Agriculture is being challenged to provide food, and increasingly fuel, for an expanding global population. Producing bioenergy crops on marginal lands--farmland suboptimal for food crops--could help meet energy goals while minimizing competition with food production. However, the ecological costs and benefits of growing bioenergy feedstocks--primarily annual grain crops--on marginal lands have been questioned. Here we show that perennial bioenergy crops provide an alternative to annual grains that increases biodiversity of multiple taxa and sustain a variety of ecosystem functions, promoting the creation of multifunctional agricultural landscapes. We found that switchgrass and prairie plantings harbored significantly greater plant, methanotrophic bacteria, arthropod, and bird diversity than maize. Although biomass production was greater in maize, all other ecosystem services, including methane consumption, pest suppression, pollination, and conservation of grassland birds, were higher in perennial grasslands. Moreover, we found that the linkage between biodiversity and ecosystem services is dependent not only on the choice of bioenergy crop but also on its location relative to other habitats, with local landscape context as important as crop choice in determining provision of some services. Our study suggests that bioenergy policy that supports coordinated land use can diversify agricultural landscapes and sustain multiple critical ecosystem services.
Agriculture has marked impacts on the production of carbon dioxide (CO(2)) and consumption of methane (CH(4)) by microbial communities in upland soils-Earths largest biological sink for atmospheric CH(4). To determine whether the diversity of microbes that catalyze the flux of these greenhouse gases is related to the magnitude and stability of these ecosystem-level processes, we conducted molecular surveys of CH(4)-oxidizing bacteria (methanotrophs) and total bacterial diversity across a range of land uses and measured the in situ flux of CH(4) and CO(2) at a site in the upper United States Midwest. Conversion of native lands to row-crop agriculture led to a sevenfold reduction in CH(4) consumption and a proportionate decrease in methanotroph diversity. Sites with the greatest stability in CH(4) consumption harbored the most methanotroph diversity. In fields abandoned from agriculture, the rate of CH(4) consumption increased with time along with the diversity of methanotrophs. Conversely, estimates of total bacterial diversity in soil were not related to the rate or stability of CO(2) emission. These combined results are consistent with the expectation that microbial diversity is a better predictor of the magnitude and stability of processes catalyzed by organisms with highly specialized metabolisms, like CH(4) oxidation, as compared with processes driven by widely distributed metabolic processes, like CO(2) production in heterotrophs. The data also suggest that managing lands to conserve or restore methanotroph diversity could mitigate the atmospheric concentrations of this potent greenhouse gas.
An intrinsic artifact of 454-based pyrosequencing leads to artificial overrepresentation of >10% of the original DNA sequencing templates. This artificial amplification of sequences is unbiased with regard to position on the pyrosequencing plate or sequence identity, and it occurs in all currently available 454 technologies. The amplified sequences start at the same position and are identical (duplicates), or vary in length, or contain a sequencing discrepancy. If the abundance of any sequence in a data set is going to be enumerated, either for comparative community analysis, transcriptional analysis or other applications, it is important to remove these artificial replicates before analysis. A web-based tool that incorporates the clustering algorithm cd-hit was developed to identify and remove artificially replicated sequences in 454-based pyrosequencing data sets. This tool cannot be used for data sets that have an initial amplification step before the standard pyrosequencing procedure, because artificial replicates cannot be distinguished from expected replication due to polymerase chain reaction (PCR) amplification, e.g., in sequencing of amplified gene "tags." This protocol provides details on how to use the replicate filter and obtain a file of unique sequences for use in metagenomic or transcriptomic analyses.
Metagenomics is providing an unprecedented view of the taxonomic diversity, metabolic potential and ecological role of microbial communities in biomes as diverse as the mammalian gastrointestinal tract, the marine water column and soils. However, we have found a systematic error in metagenomes generated by 454-based pyrosequencing that leads to an overestimation of gene and taxon abundance; between 11% and 35% of sequences in a typical metagenome are artificial replicates. Here we document the error in several published and original datasets and offer a web-based solution (http://microbiomes.msu.edu/replicates) for identifying and removing these artifacts.
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