A process-based fire regime model (SPITFIRE) has been developed, coupled with ecosystem dynamics in the LPJ Dynamic Global Vegetation Model, and used to explore fire regimes and the current impact of fire on the terrestrial carbon cycle and associated emissions of trace atmospheric constituents. The model estimates an average release of 2.24 Pg C yr(-1) as CO2 from biomass burning during the 1980s and 1990s. Comparison with observed active fire counts shows that the model reproduces where fire occurs and can mimic broad geographic patterns in the peak fire season, although the predicted peak is 1-2 months late in some regions. Modelled fire season length is generally overestimated by about one month, but shows a realistic pattern of differences among biomes. Comparisons with remotely sensed burnt-area products indicate that the model reproduces broad geographic patterns of annual fractional burnt area over most regions, including the boreal forest, although interannual variability in the boreal zone is underestimated
Abstract. A process-based fire regime model (SPITFIRE) has been developed, coupled with ecosystem dynamics in the LPJ Dynamic Global Vegetation Model, and used to explore spatial and temporal patterns of fire regimes and the current impact of fire on the terrestrial carbon cycle and associated emissions of trace atmospheric constituents. The model estimates an average release of 2.24 Pg C yr−1 as CO2 from biomass burning during the 1980s and 1990s. Comparison with observed active fire counts shows that the model reproduces where fire occurs and can mimic broad geographic patterns in the peak fire season, although the predicted peak is 1–2 months late in some regions. Modelled fire season length is generally overestimated by about one month, but shows a realistic pattern of differences among biomes. Comparisons with remotely sensed burnt-area products indicate that the model reproduces broad geographic patterns of annual fractional burnt area over most regions, including the boreal forest, although interannual variability in the boreal zone is underestimated. Overall SPITFIRE produces realistic simulations of spatial and temporal patterns of fire under modern conditions and of the current impact of fire on the terrestrial carbon cycle and associated emissions of trace greenhouse gases and aerosols.
a b s t r a c tCities are complex ecosystems affected by social, economic, environmental, and cultural factors. The problem of attaining urban sustainable development is thus an important challenge. The development of evaluation indicators and a method for assessing the status of urban sustainable development will be required to support urban ecological planning, construction, and management. By using Jining City in China's Shandong Province as a case study, the authors developed a system of 52 indicators of urban sustainable development that address economic growth and efficiency, ecological and infrastructural construction, environmental protection, social and welfare progress. The authors developed a Full Permutation Polygon Synthetic Indicator method to evaluate the capacity for urban sustainable development at different times during the next two decades. The results of our research indicate that the value of a synthetic indicator for sustainable development of Jining City was 0.24 in 2004, which indicates a low level of sustainable development. According to the ecological planning of Jining City (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020), the indicator will improve to 0.45 in 2007 and 0.62 in 2010, indicating significant improvements in sustainable development, and will reach 0.90 in 2020, indicating excellent potential for sustainable development. The Full Permutation Polygon Synthetic Indicator method provides a comprehensive, intuitive approach that reflects the system integration principle that the whole can be more than the sum of its parts. The approach thus provides a promising basis for decision-making to support urban sustainable development and monitoring of the effectiveness of these decisions.
The Last Glacial Maximum (LGM, and the Holocene Optimum (HO, c. 9-5 ka) were characterized by cold-dry and warm-wet climates respectively in the recently geological Earth. How Chinese deserts and sand fields responded to these distinctive climatic changes is still not clear, however. To reconstruct environments of the deserts and sand fields during the LGM and HO is helpful to understand the forcing mechanisms of environment change in this arid region, and to test paleoclimatic modeling results. Through our long-term field and laboratory investigations, 400 optically stimulated luminescence (OSL) ages and more than 100 depositional records in the Chinese deserts and sand fields were obtained; on the basis of these data, we reconstruct spatial distributions of the deserts and sand fields during the LGM and HO. Our results show that the sand fields of Mu Us, Hunshandake, Horqin and Hulun Buir in northern and northeastern China had expanded 25%, 37%, 38% and 270%, respectively, during the LGM; the sand fields of Gonghe in the northeastern Qinghai-Tibetan Plateau had expanded 20%, and the deserts of Badain Jaran, Tengger in central northern China had expanded 39% and 29% separately during the LGM; the deserts of Taklimakan, Gurbantünggüt and Kumtag in northwestern China had expanded 10%-20% respectively, compared to their modern areas. On the other hand, all of the sand fields were nearly completely covered by vegetation during the HO; the deserts in northwestern and central northern China were reduced by around 5%-20% in area during this time. Lakes in this arid region were probably expanded during the HO but this conclusion needs more investigation. Compared with the geological distributions of deserts and sand fields, human activity has clearly changed (expanded) the area of active sand dunes at the present time. Our observations show that environmental conditions of Chinese deserts and sand fields are controlled by regional climate together with human activity. deserts and sand fields in China, Last Glacial Maximum, Holocene Optimum, OSL dating, active sand dunes Citation:
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