Wetlands are the world's largest natural source of methane, a powerful greenhouse gas. The strong sensitivity of methane emissions to environmental factors such as soil temperature and moisture has led to concerns about potential positive feedbacks to climate change. This risk is particularly relevant at high latitudes, which have experienced pronounced warming and where thawing permafrost could potentially liberate large amounts of labile carbon over the next 100 years. However, global models disagree as to the magnitude and spatial distribution of emissions, due to uncertainties in wetland area and emissions per unit area and a scarcity of in situ observations. Recent intensive field campaigns across the West Siberian Lowland (WSL) make this an ideal region over which to assess the performance of large-scale process-based wetland models in a high-latitude environment. Here we present the results of a follow-up to the Wetland and Wetland CH₄ Intercomparison of Models Project (WETCHIMP), focused on the West Siberian Lowland (WETCHIMP-WSL). We assessed 21 models and 5 inversions over this domain in terms of total CH₄ emissions, simulated wetland areas, and CH₄ fluxes per unit wetland area and compared these results to an intensive in situ CH₄ flux data set, several wetland maps, and two satellite surface water products. We found that (a) despite the large scatter of individual estimates, 12-year mean estimates of annual total emissions over the WSL from forward models (5.34 ± 0.54 Tg CH₄ yr^-1), inversions (6.06 ± 1.22 Tg CH₄ yr^-1), and in situ observations (3.91 ± 1.29 Tg CH₄ yr^-1) largely agreed; (b) forward models using surface water products alone to estimate wetland areas suffered from severe biases in CH₄ emissions; (c) the interannual time series of models that lacked either soil thermal physics appropriate to the high latitudes or realistic emissions from unsaturated peatlands tended to be dominated by a single environmental driver (inundation or air temperature), unlike those of inversions and more sophisticated forward models; (d) differences in biogeochemical schemes across models had relatively smaller influence over performance; and (e) multiyear or multidecade observational records are crucial for evaluating models' responses to long-term climate change.

Climate factors including soil temperature and moisture, incident solar radiation, and atmospheric carbon dioxide concentration are important environmental controls on methane (CH₄) emissions from northern wetlands. We investigated the spatiotemporal distributions of the influence of these factors on northern high-latitude wetland CH₄ emissions using an enhanced version of the Variable Infiltration Capacity (VIC) land surface model. We simulated CH₄ emissions from wetlands across the pan-Arctic domain over the period 1948–2006, yielding annual average emissions of 36.1 ± 6.7 Tg CH₄ yr^-1 for the period 1997–2006. We characterized historical sensitivities of CH₄ emissions to air temperature, precipitation, incident long- and shortwave radiation, and atmospheric [CO₂] as a function of average summer air temperature and precipitation. Emissions from relatively warm and dry wetlands in the southern (permafrost-free) portion of the domain were positively correlated with precipitation and negatively correlated with air temperature, while emissions from wetter and colder wetlands further north (permafrost) were positively correlated with air temperature. Over the entire period 1948–2006, our reconstructed CH₄ emissions increased by 20 %, the majority of which can be attributed to an increasing trend in summer air temperature. We estimated future emissions in response to 21st century warming as predicted by CMIP5 (Coupled Model Intercomparison Project Phase 5) model projections to result in end-of-century CH₄ emissions 38–53 % higher than our reconstructed 1997–2006 emissions, accompanied by the northward migration of warmer and drier than optimal conditions for CH₄ emissions, implying a reduced role for temperature in driving future increases in emissions.

About 2.5 × 10⁶ snapshots on microcrystals of photoactive yellow protein (PYP) from a recent serial femtosecond crystallographic (SFX) experiment were reanalyzed to maximum resolution. The resolution is pushed to 1.46 Å, and a PYP structural model is refined at that resolution. The result is compared to other PYP models determined at atomic resolution around 1 Å and better at the synchrotron. By comparing subtleties such as individual isotropic temperature factors and hydrogen bond lengths, we were able to assess the quality of the SFX data at that resolution. We also show that the determination of anisotropic temperature factor ellipsoids starts to become feasible with the SFX data at resolutions better than 1.5 Å.

Contemporary human populations conform to ecogeographic predictions that animals will become more compact in cooler climates and less compact in warmer ones. However, it remains unclear to what extent this pattern reflects plastic responses to current environments or genetic differences among populations. Analyzing anthropometric surveys of 232,684 children and adults from across 80 ethnolinguistic groups in sub-Saharan Africa, Asia and the Americas, we confirm that body surface-to-volume correlates with contemporary temperature at magnitudes found in more latitudinally diverse samples (Adj. R² = 0.14-0.28). However, far more variation in body surface-to-volume is attributable to genetic population structure (Adj. R² = 0.50-0.74). Moreover, genetic population structure accounts for nearly all of the observed relationship between contemporary temperature and body surface-to-volume among children and adults. Indeed, after controlling for population structure, contemporary temperature accounts for no more than 4% of the variance in body form in these groups. This effect of genetic affinity on body form is also independent of other ecological variables, such as dominant mode of subsistence and household wealth per capita. These findings suggest that the observed fit of human body surface-to-volume with current climate in this sample reflects relatively large effects of existing genetic population structure of contemporary humans compared to plastic response to current environments.

Background: The transition from the home to college is a phase in which emerging adults shift toward more unhealthy eating and physical activity patterns, higher body mass indices, thus increasing risk of overweight/obesity. Currently, little is understood about how changing friendship networks shape weight gain behaviors. This paper describes the recruitment, data collection, and data analytic protocols for the SPARC (Social impact of Physical Activity and nutRition in College) study, a longitudinal examination of the mechanisms by which friends and friendship networks influence nutrition and physical activity behaviors and weight gain in the transition to college life.

Methods: The SPARC study aims to follow 1450 university freshmen from a large university over an academic year, collecting data on multiple aspects of friends and friendship networks. Integrating multiple types of data related to student lives, ecological momentary assessments (EMAs) are administered via a cell phone application, devilSPARC. EMAs collected in four 1-week periods (a total of 4 EMA waves) are integrated with linked data from web-based surveys and anthropometric measurements conducted at four times points (for a total of eight data collection periods including EMAs, separated by ~1 month). University databases will provide student card data, allowing integration of both time-dated data on food purchasing, use of physical activity venues, and geographical information system (GIS) locations of these activities relative to other students in their social networks.

Discussion: Findings are intended to guide the development of more effective interventions to enhance behaviors among college students that protect against weight gain during college.