Storm impacts on phytoplankton community dynamics in lakes

In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short-term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well-developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short- and long-term. We summarize the current understanding of storm-induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.Peer reviewe

Storm impacts on phytoplankton community dynamics in lakes

In many regions across the globe, extreme weather events, such as storms, have increased in frequency, intensity and duration. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. For lake ecosystems, high winds and rainfall associated with storms are linked by short term runoff events from catchments and physical mixing of the water column. Although we have a well-developed understanding of how such wind and precipitation events alter lake physical processes, our mechanistic understanding of how these short-term disturbances 48 translate from physical forcing to changes in phytoplankton communities is poor. Here, we provide a conceptual model that identifies how key storm features (i.e., the frequency, intensity, and duration of wind and precipitation) interact with attributes of lakes and their watersheds to generate changes in a lake’s physical and chemical environment and subsequently phytoplankton community structure and dynamics. We summarize the current understanding of storm-phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions by generating testable hypotheses across a global gradient of lake types and environmental conditions.Fil: Stockwell, Jason D.. University of Vermont; Estados UnidosFil: Adrian, Rita. Leibniz Institute of Freshwater Ecology and Inland Fisheries; AlemaniaFil: Andersen, Mikkel. Dundalk Institute of Technology; IrlandaFil: Anneville, Orlane. Institut National de la Recherche Agronomique; FranciaFil: Bhattacharya, Ruchi. University of Missouri; Estados UnidosFil: Burns, Wilton G.. University of Vermont; Estados UnidosFil: Carey, Cayelan C.. Virginia Tech University; Estados UnidosFil: Carvalho, Laurence. Freshwater Restoration & Sustainability Group; Reino UnidoFil: Chang, ChunWei. National Taiwan University; República de ChinaFil: De Senerpont Domis, Lisette N.. Netherlands Institute of Ecology; Países BajosFil: Doubek, Jonathan P.. University of Vermont; Estados UnidosFil: Dur, Gaël. Shizuoka University; JapónFil: Frassl, Marieke A.. Griffith University; AustraliaFil: Gessner, Mark O.. Leibniz Institute of Freshwater Ecology and Inland Fisheries; AlemaniaFil: Hejzlar, Josef. Biology Centre of the Czech Academy of Sciences; República ChecaFil: Ibelings, Bas W.. University of Geneva; SuizaFil: Janatian, Nasim. Estonian University of Life Sciences; EstoniaFil: Kpodonu, Alfred T. N. K.. City University of New York; Estados UnidosFil: Lajeunesse, Marc J.. University of South Florida; Estados UnidosFil: Lewandowska, Aleksandra M.. Tvarminne Zoological Station; FinlandiaFil: Llames, Maria Eugenia del Rosario. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Matsuzaki, Shin-ichiro S.. National Institute for Environmental Studies; JapónFil: Nodine, Emily R.. Rollins College; Estados UnidosFil: Nõges, Peeter. Estonian University of Life Sciences; EstoniaFil: Park, Ho-Dong. Shinshu University; JapónFil: Patil, Vijay P.. US Geological Survey; Estados UnidosFil: Pomati, Francesco. Swiss Federal Institute of Water Science and Technology; SuizaFil: Rimmer, Alon. Kinneret Limnological Laboratory; IsraelFil: Rinke, Karsten. Helmholtz-Centre for Environmental Research; AlemaniaFil: Rudstam, Lars G.. Cornell University; Estados UnidosFil: Rusak, James A.. Ontario Ministry of the Environment and Climate Change; CanadáFil: Salmaso, Nico. Research and Innovation Centre - Fondazione Mach; ItaliaFil: Schmitt, François. Laboratoire d’Océanologie et de Géosciences; FranciaFil: Seltmann, Christian T.. Dundalk Institute of Technology; IrlandaFil: Souissi, Sami. Universite Lille; FranciaFil: Straile, Dietmar. University of Konstanz; AlemaniaFil: Thackeray, Stephen J.. Lancaster Environment Centre; Reino UnidoFil: Thiery, Wim. Vrije Unviversiteit Brussel; Bélgica. Institute for Atmospheric and Climate Science; SuizaFil: Urrutia Cordero, Pablo. Uppsala University; SueciaFil: Venail, Patrick. Universidad de Ginebra; SuizaFil: Verburg, Piet. 8National Institute of Water and Atmospheric Research; Nueva ZelandaFil: Williamson, Tanner J.. Miami University; Estados UnidosFil: Wilson, Harriet L.. Dundalk Institute of Technology; IrlandaFil: Zohary, Tamar. Israel Oceanographic & Limnological Research; IsraelGLEON 20: All Hands' MeetingRottnest IslandAustraliaUniversity of Western AustraliaUniversity of AdelaideGlobal Lake Ecological Observatory Networ

