A primary aim of microbial ecology is to determine patterns and drivers of community distribution, interaction, and assembly amidst complexity and uncertainty. Microbial community composition has been shown to change across gradients of environment, geographic distance, salinity, temperature, oxygen, nutrients, pH, day length, and biotic factors 1-6 . These patterns have been identified mostly by focusing on one sample type and region at a time, with insights extra polated across environments and geography to produce generalized principles. To assess how microbes are distributed across environments globally-or whether microbial community dynamics follow funda mental ecological 'laws' at a planetary scale-requires either a massive monolithic cross environment survey or a practical methodology for coordinating many independent surveys. New studies of microbial environments are rapidly accumulating; however, our ability to extract meaningful information from across datasets is outstripped by the rate of data generation. Previous meta analyses have suggested robust gen eral trends in community composition, including the importance of salinity 1 and animal association 2 . These findings, although derived from relatively small and uncontrolled sample sets, support the util ity of meta analysis to reveal basic patterns of microbial diversity and suggest that a scalable and accessible analytical framework is needed.The Earth Microbiome Project (EMP, http://www.earthmicrobiome. org) was founded in 2010 to sample the Earth's microbial communities at an unprecedented scale in order to advance our understanding of the organizing biogeographic principles that govern microbial commu nity structure 7,8 . We recognized that open and collaborative science, including scientific crowdsourcing and standardized methods 8 , would help to reduce technical variation among individual studies, which can overwhelm biological variation and make general trends difficult to detect 9 . Comprising around 100 studies, over half of which have yielded peer reviewed publications (Supplementary Table 1), the EMP has now dwarfed by 100 fold the sampling and sequencing depth of earlier meta analysis efforts 1,2 ; concurrently, powerful analysis tools have been developed, opening a new and larger window into the distri bution of microbial diversity on Earth. In establishing a scalable frame work to catalogue microbiota globally, we provide both a resource for the exploration of myriad questions and a starting point for the guided acquisition of new data to answer them. As an example of using this Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of r...
Patterns of habitat use in animals presumably have evolved in response to diverse selective processes, so we first examined whether the theory of natural selection formed the conceptual framework for published studies (N ϭ 270) of nest-site selection by birds. Most (61%) studies of nest-site selection tested for pattern arising from natural selection (whether used nest habitat differed from available nesting habitat), many (54%) tested for evidence of the process of natural selection (whether unsuccessful nests differed from successful nests), some (10%) tested whether the process of natural selection caused subsequent adaptation, but remarkably few conceptually linked these elements or used the theory of natural selection as the rationale for their questions.We then tested for evidence of natural (phenotypic) selection with data for six species of ducks. At nests, we used six variables to describe vegetation structure/nest position and categorized patch types (pond edge, native grass, planted cover, shrubs, or trees) in which nests were found; nest fates (abandoned, depredated, or successful) were also determined. For Blue-winged Teal (Anas discors), Northern Shoveler (A. clypeata), and Mallard (A. platyrhynchos), there were significant patterns of nonrandom nest-site placement within a gradient of vegetation structure/nest position. For Blue-winged Teal and Gadwall (A. strepera), nest success varied within these gradients in a way that could exert directional selection. Several tests for adaptive nest-site choice were conducted. Nest fate did not influence fidelity of females to patch types. However, Mallards with previously unsuccessful nests dispersed farther than females with previously successful nests. Nonetheless, neither fidelity to patch type nor dispersal distance influenced subsequent nest success. In the long term (over 8 yr), there was a weak tendency within species for nest density to be higher among patch types where relative nest success was higher. In the short term (from year t to year t ϩ 1), this pattern was not observed in a vegetation-structure/nest-position gradient for any species. The strongest evidence of adaptive response to nest fate was higher nest density on an island where nest success was relatively high.
Queen health is crucial to colony survival of social bees. Recently, queen failure has been proposed to be a major driver of managed honey bee colony losses, yet few data exist concerning effects of environmental stressors on queens. Here we demonstrate for the first time that exposure to field-realistic concentrations of neonicotinoid pesticides during development can severely affect queens of western honey bees (Apis mellifera). In pesticide-exposed queens, reproductive anatomy (ovaries) and physiology (spermathecal-stored sperm quality and quantity), rather than flight behaviour, were compromised and likely corresponded to reduced queen success (alive and producing worker offspring). This study highlights the detriments of neonicotinoids to queens of environmentally and economically important social bees, and further strengthens the need for stringent risk assessments to safeguard biodiversity and ecosystem services that are vulnerable to these substances.
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