Biotechnology of the multipurpose tree species Arbutus unedo: a review

Arbutus unedo L. (strawberry tree, Ericaceae) is a woody species with a circum-Mediterranean distribu-tion. It has considerable ecological relevance in southern...     

Phenotypic diversity within native Iranian almond (<Emphasis Type="Italic">Prunus</Emphasis> spp.) species and their breeding potential

A total of 137 accessions from 18 wild almond species were collected from Iran and leaf and fruit traits were characterized. Also evaluated were flowering and ripening date, self-incompatibility and kernel bitterness. An extensive phenotypic diversity was found both among and within species. Differences in average leaf dimensions among and within species were associated with average rainfall but not altitude of collection site. Adjacent accessions located in drier areas had smaller leaf dimensions than those located in semi-humid or humid regions. No relation was found between average fruit dimensions and collection site conditions. Principal component analysis revealed that the nut weight and width, and the kernel weight had highest loading in the first component accounting for 45.8% of total variation. In contrast, leaf traits in the second component accounted for 22.3% of total variation. No significant correlations were detected between leaf dimensions and fruit traits in all species evaluated. Results document a rich source of new germplasm for almond improvement programs. Small fruit size, pollen-pistil self-incompatibility, and bitter kernel flavour are the most common obstacles to the utilization of this wild germplasm in breeding.     

Mercury in Biota and Surficial Sediments from Coatzacoalcos Estuary, Gulf of Mexico: Distribution and Seasonal Variation

Variation of mercury (Hg) in sediments and biota from Coatzacoalcos estuary during the dry, rainy and windy seasons was estimated. In sediments, Hg concentrations ranged from 0.07 μg g^?1 in site 13 (Ixhuatepec) located upstream, to 1.06 μg g^?1 in site 3 (Coatzacoalcos river), located in the industrialized area. Highest enrichment factor (EF) and index of geoaccumulation (I _geo) in surficial sediments were 53 and 5.1 respectively. From EF and I _geo, it is considered that Coatzacoalcos estuary is from moderately contaminated to contaminated. In most fish species from Coatzacoalcos estuary, the sequence of Hg concentration was liver>muscle>gills. Average Hg concentrations in soft tissue of bivalves ranged from 0.09 μg g^?1 in Corbicula fluminea to 0.18 μg g^?1 in Polymesoda caroliniana. Biota-sediment accumulation factor (BSAF) ranged from 0.9 in P. caroliniana during the rainy season (site 4) to 3.8 in P. caroliniana from the same site during the windy season.     

Dog as a model for studying conspecific and heterospecific social learning

In human communities social learning (i.e., learning by the observation of knowledgeable individuals) plays an important role; it shapes cultures, traditions, and cognition. Dogs seem to be an ideal system for modeling human cognition from the social learning aspect. The present review offers a short overview on the relevant general theories of social learning, discusses the adaptive value of social learning, introduces dog as a model system, presents evidence for different forms of social learning in dogs and argues for practical implications that social learning might have in this species.     

Modeling Bare Ground With Classification Trees in Northern Spain

Bare ground abundance is an important rangeland health indicator and its detection is a fundamental part of range management. Remote sensing of bare ground might offer solutions for land managers but also presents challenges as modeling in semiarid environments usually involves a high frequency of spectral mixing within pixels. Classification tree analysis (CTA) and maximum likelihood classifiers were used to model bare ground in the semiarid steppes of the middle Ebro valley, Aragon, Spain using Satellite Pour l'Observation de la Terre 4 (SPOT 4) imagery and topographic data such as elevation, slope, aspect, and a morphometric characterization model. A total of 374 sample points of bare-ground fraction from sixteen 500-m transects were used in the classification and validation process. Overall accuracies were 85% (Kappa statistic = 0.70) and 57% (Kappa statistic = 0.13) from the CTA and maximum likelihood classifiers, respectively. Although spectral attributes were essential in bare-ground classification, the topographic and morphometric properties of the landscape were equally critical in this modeling effort. Although the specific layers best suited for each specific model will vary from region to region, this study provided an important insight on both bare-ground modeling and the potential advantages of CTA.