Academic literature on the topic 'Terrestrial biosphere model'

Abstract. Terrestrial biosphere models show large uncertainties when simulating carbon and water cycles, and reducing these uncertainties is a priority for developing more accurate estimates of both terrestrial ecosystem statuses and future climate changes. To reduce uncertainties and improve the understanding of these carbon budgets, we investigated the ability of flux datasets to improve model simulations and reduce variabilities among multi-model outputs of terrestrial biosphere models in Japan. Using 9 terrestrial biosphere models (Support Vector Machine-based regressions, TOPS, CASA, VISIT, Biome-BGC, DAYCENT, SEIB, LPJ, and TRIFFID), we conducted two simulations: (1) point simulations at four flux sites in Japan and (2) spatial simulations for Japan with a default model (based on original settings) and an improved model (based on calibration using flux observations). Generally, models using default model settings showed large deviations in model outputs from observation with large model-by-model variability. However, after we calibrated the model parameters using flux observations (GPP, RE and NEP), most models successfully simulated seasonal variations in the carbon cycle, with less variability among models. We also found that interannual variations in the carbon cycle are mostly consistent among models and observations. Spatial analysis also showed a large reduction in the variability among model outputs, and model calibration using flux observations significantly improved the model outputs. These results show that to reduce uncertainties among terrestrial biosphere models, we need to conduct careful validation and calibration with available flux observations. Flux observation data significantly improved terrestrial biosphere models, not only on a point scale but also on spatial scales.

Abstract. Terrestrial biosphere models show large differences when simulating carbon and water cycles, and reducing these differences is a priority for developing more accurate estimates of the condition of terrestrial ecosystems and future climate change. To reduce uncertainties and improve the understanding of their carbon budgets, we investigated the utility of the eddy flux datasets to improve model simulations and reduce variabilities among multi-model outputs of terrestrial biosphere models in Japan. Using 9 terrestrial biosphere models (Support Vector Machine – based regressions, TOPS, CASA, VISIT, Biome-BGC, DAYCENT, SEIB, LPJ, and TRIFFID), we conducted two simulations: (1) point simulations at four eddy flux sites in Japan and (2) spatial simulations for Japan with a default model (based on original settings) and a modified model (based on model parameter tuning using eddy flux data). Generally, models using default model settings showed large deviations in model outputs from observation with large model-by-model variability. However, after we calibrated the model parameters using eddy flux data (GPP, RE and NEP), most models successfully simulated seasonal variations in the carbon cycle, with less variability among models. We also found that interannual variations in the carbon cycle are mostly consistent among models and observations. Spatial analysis also showed a large reduction in the variability among model outputs. This study demonstrated that careful validation and calibration of models with available eddy flux data reduced model-by-model differences. Yet, site history, analysis of model structure changes, and more objective procedure of model calibration should be included in the further analysis.

Terrestrial biosphere models are important tools for diagnosing both the current state of the terrestrial carbon cycle and forecasting terrestrial ecosystem responses to global change. While there are a number of ongoing assessments of the short-term predictive capabilities of terrestrial biosphere models using flux-tower measurements, to date there have been relatively few assessments of their ability to predict longer term, decadal-scale biomass dynamics. Here, we present the results of a regional-scale evaluation of the Ecosystem Demography version 2 (ED2)-structured terrestrial biosphere model, evaluating the model's predictions against forest inventory measurements for the northeast USA and Quebec from 1985 to 1995. Simulations were conducted using a default parametrization, which used parameter values from the literature, and a constrained model parametrization, which had been developed by constraining the model's predictions against 2 years of measurements from a single site, Harvard Forest (42.5° N, 72.1° W). The analysis shows that the constrained model parametrization offered marked improvements over the default model formulation, capturing large-scale variation in patterns of biomass dynamics despite marked differences in climate forcing, land-use history and species-composition across the region. These results imply that data-constrained parametrizations of structured biosphere models such as ED2 can be successfully used for regional-scale ecosystem prediction and forecasting. We also assess the model's ability to capture sub-grid scale heterogeneity in the dynamics of biomass growth and mortality of different sizes and types of trees, and then discuss the implications of these analyses for further reducing the remaining biases in the model's predictions.

AbstractThe biosignatures of life on Earth do not remain static, but change considerably over the planet's habitable lifetime. Earth's future biosphere, much like that of the early Earth, will consist of predominantly unicellular microorganisms due to the increased hostility of environmental conditions caused by the Sun as it enters the late stage of its main sequence evolution. Building on previous work, the productivity of the biosphere is evaluated during different stages of biosphere decline between 1 and 2.8 Gyr from present. A simple atmosphere–biosphere interaction model is used to estimate the atmospheric biomarker gas abundances at each stage and to assess the likelihood of remotely detecting the presence of life in low-productivity, microbial biospheres, putting an upper limit on the lifetime of Earth's remotely detectable biosignatures. Other potential biosignatures such as leaf reflectance and cloud cover are discussed.

