01246nas a2200205   4500008004100000022001300041245007600054210006900130260001300199300001600212490000700228520067100235653001200906653001100918653001900929100000500948700001800953700002000971856004900991       2009                        eng d  a1364032100aEnergy, economics and environmental impacts of renewable energy systems0 aEnergy economics and environmental impacts of renewable energy s  cDecember  a2716–27210 v133 aThe renewable based electricity generation technologies were assessed against a range of sustainability indicators using data obtained from the literature. These indicators are cost of electricity generation, greenhouse gas emissions and energy pay-back time. All the three parameters were found to have a very wide range for each technology. For grading different renewable energy sources a new figure of merit has been proposed, linking greenhouse gas emissions, energy pay-back time and cost of electricity generated by these renewable energy sources. It has been found out that wind and small hydro are the most sustainable source for the electricity generation.10aclimate10aenergy10asustainability1 a1 aPrakash, Ravi1 aBhat, Inder, K.  uhttp://dx.doi.org/10.1016/j.rser.2009.05.00701720nas a2200217   4500008004100000022001400041245005400055210005400109260003800163300001400201490000600215520111400221653001201335653001901347653000801366100002201374700002501396700002401421700001901445856003801464       2009                        eng d  a1752-089400aTrends in the sources and sinks of carbon dioxide0 aTrends in the sources and sinks of carbon dioxide  bNature Publishing GroupcNovember  a831–8360 v23 aEfforts to control climate change require the stabilization of atmospheric CO2 concentrations. This can only be achieved through a drastic reduction of global CO2 emissions. Yet fossil fuel emissions increased by 29% between 2000 and 2008, in conjunction with increased contributions from emerging economies, from the production and international trade of goods and services, and from the use of coal as a fuel source. In contrast, emissions from land-use changes were nearly constant. Between 1959 and 2008, 43% of each year's CO2 emissions remained in the atmosphere on average; the rest was absorbed by carbon sinks on land and in the oceans. In the past 50 years, the fraction of CO2 emissions that remains in the atmosphere each year has likely increased, from about 40% to 45%, and models suggest that this trend was caused by a decrease in the uptake of CO2 by the carbon sinks in response to climate change and variability. Changes in the CO2 sinks are highly uncertain, but they could have a significant influence on future atmospheric CO2 levels. It is therefore crucial to reduce the uncertainties.10aclimate10aclimate-change10aco21 aLe Quere, Corinne1 aRaupach, Michael, R.1 aCanadell, Josep, G.1 aMarland, Gregg  uhttp://dx.doi.org/10.1038/ngeo68902500nas a2200253   4500008004100000245008400041210006900125260001300194300001800207490000800225520177100233653001702004653001202021653001902033653001702052653001102069653000902080100002002089700002102109700002302130700002602153700002102179856004602200       2009                        eng d00aNiches, models, and climate change: Assessing the assumptions and uncertainties0 aNiches models and climate change Assessing the assumptions and u  cNovember  a19729–197360 v1063 a10.1073/pnas.0901639106 As the rate and magnitude of climate change accelerate, understanding the consequences becomes increasingly important. Species distribution models (SDMs) based on current ecological niche constraints are used to project future species distributions. These models contain assumptions that add to the uncertainty in model projections stemming from the structure of the models, the algorithms used to translate niche associations into distributional probabilities, the quality and quantity of data, and mismatches between the scales of modeling and data. We illustrate the application of SDMs using two climate models and two distributional algorithms, together with information on distributional shifts in vegetation types, to project fine-scale future distributions of 60 California landbird species. Most species are projected to decrease in distribution by 2070. Changes in total species richness vary over the state, with large losses of species in some ” hotspots” of vulnerability. Differences in distributional shifts among species will change species co-occurrences, creating spatial variation in similarities between current and future assemblages. We use these analyses to consider how assumptions can be addressed and uncertainties reduced. SDMs can provide a useful way to incorporate future conditions into conservation and management practices and decisions, but the uncertainties of model projections must be balanced with the risks of taking the wrong actions or the costs of inaction. Doing this will require that the sources and magnitudes of uncertainty are documented, and that conservationists and resource managers be willing to act despite the uncertainties. The alternative, of ignoring the future, is not an option.10abiodiversity10aclimate10aclimate-change10aconservation10amodels10asdms1 aWiens, John, A.1 aStralberg, Diana1 aJongsomjit, Dennis1 aHowell, Christine, A.1 aSnyder, Mark, A.  uhttp://dx.doi.org/10.1073/pnas.0901639106