Climate model dependence and the replicate Earth paradigm

Multi-model ensembles are commonly used in climate prediction to create a set of independent estimates, and so better gauge the likelihood of particular outcomes and better quantify prediction uncertainty. Yet researchers share literature, datasets and model code—to what extent do different simulations constitute independent estimates? What is the relationship between model performance and independence? We show that error correlation provides a natural empirical basis for defining model dependence and derive a weighting strategy that accounts for dependence in experiments where the multi-model mean would otherwise be used. We introduce the “replicate Earth” ensemble interpretation framework, based on theoretically derived statistical relationships between ensembles of perfect models (replicate Earths) and observations. We transform an ensemble of (imperfect) climate projections into an ensemble whose mean and variance have the same statistical relationship to observations as an ensemble of replicate Earths. The approach can be used with multi-model ensembles that have varying numbers of simulations from different models, accounting for model dependence. We use HadCRUT3 data and the CMIP3 models to show that in out of sample tests, the transformed ensemble has an ensemble mean with significantly lower error and much flatter rank frequency histograms than the original ensemble.     

Impact of Data Density and Geostatistical Simulation Technique on the Estimation of Residence Times in a Synthetic Two-dimensional Aquifer

Connectivity patterns of heterogeneous porous media are important in the estimation of groundwater residence time distributions (RTDs). Understanding the connectivity patterns of a hydraulic conductivity ( \(K\) ) field often requires knowledge of the entire aquifer, which is not practical. As such, the method used to estimate unknown \(K\) values using known \(K\) values is important. This study investigates how varying levels of conditioning data and four simulation techniques, one multi-Gaussian and three multi-point, are able to recreate key \(K\) field features and connectivity patterns of a synthetic two-dimensional bimodal distributed ln( \(K\) ) field with highly connected high \(K\) features. These techniques are then assessed in the context of RTD estimation. It was found that the multi-Gaussian technique presented a bias towards earlier travel times with increased conditioning data. This was due to the inability of the method to recreate multiple scales of connecting features. Of the multi-point methods investigated, the facies method was unable to predict early arrival times. The use of a continuous variable training image produced good fits to the observed residence time distribution with a high number of conditioning points. The ability of the methods to predict the shape of residence time distributions appears to be related to their ability to reproduce the connection patterns of higher \(K\) features.     

Genetic Variation in the Common Reed, <Emphasis Type="Italic">Phragmites australis</Emphasis>, in the Mississippi River Delta Marshes: Evidence for Multiple Introductions

Multiple introductions are believed to play an important role in increasing genetic diversity and adaptability of invasive species, but there are few well-documented examples. The common reed, Phragmites australis, has dramatically increased in tidal wetlands throughout the USA in the past century due primarily to the introduction of a Eurasian lineage. In the Mississippi River “Balize” delta, P. australis is the dominant vegetation where monotypic stands of an introduced form blanket the outer marshes. The delta’s interior marshes, on the other hand, are more vegetatively diverse, serving as important waterfowl foraging habitat. Recent encroachment by various phenotypic forms of P. australis into the interior marshes led to this study examining genetic variation in these stands. Our results revealed four chloroplast DNA haplotypes that also segregate based on microsatellite variation. Three of these are closely related and introduced, but differ relative to time and likely mode of introduction. The “Delta” type (haplotype M1), which is unique to the region and the most common lineage, displays considerable microsatellite diversity. The Eurasian introduced lineage of P. australis (haplotype M), which is invasive elsewhere in North America, is increasing its distribution in the delta. A novel haplotype, AD, was also identified which is phenotypically and genetically similar to haplotype M. Despite the close relatedness, we found no evidence for inter-haplotype gene exchange at the nuclear level, suggesting that intraspecific hybridization is not a contributing factor to these invasions. The site provides a unique opportunity for researchers to understand the dynamics of multiple P. australis invasions.     

