52 research outputs found

    A Human Development Framework for CO2 Reductions

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    Although developing countries are called to participate in CO2 emission reduction efforts to avoid dangerous climate change, the implications of proposed reduction schemes in human development standards of developing countries remain a matter of debate. We show the existence of a positive and time-dependent correlation between the Human Development Index (HDI) and per capita CO2 emissions from fossil fuel combustion. Employing this empirical relation, extrapolating the HDI, and using three population scenarios, the cumulative CO2 emissions necessary for developing countries to achieve particular HDI thresholds are assessed following a Development As Usual approach (DAU). If current demographic and development trends are maintained, we estimate that by 2050 around 85% of the world's population will live in countries with high HDI (above 0.8). In particular, 300Gt of cumulative CO2 emissions between 2000 and 2050 are estimated to be necessary for the development of 104 developing countries in the year 2000. This value represents between 20% to 30% of previously calculated CO2 budgets limiting global warming to 2{\deg}C. These constraints and results are incorporated into a CO2 reduction framework involving four domains of climate action for individual countries. The framework reserves a fair emission path for developing countries to proceed with their development by indexing country-dependent reduction rates proportional to the HDI in order to preserve the 2{\deg}C target after a particular development threshold is reached. Under this approach, global cumulative emissions by 2050 are estimated to range from 850 up to 1100Gt of CO2. These values are within the uncertainty range of emissions to limit global temperatures to 2{\deg}C.Comment: 14 pages, 7 figures, 1 tabl

    Monitoring and modelling landscape dynamics

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    International audienceChanges in land cover and land use are among the most pervasive and important sources of recent alterations of the Earth's land surface.This special issue also presents new directions in modelling landscape dynamics. Agent-based models have primarily been used to simulate local land use and land cover changes processes with a focus on decision making (Le 2008; Matthews et al. 2007; Parker et al. 2003; Bousquet and Le Page 2001)

    Influences of Forest Structure, Climate and Species Composition on Tree Mortality across the Eastern US

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    Few studies have quantified regional variation in tree mortality, or explored whether species compositional changes or within-species variation are responsible for regional patterns, despite the fact that mortality has direct effects on the dynamics of woody biomass, species composition, stand structure, wood production and forest response to climate change. Using Bayesian analysis of over 430,000 tree records from a large eastern US forest database we characterised tree mortality as a function of climate, soils, species and size (stem diameter). We found (1) mortality is U-shaped vs. stem diameter for all 21 species examined; (2) mortality is hump-shaped vs. plot basal area for most species; (3) geographical variation in mortality is substantial, and correlated with several environmental factors; and (4) individual species vary substantially from the combined average in the nature and magnitude of their mortality responses to environmental variation. Regional variation in mortality is therefore the product of variation in species composition combined with highly varied mortality-environment correlations within species. The results imply that variation in mortality is a crucial part of variation in the forest carbon cycle, such that including this variation in models of the global carbon cycle could significantly narrow uncertainty in climate change predictions

    Landscape history, time lags and drivers of change : urban natural grassland remnants in Potchefstroom, South Africa

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    The history of the landscape directly affects biotic assemblages, resulting in time lags in species response to disturbances. In highly fragmented environments, this phenomenon often causes extinction debts. However, few studies have been carried out in urban settings. To determine if there are time lags in the response of temperate natural grasslands to urbanization. Does it differ for indigenous species and for species indicative of disturbance and between woody and open grasslands? Do these time lags change over time? What are the potential landscape factors driving these changes? What are the corresponding vegetation changes? In 1995 and 2012 vegetation sampling was carried out in 43 urban grassland sites. We calculated six urbanization and landscape measures in a 500 m buffer area surrounding each site for 1938, 1961, 1970, 1994, 1999, 2006, and 2010. We used generalized linear models and model selection to determine which time period best predicted the contemporary species richness patterns. Woody grasslands showed time lags of 20-40 years. Contemporary open grassland communities were, generally, associated with more contemporary landscapes. Altitude and road network density of natural areas were the most frequent predictors of species richness. The importance of the predictors changed between the different models. Species richness, specifically, indigenous herbaceous species, declined from 1995 to 2012. The history of urbanization affects contemporary urban vegetation assemblages. This indicates potential extinction debts, which have important consequences for biodiversity conservation planning and sustainable future scenarios.Peer reviewe

    Quality-of-life assessment in dementia: the use of DEMQOL and DEMQOL-Proxy total scores

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    Purpose There is a need to determine whether health-related quality-of-life (HRQL) assessments in dementia capture what is important, to form a coherent basis for guiding research and clinical and policy decisions. This study investigated structural validity of HRQL assessments made using the DEMQOL system, with particular interest in studying domains that might be central to HRQL, and the external validity of these HRQL measurements. Methods HRQL of people with dementia was evaluated by 868 self-reports (DEMQOL) and 909 proxy reports (DEMQOL-Proxy) at a community memory service. Exploratory and confirmatory factor analyses (EFA and CFA) were conducted using bifactor models to investigate domains that might be central to general HRQL. Reliability of the general and specific factors measured by the bifactor models was examined using omega (?) and omega hierarchical (? h) coefficients. Multiple-indicators multiple-causes models were used to explore the external validity of these HRQL measurements in terms of their associations with other clinical assessments. Results Bifactor models showed adequate goodness of fit, supporting HRQL in dementia as a general construct that underlies a diverse range of health indicators. At the same time, additional factors were necessary to explain residual covariation of items within specific health domains identified from the literature. Based on these models, DEMQOL and DEMQOL-Proxy overall total scores showed excellent reliability (? h > 0.8). After accounting for common variance due to a general factor, subscale scores were less reliable (? h < 0.7) for informing on individual differences in specific HRQL domains. Depression was more strongly associated with general HRQL based on DEMQOL than on DEMQOL-Proxy (?0.55 vs ?0.22). Cognitive impairment had no reliable association with general HRQL based on DEMQOL or DEMQOL-Proxy. Conclusions The tenability of a bifactor model of HRQL in dementia suggests that it is possible to retain theoretical focus on the assessment of a general phenomenon, while exploring variation in specific HRQL domains for insights on what may lie at the ‘heart’ of HRQL for people with dementia. These data suggest that DEMQOL and DEMQOL-Proxy total scores are likely to be accurate measures of individual differences in HRQL, but that subscale scores should not be used. No specific domain was solely responsible for general HRQL at dementia diagnosis. Better HRQL was moderately associated with less depressive symptoms, but this was less apparent based on informant reports. HRQL was not associated with severity of cognitive impairment
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