An evaluation of semi‐automated methods for collecting ecosystem‐level data in temperate marine systems

Historically, marine ecologists have lacked efficient tools that are capable of capturing detailed species distribution data over large areas. Emerging technologies such as high‐resolution imaging and associated machine‐learning image‐scoring software are providing new tools to map species over large areas in the ocean. Here, we combine a novel diver propulsion vehicle (DPV) imaging system with free‐to‐use machine‐learning software to semi‐automatically generate dense and widespread abundance records of a habitat‐forming algae over ~5,000 m² of temperate reef. We employ replicable spatial techniques to test the effectiveness of traditional diver‐based sampling, and better understand the distribution and spatial arrangement of one key algal species. We found that the effectiveness of a traditional survey depended on the level of spatial structuring, and generally 10–20 transects (50 × 1 m) were required to obtain reliable results. This represents 2–20 times greater replication than have been collected in previous studies. Furthermore, we demonstrate the usefulness of fine‐resolution distribution modeling for understanding patterns in canopy algae cover at multiple spatial scales, and discuss applications to other marine habitats. Our analyses demonstrate that semi‐automated methods of data gathering and processing provide more accurate results than traditional methods for describing habitat structure at seascape scales, and therefore represent vastly improved techniques for understanding and managing marine seascapes.     

Analysis of conformational motions and related key residue interactions responsible for a specific function of proteins with elastic network model

Protein collective motions play a critical role in many biochemical processes. How to predict the functional motions and the related key residue interactions in proteins is important for our understanding in the mechanism of the biochemical processes. Normal mode analysis (NMA) of the elastic network model (ENM) is one of the effective approaches to investigate the structure-encoded motions in proteins. However, the motion modes revealed by the conventional NMA approach do not necessarily correspond to a specific function of protein. In the present work, a new analysis method was proposed to identify the motion modes responsible for a specific function of proteins and then predict the key residue interactions involved in the functional motions by using a perturbation approach. In our method, an internal coordinate that accounts for the specific function was introduced, and the Cartesian coordinate space was transformed into the internal/Cartesian space by using linear approximation, where the introduced internal coordinate serves as one of the axes of the coordinate space. NMA of ENM in this internal/Cartesian space was performed and the function-relevant motion modes were identified according to their contributions to the specific function of proteins. Then the key residue interactions important for the functional motions of the protein were predicted as the interactions whose perturbation largely influences the fluctuation along the internal coordinate. Using our proposed methods, the maltose transporter (MalFGK₂) from E. Coli was studied. The functional motions and the key residue interactions that are related to the channel-gating function of this protein were successfully identified.     

Synthesis and biological characterization of new aryloxyindole-4,9-diones as potent trypanosomicidal agents

A new indole-4,9-dione and their phenoxy derivatives were synthesized and evaluated in vitro against the epimastigote form of Trypanosoma cruzi, Y strain. All of these novel compounds were found to be extremely potent and selective that the standard drug nifurtimox. Interestingly, phenoxyindole-4,9-dione 9d displayed excellent nanomolar inhibitory activity, IC₅₀ = 20 nM, and high selectivity index, SI = 625. In silico studies using MOE program were performed to generate a preliminary pharmacophore model.     

9. The algal flora of the Primorsky Region, Russian Far East

A survey of the freshwater algal flora of the Primorsky Region, Russian Far East, is presented. During more than 70 years of investigations 1659 species (including varieties and forms 2276 taxa) belonging to 346 genera of different groups of algae have been recorded from this territory. The Primorsky Region is rich in habitats attractive to algae-rivers, lakes, reservoirs, and ponds. The details of the distribution of algae in different types of waterbodies have been examined. The algal flora of the region is comparable to the areas, and its taxonomical structure is typical for Eurasia. From this territory some new species and varieties have been described — Achnanthes chankensis, Cymbella ventricosa var. hankensis, Surirella alisoviana, and others. The flora includes some rare species — Fragilaria magocsyi, Perone dimorpha, and Heterothrix monochloron, and some endemics of Asia — Navicula scutelloides var. baicalensis, N. globulifera var. nipponica, Gomphonema sphaerophorum, and Surirella tientsinensis.     

Life history patterns of river invertebrates

The initiation of invertebrate distribution patterns in rivers occurs by choice of oviposition sites and is influenced by the evolved reproductive strategies of the individual species. Subsequent redistribution by migration or drifting establishes patterns which are then modified by environmental influences on growth and mortality. Continuity of life cycles is sustained by variations on a number of defined life history strategies combined with evolved behavioural responses.     

