One major concern regarding the biodiversity impacts of Reduced Emissions from Deforestation and Degradation (REDD+) is “leakage” of threats from REDD+ to non-REDD+ forests, particularly if those forests storing the highest amounts of carbon – and thus prioritized under REDD+ – do not coincide with those most important for biodiversity conservation. This concern applies globally, and has been p...

In recent decades, the area and proportion of planted forests have increased; thus, understanding the responses of planted and natural forests to drought are crucial because it forms the basis for forest risk assessments and management strategies. In this study, we combined the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI), meteorological aridity indices,...

There are few detailed carbon (C) budgets of mangrove forests, yet these are important for understanding C sequestration in mangrove forests, how they support the productivity of the coast and their vulnerability to environmental change. Here, we develop C budgets for mangroves on the islands of Twin Cays, Belize. We consider seaward fringing forests and interior scrub forests that have been fe...

Primary tropical forests are renowned for their high biodiversity and carbon storage, and considerable research has documented both species and carbon losses with deforestation and agricultural land uses. Economic drivers are now leading to the abandonment of agricultural lands, and the area in secondary forests is increasing. We know little about how long it takes for these ecosystems to achie...

Lack of hunting and predators and proximity to human communities make suburban forests prone to high deer abundance and non-native plant invasions. I investigated these likely drivers of community structure in the herb layers of six suburban forests in one region of New Jersey, USA. In 223 plots I assessed the herb layer response to 2.5 years with or without deer fencing and the early stage of ...

In this paper we study random forests through their connection with a new framework of adaptive nearest neighbor methods. We first introduce a concept of potential nearest neighbors (k-PNN’s) and show that random forests can be seen as adaptively weighted k-PNN methods. Various aspects of random forests are then studied from this perspective. We investigate the effect of terminal node sizes and...

The world's forests influence climate through physical, chemical, and biological processes that affect planetary energetics, the hydrologic cycle, and atmospheric composition. These complex and nonlinear forest-atmosphere interactions can dampen or amplify anthropogenic climate change. Tropical, temperate, and boreal reforestation and afforestation attenuate global warming through carbon seques...

Random forests are known to be good for data mining of classification tasks, because random forests are robust for datasets having insufficient information possibly with some errors. But applying random forests blindly may not produce good results, and a dataset in the domain of rotogravure printing is one of such datasets. Hence, in this paper, some best classification accuracy based on clever...

Remnant forests in urban areas provide vital ecosystem services but are susceptible to many human activities including heavy metal emissions. In this study, we collected 192 samples of mineral soils at depths of 0–3, 3–13 and 13–23 cm in 16 remnant forests (eight natural forests and eight plantation forests) in the urbanized Pearl River Delta, China. We assessed the potential risks of soil Cu, ...