A histological evaluation of pansteatitis-affected Mozambique tilapia,Oreochromis mossambicus (Peters 1852), from different geographical locations in South Africa

Pansteatitis is the leading cause for the decline in Nile crocodile populations and the sporadic mortality of fish in the Olifants River System, South Africa. To determine the prevalence of this disease in lentic systems, Mozambique tilapia, Oreochromis mossambicus, were collected from Lake Loskop, Lake Flag Boshielo, Phalaborwa Barrage and Lake Luphephe-Nwanedi. The former three impoundments are located within the main stem of the Olifants River, while the latter, which is geographically isolated and situated in the Limpopo River System, served as a reference site. Mesenteric adipose, liver, serosa of the swim bladder, gill and the skeletal muscle of fish sampled were examined for gross and microscopic evidence of pansteatitis. Microscopically observed changes were used to statistically compare pansteatitis prevalence between samples and sites. Based on histopathological evaluation, the adipose tissue in the liver, swim bladder serosa and coelom from severely debilitated individuals showed the most significant pathological changes. Lesions indicative of steatitis were observed in fish collected from Lake Loskop (75%), Lake Flag Boshielo (22%) and Lake Luphephe-Nwanedi (15%). Further investigation is warranted to understand the pervasiveness and mechanisms driving pathological changes of pansteatitis at Lake Flag Boshielo, Phalaborwa Barrage and Lake Luphephe-Nwanedi.     

The ecosystem services concept: a new Esperanto to facilitate participatory planning processes?

Landscape Ecology - Several case studies investigated the role of ecosystem services in participatory planning processes. However, no systematic study exists that cuts across a large number of...     

Prof. Dipl. Ing. Dr. Dr. h. c. Leo Tschermak zum Gedenken

Ohne Zusammenfassung     

Characterization of fungi (Fusarium and Rhizoctonia) and oomycetes (Phytophthora and Pythium) associated with apple orchards in South Africa

Several species of fungi and oomycetes including Fusarium, Rhizoctonia, Phytophthora and Pythium have been reported as root pathogens of apple where they contribute to a phenomenon known as apple replant disease. In South Africa, little is known about specific species in these genera and their pathogenicity toward apple. Therefore, these aspects were investigated along with the development and optimization of qPCR tests for detection and quantification of the most virulent oomycete species. In eight investigated orchards, the oomycete Phythophthora cactorum was widely distributed, while nine Pythium species were differentially distributed among the orchards. Pythium irregulare was the most widely distributed and the most virulent species along with P. sylvaticum, P. vexans and Ph. cactorum. Seven binucleate Rhizoctonia anastomosis groups (AGs) were also differentially distributed among the orchards, with the majority appearing to be non-pathogenic while certain AG-I and AG-F isolates exhibited low virulence on apple. In the genus Fusarium, F. oxysporum was widely distributed, but isolates were non-pathogenic. Fusarium solani and F. avenaceum were less frequently encountered, with only some isolates having low virulence. qPCR data obtained from seedling roots inoculated with the most virulent Pythium species (P. irregulare, P. sylvaticum and P. vexans) and the genus Phytophthora were not always reproducible between trials, or isolates of the same species. In general, seedling growth inhibition was associated with the presence of a low amount of pathogen DNA (±40 fg μl⁻¹ to 2 pg μl⁻¹) in roots. Pythium irregulare, although having the lowest DNA concentrations in roots, was the only species for which a significant negative correlation was found between seedling weight and pathogen DNA concentration.     

Methods to interpolate soil categorical variables from profile observations: Lessons from Iran

The paper compares semi-automated interpolation methods to produce soil-class maps from profile observations and by using multiple auxiliary predictors such as terrain parameters, remote sensing indices and similar. The Soil Profile Database of Iran, consisting of 4250 profiles, was used to test different soil-class interpolators. The target variables were soil texture classes and World Reference Base soil groups. The predictors were 6 terrain parameters, 11 MODIS EVI images and 17 physiographic regions (polygon map) of Iran. Four techniques were considered: (a) supervised classification using maximum likelihoods; (b) multinominal logistic regression; (c) regression-kriging on memberships; and (d) classification of taxonomic distances. The predictive capabilities were assessed using a control subset of 30% profiles and the kappa statistics as criterion. Supervised classification and multinominal logistic regression can lead to poor results if soil-classes overlap in the feature space, or if the correlation between the soil-classes and predictors is low. The two other methods have better predictive capabilities, although both are computationally more demanding. For both mapping of texture classes and soil types, the best prediction was achieved using regression-kriging of indicators/memberships (κ = 45%, κ = 54%). In all cases kappa was smaller than 60%, which can be explained by the preferential sampling plan, the poor definition of soil-classes and the high variability of soils. Steps to improve interpolation of soil-class data, by taking into account the fuzziness of classes directly on the field are further discussed.