sustainable development, none specifically focuses on environment-human interactions, which are the focus of the TaSE initiative and crucial to the achievement of the Goals. This report uses a new analysis to suggest which relationships between Global Goals may be most influenced by environment-human interactions. It is based on a pairwise view of relationships between Goals, assessing the influence that action (research, policy, innovation and/or management) towards one Goal may have on the potential for achieving others. It highlights 20 pairwise relationships between Goals where these influences may be especially strong, and illustrates for some of these how the knowledge and research gaps identified in Part 1 are relevant to the relationships between the Goals. In reality relationships among Goals are more complex and multidimensional than a pairwise analysis can illustrate, but visualising all connections among them is challenging. Further knowledge gaps and challenges related to the trade-offs, synergies and unintended consequences of the relationships among Goals will need to be addressed to achieve all 17 Goals. In order to understand relationships among Global Goals and prioritize action, including research, it is essential to consider multiple cross-cutting factors, including: temporal and spatial scales of action and impact; context for the action, whether local or other; the (multi) directionality of the relationships among Goals; thresholds and tipping points; number and types of people affected; human behaviour; governance, institutions and power; existence and accessibility of different types of knowledge; and the feasibility of obtaining and scaling-up research results and innovations by 2030. Several approaches have attempted to tackle interconnected challenges, including nexus thinking, pathways, leverage points, indigenous and local knowledge, integrated environmental assessments and integrated modelling. However, there is a need for more work and holistic approaches to achieve all 17 Goals. The syntheses of research evidence, innovations and policies regarding environment-human interactions relevant to each Global Goal and the analysis of the relationships among Goals provide a basis for identifying priority areas for new research, innovation and policy. The Bellagio Group has a vital role to play in building on this to help the TaSE initiative identify a research, innovation and research translation agenda in support of the Global Goals

Quality versus quantity: foraging decisions in the honeybee (Apis mellifera scutellata) feeding on wildflower nectar and fruit juice

Foraging animals must often decide among resources which vary in quality and quantity. Nectar is a resource that exists along a continuum of quality in terms of sugar concentration and is the primary energy source for bees. Alternative sugar sources exist, including fruit juice, which generally has lower energetic value than nectar. We observed many honeybees (Apis mellifera scutellata) foraging on juice from fallen guava (Psidium guajava) fruit near others foraging on nectar. To investigate whether fruit and nectar offered contrasting benefits of quality and quantity, we compared honeybee foraging performance on P. guajava fruit versus two wildflowers growing within 50 m, Richardia brasiliensis and Tridax procumbens. Bees gained weight significantly faster on fruit, 2.72 mg/min, than on either flower (0.17 and 0.12 mg/min, respectively). However, the crop sugar concentration of fruit foragers was significantly lower than for either flower (12.4% vs. 37.0% and 22.7%, respectively). Fruit foragers also spent the most time handling and the least time flying, suggesting that fruit juice was energetically inexpensive to collect. We interpret honeybee foraging decisions in the context of existing foraging models and consider how nest-patch distance may be a key factor for central place foragers choosing between resources of contrasting quality and quantity. We also discuss how dilute solutions, such as fruit juice, can help maintain colony sugar–water balance. These results show the benefits of feeding on resources with contrasting quality and quantity and that even low-quality resources have value

Thymic Development of Autoreactive T Cells in NOD Mice Is Regulated in an Age-Dependent Manner

Inefficient thymic negative selection of self-specific T cells is associated with several autoimmune diseases, including type 1 diabetes (T1D). The factors that influence the efficacy of thymic negative selection, and the kinetics of thymic output of autoreactive T cells remain ill-defined. We investigated thymic production of β cell-specific T cells using a thymus transplantation model. Thymi from different aged NOD mice representing distinct stages of T1D, were implanted into NOD.scid recipients and the diabetogenicity of the resulting T cell pool examined. Strikingly, the development of diabetes-inducing β cell-specific CD4+ and CD8+ T cells was regulated in an age-dependent manner. NOD.scid recipients of newborn NOD thymi developed diabetes. However, recipients of thymi from 7 and 10 d-old NOD donor mice remained diabetes-free, and exhibited a progressive decline in islet infiltration and β cell-specific CD4+ and CD8+ T cells. A similar temporal decrease in autoimmune infiltration was detected in some but not all tissues of recipient mice implanted with thymi from NOD mice lacking expression of the autoimmune regulator transcription factor, which develop multi-organ T cell-mediated autoimmunity. In contrast, recipients of 10 d or older thymi lacked diabetogenic T cells but developed severe colitis marked by increased effector T cells reactive to intestinal microbiota. These results demonstrate that thymic development of autoreactive T cells is limited to a narrow time-window, and occurs in a reciprocal manner compared to colonic microbiota-responsive T cells in NOD mice

Optimizing Sparse RFI Prediction using Deep Learning

Radio Frequency Interference (RFI) is an ever-present limiting factor among radio telescopes even in the most remote observing locations. When looking to retain the maximum amount of sensitivity and reduce contamination for Epoch of Reionization studies, the identification and removal of RFI is especially important. In addition to improved RFI identification, we must also take into account computational efficiency of the RFI-Identification algorithm as radio interferometer arrays such as the Hydrogen Epoch of Reionization Array grow larger in number of receivers. To address this, we present a Deep Fully Convolutional Neural Network (DFCN) that is comprehensive in its use of interferometric data, where both amplitude and phase information are used jointly for identifying RFI. We train the network using simulated HERA visibilities containing mock RFI, yielding a known "ground truth" dataset for evaluating the accuracy of various RFI algorithms. Evaluation of the DFCN model is performed on observations from the 67 dish build-out, HERA-67, and achieves a data throughput of 1.6$\times 10^{5}$ HERA time-ordered 1024 channeled visibilities per hour per GPU. We determine that relative to an amplitude only network including visibility phase adds important adjacent time-frequency context which increases discrimination between RFI and Non-RFI. The inclusion of phase when predicting achieves a Recall of 0.81, Precision of 0.58, and $F_{2}$ score of 0.75 as applied to our HERA-67 observations.Comment: 11 pages, 7 figure

Mitigating Internal Instrument Coupling for 21 cm Cosmology. II. A Method Demonstration with the Hydrogen Epoch of Reionization Array

We present a study of internal reflection and cross-coupling systematics in Phase I of the Hydrogen Epoch of Reionization Array (HERA). In a companion paper, we outlined the mathematical formalism for such systematics and presented algorithms for modeling and removing them from the data. In this work, we apply these techniques to data from HERA's first observing season as a method demonstration. The data show evidence for systematics that, without removal, would hinder a detection of the 21 cm power spectrum for the targeted Epoch of Reionization (EoR) line-of-sight modes in the range 0.2 h −1 Mpc−1 < ${k}_{\parallel }$ < 0.5 h −1 Mpc−1. In particular, we find evidence for nonnegligible amounts of spectral structure in the raw autocorrelations that overlaps with the EoR window and is suggestive of complex instrumental effects. Through systematic modeling on a single night of data, we find we can recover these modes in the power spectrum down to the integrated noise floor, achieving a dynamic range in the EoR window of 106 in power (mK2 units) with respect to the bright galactic foreground signal. Future work with deeper integrations will help determine whether these systematics can continue to be mitigated down to EoR levels. For future observing seasons, HERA will have upgraded analog and digital hardware to better control these systematics in the field