Territorial Differential Meta-Evolution: An Algorithm for Seeking All the Desirable Optima of a Multivariable Function.

Territorial Differential Meta-Evolution (TDME) is an efficient, versatile, and reliable algorithm for seeking all the global or desirable local optima of a multivariable function. It employs a progressive niching mechanism to optimize even challenging, highdimensional functions with multiple global optima and misleading local optima. This article introduces TDME and uses standard and novel benchmark problems to quantify its advantages over HillVallEA, which is the best-performing algorithm on the standard benchmark suite that has been used by all major multimodal optimization competitions since 2013. TDME matches HillVallEA on that benchmark suite and categorically outperforms it on a more comprehensive suite that better reflects the potential diversity of optimization problems. TDME achieves that performance without any problem-specific parameter tuning.

Detecting forest response to droughts with global observations of vegetation water content.

Droughts in a warming climate have become more common and more extreme, making understanding forest responses to water stress increasingly pressing. Analysis of water stress in trees has long focused on water potential in xylem and leaves, which influences stomatal closure and water flow through the soil-plant-atmosphere continuum. At the same time, changes of vegetation water content (VWC) are linked to a range of tree responses, including fluxes of water and carbon, mortality, flammability, and more. Unlike water potential, which requires demanding in situ measurements, VWC can be retrieved from remote sensing measurements, particularly at microwave frequencies using radar and radiometry. Here, we highlight key frontiers through which VWC has the potential to significantly increase our understanding of forest responses to water stress. To validate remote sensing observations of VWC at landscape scale and to better relate them to data assimilation model parameters, we introduce an ecosystem-scale analog of the pressure-volume curve, the non-linear relationship between average leaf or branch water potential and water content commonly used in plant hydraulics. The sources of variability in these ecosystem-scale pressure-volume curves and their relationship to forest response to water stress are discussed. We further show to what extent diel, seasonal, and decadal dynamics of VWC reflect variations in different processes relating the tree response to water stress. VWC can also be used for inferring belowground conditions-which are difficult to impossible to observe directly. Lastly, we discuss how a dedicated geostationary spaceborne observational system for VWC, when combined with existing datasets, can capture diel and seasonal water dynamics to advance the science and applications of global forest vulnerability to future droughts.

Methane dynamics regulated by microbial community response to permafrost thaw.

Permafrost contains about 50% of the global soil carbon. It is thought that the thawing of permafrost can lead to a loss of soil carbon in the form of methane and carbon dioxide emissions. The magnitude of the resulting positive climate feedback of such greenhouse gas emissions is still unknown and may to a large extent depend on the poorly understood role of microbial community composition in regulating the metabolic processes that drive such ecosystem-scale greenhouse gas fluxes. Here we show that changes in vegetation and increasing methane emissions with permafrost thaw are associated with a switch from hydrogenotrophic to partly acetoclastic methanogenesis, resulting in a large shift in the δ(13)C signature (10-15‰) of emitted methane. We used a natural landscape gradient of permafrost thaw in northern Sweden as a model to investigate the role of microbial communities in regulating methane cycling, and to test whether a knowledge of community dynamics could improve predictions of carbon emissions under loss of permafrost. Abundance of the methanogen Candidatus 'Methanoflorens stordalenmirensis' is a key predictor of the shifts in methane isotopes, which in turn predicts the proportions of carbon emitted as methane and as carbon dioxide, an important factor for simulating the climate feedback associated with permafrost thaw in global models. By showing that the abundance of key microbial lineages can be used to predict atmospherically relevant patterns in methane isotopes and the proportion of carbon metabolized to methane during permafrost thaw, we establish a basis for scaling changing microbial communities to ecosystem isotope dynamics. Our findings indicate that microbial ecology may be important in ecosystem-scale responses to global change.

Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales.

Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model was able to explain most of the variability in GEP at hourly (R2  = 0.77) to interannual (R2  = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). This work highlights the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms.

Methylotrophy in the Mire: direct and indirect routes for methane production in thawing permafrost.

