Taxonomic versus allometric constraints on non‐linear interaction strengths

Recently, the importance of body mass and allometric scaling for the structure and dynamics of ecological networks has been highlighted in several ground‐breaking studies. However, advances in the understanding of generalities across ecosystem types are impeded to a considerable extent by a methodological dichotomy contrasting a considerable portion of marine ecology on the one hand opposite to traditional community ecology on the other hand. Many marine ecologists are bound to the taxonomy‐neglecting size spectrum approach when describing and analysing community patterns. In contrast, the mindset of the other school is focused on taxonomies according to the Linnean system at the cost of obscuring information due to applying species or population averages of body masses and other traits. Following other pioneering studies, we addressed this lingering gap, and studied non‐linear interaction strengths (i.e. functional responses) between two taxonomically‐distinct terrestrial arthropod predators (centipedes and spiders) of varying individual body masses and their prey. We fitted three non‐linear functional response models to the data: (1) a taxonomic model not accounting for variance in body masses amongst predator individuals, (2) an allometric model ignoring taxonomic differences between predator individuals, and (3) a combined model including body mass and taxonomic effects. Ranked according to their AICs, the combined model performs better than the allometric model, which provides a superior fit to the data than the taxonomic model. These results strongly indicate that the body masses of predator and prey individuals were responsible for most of the variation in non‐linear interaction strengths. Taxonomy explained some specific patterns in allometric exponents between groups and revealed mechanistic insights in predation efficiencies. Reconciling quantitative allometric models as employed by the marine size‐spectrum approach with taxonomic information may thus yield quantitative results that are generalized across ecosystem types and taxonomic groups. Using these quantitative models as novel null models should also strengthen subsequent taxonomic analyses.     

Classification trees: An alternative non‐parametric approach for predicting species distributions

Abstract. The use of Generalized Linear Models (GLM) in vegetation analysis has been advocated to accommodate complex species response curves. This paper investigates the potential advantages of using classification and regression trees (CART), a recursive partitioning method that is free of distributional assumptions. We used multiple logistic regression (a form of GLM) and CART to predict the distribution of three major oak species in California. We compared two types of model: polynomial logistic regression models optimized to account for non‐linearity and factor interactions, and simple CART‐models. Each type of model was developed using learning data sets of 2085 and 410 sample cases, and assessed on test sets containing 2016 and 3691 cases respectively. The responses of the three species to environmental gradients were varied and often non‐homogeneous or context dependent. We tested the methods for predictive accuracy: CART‐models performed significantly better than our polynomial logistic regression models in four of the six cases considered, and as well in the two remaining cases. CART also showed a superior ability to detect factor interactions. Insight gained from CART‐models then helped develop improved parametric models. Although the probabilistic form of logistic regression results is more adapted to test theories about species responses to environmental gradients, we found that CART‐models are intuitive, easy to develop and interpret, and constitute a valuable tool for modeling species distributions.     

Roles of non‐native hydrogen‐bonding interaction in helix‐coil transition of a single polypeptide as revealed by comparison between Gō‐like and non‐Gō models

To explore the role of non‐native interactions in the helix‐coil transition, a detailed comparison between a Gō‐like model and a non‐Gō model has been performed via lattice Monte Carlo simulations. Only native hydrogen bonding interactions occur in the Gō‐like model, and the non‐native ones with sequence interval more than 4 is also included into the non‐Gō model. Some significant differences between the results from those two models have been found. The non‐native hydrogen bonds were found most populated at temperature around the helix‐coil transition. The rearrangement of non‐native hydrogen bonds into native ones in the formation of α‐helix leads to the increase of susceptibility of chain conformation, and even two peaks of susceptibility of radius of gyration versus temperature exist in the case of non‐Gō model for a non‐short peptide, while just a single peak exists in the case of Gō model for a single polypeptide chain with various chain lengths. The non‐native hydrogen bonds have complicated the temperature‐dependence of Zimm‐Bragg nucleation constant. The increase of relative probability of non‐native hydrogen bonding for long polypeptide chains leads to non‐monotonous chain length effect on the transition temperature. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Landscape‐scale determinants of non‐native fish communities

