Landscape‐ and small‐scale determinants of grassland species diversity: direct and indirect influences

Species richness is influenced both by mechanisms occurring at landscape scales, such as habitat availability, and local‐scale processes, that are related to abiotic conditions and plant–plant interactions. However, it is rarely tested to what extent local species richness can be explained by the combined effect of factors measured at multiple spatial scales. In this study, we quantified the simultaneous influence of historical landscape‐scale factors (past human population density, and past habitat availability – an index combining area and connectivity) and small‐scale environmental conditions (shrub cover, and heterogeneity of light, soil depth, and other soil environmental variables) on plant species richness in dry calcareous grasslands (alvars). By applying structural equation modelling (SEM) we found that both landscape conditions and local environmental factors had significant direct and indirect (i.e. through the modification of another factor), effects on species richness. At the landscape scale, we found a direct positive influence of historical habitat availability on species richness, and indirect positive influence of past human population (via its effects on historical habitat availability). At small scales, we found a positive direct influence of light heterogeneity and shrub cover on species richness. Conversely, we found that small‐scale soil environmental heterogeneity, which was mainly determined by soil depth heterogeneity, had a negative effect on species richness. Our study indicates that patterns of species richness in alvar grasslands are positively influenced by the anthropogenic management regime that maintained the landscape habitat conditions in the past. However, the abandonment of management, leading to shrub invasion and increased competition for light resources also influenced species richness. In contrast to the positive heterogeneity–diversity relationship we found that soil heterogeneity reduced species richness. Environmental heterogeneity, occurring at the plant neighbourhood scale (i.e. centimetres), can increase the isolation among suitable soil patches and thus hinder the normal functioning of populations. The combination of previous knowledge of the system with new ecological theories facilitates disentangling how species richness responds to complex relationships among factors operating at multiple scales.     

Point-of-Care Autofluorescence Imaging for Real-Time Sampling and Treatment Guidance of Bioburden in Chronic Wounds: First-in-Human Results

Background

Traditionally, chronic wound infection is diagnosed by visual inspection under white light and microbiological sampling, which are subjective and suboptimal, respectively, thereby delaying diagnosis and treatment. To address this, we developed a novel handheld, fluorescence imaging device (PRODIGI) that enables non-contact, real-time, high-resolution visualization and differentiation of key pathogenic bacteria through their endogenous autofluorescence, as well as connective tissues in wounds.

Methods and Findings

This was a two-part Phase I, single center, non-randomized trial of chronic wound patients (male and female, ≥18 years; UHN REB #09-0015-A for part 1; UHN REB #12-5003 for part 2; clinicaltrials.gov Identifier: NCT01378728 for part 1 and NCT01651845 for part 2). Part 1 (28 patients; 54% diabetic foot ulcers, 46% non-diabetic wounds) established the feasibility of autofluorescence imaging to accurately guide wound sampling, validated against blinded, gold standard swab-based microbiology. Part 2 (12 patients; 83.3% diabetic foot ulcers, 16.7% non-diabetic wounds) established the feasibility of autofluorescence imaging to guide wound treatment and quantitatively assess treatment response. We showed that PRODIGI can be used to guide and improve microbiological sampling and debridement of wounds in situ, enabling diagnosis, treatment guidance and response assessment in patients with chronic wounds. PRODIGI is safe, easy to use and integrates into the clinical workflow. Clinically significant bacterial burden can be detected in seconds, quantitatively tracked over days-to-months and their biodistribution mapped within the wound bed, periphery, and other remote areas.

Conclusions

PRODIGI represents a technological advancement in wound sampling and treatment guidance for clinical wound care at the point-of-care.