Abstract. The terrestrial biosphere and atmospheric chemistry interact through multiple feedbacks, but the models of vegetation and chemistry are developed separately. In this study, the Yale Interactive terrestrial Biosphere (YIBs) model, a dynamic vegetation model with biogeochemical processes, is implemented into the Chemical Transport Model GEOS-Chem (GC) version 12.0.0. Within this GC-YIBs framework, leaf area index (LAI) and canopy stomatal conductance dynamically predicted by YIBs are used for dry deposition calculation in GEOS-Chem. In turn, the simulated surface ozone (O3) by GEOS-Chem affect plant photosynthesis and biophysics in YIBs. The updated stomatal conductance and LAI improve the simulated O3 dry deposition velocity and its temporal variability for major tree species. For daytime dry deposition velocities, the model-to-observation correlation increases from 0.69 to 0.76, while the normalized mean error (NME) decreases from 30.5 % to 26.9 % using the GC-YIBs model. For the diurnal cycle, the NMEs decrease by 9.1 % for Amazon forests, 6.8 % for coniferous forests, and 7.9 % for deciduous forests using the GC-YIBs model. Furthermore, we quantify the damaging effects of O3 on vegetation and find a global reduction of annual gross primary productivity by 1.5 %–3.6 %, with regional extremes of 10.9 %–14.1 % in the eastern USA and eastern China. The online GC-YIBs model provides a useful tool for discerning the complex feedbacks between atmospheric chemistry and the terrestrial biosphere under global change.

Abstract. Land surface models are excellent tools for studying how climate change and land use affect surface hydrology. However, in order to assess the impacts of Earth processes on river flows, simulated changes in runoff need to be routed through the landscape. In this technical note, we describe the integration of the Ecosystem Demography (ED2) model with a hydrological routing scheme. The purpose of the study was to create a tool capable of incorporating to hydrological predictions the terrestrial ecosystem responses to climate, carbon dioxide, and land-use change, as simulated with terrestrial biosphere models. The resulting ED2+R model calculates the lateral routing of surface and subsurface runoff resulting from the terrestrial biosphere models' vertical water balance in order to determine spatiotemporal patterns of river flows within the simulated region. We evaluated the ED2+R model in the Tapajós, a 476 674 km2 river basin in the southeastern Amazon, Brazil. The results showed that the integration of ED2 with the lateral routing scheme results in an adequate representation (Nash–Sutcliffe efficiency up to 0.76, Kling–Gupta efficiency up to 0.86, Pearson's R up to 0.88, and volume ratio up to 1.06) of daily to decadal river flow dynamics in the Tapajós. These results are a consistent step forward with respect to the no river representation common among terrestrial biosphere models, such as the initial version of ED2.

The carbon cycle of the terrestrial biosphere plays a vital role in controlling the global carbon balance and, consequently, climate change. Reliably modeled CO2 fluxes between the terrestrial biosphere and the atmosphere are necessary in projections of policy strategies aiming at constraining carbon emissions and of future climate change. In this study, SMOS (Soil Moisture and Ocean Salinity) L3 soil moisture and JRC-TIP FAPAR (Joint Research Centre—Two-stream Inversion Package Fraction of Absorbed Photosynthetically Active Radiation) data with respective original resolutions at 10 sites were used to constrain the process-based terrestrial biosphere model, BETHY (Biosphere, Energy Transfer and Hydrology), using the carbon cycle data assimilation system (CCDAS). We find that simultaneous assimilation of these two datasets jointly at all 10 sites yields a set of model parameters that achieve the best model performance in terms of independent observations of carbon fluxes as well as soil moisture. Assimilation in a single-site mode or using only a single dataset tends to over-adjust related parameters and deteriorates the model performance of a number of processes. The optimized parameter set derived from multi-site assimilation with soil moisture and FAPAR also improves, when applied at global scale simulations, the model-data fit against atmospheric CO2. This study demonstrates the potential of satellite-derived soil moisture and FAPAR when assimilated simultaneously in a model of the terrestrial carbon cycle to constrain terrestrial carbon fluxes. It furthermore shows that assimilation of soil moisture data helps to identity structural problems in the underlying model, i.e., missing management processes at sites covered by crops and grasslands.