Range‐wide patterns of greater sage‐grouse persistence

Aim Greater sage‐grouse (Centrocercus urophasianus), a shrub‐steppe obligate species of western North America, currently occupies only half its historical range. Here we examine how broad‐scale, long‐term trends in landscape condition have affected range contraction. Location Sagebrush biome of the western USA. Methods Logistic regression was used to assess persistence and extirpation of greater sage‐grouse range based on landscape conditions measured by human population (density and population change), vegetation (percentage of sagebrush habitat), roads (density of and distance to roads), agriculture (cropland, farmland and cattle density), climate (number of severe and extreme droughts) and range periphery. Model predictions were used to identify areas where future extirpations can be expected, while also explaining possible causes of past extirpations. Results Greater sage‐grouse persistence and extirpation were significantly related to sagebrush habitat, cultivated cropland, human population density in 1950, prevalence of severe droughts and historical range periphery. Extirpation of sage‐grouse was most likely in areas having at least four persons per square kilometre in 1950, 25% cultivated cropland in 2002 or the presence of three or more severe droughts per decade. In contrast, persistence of sage‐grouse was expected when at least 30 km from historical range edge and in habitats containing at least 25% sagebrush cover within 30 km. Extirpation was most often explained (35%) by the combined effects of peripherality (within 30 km of range edge) and lack of sagebrush cover (less than 25% within 30 km). Based on patterns of prior extirpation and model predictions, we predict that 29% of remaining range may be at risk. Main Conclusions Spatial patterns in greater sage‐grouse range contraction can be explained by widely available landscape variables that describe patterns of remaining sagebrush habitat and loss due to cultivation, climatic trends, human population growth and peripherality of populations. However, future range loss may relate less to historical mechanisms and more to recent changes in land use and habitat condition, including energy developments and invasions by non‐native species such as cheatgrass (Bromus tectorum) and West Nile virus. In conjunction with local measures of population performance, landscape‐scale predictions of future range loss may be useful for prioritizing management and protection. Our results suggest that initial conservation efforts should focus on maintaining large expanses of sagebrush habitat, enhancing quality of existing habitats, and increasing habitat connectivity.     

Feral cat diet and impact on sooty terns at Juan de Nova Island, Mozambique Channel

Feral cat Felis catus predation on seabirds has been well documented; however, details regarding shifts in feral cat diet in relation to seabird availability, seabird predation rate and impact on seabird population dynamics are scarce. Here, we present data documenting a seasonal shift in feral cat diet at Juan de Nova Island, Mozambique Channel. We also quantify sooty tern Sterna fuscata predation by feral cats and examine the impact on sooty terns over both the short term (by removing individual cats from sub-colonies) and over the longer term by highlighting their influence on population growth rate ( λ ) using a deterministic matrix model. Cat diet shifted dramatically from insects, rats and mice outside the tern breeding season to primarily terns when terns were breeding. The predation rate of sooty terns at Juan de Nova was estimated at 5.94 terns cat⁻¹ day⁻¹, with a proportion of these (22%) being killed without being consumed ('surplus kills'). When only one cat was removed from each sub-colony, tern predation declined tenfold in the short term. From our matrix model, the annual growth rate for sooty terns was 1.01 in the absence of cat predation. It remained above one until a predation impact equivalent to approximately three times the estimated cat density (12.04 per km²) was incorporated. Our results demonstrate that cats preferentially predate and have an impact on breeding sooty terns at Juan de Nova, and that an increase in cat density could lead to negative effects on population growth, despite the large breeding tern population.     

The scale of analysis determines the spatial pattern of woody species diversity in the Mediterranean environment

We examine the spatial pattern of woody species diversity at different scales, in two sites of Mt. Holomontas in northern Greece, which falls within the transitional zone between temperate forests and Mediterranean-type ecosystems. We investigate how diversity is distributed in space and whether the perceived pattern changes with the scale of observation. We use two different metrics of diversity: species richness and species turnover. Our main finding is that the spatial pattern of diversity changes with the scale of observation or analysis. For a given scale, the pattern of species richness (alpha diversity) is negatively correlated with the pattern of species turnover (beta diversity). Species-rich areas have more species in common with their neighbors than species-poor areas. The between-scale disparity of the spatial pattern of diversity may be a general feature of ecological systems. For this to be validated, studies with different groups of species in different biomes and in different biogeographical areas are required; our study contributes to this direction providing evidence that this holds true for woody species in Mediterranean communities. Finally, we discuss how these findings might affect important issues in theoretical and applied ecology, such as identifying the environmental factors driving biodiversity.