Seasonal and spatial patterns of eukaryotic phytoplankton communities in an urban river based on marker gene

The seasonal and spatial eukaryotic phytoplankton composition in the Fenhe River was investigated based on the 18S rDNA V4 region. The relationship between phytoplankton functional groups and environmental factors was explored to effectively capture the responses of these taxa to environmental gradients and their effects on ecosystem function. Our results indicated that the Chlorophyta and Bacillariophyta had higher relative abundance than other taxa, and their diversity and richness indices in spring were higher than those in other seasons. The linear discriminant analysis effect size (LEfSe) analyses detected that the potential seasonal biomarkers included Desmodesmus, Cyclotella, Pseudoschroederia, Discostella, Scenedesmus, Monoraphidium, and Nannochloropsis; the spatial biomarkers included Amphora, Neochloris, Hindakia, Pseudomuriella, Coccomyxa, Chloroidium, Scherffelia, Chromochloris, and Scotinosphaera. The systemic evolution and distribution characteristics of the first 50 representative sequences showed that the dominant genus included Desmodesmus in spring, Pseudopediastrum in summer, Mychonastes in autumn, and Monoraphidium in winter. Main seasonal variation of phytoplankton functional groups was as follows: spring (J + F + C + X1) → summer (J + F + X1 + X2) → autumn (J + F + X1 + C) → winter (X1 + J + B + X2). Pearson correlation, redundancy analysis, and variance partitioning analysis showed temperature and phosphate were the determining factors causing the changes of phytoplankton functional groups and community composition in the Fenhe River.

Microplastics interact with benthic biostabilization processes

Marine microplastics accumulate in sediments but impacts on ecosystem functions are poorly understood. Microplastics interactions with stabilizing benthic flora/fauna or biostabilization processes, have not been fully investigated, yet this is critical for unravelling microplastics effects on ecosystem-scale processes and functions. This is also vital for understanding feedback processes that may moderate the stock and flow of microplastics as they are transported through estuaries. The relationships between sedimentary microplastics, biota, environmental properties and sediment stability from field sediments, were examined using variance partitioning (VP) and correlation analyses. VP was used to identify common and unique contributions of different groups of variables (environmental, fauna and microplastic variables) to sediment stability. The influence of microplastic presence (fragment/fiber abundances and microplastic diversity) on sediment stability (defined using erosion thresholds and erosion rates) was demonstrated. Furthermore, microplastics appeared to mediate the biostabilizing effects of environmental properties (including microorganisms) and fauna. Environmental properties and sediment stability could also explain the variation in microplastics across sites suggesting biostabilizing properties may mediate the abundance, type and diversity of microplastics that accumulate in the bed. The potential for microplastics to influence biota and biostabilization processes and mediate microplastic resuspension dynamics within estuaries is discussed.

Molecular Characterization and Population Genetic Structure of Fagopyrum Species Cultivated in Himalayan Regions

Fagopyrum spp. (buckwheat) is a dicotyledonous pseudocereal crop mainly cultivated in the north-western Himalayan regions for its highly nutritional, antioxidant and therapeutic values. In the present investigation, molecular characterization was performed by using ISSR (inter simple sequence repeat) markers on 42 accessions of four buckwheat species (Fagopyrum esculentum, F. sagittatum, F. tataricum and F. kashmirianum). The 12 pre-screened ISSR primers amplified 102 bands, and amongst them 85 bands exhibited polymorphism with an average polymorphism of 82.73%. The results revealed that Shannon’s information indices (I) and Nei’s genetic diversity (H) were low for F. tataricum (I = 0.1028 ± 0.2307; H = 0.0707 ± 0.1617) and high for F. esculentum (I = 0.1715 ± 0.2622; H = 0.1164 ± 0.1796). It was estimated that within the accessions of Fagopyrum species, the species diversity (HT) and mean diversity (HS) were 0.3200 and 0.1041, respectively. Molecular variance partitioning by AMOVA also indicated a significant genetic differentiation accounting for 73% among and 27% within the accessions of Fagopyrum species. Overall, accessions of F. esculentum had the greatest distance from the other accessions of buckwheat species, which includes F. sagittatum, F. tataricum and F. kashmirianum as revealed by FST distance and Nei’s unbiased genetic distance. The dendograms based on UPGMA and PCoA segregated 42 accessions of four buckwheat species into three major groups. This study clearly reveals a considerable amount of genetic diversity at the intra-specific level in F. esculentum, F. sagittatum and F. kashmirianum accessions. The factors responsible for it are diverse geographical conditions, pollinating behavior and cultivation practices adapted in these regions. The study also indicated a close phylogenetic relationship between F. tataricum and F. kashmirianum.

