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Michael Battaglia

Researcher at United States Forest Service

Publications -  166
Citations -  7468

Michael Battaglia is an academic researcher from United States Forest Service. The author has contributed to research in topics: Climate change & Eucalyptus nitens. The author has an hindex of 48, co-authored 158 publications receiving 6308 citations. Previous affiliations of Michael Battaglia include United States Department of Agriculture & Commonwealth Scientific and Industrial Research Organisation.

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Underimmunization Among Children: Effects of Vaccine Safety Concerns on Immunization Status

TL;DR: Although concerns were significantly more common among parents of underimmunized children, many parents of fully immunized children demonstrated similar attitudes, beliefs, and behaviors, suggesting a risk to the currently high vaccination levels.
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CABALA: a linked carbon, water and nitrogen model of forest growth for silvicultural decision support

TL;DR: In this article, a dynamic forest growth model, CArbon BALAnce (CABALA), that links carbon, water and nitrogen flows through the atmosphere, trees and soil including soil organic matter is presented as a central part of a silvicultural decision support system.
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Photosynthetic temperature responses of Eucalyptus globulus and Eucalyptus nitens.

TL;DR: Comparing the light response curves of the plants showed that the maximum rate of net photosynthesis was affected by the growth temperature, whereas the apparent quantum efficiency remained unchanged, and incomplete acclimation generally resulted in a greater daily carbon uptake than complete acclimations.
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Density‐dependent vulnerability of forest ecosystems to drought

TL;DR: Managing pine forest ecosystems at low tree population density represents a promising adaptive strategy for reducing the adverse impacts of drought on forest growth in coming decades, and the broader applicability of the findings to other types of forest ecosystems merits additional investigation.
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Process-based forest productivity models and their application in forest management

TL;DR: In this paper, a survey of recent literature examines in which areas, and by whom, existing forest productivity models are being applied, and concludes that many current management questions can be adequately answered using models in which a phenomenological approach is applied to predict annual forest growth at the stand-scale.