Wood-inhabiting macrofungal assemblages in 43-year-old regenerating wet Eucalyptus Obliqua L'Her.Forest

This study focuses on the diversity and ecology of wood-inhabiting macrofungal species assemblages in a regenerating tall, wet, native Eucalyptus obliqua forest in southeast Tasmania, 43 years after natural and anthropogenic disturbances. Two plots subjected to "clearfell, burn and sow" silviculture were compared with two other nearby plots that had experienced wildfire. A total of 90 species was identified from 619 macro fungal records during six fortnightly visits between May and July 2010. The plots with abundant live Pomaderris ape tala trees in the understorey (i.e., those at Edwards Rd) had markedly different macrofungal assemblages from those with no or with sparse Pomaderris apetala (i.e., at Hartz Rd). This study provided evidence that a 43-year-old regenerating forest maintains a core of common wood-inhabiting macrofungal species irrespective of type of disturbance. Furthermore, species most frequently observed in older forests in Tasmania can also occur in younger managed forests if biological legacies such as large diameter wood, well-decayed wood, large living trees and a diversity of tree species remain after silvicultural treatment

Quantitative microbiology: a basis for food safety.

Because microorganisms are easily dispersed, display physiologic diversity, and tolerate extreme conditions, they are ubiquitous and may contaminate and grow in many food products. The behavior of microbial populations in foods (growth, survival, or death) is determined by the properties of the food (e.g., water activity and pH) and the storage conditions (e.g., temperature, relative humidity, and atmosphere). The effect of these properties can be predicted by mathematical models derived from quantitative studies on microbial populations. Temperature abuse is a major factor contributing to foodborne disease; monitoring temperature history during food processing, distribution, and storage is a simple, effective means to reduce the incidence of food poisoning. Interpretation of temperature profiles by computer programs based on predictive models allows informed decisions on the shelf life and safety of foods. In- or on-package temperature indicators require further development to accurately predict microbial behavior. We suggest a basis for a "universal" temperature indicator. This article emphasizes the need to combine kinetic and probability approaches to modeling and suggests a method to define the bacterial growth/no growth interface. Advances in controlling foodborne pathogens depend on understanding the pathogens' physiologic responses to growth constraints, including constraints conferring increased survival capacity