Social-affective features drive human representations of observed actions

Humans observe actions performed by others in many different visual and social settings. What features do we extract and attend when we view such complex scenes, and how are they processed in the brain? To answer these questions, we curated two large-scale sets of naturalistic videos of everyday actions and estimated their perceived similarity in two behavioral experiments. We normed and quantified a large range of visual, action-related and social-affective features across the stimulus sets. Using a cross-validated variance partitioning analysis, we found that social-affective features predicted similarity judgments better than, and independently of, visual and action features in both behavioral experiments. Next, we conducted an electroencephalography (EEG) experiment, which revealed a sustained correlation between neural responses to videos and their behavioral similarity. Visual, action, and social-affective features predicted neural patterns at early, intermediate and late stages respectively during this behaviorally relevant time window. Together, these findings show that social-affective features are important for perceiving naturalistic actions, and are extracted at the final stage of a temporal gradient in the brain.

Doors and corners of variance partitioning in statistical ecology

Variance partitioning is a common tool for statistical analysis and interpretation in both observational and experimental studies in ecology. Its popularity has led to a proliferation of methods with sometimes confusing or contradicting interpretations. Here, we present variance partitioning as a general tool in a model based Bayesian framework for summarizing and interpreting regression-like models. To demonstrate our approach we present a case study comprising of a simple occupancy model for a metapopulation of the Glanville fritillary butterfly. We pay special attention to the thorny issue of correlated covariates and random effects, and highlight uncertainty in variance partitioning. We recommend several alternative measures of variance, which jointly can be used to better interpret variance partitions. Additionally, we extend the general approach to encompass partitioning of variance within and between groups of observations, an approach very similar to analysis of variance. While noting that many troublesome issues relating to variance partitioning, such as uncertainty quantification, have been neglected in the literature, we likewise feel that the rather general applicability of the methods as an extension of statistical model-based analyses has not been fully utilized by the ecological research community either.

Coexistence of “Cream Skimmer” and “Crumb Picker” Phenotypes in Nature and in Cancer

Over 40 years ago, seminal papers by Armstrong and McGehee and by Levins showed that temporal fluctuations in resource availability could permit coexistence of two species on a single resource. Such coexistence results from non-linearities or non-additivities in the way resource supply translates into fitness. These reflect trade-offs where one species benefits more than the other during good periods and suffers more (or does less well) than the other during less good periods, be the periods stochastic, unstable population dynamics, or seasonal. Since, coexistence based on fluctuating conditions has been explored under the guises of “grazers” and “diggers,” variance partitioning, relative non-linearity, “opportunists” and “gleaners,” and as the storage effect. Here we focus on two phenotypes, “cream skimmers” and “crumb pickers,” the former having the advantage in richer times and the latter in less rich times. In nature, richer and poorer times, with regular or stochastic appearances, are the norm and occur on many time scales. Fluctuations among richer and poorer times also appear to be the norm in cancer ecosystems. Within tumors, nutrient availability, oxygen, and pH can fluctuate stochastically or periodically, with swings occurring over seconds to minutes to hours. Despite interest in tumor heterogeneity and how it promotes the coexistence of different cancer cell types, the effects of fluctuating resource availability have not been explored for cancer. Here, in the context of pulsed resources, we (1) develop models of foraging consumers who experience pulsed resources to examine four types of trade-offs that can promote coexistence of phenotypes that do relatively better in richer versus in poorer times, (2) establish that conditions in tumors are conducive for this mechanism, (3) propose and empirically explore biomarkers indicative of the two phenotypes (HIF-1, GLUT-1, CA IX, CA XII), and (4) and compare cream skimmer and crumb picker biology and ecology in nature and cancer to provide cross-disciplinary insights into this interesting, and, we argue, likely very common, mechanism of coexistence.

Using trait data improves correlation between environment and community data only if abundances are considered

