What can intraspecific trait variability tell us about fungal communities and adaptations?

Analyses of species functional traits are suitable to better understand the coexistence of species in a given environment. Trait information can be applied to investigate diversity patterns along environmental gradients and subsequently to predict and mitigate threats associated with climate change and land use. Species traits are used to calculate community trait means, which can be related to environmental gradients. However, while species traits can provide insights into the mechanisms underlying community assembly, they can lead to erroneous inferences if mean trait values are used. An alternative is to incorporate intraspecific trait variability (ITV) into calculating the community trait means. This approach gains increasing acceptance in plant studies. For macrofungi, functional traits have recently been applied to examine their community ecology but, to our knowledge, ITV has yet to be incorporated within the framework of community trait means. Here, we present a conceptual summary of the use of ITV to investigate the community ecology of macrofungi, including the underlying ecological theory. Inferences regarding community trait means with or without the inclusion of ITV along environmental gradients are compared. Finally, an existing study is reconsidered to highlight the variety of possible outcomes when ITV is considered. We hope this Opinion will increase awareness of the potential for within-species trait variability and its importance for statistical inferences, interpretations, and predictions of the mechanisms structuring communities of macro- and other fungi.

Conflicting and Ambiguous Names of Overlapping ORFs in SARS-CoV-2: A Homology-Based Resolution

At least six small alternate-frame open reading frames (ORFs) overlapping well-characterized SARS-CoV-2 genes have been hypothesized to encode accessory proteins. Researchers have used different names for the same ORF or the same name for different ORFs, resulting in erroneous homological and functional inferences. We propose standard names for these ORFs and their shorter isoforms, developed in consultation with the Coronaviridae Study Group of the ICTV. We recommend calling the 39 codon Spike-overlapping ORF ORF2b; the 41, 57, and 22 codon ORF3a-overlapping ORFs ORF3c, ORF3d, and ORF3b; the 33 codon ORF3d isoform ORF3d-2; and the 97 and 73 codon Nucleocapsid-overlapping ORFs ORF9b and ORF9c. Finally, we document conflicting usage of the name ORF3b in 32 studies, and consequent erroneous inferences, stressing the importance of reserving identical names for homologs. We recommend that authors referring to these ORFs provide lengths and coordinates to minimize ambiguity due to prior usage of alternative names.

Large Uncertainties in Earthquake Stress-Drop Estimates and Their Tectonic Consequences

Earthquake stress drop, the stress change on a fault due to an earthquake, is important for seismic hazard analysis because it controls the level of high-frequency ground motions that damage structures. Numerous studies report that stress drops vary by tectonic environment, providing insight into a region’s seismic hazard. Here, we show that teleseismic stress-drop estimates have large uncertainties that make it challenging to distinguish differences between the stress drops of different earthquakes. We compared stress drops for ∼900 earthquakes derived from two independent studies using teleseismic data and found practically zero correlation. Estimates for the same earthquake can differ by orders of magnitude. Therefore, reported stress-drop differences between earthquakes may not reflect true differences. As a result of these larger uncertainties, some tectonic environment stress-drop patterns that appear in one study do not appear in the other analysis of the same earthquakes. These large uncertainties in teleseismic estimates might lead to erroneous inferences about earthquake hazards. In many applications, it may be more appropriate to assume that earthquakes in different regions have approximately the same average stress drop.

Defining a supergiant petroleum system in Brazil’s Santos Basin with multidisciplinary methods: One template for exploration success

Is there a petroleum system here? How extensive and effective is it? How is it defined? Although we had presented a 2005 AAPG poster to address these questions, we now have performed an exploration look-back or case study demonstrating basin-wide presalt charge across Brazil’s Santos Basin. Santos has been a disappointing gas province with meager results compared to the adjacent Campos Basin for the past two decades. We have reviewed and expanded presentations at AAPG and SEG conferences from 1998 to 2005, which were followed 17 months later by the supergiant Tupi discovery, now Lula Field. We document the progression of analyses and revision of interpretations as a case history for multidisciplinary work in a frontier region with, at the time, scant coverage of key data types. Despite our access to a broad range of material (oil and cuttings samples, piston core extracts, slicks analysis, regional seismic lines, potential field coverages, and published literature), only a handful of point samples directly fitted our hypothesis of a mature oil-prone presalt source, supported by our inference, from leakage at the basin margins, of basin-wide migration and charge. Although the volumes of data collected across the Santos Basin are orders of magnitude larger in 2019, with a concomitant improvement in understanding the petroleum system and overall basin evolution, we take pains to limit our focus to what was known as of mid-2005 (although perhaps published later), which still sufficed to point to the future success. Because the source presence and effectiveness are the first consideration in evaluating frontier basins, our methodology provides one template for understanding a key geologic risk. We emphasize the importance of careful screening of inputs when information is scant and thus erroneous inferences are easily reached, with the need to take an exploration inference wherever data, once cross-validated, direct the explorer.

