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Abstract Pollen protein content has been demonstrated to be an essential nutritional component for bees and thus important in mediating plant–pollinator interactions. However, little is known on the drivers and consequences of among‐species variation in pollen protein content and how this can impact male and female reproductive success across plant species. Among‐species variation in resources allocated to pollen nutrition could further be constrained by life‐history strategies (e.g. survival‐reproduction trade‐offs) or evolutionary history.Here, we surveyed pollen protein content for 29 species within a diverse co‐flowering community and evaluated the effect of pollen protein on male and female reproductive success. We also tested the role of life history (annuals vs. perennials) and phylogeny in mediating differences in resource allocation to pollen nutrition.We found that pollen protein content influences components of male (bee visitor abundance and pollen dispersal) but not female (conspecific pollen deposition and pollen tube growth) reproductive success, suggesting this trait affects plants only via male function. This sex‐specific effect further suggests the potential for sexual conflicts driven by differential investment on this trait. We found no phylogenetic signal on pollen protein content. However, pollen protein content was higher in annual compared to perennial species suggesting survival versus reproduction trade‐offs also contribute to variation in pollen protein at the community level.Our study underscores the importance of understanding the ecological and evolutionary drivers of pollen protein content across plant species. Our results further suggest the existence of sexual conflicts and ecological trade‐offs mediated by differential investment in pollen nutritional quality, with important implications for community assembly and the structure of plant–pollinator interactions. Read the freePlain Language Summaryfor this article on the Journal blog. 

Abstract The patterns and drivers of pollen transport on insect bodies can have important consequences for plant reproductive success and floral evolution; however, they remain little studied. Recently, pollinator bodies have been further described as pollen competitive arenas, where pollen grains can compete for space, with implications for the evolution of pollen dispersal strategies and plant community assembly. However, the identity, strength, and diversity of pollen competitive interactions and how they vary across pollinator functional groups is not known. Evaluating patterns and drivers of the pollen co‐transport landscape and how these vary across different pollinator groups is central to further our understanding of floral evolution and co‐flowering community assembly.Here, we integrate information on the number and identity of pollen grains on individual insect pollen loads with network analyses to uncover novel pollen co‐transport networks and how these vary across pollinator functional groups (bees and bee flies). We further evaluate differences in pollen load size, species composition, diversity and phylogenetic diversity among insect groups and how these relate to body size and gender.Pollen co‐transport networks were diverse and highly modular in bees, with groups of pollen species interacting more often with each other on insect bodies. However, the number, identity and frequency of competitors that pollen grains encounter on insect bodies vary between some pollinator functional groups. Other aspects of pollen loads such as their size, richness and phylogenetical diversity were shaped by bee size or gender, with females carrying larger but less phylogenetically diverse pollen loads than males.Synthesis. Our results show that the number, identity and phylogenetic relatedness of pollen competitors changes as pollen grains travel on the body of different pollinators. As a result, pollinator groups impose vastly different interaction landscapes during pollen transport, with so far unknown consequences for plant reproductive success, floral evolution and community assembly. 

Abstract Seamounts and basaltic basement can influence deformation and mass fluxes within subduction zones. We examined seamounts and volcanic units across the western Hikurangi Plateau, near the Hikurangi subduction margin, New Zealand, with seismic reflection images. Volcanism at the Hikurangi Plateau occurred in at least three phases that we attribute to (1) Early Cretaceous large igneous province formation, the top of which is marked by laterally continuous and dipping wedges of reflections that we interpret as lava flows; (2) Late Cretaceous seamounts and volcaniclastics that erupted onto the crust of the Hikurangi Plateau and make up the majority of seamount volume and basement relief; and (3) late-stage, Pliocene volcanics that erupted through and adjacent to Cretaceous seamounts and younger sediments of the north-central Hikurangi Plateau. The Pliocene volcanoes do not appear to be strongly welded to the plateau basement and may be petit spot volcanoes that are related to the displacement and accumulation of hydrous transition zone melts. Large seamounts and volcaniclastic units are evenly distributed across most of the Hikurangi Plateau near the Hikurangi margin but are absent from the Pegasus Basin. Although faults are imaged throughout the basement of the Pegasus Basin, contemporary normal faulting of the Hikurangi Plateau is uncommon, except for a zone of Quaternary normal faults near the Pliocene volcanics. These trends indicate that the Hikurangi megathrust may be more influenced by volcanic structures in the north and central Hikurangi margin, where plateau rifting and voluminous seamount eruptions have more substantially overprinted the original Early Cretaceous basement. 

Recurring slow slip along near-trench megathrust faults occurs at many subduction zones, but for unknown reasons, this process is not universal. Fluid overpressures are implicated in encouraging slow slip; however, links between slow slip, fluid content, and hydrogeology remain poorly known in natural systems. Three-dimensional seismic imaging and ocean drilling at the Hikurangi margin reveal a widespread and previously unknown fluid reservoir within the extensively hydrated (up to 47 vol % H₂O) volcanic upper crust of the subducting Hikurangi Plateau large igneous province. This ~1.5 km thick volcaniclastic upper crust readily dewaters with subduction but retains half of its fluid content upon reaching regions with well-characterized slow slip. We suggest that volcaniclastic-rich upper crust at volcanic plateaus and seamounts is a major source of water that contributes to the fluid budget in subduction zones and may drive fluid overpressures along the megathrust that give rise to frequent shallow slow slip. 

With only 536 COVID-19 cases and 11 fatalities, India took the historic decision of a 21-day national lockdown on March 25, 2020. The lockdown was first extended to May 3 soon after the analysis of this article was completed, and then to May 18 while this article was being revised. In this article, we use a Bayesian extension of the susceptible-infected-removed (eSIR) model designed for intervention forecasting to study the short- and long-term impact of an initial 21-day lockdown on the total number of COVID-19 infections in India compared to other, less severe nonpharmaceutical interventions. We compare effects of hypothetical durations of lockdown on reducing the number of active and new infections. We find that the lockdown, if implemented correctly, can reduce the total number of cases in the short term, and buy India invaluable time to prepare its health care and disease-monitoring system. Our analysis shows we need to have some measures of suppression in place after the lockdown for increased benefit (as measured by reduction in the number of cases). A longer lockdown from 42–56 days is preferable to substantially ‘flatten the curve’ when compared to 21–28 days of lockdown. Our models focus solely on projecting the number of COVID-19 infections and thus inform policymakers about one aspect of this multifaceted decision-making problem. We conclude with a discussion on the pivotal role of increased testing, reliable and transparent data, proper uncertainty quantification, accurate interpretation of forecasting models, reproducible data science methods, and tools that can enable data-driven policymaking during a pandemic. Our software products are available at covind19.org.