A straightforward way to explore variation between communities is to calculate dissimilarity indices and relate them with environmental and spatial variables. Communities are most often represented by the (relative) abundances of taxa they comprise; however, more recently, the distribution of traits of organisms included in the communities has been shown more strongly related to ecosystem properties. In this study, we test whether taxon- or trait-based dissimilarity is correlated more tightly with environmental difference and geographical distance and how the abundance scale influences this correlation. Our study system is grassland vegetation in Hungary, where we sampled vegetation plots spanning a long productivity gradient from open dry grasslands to marshes in three sites. We considered three traits for vascular plants: canopy height, specific leaf area and seed mass. We obtained field estimates of normalized vegetation difference index (NDVI) as proxy of productivity (water availability) for each plot. We calculated between-community dissimilarities using a taxon-based and a trait-based index, using raw and square-root transformed abundances and presence/absence data. We fitted distance-based redundancy analysis models with NDVI difference and geographical distance on the dissimilarity matrices and evaluated them using variance partitioning. Then, using the pooled data, we calculated non-metric multidimensional scaling ordinations (NMDS) from all types of dissimilarity matrices and made pairwise comparisons using Procrustes analysis. Data analysis was done separately for the three sites.We found that taxonomical dissimilarity matches environmental and spatial variables better when presence/absence data is used instead of abundance. This pattern was mainly determined by the increasing variation explained by space at the presence/absence scale. In contrast to this trend, with trait-based dissimilarity, accounting for abundance increased explained variation significantly due to the higher explanatory power of NDVI. With abundance data, considering traits improved environmental matching to a great extent in comparison with taxonomical information. However, with presence/absence data, traits brought no advantage over taxon-based dissimilarity in any respect. Changing the abundance scale caused larger difference between ordinations in the case of trait-based dissimilarity than with taxonomical dissimilarity.We conclude that considering relevant traits improves environmental matching only if abundances are also accounted for.Supporting informationAdditional graphs supporting the results are presented as appendix.Open researchData used in this research are publicly available from Dryad ###link to be supplied upon acceptance###

Do Morphological Traits Predict Ecological Guilds of the Mekong Fish Fauna?

Southeast Asian riverine fishes are classified into three guilds (‘black’, ‘white’ and ‘grey’ species) based on their reproductive and migration strategies. In this study, we aimed to investigate whether fish morphology could be used to predict the Mekong fish guilds. Nine dimensionless ratios of fish morphological traits were used to describe the locomotion and food acquisition strategies of 121 fish species. The links between morphological traits and fish guilds were assessed using a principal component analysis (PCA) and a variance partitioning analysis, which revealed a strong morphological overlap between the guilds. Despite the high contribution of intra-guild variability to overall morphological variability (~90%), black and white fish significantly differed in terms of locomotion-related traits. Mekong fish guilds were satisfactorily predicted by using a random forest (RF) model, which produced a percentage of successful classification of ca 50% for each of the three guilds. Caudal propulsion efficiency, pectoral fin vertical position and body elongation were the most significant traits in the RF predictive model. Although the present study provides initial insight into the links between Mekong fish morphology and ecological guilds, further research is needed in order to clarify the relationship between species morphology, migratory status and responses to environmental variation.

Ranking the explanatory power of factors associated with worldwide new Covid-19 cases

Disease spread is a complex phenomenon requiring an interdisciplinary approach. Covid-19 exhibited a global spatial spread in a very short time frame resulting in a global pandemic. Data of new Covid-19 cases per million were analysed worldwide at the spatial scale of a country and time replicated from the end of December 2019 to late May 2020. Data driven analysis of epidemiological, economic, public health, and governmental intervention variables was performed in order to select the optimal variables in explaining new Covid-19 cases across all countries in time. Sequentially, hierarchical variance partitioning of the optimal variables was performed in order to quantify the independent contribution of each variable in the total variance of new Covid-19 cases per million. Results indicated that from the variables available new tests per thousand explained the vast majority of the total variance in new cases (51.6%) followed by the governmental stringency index (15.2%). Availability of hospital beds per 100k inhabitants explained 9% extreme poverty explained 8.8%, hand washing facilities 5.3%, the fraction of the population aged 65 or older explained 3.9%, and other disease prevalence (cardiovascular diseases plus diabetes) explained 2.9%. The percentage of smokers within the population explained 2.6% of the total variance, while population density explained 0.6%.

Great tits who remember more accurately have difficulty forgetting, but variation is not driven by environmental harshness

The causes of individual variation in memory are poorly understood in wild animals. Harsh environments with sparse or rapidly changing food resources are hypothesized to favour more accurate spatial memory to allow animals to return to previously visited patches when current patches are depleted. A potential cost of more accurate spatial memory is proactive interference, where accurate memories block the formation of new memories. This relationship between spatial memory, proactive interference, and harsh environments has only been studied in scatter-hoarding animals. We compare spatial memory accuracy and proactive interference performance of non-scatter hoarding great tits (Parus major) from high and low elevations where harshness increases with elevation. In contrast to studies of scatter-hoarders, we did not find a significant difference between high and low elevation birds in their spatial memory accuracy or proactive interference performance. Using a variance partitioning approach, we report the first among-individual trade-off between spatial memory and proactive interference, uncovering variation in memory at the individual level where selection may act. Although we have no evidence of harsh habitats affecting spatial memory, our results suggest that if elevation produced differences in spatial memory between elevations, we could see concurrent changes in how quickly birds can forget.