Explicitly Accounting for Pixel Dimension in Calculating Classical and Fractal Landscape Shape Metrics

Different summarized shape indices, like mean shape index (MSI) and area weighted mean shape index (AWMSI) can change over multiple size scales. This variation is important to describe scale heterogeneity of landscapes, but the exact mathematical form of the dependence is rarely known. In this paper, the use of fractal geometry (by the perimeter and area Hausdorff dimensions) made us able to describe the scale dependence of these indices. Moreover, we showed how fractal dimensions can be deducted from existing MSI and AWMSI data. In this way, the equality of a multiscale tabulated MSI and AWMSI dataset and two scale-invariant fractal dimensions has been demonstrated.     

Peroxisome proliferator-activated receptor alpha agonists as therapy for autoimmune disease

Peroxisome proliferator-activated receptors (PPARs) are members of the nuclear hormone receptor superfamily. PPAR gamma ligands, which include the naturally occurring PG metabolite 15-deoxy-Delta(12,14)-PGJ(2) (15d-PGJ(2)), as well as thiazolidinediones, have been shown to have anti-inflammatory activity. The PPAR alpha agonists, gemfibrozil, ciprofibrate, and fenofibrate, have an excellent track history as oral agents used to treat hypertriglyceridemia. In the present study, we demonstrate that these PPAR alpha agonists can increase the production of the Th2 cytokine, IL-4, and suppress proliferation by TCR transgenic T cells specific for the myelin basic protein Ac1-11, as well as reduce NO production by microglia. Oral administration of gemfibrozil and fenofibrate inhibited clinical signs of experimental autoimmune encephalomyelitis. More importantly, gemfibrozil was shown to shift the cytokine secretion of human T cell lines by inhibiting IFN-gamma and promoting IL-4 secretion. These results suggest that PPAR alpha agonists such as gemfibrozil and fenofibrate, may be attractive candidates for use in human inflammatory conditions such as multiple sclerosis.     

Reduced short-term thermic effects of a meal in obese adolescent girls

Post-meal energy expenditure (TEM) was compared for 14 healthy obese (body fat = 45.3%, body mass index, BMI = 35.9 kg m-2) and 9 healthy nonobese (body fat = 20.7%, BMI = 17.8 kg m-2) adolescent girls. The test meal for both groups was a standard 3348.8-kJ, 0.473-1 chocolate milkshake of 15% protein (casein), 40% fat (polyunsaturated/saturated ratio = 0.05; 75 mg cholesterol) and 45% carbohydrate (lactose and sucrose). Glucose, insulin and resting energy expenditure (RMR) were measured at rest prior to meal consumption and 20, 40, 60, 90, and 120 min after the meal. Cumulative net TEM was calculated as the integrated area under the TEM curve with RMR as baseline. Reliability was assessed by retesting 4 subjects, and a placebo effect was tested by administering a flavored energy-free drink. Results indicated high reliability and no placebo effect. The meal resulted in a greater rise in insulin and glucose for the obese compared to the nonobese subjects (P < or = 0.05), and a significant TEM for both groups (P < or = 0.05). The cumulative TEM (W kg-1) was 61.9% greater for the nonobese (P < 0.01) when expressed relative to body mass, and 33.2% greater for the nonobese (P < or = 0.01) when expressed relative to the fat-free body mass. Expressed relative to the meal, the TEM was 25.5% less for the obese (P < 0.01). The data support an energy conservation hypothesis for obese female adolescents.     

A landscape genetics approach reveals ecological‐based differentiation in populations of holm oak (Quercus ilex L.) at the northern limit of its range

The holm oak plays a relevant role in the functioning of Mediterranean forests. In the area north of Garda Lake, Italian Prealps, holm oak populations are at the northernmost edge of their distribution. Being peripheral, these populations are of particular interest for ecological, evolutionary and conservation studies. Through an explicit individual‐based landscape genetics approach, we addressed the following questions: (1) are levels of genetic variation reduced in these marginal populations compared with central populations?; (2) despite the narrow geographical scale, do individual‐based analyses have some power to detect genetic differentiation?; (3) do environmental and/or climatic factors exert a role in shaping patterns of genetic variation and differentiation? Through a Bayesian method, we identified three clusters whose genetic variability can be considered to be of the same order as that recorded in central Quercus ilex populations. Although being geographically very close (< 20 km), the differentiation was statistically significant (P < 0.05) with global F _st and Φ _Pt values of 0.019 and 0.038, respectively. Geography and phylogeography could not be invoked to explain this differentiation. A redundancy discriminant analysis revealed that relevant eco‐pedological and climatic features, such as soil depth, aspect, elevation and humidity, were correlated with the observed pattern of differentiation. Toblino was ecologically separated from the other clusters, as it lies on deep soil with subhumid conditions. The differentiation of the Brione–Ranzo–Val Busa cluster appeared to be related to superficial soils and drier conditions, whereas the Nanzone–Padaro cluster was differentiated mainly according to its mid‐elevation. Coupling spatial and genetic information on a local scale proved to be effective to investigate the evolutionary and demographic history of peripheral populations. © 2012 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, ?? , ??–??.     

