The Environmental balance sheet of nations: reflections on global climate change scenarios

2012 ◽  
Vol 9 (1) ◽  
pp. 60-102 ◽  
Author(s):  
José Roberto Kassai ◽  
Rafael Feltran-Barbieri ◽  
Luiz Nelson Carvalho ◽  
Yara Consuelo Cintra ◽  
Luís Eduardo Afonso ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Global Climate ◽  
Balance Sheet ◽  
Climate Change Scenarios ◽  
Environmental Balance

Future projections for Mexican faunas under global climate change scenarios

Nature ◽  
2002 ◽  
Vol 416 (6881) ◽  
pp. 626-629 ◽  
Author(s):  
A. Townsend Peterson ◽  
Miguel A. Ortega-Huerta ◽  
Jeremy Bartley ◽  
Victor Sánchez-Cordero ◽  
Jorge Soberón ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Global Climate ◽  
Climate Change Scenarios ◽  
Future Projections

scholarly journals Throwing light on dark diversity of vascular plants in China: predicting the distribution of dark and threatened species under global climate change

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6731 ◽  
Author(s):  
Lili Tang ◽  
Runxi Wang ◽  
Kate S. He ◽  
Cong Shi ◽  
Tong Yang ◽  
...  
Keyword(s):  
Climate Change ◽  
Species Distribution ◽  
Global Climate Change ◽  
Vascular Plants ◽  
Global Climate ◽  
Ex Situ ◽  
Climate Change Scenarios ◽  
Distribution Models ◽  
Maxent Model ◽  
Maxent Modeling

Background As global climate change accelerates, ecologists and conservationists are increasingly investigating changes in biodiversity and predicting species distribution based on species observed at sites, but rarely consider those plant species that could potentially inhabit but are absent from these areas (i.e., the dark diversity and its distribution). Here, we estimated the dark diversity of vascular plants in China and picked up threatened dark species from the result, and applied maximum entropy (MaxEnt) model to project current and future distributions of those dark species in their potential regions (those regions that have these dark species). Methods We used the Beals probability index to estimate dark diversity in China based on available species distribution information and explored which environmental variables had significant impacts on dark diversity by incorporating bioclimatic data into the random forest (RF) model. We collected occurrence data of threatened dark species (Eucommia ulmoides, Liriodendron chinense, Phoebe bournei, Fagus longipetiolata, Amentotaxus argotaenia, and Cathaya argyrophylla) and related bioclimatic information that can be used to predict their distributions. In addition, we used MaxEnt modeling to project their distributions in suitable areas under future (2050 and 2070) climate change scenarios. Results We found that every study region’s dark diversity was lower than its observed species richness. In these areas, their numbers of dark species are ranging from 0 to 215, with a generally increasing trend from western regions to the east. RF results showed that temperature variables had a more significant effect on dark diversity than those associated with precipitation. The results of MaxEnt modeling showed that most threatened dark species were climatically suitable in their potential regions from current to 2070. Discussions The results of this study provide the first ever dark diversity patterns concentrated in China, even though it was estimated at the provincial scale. A combination of dark diversity and MaxEnt modeling is an effective way to shed light on the species that make up the dark diversity, such as projecting the distribution of specific dark species under global climate change. Besides, the combination of dark diversity and species distribution models (SDMs) may also be of value for ex situ conservation, ecological restoration, and species invasion prevention in the future.

Review of current understanding of global climate change and its impacts

2012 ◽  
Vol 2 (3) ◽  
pp. 594-600
Author(s):  
M. Sciortino
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Physical Science ◽  
Review Paper ◽  
Global Climate ◽  
Climate Change Scenarios ◽  
The European Union ◽  
Natural Ecosystems ◽  
Intergovernmental Panel ◽  
Group I

This review paper is based on the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change, in particular on the Working Group I (WG I) ‘The physical science basis’ and on the WG II ‘Impacts adaptation and vulnerability’ reports. The WG I report represents the state of the current scientific understanding of the observed and projected climate changes. The natural and anthropogenic drivers of climate change are addressed, focusing on the physical science understanding of observed records and on model-generated global climate change scenarios. The WG II report concerns the relationship between the observed changes of climate variables and the changes in the natural and human environment, addressing key policy-relevant scientific findings. Projected impacts and findings about vulnerability and adaptation on fresh water, natural ecosystems, food, fiber, coastal areas industry and health are also addressed for all continents. Scientific findings subsequent to the publication of the AR4 are not included in this review paper, whereas the recent decisions by the European Union (EU) and the agreements adopted within the United Nation Framework Convention on Climate Change based on the AR4 are reported.

Mapping environments at risk under different global climate change scenarios

2004 ◽  
Vol 8 (1) ◽  
pp. 53-60 ◽  
Author(s):  
Earl Saxon ◽  
Barry Baker ◽  
William Hargrove ◽  
Forrest Hoffman ◽  
Chris Zganjar
Keyword(s):  
Climate Change ◽  
At Risk ◽  
Global Climate Change ◽  
Global Climate ◽  
Climate Change Scenarios

Hydroclimatology of the U.S. Gulf Coast Under Global Climate Change Scenarios

2011 ◽  
Vol 32 (6) ◽  
pp. 561-582 ◽  
Author(s):  
Barry D. Keim ◽  
Royce Fontenot ◽  
Claudia Tebaldi ◽  
David Shankman
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Gulf Coast ◽  
Global Climate ◽  
Climate Change Scenarios ◽  
The U.S
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