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Abstract The allometric trophic network (ATN) framework for modeling population dynamics has provided numerous insights into ecosystem functioning in recent years. Herein we extend ATN modeling of the intertidal ecosystem off central Chile to include empirical data on pelagic chlorophyll-a concentration. This intertidal community requires subsidy of primary productivity to support its rich ecosystem. Previous work models this subsidy using a constant rate of phytoplankton input to the system. However, data shows pelagic subsidies exhibit highly variable, pulse-like behavior. The primary contribution of our work is incorporating this variable input into ATN modeling to simulate how this ecosystem may respond to pulses of pelagic phytoplankton. Our model results show that: (1) closely related sea snails respond differently to phytoplankton variability, which is explained by the underlying network structure of the food web; (2) increasing the rate of pelagic-intertidal mixing increases fluctuations in species’ biomasses that may increase the risk of local extirpation; (3) predators are the most sensitive species to phytoplankton biomass fluctuations, putting these species at greater risk of extirpation than others. Finally, our work provides a straightforward way to incorporate empirical, time-series data into the ATN framework that will expand this powerful methodology to new applications. 

Abstract. With the onset of anthropogenic climate change, it is vital that we understand climate sensitivity and rates of change during periods of warming in the Earth's past to properly inform climate forecasts. To best inform modeling of ongoing and future changes, environmental conditions during past periods of extreme warmth are ideally developed from multiproxy approaches, including the development of novel proxies where traditional approaches fail. This study builds on a proposed sea surface temperature (SST) proxy for the high-latitude Southern Ocean, based on the morphometrics of the ubiquitous Antarctic diatom Fragilariopsis kerguelensis. This species has been shown to display two distinct morphotypes; a low-rectangularity morphotype is interpreted to be more common in warmer waters while a high-rectangularity morphotype is more common in cooler waters. The proportion of the low-rectangularity morphotype (pLR) has been correlated to SST and summer SST (SSST). Here, we examine this proxy by reconstructing SST using sediment samples from the modern seafloor surface in the Amundsen Sea and the Sabrina Coast to test how well two published calibrations of this relationship (Kloster et al., 2018; Glemser et al., 2019) reconstruct SST and SSST in the modern ocean. In the Amundsen Sea surface sediments, we calculate derived SST −1.6 to −1.2 °C and derived SSST 0.6 to 0.7 °C. In the Sabrina Coast surface sediments, we calculate derived SST −0.3 to 0.5 °C and derived SSST 1.4 to 2.5 °C. We discuss the differing population dynamics of F. kerguelensis in our surface samples between the Amundsen Sea and Sabrina Coast because the Amundsen Sea specimens display a lower pLR than Sabrina Coast specimens, although they exist in warmer waters and should display a higher pLR. We also use the two published calibrations to preliminarily reconstruct SST and SSST in the Amundsen Sea over the last interglacial, Marine Isotope Stage 5 (MIS-5). We calculate SSTs that are slightly cooler or within the range of the modern Amundsen Sea for the duration of the last interglacial; we calculate summer SSTs ∼ 1 °C warmer than the modern Amundsen Sea. This suggests MIS-5 SSTs were at most marginally warmer than the modern Amundsen Sea. 

Amabiko is a lytic subcluster BE2 bacteriophage that infects Streptomyces scabiei — a bacterium causing common scab in potatoes. Its 131,414 bp genome has a GC content of 49.5% and contains 245 putative protein-coding genes, 45 tRNAs, and one tmRNA. Amabiko is closely related to Streptomyces bacteriophage MindFlayer (gene content similarity: 86.5%). 

The objective of this article was to review existing research to assess the evidence for predictive processing (PP) in sign language, the conditions under which it occurs, and the effects of language mastery (sign language as a first language, sign language as a second language, bimodal bilingualism) on the neural bases of PP. This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. We searched peer-reviewed electronic databases (SCOPUS, Web of Science, PubMed, ScienceDirect, and EBSCO host) and gray literature (dissertations in ProQuest). We also searched the reference lists of records selected for the review and forward citations to identify all relevant publications. We searched for records based on five criteria (original work, peer-reviewed, published in English, research topic related to PP or neural entrainment, and human sign language processing). To reduce the risk of bias, the remaining two authors with expertise in sign language processing and a variety of research methods reviewed the results. Disagreements were resolved through extensive discussion. In the final review, 7 records were included, of which 5 were published articles and 2 were dissertations. The reviewed records provide evidence for PP in signing populations, although the underlying mechanism in the visual modality is not clear. The reviewed studies addressed the motor simulation proposals, neural basis of PP, as well as the development of PP. All studies used dynamic sign stimuli. Most of the studies focused on semantic prediction. The question of the mechanism for the interaction between one’s sign language competence (L1 vs. L2 vs. bimodal bilingual) and PP in the manual-visual modality remains unclear, primarily due to the scarcity of participants with varying degrees of language dominance. There is a paucity of evidence for PP in sign languages, especially for frequency-based, phonetic (articulatory), and syntactic prediction. However, studies published to date indicate that Deaf native/native-like L1 signers predict linguistic information during sign language processing, suggesting that PP is an amodal property of language processing. Systematic Review Registration [ https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021238911 ], identifier [CRD42021238911]. 

Abstract Sign languages are human communication systems that are equivalent to spoken language in their capacity for information transfer, but which use a dynamic visual signal for communication. Thus, linguistic metrics of complexity, which are typically developed for linear, symbolic linguistic representation (such as written forms of spoken languages) do not translate easily into sign language analysis. A comparison of physical signal metrics, on the other hand, is complicated by the higher dimensionality (spatial and temporal) of the sign language signal as compared to a speech signal (solely temporal). Here, we review a variety of approaches to operationalizing sign language complexity based on linguistic and physical data, and identify the approaches that allow for high fidelity modeling of the data in the visual domain, while capturing linguistically-relevant features of the sign language signal. 

Longstanding cross-linguistic work on event representations in spoken languages have argued for a robust mapping between an event’s underlying representation and its syntactic encoding, such that–for example–the agent of an event is most frequently mapped to subject position. In the same vein, sign languages have long been claimed to construct signs that visually represent their meaning, i.e., signs that are iconic. Experimental research on linguistic parameters such as plurality and aspect has recently shown some of them to be visually universal in sign, i.e. recognized by non-signers as well as signers, and have identified specific visual cues that achieve this mapping. However, little is known about what makes action representations in sign language iconic, or whether and how the mapping of underlying event representations to syntactic encoding is visually apparent in the form of a verb sign. To this end, we asked what visual cues non-signers may use in evaluating transitivity (i.e., the number of entities involved in an action). To do this, we correlated non-signer judgments about transitivity of verb signs from American Sign Language (ASL) with phonological characteristics of these signs. We found that non-signers did not accurately guess the transitivity of the signs, but that non-signer transitivity judgments can nevertheless be predicted from the signs’ visual characteristics. Further, non-signers cue in on just those features that code event representations across sign languages, despite interpreting them differently. This suggests the existence of visual biases that underlie detection of linguistic categories, such as transitivity, which may uncouple from underlying conceptual representations over time in mature sign languages due to lexicalization processes.