Priorities, opportunities, and challenges for integrating microorganisms into Earth system models for climate change prediction.

Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a "top 10" list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Rapid plant trait evolution can alter coastal wetland resilience to sea level rise.

Rapid evolution remains a largely unrecognized factor in models that forecast the fate of ecosystems under scenarios of global change. In this work, we quantified the roles of heritable variation in plant traits and of trait evolution in explaining variability in forecasts of the state of coastal wetland ecosystems. A common garden study of genotypes of the dominant sedge Schoenoplectus americanus, "resurrected" from time-stratified seed banks, revealed that heritable variation and evolution explained key ecosystem attributes such as the allocation and distribution of belowground biomass. Incorporating heritable trait variation and evolution into an ecosystem model altered predictions of carbon accumulation and soil surface accretion (a determinant of marsh resilience to sea level rise), demonstrating the importance of accounting for evolutionary processes when forecasting ecosystem dynamics.

Quantifying global soil carbon losses in response to warming.

The majority of the Earth's terrestrial carbon is stored in the soil. If anthropogenic warming stimulates the loss of this carbon to the atmosphere, it could drive further planetary warming. Despite evidence that warming enhances carbon fluxes to and from the soil, the net global balance between these responses remains uncertain. Here we present a comprehensive analysis of warming-induced changes in soil carbon stocks by assembling data from 49 field experiments located across North America, Europe and Asia. We find that the effects of warming are contingent on the size of the initial soil carbon stock, with considerable losses occurring in high-latitude areas. By extrapolating this empirical relationship to the global scale, we provide estimates of soil carbon sensitivity to warming that may help to constrain Earth system model projections. Our empirical relationship suggests that global soil carbon stocks in the upper soil horizons will fall by 30 ± 30 petagrams of carbon to 203 ± 161 petagrams of carbon under one degree of warming, depending on the rate at which the effects of warming are realized. Under the conservative assumption that the response of soil carbon to warming occurs within a year, a business-as-usual climate scenario would drive the loss of 55 ± 50 petagrams of carbon from the upper soil horizons by 2050. This value is around 12-17 per cent of the expected anthropogenic emissions over this period. Despite the considerable uncertainty in our estimates, the direction of the global soil carbon response is consistent across all scenarios. This provides strong empirical support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon-climate feedback that could accelerate climate change.

Whole-genome association study of bipolar disorder.

We performed a genome-wide association scan in 1461 patients with bipolar (BP) 1 disorder, 2008 controls drawn from the Systematic Treatment Enhancement Program for Bipolar Disorder and the University College London sample collections with successful genotyping for 372,193 single nucleotide polymorphisms (SNPs). Our strongest single SNP results are found in myosin5B (MYO5B; P=1.66 x 10(-7)) and tetraspanin-8 (TSPAN8; P=6.11 x 10(-7)). Haplotype analysis further supported single SNP results highlighting MYO5B, TSPAN8 and the epidermal growth factor receptor (MYO5B; P=2.04 x 10(-8), TSPAN8; P=7.57 x 10(-7) and EGFR; P=8.36 x 10(-8)). For replication, we genotyped 304 SNPs in family-based NIMH samples (n=409 trios) and University of Edinburgh case-control samples (n=365 cases, 351 controls) that did not provide independent replication after correction for multiple testing. A comparison of our strongest associations with the genome-wide scan of 1868 patients with BP disorder and 2938 controls who completed the scan as part of the Wellcome Trust Case-Control Consortium indicates concordant signals for SNPs within the voltage-dependent calcium channel, L-type, alpha 1C subunit (CACNA1C) gene. Given the heritability of BP disorder, the lack of agreement between studies emphasizes that susceptibility alleles are likely to be modest in effect size and require even larger samples for detection.