Aim Predicting and preventing invasions depends on knowledge of the factors that make ecosystems susceptible to invasion. Current studies generally rely on non‐native species richness (NNSR) as the sole measure of ecosystem invasibility; however, species identity is a critical consideration, given that different ecosystems may have environmental characteristics suitable to different species. Our aim was to examine whether non‐native freshwater fish community composition was related to ecosystem characteristics at the landscape scale. Location United States. Methods We described spatial patterns in non‐native freshwater fish communities among watersheds in the Mid‐Atlantic region of the United States based on records of establishment in the U.S. Geological Survey’s Nonindigenous Aquatic Species Database. We described general relationships between non‐native species and ecosystem characteristics using canonical correspondence analysis. We clustered watersheds by non‐native fish community and described differences among clusters using indicator species analysis. We then assessed whether non‐native communities could be predicted from ecosystem characteristics using random forest analysis and predicted non‐native communities for uninvaded watersheds. We estimated which ecosystem characteristics were most important for predicting non‐native communities using conditional inference trees. Results We identified four non‐native fish communities, each with distinct indicator species. Non‐native communities were predicted based on ecosystem characteristics with an accuracy of 80.6%, with temperature as the most important variable. Relatively uninvaded watersheds were predicted to be invasible by the most diverse non‐native community. Main conclusions Non‐native species identity is an important consideration when assessing ecosystem invasibility. NNSR alone is an insufficient measure of invasibility because ecosystems with equal NNSR may not be equally invasible by the same species. Our findings can help improve predictions of future invasions and focus management and policy decisions on particular species in highly invasible ecosystems.     

Non‐breeding range size predicts the magnitude of population trends in trans‐Saharan migratory passerine birds

Understanding why populations of some migratory species show a directional change over time, i.e. increase or decrease, while others do not, remains a challenge for ecological research. One possible explanation is that species with smaller non‐breeding ranges may have more pronounced directional population trends, and their populations are thus more sensitive to the variation in environmental conditions in their non‐breeding quarters. According to the serial residency hypothesis, this sensitivity should lead to higher magnitudes (i.e. absolute values) of population trends for species with smaller non‐breeding ranges, with the direction of trend being either positive or negative depending on the nature of the environmental change. We tested this hypothesis using population trends over 2001–2012 for 36 sub‐Saharan migratory passerine birds breeding in Europe. Namely, we related the magnitude of the species' population trends to the size of their sub‐Saharan non‐breeding grounds, whilst controlling for factors including number of migration routes, non‐breeding habitat niche and wetness, breeding habitat type and life‐history strategy. The magnitude of species' population trends grew with decreasing absolute size of sub‐Saharan non‐breeding ranges, and this result remained significant when non‐breeding range size was expressed relative to the size of the breeding range. After repeating the analysis with the trend direction, the relationship with the non‐breeding range size disappeared, indicating that both population decreases and increases are frequent amongst species with small non‐breeding range sizes. Therefore, species with small non‐breeding ranges are at a higher risk of population decline due to adverse factors such as habitat loss or climatic extremes, but their populations are also more likely to increase when suitable conditions appear. As non‐breeding ranges may originate from stochasticity of non‐breeding site selection in naive birds (‘serial‐residency’ hypothesis), it is crucial to maintain a network of stable and resilient habitats over large areas of birds’ non‐breeding quarters.     

The incoherent feed‐forward loop can generate non‐monotonic input functions for genes

Gene regulation networks contain recurring circuit patterns called network motifs. One of the most common network motif is the incoherent type 1 feed‐forward loop (I1‐FFL), in which an activator controls both gene and repressor of that gene. This motif was shown to act as a pulse generator and response accelerator of gene expression. Here we consider an additional function of this motif: the I1‐FFL can generate a non‐monotonic dependence of gene expression on the input signal. Here, we study this experimentally in the galactose system of Escherichia coli, which is regulated by an I1‐FFL. The promoter activity of two of the gal operons, galETK and galP, peaks at intermediate levels of the signal cAMP. We find that mutants in which the I1‐FFL is disrupted lose this non‐monotonic behavior, and instead display monotonic input functions. Theoretical analysis suggests that non‐monotonic input functions can be achieved for a wide range of parameters by the I1‐FFL. The models also suggest regimes where a monotonic input‐function can occur, as observed in the mglBAC operon regulated by the same I1‐FFL. The present study thus experimentally demonstrates how upstream circuitry can affect gene input functions and how an I1‐FFL functions within its natural context in the cell.     

