| 1. |
- Kebede, A. S., et al.
(författare)
-
Direct and indirect impacts of climate and socio-economic change in Europe : a sensitivity analysis for key land- and water-based sectors
- 2015
-
Ingår i: Climatic Change. - : Springer Science and Business Media LLC. - 0165-0009 .- 1573-1480. ; 128:3-4, s. 261-277
-
Tidskriftsartikel (refereegranskat)abstract
- Integrated cross-sectoral impact assessments facilitate a comprehensive understanding of interdependencies and potential synergies, conflicts, and trade-offs between sectors under changing conditions. This paper presents a sensitivity analysis of a European integrated assessment model, the CLIMSAVE integrated assessment platform (IAP). The IAP incorporates important cross-sectoral linkages between six key European land- and water-based sectors: agriculture, biodiversity, flooding, forests, urban, and water. Using the IAP, we investigate the direct and indirect implications of a wide range of climatic and socioeconomic drivers to identify: (1) those sectors and regions most sensitive to future changes, (2) the mechanisms and directions of sensitivity (direct/indirect and positive/negative), (3) the form and magnitudes of sensitivity (linear/non-linear and strong/weak/insignificant), and (4) the relative importance of the key drivers across sectors and regions. The results are complex. Most sectors are either directly or indirectly sensitive to a large number of drivers (more than 18 out of 24 drivers considered). Over twelve of these drivers have indirect impacts on biodiversity, forests, land use diversity, and water, while only four drivers have indirect effects on flooding. In contrast, for the urban sector all the drivers are direct. Moreover, most of the driver indicator relationships are non-linear, and hence there is the potential for ‘surprises’. This highlights the importance of considering cross-sectoral interactions in future impact assessments. Such systematic analysis provides improved information for decision-makers to formulate appropriate adaptation policies to maximise benefits and minimise unintended consequences.
|
|
| 2. |
- Lehsten, Veiko, et al.
(författare)
-
Fuel fragmentation and fire size distributions in managed and unmanaged boreal forests in the province of Saskatchewan, Canada
- 2016
-
Ingår i: Forest Ecology and Management. - : Elsevier BV. - 0378-1127. ; 376, s. 148-157
-
Tidskriftsartikel (refereegranskat)abstract
- Forest fires are an important disturbance factor of boreal forests, annually burning about 0.5% of the forested area in Canada. Wildfire regimes are influenced by climate and a number of studies project an increase in wildfire activity with climate change. Another factor influencing wildfires is human intervention (fire suppression), and one factor that has rarely been assessed is fuel fragmentation. Studies evaluating the effect of forest fire suppression concluded that in areas with strong suppression effort the burned area as well as the fire size decreased.Here we evaluate wildfire distributions over the last three decades for two areas that differ mainly in their level of forest management and fire suppression: the Boreal Shield (unmanaged) and the Boreal Plain regions (intensively managed) in the Canadian Province of Saskatchewan.We calculate a fuel fragmentation index and relate fire sizes and burned areas to fire weather. We use the concept of the characteristic fire size (CFS); hence we analyze how much burned area is contributed to the total burned area per fire size class.Both areas show a uni-modal distribution of the CFS, indicating that the majority of burned area was contributed by medium sized fires (Boreal Shield 6.39 · 104 ha, the Boreal Plain 8.79 · 104 ha). Burned area as well as fuel fragmentation is lower in the managed forest compared to the unmanaged area.The fuel fragmentation index constantly increased since the 1980s in both regions. Despite the large efforts of fire suppression in the Boreal Plains, the CFS is slightly larger in this managed region. Neither the burned area nor the fire size could be linked statistically to the weather conditions, at the time of the fire (using the Canadian Fire Weather Index).We argue that the high fragmentation over the last decades have decreased the burned area. The slightly higher characteristic fire size in the managed area might be explained by the considerably lower fragmentation, counteracting fire suppression efforts. Fuel fragmentation is likely to decrease over the next decades due re-growth. Though a strong link between fire weather and burned area at the fine scale of this study could not be detected we expect that a decrease in fragmentation in combination with an increase in fire prone weather conditions (as expected for the future) might increase the risk of large fires in both areas. We suggest that future fire risk analysis should include an assessment of the effect of fuel fragmentation.
|
|
| 3. |
|
|
| 4. |
- Sallaba, Florian, et al.
