To study the carbon storage increase of major forest ecosystems in tropical South America, such as Amazon rain forest, Atlantic rain forest, semideciduous forest, and Araucaria forest, the Last Glacial Maximum (LGM) and the early Holocene vegetation cover were reconstructed by pollen records. Marked forest expansion points to a significant total carbon storage increase by tropical forests in So...

Road traffic and the loss of forests are both known to have negative effects on anurans. However, the relative importance of these two predictors is poorly understood because forest cover in the landscape is usually negatively correlated with the density of roads and traffic. To evaluate the independent effects of traffic and forest cover, we selected 36 ponds near Ottawa, Canada, at the center...

Forest understories across the northern United States (US) are a complex of tree seedlings, endemic forbs, herbs, shrubs, and introduced plant species within a forest structure defined by tree and forest floor attributes. The substantial increase in white-tailed deer (Odocoileus virginianus Zimmerman) populations over the past decades has resulted in heavy browse pressure in many of these fores...

In the current scenario of a fragmented Atlantic Forest, with less than 7% of the original cover remaining, the dominant agricultural and agroforestal matrices should be incorporated into conservation planning. However, little information is available on the conservation value of different land uses, especially those of commercial tree plantations. We studied bird communities in native forests ...

Landowners need a simple-to-use, readily available tool to contribute to sustainable management of family forests. We developed an Internetbased decision-support system, 4S Tool (Forest Stand Software Support System), which is designed to encourage informed forest management and to bridge the gap between a new generation of family forest owners (e.g. exurbanites) and natural resources professio...

This research evaluates the utility and performance of a machine learning decision tree classification technique – random forests – for forest classification using remote sensing and ancillary spatial data, across a large area of heterogeneous forest ecosystems in Victoria, Australia. Random forest classification models for forest extent, type and height were trained using 786 2 km x 2 km aeria...