Maximizing plant species inventory efficiency by means of remotely sensed spectral distances

Aim Inventorying plant species in an area based on randomly placed quadrats can be quite inefficient. The aim of this paper is to test whether plant species richness can be inventoried more efficiently by means of a spectrally‐based ordering of sites to be sampled. Location The study area was a complex wetland ecosystem, the Lake Montepulciano Nature Reserve, central Italy. This is one of the most important wetland areas of central Italy because of the diverse plant communities and the seasonal avifauna. Methods Field sampling, based on a random stratified sampling design, was performed in June 2002. Plant species composition was recorded within sampling units of 100 m² (plots) and 1 ha (macroplots). A QuickBird multispectral image of the same date was acquired and corrected both geometrically and radiometrically. Species accumulation curves based on spectral information were obtained by ordering sites to be sampled according to a maximum spectral distance criterion (i.e. by ordering sampling units based on the maximum distances among them in a four‐dimensional spectral space derived from the remotely sensed data). Different distance measures based on mean and maximum spectral distances among sampling units were tested. The performance of the species accumulation curve derived by the spectrally‐based ordering of sampling units was tested against a rarefaction curve obtained from the mean of 10,000 accumulation curves based on randomly ordered sampling units. Results The spectrally‐derived curve based on the maximum spectral distance among sampling units showed the most rapid accumulation of species, well above the rarefaction curve, at both the plot and the macroplot scales. Other ordering criteria of sampling units captured less richness over most of the species accumulation curves at both the spatial scales. The accumulation curves based on other measurements of distance were much closer to the random curve and did not show differences with respect to the species rarefaction curve based on random ordering of sampling units. Main conclusions The present investigation demonstrated that spectral‐based ordering of sites to be sampled can lead to the maximization of the efficiency of plant species inventories, an activity usually driven by the ‘botanist's internal algorithm’ (intuition), without any formalized rule to drive field sampling. The proposed approach can reduce costs of plant species inventorying through a more efficient allotment of time and sampling.     

The role of regional and local scale predictors for plant species richness in Mediterranean forests

Abstract

Both local and regional predictors play a role in determining plant community structure and composition. Climate, soil features as well as different local history and management affect forest understorey and tree species composition, but to date their specific role is relatively unknown. Few studies have addressed the importance of these predictors, especially in the Mediterranean area, where environmental conditions and human impacts have generated heterogeneous forest communities. In this study, the relationships between environmental variables and species richness of different groups of vascular plants (vascular species, woody species and open habitat species) and bryophytes were investigated in Tuscan forests. A total of 37 environmental variables were used by generalised linear model fitting in order to find parsimonious sub-sets of environmental factors (predictors) that are able to explain species diversity patterns at the local scale. Moreover, the role of regional and local variable groups on species richness of the considered plant groups was estimated by using the variance partitioning approach. We found that local variables, such as forest management and structure, explained more variance than regional variables for total species richness, open habitat species richness and bryophyte species richness. On the other hand, regional variables (such as elevation) played a central role for woody species richness.     

Relationship of fat patterning to coronary artery disease risk in obese adolescents

Fatness and fat patterning of 27 male and 33 female obese adolescents were identified by principal-components analysis of five skinfolds (triceps, subscapular, iliac, abdominal, and thigh). Correlations were computed between the component scores, based on the eigen vectors, and anthropometric and physiological variables. Overall fatness, component I, was highly correlated with all anthropometric and body composition variables. Also, component I significantly correlated with fasting insulin and VO2 max for both sexes and with basal metabolism and HDL-cholesterol for females and males, respectively. Extremity fat patterning, component II, was poorly correlated with all the anthropometric and physiological variables except diastolic blood pressure for the females. Upper-lower body fat patterning, component III, was correlated with the fewest physiological variables.     

A test of vegetation–environment relationship in serpentine soils of Tuscany, Italy

The present study evaluates the relative importance of environmental factors in affecting the species composition and abundance of the plant communities on ultramafic soils in Tuscany, Italy. We used rigorous sampling techniques to test hypotheses generated from exploratory studies performed previously. Vegetation–environmental relationships were analyzed using 50 plots, each 1 m², randomly located throughout a 22-ha area in the Upper Tiber Valley. We confirm that the exchangeable fraction of nickel in the soil is almost never high enough to affect the vegetation. However, physical factors (e.g. substrate setting and elevation) are important in controlling the distribution of plant species. Tree cover (almost exclusively due to the introduced plantation pines) also had a significant affect on the vegetation composition and on soil features such as the C/N ratio. Other important factors significantly related to the gradients in vegetation composition (e.g. rockiness and total soil nitrogen) are interpreted as factors related to the vegetation composition through a positive feedback mechanism.