(författare)
-
A rapid NPP meta-model for current and future climate and CO2 scenarios in Europe
- 2015
-
Ingår i: Ecological Modelling. - : Elsevier BV. - 0304-3800. ; 302, s. 29-41
-
Tidskriftsartikel (refereegranskat)abstract
- Net primary production (NPP) is the difference in gross photosynthetic assimilation of carbon and carbon loss due to autotrophic respiration, and is an important ecosystem variable that facilitates understanding of climate change impacts on terrestrial ecosystem productivity and ecosystem services. The aim of this study is to rapidly estimate the NPP of European potential natural vegetation for current and future climate and carbon-dioxide scenarios (CO2). A NPP meta-model was developed and evaluated based on the dynamic global vegetation model LPJ-GUESS. LPJ-GUESS was used to simulate NPP under current and future climate change as well as CO2 scenarios. The NPP dataset produced from these simulations was used to determine the empirical relationships between NPP and driving climate variables (maximum temperature, minimum temperature, summer precipitation, winter precipitation) along with CO2 concentration. The climate variables’ relationships were combined in a synergistic function including CO2 relationships to estimate NPP. The meta-model was compared with randomly chosen NPP data originated from LPJ-GUESS. Furthermore, the meta-model's performance was evaluated on the European level with LPJ-GUESS simulations. The meta-model performed reasonably well with regard to estimating total NPP while performances for species-specific NPP were poor. For total NPP, the meta-model generated an agreement of R2 = 0.68 and RMSE = 0.06 at CO2 = 350 ppm in comparison to LPJ-GUESS simulations. The consideration of all CO2 concentration scenarios yielded R2 = 0.62 and RMSE = 0.08. A rapid synergistic approach is suggested that enables interactions between climate variables and their intra-annual variability to estimate NPP. This is a useful alternative to traditional empirical models that control NPP with the most limiting climate variable. The meta-model performed reasonably well for estimating total NPP for future climate change and CO2 scenarios. However, species-specific NPP estimates were unsatisfactory, implying that the synergistic approach cannot account for species specific dynamics. Comparison between the meta-model and LPJ-GUESS at the European scale showed that additional environmental variables (e.g. solar radiation) would be necessary to improve the meta-model.
|
|
| 5. |
- Sallaba, Florian
(författare)
-
Biophysical and Human Controls of Land Productivity under Global Change : Development and Demonstration of Parsimonious Modelling Techniques
- 2016
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Net primary production (NPP) serves as an indicator for plant-based resources such as food, timber and biofuel for human appropriation. It is defined by the annual production of plant matter and is mainly controlled by climate and human activities. Climate change in combination with human activities is altering NPP. As the controls of NPP are expected to further change in the future, it is vital to investigate alterations in NPP and their magnitudes. The impacts of climate change and human activities on NPP can be explored in integrated assessment (IA) frameworks, where sectoral models are coupled and interact rapidly. For such frameworks, parsimonious models are desired because they enable rapid estimates and facilitate easy model coupling for explorations of multiple global change scenarios (i.e. large volumes of data). This thesis aims to advance parsimonious modelling techniques for quantifying current and future NPP on land. This is accomplished by developing and testing rapid models that facilitate easy model coupling to explore the impacts of multiple global change scenarios on NPP. The model development is based on the meta-modelling concept, which can be applied to simplify the dynamic vegetation model LPJ-GUESS in a parsimonious model. For this, multiple climate change and [CO2] perturbations are applied to LPJ-GUESS to simulate NPP. The NPP data are then used to define biophysically motivated relationships between NPP and the driving climate variables along with [CO2]. The relationships are then combined in a synergistic function – the meta-model. Thereafter, the meta-models are assessed for their performance in estimating NPP by comparing them to LPJ-GUESS NPP simulations, to