Complexity is costly: a meta‐analysis of parametric and non‐parametric methods for short‐term population forecasting

Short‐term forecasts based on time series of counts or survey data are widely used in population biology to provide advice concerning the management, harvest and conservation of natural populations. A common approach to produce these forecasts uses time‐series models, of different types, fit to time series of counts. Similar time‐series models are used in many other disciplines, however relative to the data available in these other disciplines, population data are often unusually short and noisy and models that perform well for data from other disciplines may not be appropriate for population data. In order to study the performance of time‐series forecasting models for natural animal population data, we assembled 2379 time series of vertebrate population indices from actual surveys. Our data were comprised of three vastly different types: highly variable (marine fish productivity), strongly cyclic (adult salmon counts), and small variance but long‐memory (bird and mammal counts). We tested the predictive performance of 49 different forecasting models grouped into three broad classes: autoregressive time‐series models, non‐linear regression‐type models and non‐parametric time‐series models. Low‐dimensional parametric autoregressive models gave the most accurate forecasts across a wide range of taxa; the most accurate model was one that simply treated the most recent observation as the forecast. More complex parametric and non‐parametric models performed worse, except when applied to highly cyclic species. Across taxa, certain life history characteristics were correlated with lower forecast error; specifically, we found that better forecasts were correlated with attributes of slow growing species: large maximum age and size for fishes and high trophic level for birds. Synthesis Evaluating the data support for multiple plausible models has been an integral focus of many ecological analyses. However, the most commonly used tools to quantify support have weighted models’ hindcasting and forecasting abilities. For many applications, predicting the past may be of little interest. Concentrating only on the future predictive performance of time series models, we performed a forecasting competition among many different kinds of statistical models, applying each to many different kinds of vertebrate time series of population abundance. Low‐dimensional (simple) models performed well overall, but more complex models did slightly better when applied to time series of cyclic species (e.g. salmon).     

Long non‐coding RNAs in non‐small cell lung cancer as biomarkers and therapeutic targets

Lung cancer‐associated mortality is the most common cause of cancer death worldwide. Non‐coding RNAs (ncRNAs), with no protein‐coding ability, have multiple biological roles. Long non‐coding RNAs (lncRNAs) are a recently characterized class of ncRNAs that are over 200 nucleotides in length. Many lncRNAs have the ability of facilitating or inhibiting the development and progression of tumours, including non‐small cell lung cancer (NSCLC). Because of their fundamental roles in regulating gene expression, along with their involvement in the biological mechanisms underlying tumourigenesis, they are a promising class of tissue‐ and/or blood‐based cancer biomarkers. In this review, we highlight the emerging roles of lncRNAs in NSCLC, and discuss their potential clinical applications as diagnostic and prognostic markers and as therapeutic targets.     

Shift down,look up: A test of the non‐linearity and fear hypothesis in a non‐vocal skink

The non‐linearity and fear hypothesis predicts that certain non‐linear sounds are one way to evoke antipredator responses in both birds and mammals. This hypothesis, however, has not been studied in non‐vocal species or in reptiles. Such a study would be important because if non‐linear sounds are evocative even in a species that does not produce sounds, then there may be generally salient cues of risk in these sounds. We asked whether non‐vocal lizards, white‐bellied copper‐striped skinks (Emoia cyanura), respond to experimentally broadcast non‐linearities. This species is ideal to ask the question in because prior research has shown that they respond to predator sounds and alarm calls of other species even though they are not vocal. We conducted playback experiments with three computer‐generated simulated non‐linearities to assess whether or not skinks increased antipredator behavior after hearing them. We controlled for novelty by broadcasting a 3‐kHz, 500‐ms pure tone and tropical kingbird (Tyrannus melancholicus) song. Our treatments consisted of a 3‐kHz, 400‐ms pure tone followed by a frequency shift up to 5‐kHz for 100‐ms, a 3‐kHz, 400‐ms pure tone to frequency shift down to 1‐kHz for 100‐ms, and a pure tone followed by 100‐ms of white noise. Following a total of 222 playbacks, we categorized responses into looking, locomotion, and high locomotion, focusing on how skinks changed their rates of time allocation from baseline. We examined 95% confidence intervals to identify whether skinks responded to playbacks and fitted general linear models followed by pairwise comparisons to ask whether skinks discriminated between broadcast stimuli. We found that skinks were especially responsive to frequency downshifts: They significantly increased looking and locomotion, consistent with our predictions based on the non‐linearity and fear hypothesis. Surprisingly, they decreased rates of looking behavior after hearing frequency upshifts, possibly suggesting an increase in relaxed behavior. While skinks responded to noise by increasing their rate of locomotion, this response was not significantly different from controls. We conclude that skinks increase antipredator behavior after hearing downshifts more than any other type of non‐linearity. This provides some support for the non‐linearity and fear hypothesis; even non‐vocal species may respond fearfully to specific types of non‐linear sounds.     

