Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of the endangered Camphora swamp eucalypt (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia). The eucalypt community provides both habitat and food for a variety of threatened and endangered flora and fauna. Over the last 20 years the E. camphora has become increasingl
Species distribution models (SDMs) are increasingly proposed to support conservation decision making...
Resources for biodiversity conservation are limited and it is therefore imperative that management a...
Along the Santa Clara River in California, populations of the federally and state-listed Least Bell'...
Wildlife managers are often required to make important conservation and recovery decisions despite i...
An expert elicitation approach for Bayesian classification trees is developed in this paper. This ap...
We developed a set of decision-aiding models as Bayesian belief networks (BBNs) that represented a c...
Species distribution models (SDMs) are increasingly proposed to support conservation decision making...
Species distribution models (SDMs) are increasingly proposed to support conservation decision making...
Threatened species management is a priority in global conservation. Despite many international and n...
This thesis explores the kinds of models that may be built to support environmental decisions when d...
© 2015 Dr. Stefano CanessaPrograms for the recovery of threatened species increasingly involve activ...
Abstract: It is evident that land-use decisions pose a risk to habitats, biodiversity and endangered...
Determining a species’ legal status is essential for identifying those in real danger of becoming ex...
Considerable funding and effort is dedicated to the conservation and recovery of threatened species ...
Adaptive management is an iterative process of gathering new knowledge regarding a system's behavior...
Species distribution models (SDMs) are increasingly proposed to support conservation decision making...
Resources for biodiversity conservation are limited and it is therefore imperative that management a...
Along the Santa Clara River in California, populations of the federally and state-listed Least Bell'...
Wildlife managers are often required to make important conservation and recovery decisions despite i...
An expert elicitation approach for Bayesian classification trees is developed in this paper. This ap...
We developed a set of decision-aiding models as Bayesian belief networks (BBNs) that represented a c...
Species distribution models (SDMs) are increasingly proposed to support conservation decision making...
Species distribution models (SDMs) are increasingly proposed to support conservation decision making...
Threatened species management is a priority in global conservation. Despite many international and n...
This thesis explores the kinds of models that may be built to support environmental decisions when d...
© 2015 Dr. Stefano CanessaPrograms for the recovery of threatened species increasingly involve activ...
Abstract: It is evident that land-use decisions pose a risk to habitats, biodiversity and endangered...
Determining a species’ legal status is essential for identifying those in real danger of becoming ex...
Considerable funding and effort is dedicated to the conservation and recovery of threatened species ...
Adaptive management is an iterative process of gathering new knowledge regarding a system's behavior...
Species distribution models (SDMs) are increasingly proposed to support conservation decision making...
Resources for biodiversity conservation are limited and it is therefore imperative that management a...
Along the Santa Clara River in California, populations of the federally and state-listed Least Bell'...