Cascades and Connectivity: The Influence of Spatial Scale on Understanding Ecosystem Processes (2015-02-27)

Dr. Nate Nibbelink of the University of Georgia speaks on Cascades and Connectivity: The Influence of Spatial Scale on Understanding Ecosystem ProcessesUMD Department of Biolog

Habitat Suitability Modeling of Rare Turkeybeard (<i>Xerophyllum asphodeloides</i>) Species in the Talladega National Forest, Alabama, USA

This study focused on the rare and threatened plant species eastern turkeybeard (Xerophyllum asphodeloides (L.) Nutt.) and its presence or absence in the Talladega National Forest in Alabama, USA. An ensemble suitable habitat map was developed using four different modeling methods (MaxEnt, Generalized Linear Model, Generalized Additive Model, and Random Forest). AUC evaluation scores for each model were 0.99, 0.96, 0.98, and 0.99, respectively. Biserial correlation scores for models ranged from 0.71 (GLM) to 0.94 (RF). The four different models agreed suitable habitat was found to cover 159.57 ha of the land. The ground slope variable was the most contributive variable in the MaxEnt and RF models and was also significant in the GLM and GAM models. The knowledge gained from this research can be used to establish and implement habitat suitability strategies across the Talladega National Forest and similar ecosystems in the southern United States

Habitat Suitability Modeling of Rare Turkeybeard (Xerophyllum asphodeloides) Species in the Talladega National Forest, Alabama, USA

This study focused on the rare and threatened plant species eastern turkeybeard (Xerophyllum asphodeloides (L.) Nutt.) and its presence or absence in the Talladega National Forest in Alabama, USA. An ensemble suitable habitat map was developed using four different modeling methods (MaxEnt, Generalized Linear Model, Generalized Additive Model, and Random Forest). AUC evaluation scores for each model were 0.99, 0.96, 0.98, and 0.99, respectively. Biserial correlation scores for models ranged from 0.71 (GLM) to 0.94 (RF). The four different models agreed suitable habitat was found to cover 159.57 ha of the land. The ground slope variable was the most contributive variable in the MaxEnt and RF models and was also significant in the GLM and GAM models. The knowledge gained from this research can be used to establish and implement habitat suitability strategies across the Talladega National Forest and similar ecosystems in the southern United States

Data from: Targeting global conservation funding to limit immediate biodiversity declines

Inadequate funding levels are a major impediment to effective global biodiversity conservation and are likely associated with recent failures to meet United Nations biodiversity targets. Some countries are more severely underfunded than others and therefore represent urgent financial priorities. However, attempts to identify these highly underfunded countries have been hampered for decades by poor and incomplete data on actual spending, coupled with uncertainty and lack of consensus over the relative size of spending gaps. Here, we assemble a global database of annual conservation spending. We then develop a statistical model that explains 86% of variation in conservation expenditures, and use this to identify countries where funding is robustly below expected levels. The 40 most severely underfunded countries contain 32% of all threatened mammalian diversity and include neighbors in some of the world’s most biodiversity-rich areas (Sundaland, Wallacea, and Near Oceania). However, very modest increases in international assistance would achieve a large improvement in the relative adequacy of global conservation finance. Our results could therefore be quickly applied to limit immediate biodiversity losses at relatively little cost

Biodiversity conservation spending by country by source 2001-2008

File shows the amount allocated to biodiversity conservation by domestic and international sources, in millions of 2005 US dollars, for the period 2001-2008. File also contains numerous comments adding further information. See online material for the published article for details of how data were compiled