Mountain roads shift native and non‐native plant species' ranges

Roads are known to act as corridors for dispersal of plant species. With their variable microclimate, role as corridors for species movement and reoccurring disturbance events, they show several characteristics that might influence range dynamics of both native and non‐native species. Previous research on plant species ranges in mountains however seldom included the effects of roads. To study how ranges of native and non‐native species differ between roads and adjacent vegetation, we used a global dataset of plant species composition along mountain roads. We compared average elevation and range width of species, and used generalized linear mixed models (GLMMs) to compile their range optimum and amplitude. We then explored differences between roadside and adjacent plots based on a species’ origin (native vs non‐native) and nitrogen and temperature affinity. Most non‐native species had on average higher elevational ranges and broader amplitudes in roadsides. Higher optima for non‐native species were associated with high nitrogen and temperature affinity. While lowland native species showed patterns comparable to those in non‐native species, highland native species had significantly lower elevational ranges in roadsides compared to the adjacent vegetation. We conclude that roadsides indeed change the elevational ranges of a variety of species. These changes are not limited to the expansion of non‐native species along mountain roads, but also include both upward and downward changes in ranges of native species. Roadsides may thus facilitate upward range shifts, for instance related to climate change, and they could serve as corridors to facilitate migration of alpine species between adjacent high‐elevation areas. We recommend including the effects of mountain roads in species distribution models to fine‐tune the predictions of range changes in a warming climate.     

The purple non‐sulfur bacterium Rhodopseudomonas palustris produces novel petrobactin‐related siderophores under aerobic and anaerobic conditions

Many bacteria produce siderophores to bind and take up Fe(III), an essential trace metal with extremely low solubility in oxygenated environments at circumneutral pH. The purple non‐sulfur bacterium Rhodopseudomonas palustris str. CGA009 is a metabolically versatile model organism with high iron requirements that is able to grow under aerobic and anaerobic conditions. Siderophore biosynthesis has been predicted by genomic analysis, however, siderophore structures were not identified. Here, we elucidate the structure of two novel siderophores from R. palustris: rhodopetrobactin A and B. Rhodopetrobactins are structural analogues of the known siderophore petrobactin in which the Fe chelating moieties are conserved, including two 3,4‐dihydroxybenzoate and a citrate substructure. In the place of two spermidine linker groups in petrobactin, rhodopetrobactins contain two 4,4′‐diaminodibutylamine groups of which one or both are acetylated at the central amine. We analyse siderophore production under different growth modes and show that rhodopetrobactins are produced in response to Fe limitation under aerobic as well as under anaerobic conditions. Evaluation of the chemical characteristics of rhodopetrobactins indicates that they are well suited to support Fe acquisition under variable oxygen and light conditions.     

Niche conservatism among non‐native vertebrates in Europe and North America

Niche conservatism, the hypothesis that niches remain constant through time and space, is crucial for the study of biological invasions as it underlies native‐range based predictions of invasion risk. Niche changes between native and non‐native populations are increasingly reported. However, it has been argued that these changes arise mainly because in their novel range, species occupy only a subset of the environments they inhabit in their native range, and not because they expand into environments entirely novel to them. Here, using occurrences of 29 vertebrate species native to either Europe or North America and introduced into the other continent, we assess the prevalence of niche changes between native and non‐native populations and assess whether the changes detected are caused primarily by native niche unfilling in the non‐native range rather than by expansion into novel environments. We show that niche overlap between native and non‐native populations is generally low because of a large degree of niche unfilling in the non‐native range. This most probably reflects an ongoing colonization of the novel range, as niche changes were smaller for species that were introduced longer ago and into a larger number of locations. Niche expansion was rare, and for the few species exhibiting larger amounts of niche overlap, an unfilling of the niche in the native range (e.g. through competition or dispersal limitations) is the most probable explanation. The fact that for most species, the realized non‐native niche is a subset of the realized native niche allows native‐range based niche models to generate accurate predictions of invasion risk. These results suggest that niche changes arising during biological invasions are strongly influenced by propagule pressure and colonization processes, and we argue that introduction history should be taken into account when evaluating niche conservatism in the context of biological invasions.     