Finding Our Way through Phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility

Seasonal Fluctuations of Astrovirus, But Not Coronavirus Shedding in Bats Inhabiting Human-Modified Tropical Forests

Emerging infectious diseases (EIDs) are considered a major threat to global health. Most EIDs appear to result from increased contact between wildlife and humans, especially when humans encroach into formerly pristine habitats. Habitat deterioration may also negatively affect the physiology and health of wildlife species, which may eventually lead to a higher susceptibility to infectious agents and/or increased shedding of the pathogens causing EIDs. Bats are known to host viruses closely related to important EIDs. Here, we tested in a paleotropical forest with ongoing logging and fragmentation, whether habitat disturbance influences the occurrence of astro- and coronaviruses in eight bat species. In contrast to our hypothesis, anthropogenic habitat disturbance was not associated with corona- and astrovirus detection rates in fecal samples. However, we found that bats infected with either astro- or coronaviruses were likely to be coinfected with the respective other virus. Additionally, we identified two more risk factors influencing astrovirus shedding. First, the detection rate of astroviruses was higher at the beginning of the rainy compared to the dry season. Second, there was a trend that individuals with a poor body condition had a higher probability of shedding astroviruses in their feces. The identification of risk factors for increased viral shedding that may potentially result in increased interspecies transmission is important to prevent viral spillovers from bats to other animals, including humans

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Finding Our Way through Phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility

Phenotypes shared across biology.

<p>Phenotype data are relevant to many different domains, but they are currently isolated in data “silos.” Research from a broad array of seemingly disconnected domains, as outlined here, can be dramatically accelerated with a computable data store. (<b>A</b>) <b>Domains</b>: Diverse fields such as evolutionary biology, human disease and medicine, and climate change relate to phenotypes. (<b>B</b>) <b>Phenotypes</b>: insects, vertebrates, plants, and even forests all have features that are branched in some way, but they are described using different terms. For a computer to discover this, the phenotypes must be annotated with unique identifiers from ontologies that are logically linked. Under “shape” in the PATO quality ontology <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Gkoutos1" target="_blank">[106]</a>, “branchiness” is an encompassing parent term with subtypes “branched” and “increased branchiness.” From left to right, top layer, insects, vertebrates and plants have species that demonstrate phenotypes for which the genetic basis is not known. Often their companion model species, however, have experimental genetic work that is relevant to proposing candidate genes and gene networks. Insects (1): An evolutionary novelty in bees (top layer) is the presence of branched setae used for pollen collection. Nothing is known about the genetic basis of this feature. One clue to the origin of this evolutionary feature comes from studies of <i>Drosophila</i> (bottom layer), where <i>Mical</i> overexpression in unbranched wild-type bristles generates a branched morphology <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Hung1" target="_blank">[119]</a>. Mical directly links semaphorins and their plexin receptors to the precise control of actin filament dynamics <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Hung1" target="_blank">[119]</a>. Vertebrates (2): In humans, aberrant angiogenesis, including excessive blood vessel branching (top layer), is one of the six central hallmarks of cancer <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Hanahan1" target="_blank">[121]</a>. Candidate genes have been identified using data from model organisms. In zebrafish (middle layer), studies of the control of sprouting in blood vessel development show that signaling via semaphorins <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Yazdani1" target="_blank">[122]</a> and their plexin receptors is required for proper abundance and distribution <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Gu1" target="_blank">[123]</a>; disruption of <i>plxnd1</i> results in increased branching <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Alvarez1" target="_blank">[120]</a>,<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Zygmunt1" target="_blank">[124]</a>,<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-TorresVazquez1" target="_blank">[125]</a>. In mouse (bottom layer), branching of salivary glands is dependent on semaphorin signaling <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Chung1" target="_blank">[126]</a>, as is the branching of various other epithelial organs <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Korostylev1" target="_blank">[127]</a>. Plants (3): The uppermost canopy of trees of the rainforest (top layer) undergo a marked increase in branching associated with climate change <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Niinemets1" target="_blank">[128]</a>. Nothing is known about the genetic basis of this feature. The branching of plant trichomes (bottom layer), tiny outgrowths with a variety of functions including seed dispersal, has been studied in the model <i>Arabidopsis thaliana.</i> Branching occurs in association with many MYB-domain genes <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Serna1" target="_blank">[129]</a>, transcription factors that are found in both plants and animals <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Rosinski1" target="_blank">[130]</a>. (<b>C</b>) <b>Environment</b>: Diverse input from the environment influences organismal phenotype. (<b>D</b>) <b>Genes</b>: At the genetic level, previously unknown associations with various types of “branchiness” between insects and vertebrates are here made to possibly a common core or network of genes (the semaphorin-plexin signaling network). No association between genes associated with plant branching (Myb transcription factors) and animal branching is obvious from the literature. Image credit: Anya Broverman-Wray.</p