Big Data from the Ground Up: Mobile Maps and Geographic Knowledge

Consumer users of maps on mobile devices are producing noteworthy geographic knowledges in the contexts of their own lives that are distinct from those of professional data scientists. By leveraging the streaming nature of big data in mobile maps and zooming multiscalar views, consumer users' mobile map practices produce a popular, multiscalar form of visual geographic knowledge that is both enabled and limited by its big data assemblage and associated technologies. The first half of this article outlines the role of consumer user practices amidst spatial big data assemblages, not for volunteered geographic information or aggregate analysis but for contextual, everyday use. Consumer users and their knowledges are coconstituted through mobile map viewing and as materially limited technological practices. This article focuses specifically on the consumer users' concept of scale in this context, for Web-based maps' multiscalar views differentiate them from older maps. The second half analyzes mobile map consumer users' concepts of scale in a series of focus groups that involved both questions and observing participants' actions with maps on their own phones. Instead of passively accepting maps at predetermined optimized scales from the map application, consumer users actively viewed the map across scales while searching but not while navigating.     

Use of microbial enrichments for the study of the anaerobic degradation of cholesterol

To demonstrate the potential of model microbial assemblages in studies of the biogeochemistry of complex organic molecules, anaerobic microbial populations capable of degrading cholesterol (cholest-5-en-3β-ol) have been enriched from marine sediment sources. The bacterial enrichments actively mineralized the C-4 nucleus of the cholesterol ring system to carbon dioxide when nitrate was present as the terminal electron acceptor. Nitrite was found as an intermediate in the reduction of nitrate, indicating the presence of denitrifying bacteria in the enrichments. When sulfate was supplied as the sole electron acceptor, active dissimilation of cholesterol was not observed. In enrichments containing 5 mM nitrate, 95–98% of the added cholesterol was recovered as carbon dioxide (2–5%), transformation products (20–30%), or as the unmodified sterol (70–80%). Cholesterol transformation products thus far identified include 5α- and 5β-cholestan-3β-ol, cholest-4-en-3-one, 5α-androstan-3, 17-dione and androst-4-en-3, 17 dione.     

Minor-element and Sr-isotope geochemistry of tertiary stocks,Colorado mineral belt

Rocks of the northeast portion of the Colorado mineral belt form two petrographically, chemically and geographically distinct rock suites: (1) a silica oversaturated granodiorite suite; and (2) a silica saturated, high alkali monzonite suite. Rocks of the granodiorite suite generally have Sr contents less than 1000 ppm, subparallel REE patterns and initial ⁸⁷Sr/ ⁸⁶Sr ratios greater than 0.707. Rocks of the monzonite suite are restricted to the northeast part of the mineral belt, where few rocks of the granodiorite suite occur, and generally have Sr contents greater than 1000 ppm, highly variable REE patterns and ⁸⁷Sr/⁸⁶Sr initial ratios less than 0.706.Despite forming simple, smooth trends on major element variation diagrams, trace element data for rocks of the granodiorite suite indicate that they were not derived from a single magma. These rocks were derived from magmas having similar REE patterns, but variable Rb and Sr contents, and Rb/Sr ratios. The preferred explanation for these rocks is that they were derived by partial melting of a mixed source, which yielded pyroxene granulite or pyroxenite residues.The monzonite suite is chemically and petrographically more complex than the granodiorite suite. It is subdivided here into alkalic and mafic monzonites, and quartz syenites, based on the textural relations of their ferromagnesian phases and quartz. The geochemistry of these three rock types require derivation from separate and chemically distinct magma types. The preferred explanation for the alkalic monzonites is derivation from a heterogeneous mafic source, leaving a residue dominated by garnet and clinopyroxene. Early crystallization of sphene from these magmas was responsible for the severe depletion of the REE observed in the residual magmas. The lower Sr content and higher Rb/Sr ratios of the mafic monzonites requires a plagioclase-bearing source.The Sr-isotope systematics of the majority of these rocks are interpreted to be largely primary, and not the result of crustal contamination. The positive correlation of Rb/Sr and ⁸⁷Sr/⁸⁶Sr ratios for the least fractionated samples indicate that the sources from which parent magmas of both the granodiorite and monzonite suites were derived are Precambrian in age.