Trial Registration

ClinicalTrials.gov NCT01651845; ClinicalTrials.gov NCT01378728     

Novel function of alternatively activated macrophages: stabilin-1-mediated clearance of SPARC

The matricellular protein SPARC (secreted protein acidic and rich in cysteine) has been implicated in development, differentiation, response to injury, and tumor biology by virtue of its regulation of extracellular matrix production/assembly and its antiadhesive and antiproliferative effects on different cell types. Despite numerous biological activities described for SPARC, cell surface receptors for this protein have not been identified. By phage display and in vitro-binding assays, we now show that SPARC interacts with stabilin-1, a scavenger receptor expressed by tissue macrophages and sinusoidal endothelial cells. The interaction is mediated by the extracellular epidermal growth factor-like region of stabilin-1 containing the sequence FHGTAC. Using FACS analysis and confocal microscopy, we demonstrate that stabilin-1 internalizes and targets SPARC to an endosomal pathway in Chinese hamster ovary cells stably transfected with this receptor. In human macrophages, stabilin-1 expression is required for receptor-mediated endocytosis of SPARC. SPARC was efficiently endocytosed by alternatively activated macrophages stimulated by IL-4 and dexamethasone, but not solely by Th1 or Th2 cytokines. A time course of ligand exposure to alternatively activated macrophages revealed that stabilin-1-mediated endocytosis of SPARC was followed by its targeting for degradation, similar to the targeting of acetylated low density lipoprotein, another stabilin-1 ligand. We propose that alternatively activated macrophages coordinate extracellular matrix remodeling, angiogenesis, and tumor progression via stabilin-1-mediated endocytosis of SPARC and thereby regulate its extracellular concentration.     

Simultaneous degradation of atrazine and phenol by Pseudomonas sp. strain ADP: effects of toxicity and adaptation

The strain Pseudomonas sp. strain ADP is able to degrade atrazine as a sole nitrogen source and therefore needs a single source for both carbon and energy for growth. In addition to the typical C source for Pseudomonas, Na(2)-succinate, the strain can also grow with phenol as a carbon source. Phenol is oxidized to catechol by a multicomponent phenol hydroxylase. Catechol is degraded via the ortho pathway using catechol 1,2-dioxygenase. It was possible to stimulate the strain in order to degrade very high concentrations of phenol (1,000 mg/liter) and atrazine (150 mg/liter) simultaneously. With cyanuric acid, the major intermediate of atrazine degradation, as an N source, both the growth rate and the phenol degradation rate were similar to those measured with ammonia as an N source. With atrazine as an N source, the growth rate and the phenol degradation rate were reduced to approximately 35% of those obtained for cyanuric acid. This presents clear evidence that although the first three enzymes of the atrazine degradation pathway are constitutively present, either these enzymes or the uptake of atrazine is the bottleneck that diminishes the growth rate of Pseudomonas sp. strain ADP with atrazine as an N source. Whereas atrazine and cyanuric acid showed no significant toxic effect on the cells, phenol reduces growth and activates or induces typical membrane-adaptive responses known for the genus Pseudomonas. Therefore Pseudomonas sp. strain ADP is an ideal bacterium for the investigation of the regulatory interactions among several catabolic genes and stress response mechanisms during the simultaneous degradation of toxic phenolic compounds and a xenobiotic N source such as atrazine.     

Evaluating Functional Diversity: Missing Trait Data and the Importance of Species Abundance Structure and Data Transformation

Functional diversity (FD) is an important component of biodiversity that quantifies the difference in functional traits between organisms. However, FD studies are often limited by the availability of trait data and FD indices are sensitive to data gaps. The distribution of species abundance and trait data, and its transformation, may further affect the accuracy of indices when data is incomplete. Using an existing approach, we simulated the effects of missing trait data by gradually removing data from a plant, an ant and a bird community dataset (12, 59, and 8 plots containing 62, 297 and 238 species respectively). We ranked plots by FD values calculated from full datasets and then from our increasingly incomplete datasets and compared the ranking between the original and virtually reduced datasets to assess the accuracy of FD indices when used on datasets with increasingly missing data. Finally, we tested the accuracy of FD indices with and without data transformation, and the effect of missing trait data per plot or per the whole pool of species. FD indices became less accurate as the amount of missing data increased, with the loss of accuracy depending on the index. But, where transformation improved the normality of the trait data, FD values from incomplete datasets were more accurate than before transformation. The distribution of data and its transformation are therefore as important as data completeness and can even mitigate the effect of missing data. Since the effect of missing trait values pool-wise or plot-wise depends on the data distribution, the method should be decided case by case. Data distribution and data transformation should be given more careful consideration when designing, analysing and interpreting FD studies, especially where trait data are missing. To this end, we provide the R package “traitor” to facilitate assessments of missing trait data.