Choice of biodiversity index drives optimal fire management decisions

Title : Optimal fire histories for biodiversity conservation

Can behavioral decision theory explain risk-averse fire management decisions?

Organizations managing forest land often make fire management decisions that seem overly risk-averse in relation to their stated goals for ecosystem restoration, protection of sensitive species and habitats, and protection of water and timber resources. Research in behavioral decision theory has shown that people faced with difficult decisions under uncertainty and decisions with multiple and c...

R 9 Fire and biodiversity

In a famous passage in the concluding chapter of The Origin of Species, Darwin (1859, 1964) invites the reader to “contemplate an entangled bank, clothed with many plants of many kinds, with birds singing on the bushes, with various insects flitting about, and with worms crawling through the damp earth” and “reflect that these elaborately constructed forms, so different from each other, and dep...

The Optimal Choice of Index-Linked GICs: Some Canadian Evidence

Indexed Linked Guaranteed Investment Certificates (ILGICs), also known as equity linked term deposits, have become quite popular over the last few years. From the consumer’s point of view, there are two basic categories of Indexed Linked GIG, the Capped ILGIC and the Participating ILGIC. This paper compares the relative value and appeal of the two ILGIC products from the perspective of the indi...

Land cover, more than monthly fire weather, drives fire-size distribution in Southern Québec forests: Implications for fire risk management

Fire activity in North American forests is expected to increase substantially with climate change. This would represent a growing risk to human settlements and industrial infrastructure proximal to forests, and to the forest products industry. We modelled fire size distributions in southern Québec as functions of fire weather and land cover, thus explicitly integrating some of the biotic intera...