While wetlands are major sources of biogenic methane (CH4), our understanding of resident microbial metabolism is incomplete, which compromises the prediction of CH4 emissions under ongoing climate change. Here, we employed genome-resolved multi-omics to expand our understanding of methanogenesis in the thawing permafrost peatland of Stordalen Mire in Arctic Sweden. In quadrupling the genomic representation of the site's methanogens and examining their encoded metabolism, we revealed that nearly 20% of the metagenome-assembled genomes (MAGs) encoded the potential for methylotrophic methanogenesis. Further, 27% of the transcriptionally active methanogens expressed methylotrophic genes; for Methanosarcinales and Methanobacteriales MAGs, these data indicated the use of methylated oxygen compounds (e.g., methanol), while for Methanomassiliicoccales, they primarily implicated methyl sulfides and methylamines. In addition to methanogenic methylotrophy, >1,700 bacterial MAGs across 19 phyla encoded anaerobic methylotrophic potential, with expression across 12 phyla. Metabolomic analyses revealed the presence of diverse methylated compounds in the Mire, including some known methylotrophic substrates. Active methylotrophy was observed across all stages of a permafrost thaw gradient in Stordalen, with the most frozen non-methanogenic palsa found to host bacterial methylotrophy and the partially thawed bog and fully thawed fen seen to house both methanogenic and bacterial methylotrophic activities. Methanogenesis across increasing permafrost thaw is thus revised from the sole dominance of hydrogenotrophic production and the appearance of acetoclastic at full thaw to consider the co-occurrence of methylotrophy throughout. Collectively, these findings indicate that methanogenic and bacterial methylotrophy may be an important and previously underappreciated component of carbon cycling and emissions in these rapidly changing wetland habitats.IMPORTANCEWetlands are the biggest natural source of atmospheric methane (CH4) emissions, yet we have an incomplete understanding of the suite of microbial metabolism that results in CH4 formation. Specifically, methanogenesis from methylated compounds is excluded from all ecosystem models used to predict wetland contributions to the global CH4 budget. Though recent studies have shown methylotrophic methanogenesis to be active across wetlands, the broad climatic importance of the metabolism remains critically understudied. Further, some methylotrophic bacteria are known to produce methanogenic by-products like acetate, increasing the complexity of the microbial methylotrophic metabolic network. Prior studies of Stordalen Mire have suggested that methylotrophic methanogenesis is irrelevant in situ and have not emphasized the bacterial capacity for metabolism, both of which we countered in this study. The importance of our findings lies in the significant advancement toward unraveling the broader impact of methylotrophs in wetland methanogenesis and, consequently, their contribution to the terrestrial global carbon cycle.

The line shape problem in the near-infrared spectrum of self-colliding CO2 molecules: experimental investigation and test of semiclassical models.

An intensity-stabilized diode laser absorption spectrometer was developed and used to perform a highly accurate study of the line shape of CO(2) absorption lines, in the spectral region around 5000 cm(-1), belonging to the nu(1) + 2nu(2)(0) + nu(3) combination band, at a temperature of 296.00 K. Standard and complex semiclassical models, including Dicke narrowing and speed-dependent broadening effects, were applied, tested, and compared in the pressure range between 0.7 and 4 kPa, in order to single out the model best reproducing the absorption profile and, hence, the physical situation of self-colliding CO(2) molecules. Line intensity factors and self-broadening coefficients were determined. The 1-sigma overall accuracy of our determinations is at a level of 0.1%, which is, to our knowledge, the highest ever reached.

Highly accurate determinations of CO(2) line strengths using intensity-stabilized diode laser absorption spectrometry.

An intensity-stabilized laser absorption spectrometer, which incorporates a mirror-extended cavity diode laser, a temperature-stabilized gas cell, and a Michelson interferometer, was developed and applied to a highly accurate investigation of line intensity factors within the nu(1)+2nu(2) (0)+nu(3) combination band of carbon dioxide, around 2 microm wavelength, at a temperature of 296.0 K. This relatively complex apparatus enables one to observe the absorption line shape with high precision and accuracy in such a way that it is possible to retrieve the integrated absorbance with a relative uncertainty better than 0.1%. The absorption spectra were interpolated with the uncorrelated strong-collision model of Rautian and Sobel'man in order to take into account Dicke narrowing effects, thus obtaining an agreement at a level of a few parts per 10(-5). We report line strength values for the R(2)-R(18) transitions with an unprecedented level of accuracy, in the range between 0.1% and 0.15%. Finally, we discuss the possibility of providing a first experimental test of the theoretical model for molecular line strengths based on the Herman-Wallis expansion.

Dynamic spectroscopic measurements of the temperature and pressure cycles in a MOPITT pressure modulator cell.

The temperature and pressure cycles inside a pressure modulator cell (PMC) of the type used for gas-correlation radiometry aboard the Measurements of Pollution in the Troposphere (MOPITT) satellite instrument have been determined from dynamic measurements of the spectral line shapes of the R(0) and R(18) transitions in the fundamental vibrational-rotational band of carbon monoxide. The line strengths and linewidths were used to calculate the temperature and pressure, respectively, with a temporal resolution of approximately 200 micros, or 1/100 of a PMC cycle. The results are compared with a thermodynamic box model.