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...

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Genetic tools have become a critical complement to traditional approaches for meeting short- and long-term goals of ex situ conservation programs. The San Diego Zoo (SDZ) harbors a collection of wild-born and captive-born Galápagos giant tortoises (n = 22) of uncertain species designation and unknown genealogical relationships. Here, we used mitochondrial DNA haplotypic data and nuclear microsatellite genotypic data to identify the evolutionary lineage of wild-born and captive-born tortoises of unknown ancestry, to infer levels of relatedness among founders and captive-born tortoises, and assess putative pedigree relationships assigned by the SDZ studbook. Assignment tests revealed that 12 wild-born and five captive-born tortoises represent five different species from Isabela Island and one species from Santa Cruz Island, only five of which were consistent with current studbook designations. Three wild-born and one captive-born tortoise were of mixed ancestry. In addition, kinship analyses revealed two significant first-order relationship pairs between wild-born and captive-born tortoises, four second-order relationships (half-sibling) between wild-born and captive tortoises (full-sibs or parent-offspring), and one second-order relationship between two captive-born tortoises. Of particular note, we also reconstructed a first-order relationship between two wild-born individuals, violating the founder assumption. Overall, our results contribute to a worldwide effort in identifying genetically important Galápagos tortoises currently in captivity while revealing closely related founders, reconstructing genealogical relationships, and providing detailed management recommendations for the SDZ tortoises.

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