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- 2019
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Apraiz Larrucea, Itxaso, 1980-
(författare)
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Development and application of a proteomic approach to the assessment of pollution in the marine environment
- 2009
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Today, assessment of the health of coastal waters is recognized as being important for both the conservation of nature and well-being of humans. Anthropogenic pollution has been the focus of extensive research for some time and a variety of programs for the monitoring and assessment of environmental pollution have been developed. Determination of the levels of pollution in sensitive ‘sentinels’ such as mussels, allows monitoring of these levels in a given area over a prolonged period of time. Furthermore, the biological effects of pollution are reflected in a series of biomarkers, none of which provides a general picture of the sentinel’s state of health and all of which are individually specific for certain pollutants and influenced by both biotic and abiotic factors. In an attempt to improve biomonitoring of marine pollution, we have developed two proteomic approaches here. In the first portion of the thesis, a proteomic analysis was performed on peroxisomes isolated from mussels exposed either to one of three model anthropogenic pollutants, or two different types of crude oil, or from mussels exposed to the Prestige oil spill. Application of two-dimensional electrophoresis (2-DE) provided protein expression signatures (PES) for exposure to these different pollutants.Furthermore, several individual protein components of these PES could be putatively identified. In the second portion of this work, such analysis of subproteomes was developed further in order to improve the applicability of this approach to biomonitoring. A simple fractionation procedure in combination with liquid chromatography and 2-DE provided samples from mussels residing in different regions of a pollution gradient around the harbor of Gothenburg, as well as from mussels exposed to two types of fuel oil similar to that of the Prestige that were suitable for environmental proteomics. In addition, we constructed a model for this approach that can be cross-validated in the future and applied to assess sources of fuel oil pollution in connection with biomonitoring programs.
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| 4. |
- Hantson, Stijn, et al.
(författare)
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Quantitative assessment of fire and vegetation properties in simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project
- 2020
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Ingår i: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 13:7, s. 3299-3318
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Tidskriftsartikel (refereegranskat)abstract
- Global fire-vegetation models are widely used to assess impacts of environmental change on fire regimes and the carbon cycle and to infer relationships between climate, land use and fire. However, differences in model structure and parameterizations, in both the vegetation and fire components of these models, could influence overall model performance, and to date there has been limited evaluation of how well different models represent various aspects of fire regimes. The Fire Model Intercomparison Project (FireMIP) is coordinating the evaluation of state-of-the-art global fire models, in order to improve projections of fire characteristics and fire impacts on ecosystems and human societies in the context of global environmental change. Here we perform a systematic evaluation of historical simulations made by nine FireMIP models to quantify their ability to reproduce a range of fire and vegetation benchmarks. The FireMIP models simulate a wide range in global annual total burnt area (39-536 Mha) and global annual fire carbon emission (0.91-4.75 Pg C yr-1) for modern conditions (2002-2012), but most of the range in burnt area is within observational uncertainty (345-468 Mha). Benchmarking scores indicate that seven out of nine FireMIP models are able to represent the spatial pattern in burnt area. The models also reproduce the seasonality in burnt area reasonably well but struggle to simulate fire season length and are largely unable to represent interannual variations in burnt area. However, models that represent cropland fires see improved simulation of fire seasonality in the Northern Hemisphere. The three FireMIP models which explicitly simulate individual fires are able to reproduce the spatial pattern in number of fires, but fire sizes are too small in key regions, and this results in an underestimation of burnt area. The correct representation of spatial and seasonal patterns in vegetation appears to correlate with a better representation of burnt area. The two older fire models included in the FireMIP ensemble (LPJ-GUESS-GlobFIRM, MC2) clearly perform less well globally than other models, but it is difficult to distinguish between the remaining ensemble members; some of these models are better at representing certain aspects of the fire regime; none clearly outperforms all other models across the full range of variables assessed.
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- Rabin, Sam S., et al.
(författare)
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The Fire Modeling Intercomparison Project (FireMIP), phase 1 : Experimental and analytical protocols with detailed model descriptions
- 2017
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Ingår i: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 10:3, s. 1175-1197
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Tidskriftsartikel (refereegranskat)abstract
- The important role of fire in regulating vegetation community composition and contributions to emissions of greenhouse gases and aerosols make it a critical component of dynamic global vegetation models and Earth system models. Over 2 decades of development, a wide variety of model structures and mechanisms have been designed and incorporated into global fire models, which have been linked to different vegetation models. However, there has not yet been a systematic examination of how these different strategies contribute to model performance. Here we describe the structure of the first phase of the Fire Model Intercomparison Project (FireMIP), which for the first time seeks to systematically compare a number of models. By combining a standardized set of input data and model experiments with a rigorous comparison of model outputs to each other and to observations, we will improve the understanding of what drives vegetation fire, how it can best be simulated, and what new or improved observational data could allow better constraints on model behavior. In this paper, we introduce the fire models used in the first phase of FireMIP, the simulation protocols applied, and the benchmarking system used to evaluate the models. We have also created supplementary tables that describe, in thorough mathematical detail, the structure of each model.
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