Finding phenotypes.

<p>The rich legacy of research in the life sciences includes a wealth of phenotype data contained in many sources, for millions of extinct and extant species. Some important sources of phenotypes date from more than 250 years ago <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-AristotleBalme1" target="_blank">[74]</a>–<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Darwin1" target="_blank">[77]</a>. With very few exceptions, phenotype data are not computationally accessible <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Ramrez2" target="_blank">[78]</a>.</p><p>Finding phenotypes.</p

How to discover branching phenotypes?

<p>(Bottom panel) Phenotype data exhibiting various forms of branchiness are not easily discerned from diverse natural language descriptions. (A) Bee hairs are different from most other insect hairs in that they are plumose, which facilitates pollen collection. (B) A mutant of <i>Drosophila melanogaster</i> exhibits forked bristles, due to a variation in <i>mical</i>. (C) In zebrafish larvae (<i>Danio rerio</i>), angiogenesis begins with vessels branching. (D) Plant trichomes take on many forms, including trifurcation. (Top) Phenotypes involving some type of “branched” are easily recovered when they are represented with ontologies. In a semantic graph, free text descriptions are converted into phenotype statements involving an anatomy term from animal or plant ontologies <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Haendel1" target="_blank">[56]</a>,<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Cooper1" target="_blank">[118]</a> and a quality term from a quality ontology <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Gkoutos1" target="_blank">[106]</a>, connected by a logical expression (“inheres_in some”). Anatomy (purple) and quality (green) terms (ontology IDs beneath) relate phenotype statements from different species by virtue of the logic inherent in the ontologies, e.g., plumose, bifurcated, branched, and tripartite are all subtypes of “branched.” Image credits: bumble bee with pollen by Thomas Bresson, seta with pollen by István Mikó, <i>Arabidopsis</i> plants with hair-like structures (trichomes) by Annkatrin Rose, <i>Drosophila</i> photo by John Tann, <i>Drosophila</i> bristles redrawn from <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Hung1" target="_blank">[119]</a>, scanning electron micrograph of <i>Arabidopsis</i> trichome by István Mikó, zebrafish embryos by MichianaSTEM, zebrafish blood vessels from <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002033#pbio.1002033-Alvarez1" target="_blank">[120]</a>. Figure assembled by Anya Broverman-Wray.</p