Population genomic analyses from low‐coverage RAD‐Seq data: a case study on the non‐model cucurbit bottle gourd

Restriction site‐associated DNA sequencing (RAD‐Seq), a next‐generation sequencing‐based genome ‘complexity reduction’ protocol, has been useful in population genomics in species with a reference genome. However, the application of this protocol to natural populations of genomically underinvestigated species, particularly under low‐to‐medium sequencing depth, has not been well justified. In this study, a Bayesian method was developed for calling genotypes from an F₂ population of bottle gourd [Lagenaria siceraria (Mol.) Standl.] to construct a high‐density genetic map. Low‐depth genome shotgun sequencing allowed the assembly of scaffolds/contigs comprising approximately 50% of the estimated genome, of which 922 were anchored for identifying syntenic regions between species. RAD‐Seq genotyping of a natural population comprising 80 accessions identified 3226 single nuclear polymorphisms (SNPs), based on which two sub‐gene pools were suggested for association with fruit shape. The two sub‐gene pools were moderately differentiated, as reflected by the Hudson's F_ST value of 0.14, and they represent regions on LG7 with strikingly elevated F_ST values. Seven‐fold reduction in heterozygosity and two times increase in LD (r²) were observed in the same region for the round‐fruited sub‐gene pool. Outlier test suggested the locus LX3405 on LG7 to be a candidate site under selection. Comparative genomic analysis revealed that the cucumber genome region syntenic to the high F_ST island on LG7 harbors an ortholog of the tomato fruit shape gene OVATE. Our results point to a bright future of applying RAD‐Seq to population genomic studies for non‐model species even under low‐to‐medium sequencing efforts. The genomic resources provide valuable information for cucurbit genome research.     

Incorporating Inter‐item Correlations in Item Response Data Analysis

This paper concerns with the analysis of item response data, which are usually measured on a rating scale and are therefore ordinal. These study items tended to be highly inter‐correlated. Rasch models, which convert ordinal categorical scales into linear measurements, are widely used in ordinal data analysis. In this paper, we improve the current methodology in order to incorporate inter‐item correlations. We have advocated the latent variable approach for this purpose, in combination with generalized estimating equations to estimate the Rasch model parameters. The data on a study of families of lung cancer patients demonstrate the utility of our methods.     

Equilibrium and non‐equilibrium phases in the radiation of Hakea and the drivers of diversity in Mediterranean‐type ecosystems

Mediterranean‐type ecosystems (MTEs) contain exceptional plant diversity. Explanations for this diversity are usually classed as either “equilibrium,” with elevated MTE diversity resulting from greater ecological carrying capacities, or “non‐equilibrium,” with MTEs having a greater accumulation of diversity over time than other types of ecosystems. These models have typically been considered as mutually exclusive. Here, we present a trait‐based explanatory framework that incorporates both equilibrium and non‐equilibrium dynamics. Using a large continental Australian plant radiation (Hakea) as a case study, we identify traits associated with niche partitioning in coexisting species (α‐traits) and with environmental filtering (β‐traits), and reconstruct the mode and relative timing of diversification of these traits. Our results point to a radiation with an early non‐equilibrium phase marked by divergence of β‐traits as Hakea diversified exponentially and expanded from the southwest Australian MTE into biomes across the Australian continent. This was followed from seven million years ago by an equilibrium phase, marked by diversification of α‐traits and a slowdown in lineage diversification as MTE‐niches became saturated. These results suggest that processes consistent with both equilibrium and non‐equilibrium models have been important during different stages of the radiation of Hakea, and together they provide a richer explanation of present‐day diversity patterns.