independent field observations and to NPP experiments under enriched [CO2] on biome level. The results provide confidence in the modelled NPP estimates for the most productive biomes, which are important for global quantifications of NPP. The meta-models capture NPP enhancement under enhanced [CO2] adequately in the majority of the studied biomes. Finally, the NPP meta-models are coupled with other sectoral models in two IA modelling-frameworks in order to explore the impacts of global change on ecosystem indicators. The first framework enables an IA of climate change impacts and vulnerabilities for a range of sectors on the European level. This thesis conducts a sensitivity analysis on the effects of climatic and socio-economic change drivers on model outputs related to key sectors. This provides better quantification and increased understanding of the complex relationships between input and output variables in IA modelling-frameworks. The second framework addresses the NPP supply-demand balance in the Sahel region by coupling two sectoral models in order to analyze the timings and geographies of NPP shortfalls in the 21st century Sahel under global change. The results show consistent regional NPP shortfalls in the Sahel for the majority of global change scenarios.Overall, the parsimonious modelling techniques developed in this thesis contribute with rapid NPP estimates on the biome and global scale. BME NPP estimates agree reasonably well with NPP observations in the majority of biomes (especially in the most productive biomes). This thesis demonstrates that NPP meta-models facilitate easy model coupling for exploring the impacts of global change on human-environmental systems in IA modelling-frameworks.
|
|
| 6. |
- Sallaba, Florian, et al.
(författare)
-
Future supply and demand of net primary production in the Sahel
- 2017
-
Ingår i: Earth System Dynamics. - : Copernicus GmbH. - 2190-4979 .- 2190-4987. ; 8:4, s. 1191-1221
-
Tidskriftsartikel (refereegranskat)abstract
- In the 21st century, climate change in combination with increasing demand, mainly from population growth, will exert greater pressure on the ecosystems of the Sahel to supply food and feed resources. The balance between supply and demand, defined as the annual biomass required for human consumption, serves as a key metric for quantifying basic resource shortfalls over broad regions.Here we apply an exploratory modelling framework to analyse the variations in the timing and geography of different NPP (net primary production) supply-demand scenarios, with distinct assumptions determining supply and demand, for the 21st century Sahel. We achieve this by coupling a simple NPP supply model forced with projections from four representative concentration pathways with a global, reduced-complexity demand model driven by socio-economic data and assumptions derived from five shared socio-economic pathways.For the scenario that deviates least from current socio-economic and climate trends, we find that per capita NPP begins to outstrip supply in the 2040s, while by 2050 half the countries in the Sahel experience NPP shortfalls. We also find that despite variations in the timing of the onset of NPP shortfalls, demand cannot consistently be met across the majority of scenarios. Moreover, large between-country variations are shown across the scenarios, in which by the year 2050 some countries consistently experience shortage or surplus, while others shift from surplus to shortage. At the local level (i.e. grid cell), hotspots of total NPP shortfall consistently occur in the same locations across all scenarios but vary in size and magnitude. These hotspots are linked to population density and high demand. For all scenarios, total simulated NPP supply doubles by 2050 but is outpaced by increasing demand due to a combination of population growth and the adoption of diets rich in animal products. Finally, variations in the timing of the onset and end of supply shortfalls stem from the assumptions that underpin the shared socio-economic pathways rather than the representative concentration pathways.Our results suggest that the UN sustainable development goals for eradicating hunger are at high risk for failure. This emphasizes the importance of policy interventions such as the implementation of sustainable and healthy diets, family planning, reducing yield gaps, and encouraging the transfer of resources to impoverished areas via trade relations.
|
|
