Conference on Adaptive Ecosystem Restoration and Management


Book Description

This conference was meant to facilitate the development of mutually beneficial human-wildland interactions by exploring ways in which to restore and sustain land health, as well as that of dependent human communities, in an adaptive ecosystem management context. General adaptive ecosystem restoration and management principles were discussed, however the conference was specifically designed to encourage cooperative North American work. The primary focus was on long-needled pine (principally ponderosa and closely related pines) and mixed-conifer landscape systems in the Western U.S.










Sustainable Ecological Systems


Book Description

"This conference brought together scientists and managers from federal, state, and local agencies, along with private-sector interests, to examine key concepts involving sustainable ecological systems, and ways in which to apply these concepts to ecosystem management. Session topics were: ecological consequences of land and water use changes, biology of rare and declining species and habitats, conservation biology and restoration ecology, developing and applying ecological theory to management of ecological systems and forest health, and sustainable ecosystems to respond to human needs. A plenary session established the philosophical and historical contexts for ecosystem management."--Title page verso.




Approaches to Predicting Potential Impacts of Climate Change on Forest Disease


Book Description

Predicting climate change influences on forest diseases will foster forest management practices that minimize adverse impacts of diseases. Precise locations of accurately identified pathogens and hosts must be documented and spatially referenced to determine which climatic factors influence species distribution. With this information, bioclimatic models can predict the occurrence and distribution of suitable climate space for host and pathogen species under projected climate scenarios. Predictive capacity is extremely limited for forest pathogens because distribution data are usually lacking. Using Armillaria root disease as an example, predictive approaches using available data are presented.