Accounting for Gene Flow from Unsampled ‘Ghost’ Populations while Estimating Evolutionay History under the Isolation with Migration Model

Unsampled or extinct ‘ghost’ populations leave signatures on the genomes of individuals from extant, sampled populations, especially if they have exchanged genes with them over evolutionary time. This gene flow from ‘ghost’ populations can introduce biases when estimating evolutionary history from genomic data, often leading to data misinterpretation and ambiguous results. Here we assess these biases while accounting, or not accounting for gene flow from ‘ghost’ populations under the Isolation with Migration (IM) model. We perform extensive simulations under five scenarios with no gene flow (Scenario A), to extensive gene flow to- and from- an unsampled ‘ghost’ population (Scenarios B, C, D, and E). Estimates of evolutionary history across all scenarios A-E (effective population sizes, divergence times, and migration rates) indicate consistent a) under-estimation of divergence times between sampled populations, (b) over-estimation of effective population sizes of sampled populations, and (c) under-estimation of migration rates between sampled populations, with increased gene flow from the unsampled ‘ghost’ population. Without accounting for an unsampled ‘ghost’, summary statistics like FST are under-estimated, and π is over-estimated with increased gene flow from the‘ghost’. To show this persistent issue in empirical data, we use a 355 locus dataset from African Hunter-Gatherer populations and discuss similar biases in estimating evolutionary history while not accounting for unsampled ‘ghosts’. Considering the large effects of gene flow from these ‘ghosts’, we propose a multi-pronged approach to account for the presence of unsampled ‘ghost’ populations in population genomics studies to reduce erroneous inferences.

Inferential Practices in Social Interaction: A Conversation-Analytic Account

This paper argues that conversation analysis has largely neglected the fact that meaning in interaction relies on inferences to a high degree. Participants treat each other as cognitive agents, who imply and infer meanings, which are often consequential for interactional progression. Based on the study of audio- and video-recordings from German talk-in-interaction, the paper argues that inferences matter to social interaction in at least three ways. They can be explicitly formulated; they can be (conventionally) indexed, but not formulated; or they may be neither indexed nor formulated yet would be needed for the correct understanding of a turn. The last variety of inferences usually remain tacit, but are needed for smooth interactional progression. Inferences in this case become an observable discursive phenomenon if misunderstandings are treated by the explication of correct (accepted) and wrong (unaccepted) inferences. The understanding of referential terms, analepsis, and ellipsis regularly rely on inferences. Formulations, third-position repairs, and fourth-position explications of erroneous inferences are practices of explicating inferences. There are conventional linguistic means like discourse markers, connectives, and response particles that index specific kinds of inferences. These practices belong to a larger class of inferential practices, which play an important role for indexing and accomplishing intersubjectivity in talk in interaction.

Standardised cigarette packaging may reduce the implied safety of Natural American Spirit cigarettes

BackgroundOver two-thirds of Natural American Spirit (NAS) smokers believe their cigarettes might be ‘less harmful’, but toxicological evidence does not support this belief. We assessed whether standardised packaging could reduce the possibility of erroneous inferences of ‘safety’ drawn from NAS cigarette packaging.MethodsUS adult smokers (n=909) were recruited to a between-subject survey experiment (3 brands×3 packaging/labelling styles) through Amazon Mechanical Turk and rated their perception of whether a randomly assigned cigarette package conveyed that the brand was ‘safer’ on a three-item scale (Cronbach’s α=0.92). We assessed whether NAS packs were rated higher on the ‘implied safety’ scale than two other brands and estimated the effect that plain packaging (ie, all branding replaced with a drab dark brown colour) and Australian-like packaging (ie, all branding replaced with a drab dark brown colour and a graphic image and text on 75% of the pack surface) had on perceptions of the NAS cigarette package.ResultsSmokers’ ratings of the standard NAS pack on the implied safety scale (mean=4.6; SD=2.9) were 1.9 times (P <0.001) higher than smokers’ ratings of a Marlboro Red pack (mean=2.4; SD=2.3) and 1.7 times (P <0.001) higher than smokers’ ratings of a Newport Menthol pack (mean=2.7; SD=2.4). These perceptions of implied safety were lower when plain packaging was used (Cohen’s d=0.66; P <0.001) and much lower when Australian-like packaging was used (Cohen’s d=1.56; P <0.001).ConclusionThe results suggest that NAS cigarette packaging conveys that its cigarettes are ‘safer’ and that such perceptions are lower with standardised packaging, both with and without warning images.

Biased evolutionary inferences from bulk tumor samples

ABSTRACTIt is generally agreed that tumors are composed of multiple cell clones defined by different somatic mutations. Characterizing the evolutionary mechanisms driving this intratumor genetic heterogeneity (ITH) is crucial to improve both cancer diagnosis and therapeutic strategies. For that purpose, recent ITH studies have focused on qualitative comparisons of mutational profiles derived from bulk sequencing of multiple tumor samples extracted from the same patient. Here, we show some examples where the naive use of bulk data in multiregional studies may lead to erroneous inferences of the evolutionary trajectories that underlie tumor progression, including biased timing of somatic mutations, spurious parallel mutation events, and/or incorrect chronological ordering of metastatic events. In addition, we analyze three real datasets to highlight how the use of bulk mutational profiles instead of inferred clones can lead to different conclusions about mutational recurrence and population structure.