Abstract. A new global synthesis and biomization of long (> 40 kyr) pollen-data records is presented and used with simulations from the HadCM3 and FAMOUS climate models and the BIOME4 vegetation model to analyse the dynamics of the global terrestrial biosphere and carbon storage over the last glacial–interglacial cycle. Simulated biome distributions using BIOME4 driven by HadCM3 and FAMOUS at the global scale over time generally agree well with those inferred from pollen data. Global average areas of grassland and dry shrubland, desert, and tundra biomes show large-scale increases during the Last Glacial Maximum, between ca. 64 and 74 ka BP and cool substages of Marine Isotope Stage 5, at the expense of the tropical forest, warm-temperate forest, and temperate forest biomes. These changes are reflected in BIOME4 simulations of global net primary productivity, showing good agreement between the two models. Such changes are likely to affect terrestrial carbon storage, which in turn influences the stable carbon isotopic composition of seawater as terrestrial carbon is depleted in 13C.

Severe drought plays a critical role in altering the magnitude and interannual variability of the net terrestrial carbon sink. Drought events immediately decrease net primary production (NPP), and drought length and magnitude tend to enhance this negative impact. However, satellite and in-situ measurements have also indicated that ecosystem recovery from extreme drought can extend several years beyond the return to normal climate conditions. If an ecosystem’s drought recovery time exceeds the time interval between successive droughts, these legacy effects may reinforce the impact of future drought. Since the frequency and severity of extreme climate events are expected to increase with climate change, both the immediate and prolonged impact of drought may contribute to amplified climate warming by decreasing the strength of the land carbon sink. However, it is unknown whether terrestrial biosphere models capture the impact of drought legacy effects on carbon stocks and cycling. Using a suite of twelve land surface models from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we assessed model ability to simulate drought legacy effects by analyzing the modeled NPP response to drought events across forested regions of the US and Europe. We found that modeled drought legacy effects last about one year (2% reduction in NPP), with complete NPP recovery in the second post-drought year. Since observations suggest that legacy effects extend up to four years post-drought, with a 9% growth reduction in the first post-drought year, models appear to underestimate both the timescales and magnitude of drought legacy effects. We further explored vegetation sensitivity to climate anomalies through global, time-lagged correlation analysis of NPP and climatic water deficit. Regional differences in the lag time between climate anomaly and NPP response are prevalent, but low sensitivities (correlations) characterize the entire region. Significant correlations coincided with characteristic lag times of 0 to 6 months, indicating relatively immediate NPP response to moisture anomalies. Model ability to accurately simulate vegetation’s response to drought and sensitivity to climate anomalies is necessary in order to produce reliable forecasts of land carbon sink strength and, consequently, to predict the rate at which climate change will progress in the future. Thus, the discrepancies between observed and simulated vegetation recovery from drought points to a potential critical model deficiency.

At present, carbon sequestration in terrestrial ecosystems slows the growth rate of atmospheric CO₂ concentrations, and thereby reduces the impact of anthropogenic fossil fuel emissions on the climate system. Changes in climate and land use affect terrestrial biosphere structure and functioning at present, and will likely impact on the terrestrial carbon balance during the coming decades - potentially providing a positive feedback to the climate system due to soil carbon releases under a warmer climate. Quantifying changes, and the associated uncertainties, in regional terrestrial carbon budgets resulting from these effects is relevant for the scientific understanding of the Earth system and for long-term climate mitigation strategies.

A model describing the relevant processes that govern the terrestrial carbon cycle is a necessary tool to project regional carbon budgets into the future. This study (1) provides an extensive evaluation of the parameter-based uncertainty in model results of a leading terrestrial biosphere model, the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM), against a range of observations and under climate change, thereby complementing existing studies on other aspects of model uncertainty; (2) evaluates different hypotheses to explain the age-related decline in forest growth, both from theoretical and experimental evidence, and introduces the most promising hypothesis into the model; (3) demonstrates how forest statistics can be successfully integrated with process-based modelling to provide long-term constraints on regional-scale forest carbon budget estimates for a European forest case-study; and (4) elucidates the combined effects of land-use and climate changes on the present-day and future terrestrial carbon balance over Europe for four illustrative scenarios - implemented by four general circulation models - using a comprehensive description of different land-use types within the framework of LPJ-DGVM.

This study presents a way to assess and reduce uncertainty in process-based terrestrial carbon estimates on a regional scale. The results of this study demonstrate that simulated present-day land-atmosphere carbon fluxes are relatively well constrained, despite considerable uncertainty in modelled net primary production. Process-based terrestrial modelling and forest statistics are successfully combined to improve model-based estimates of vegetation carbon stocks and their change over time. Application of the advanced model for 77 European provinces shows that model-based estimates of biomass development with stand age compare favourably with forest inventory-based estimates for different tree species. Driven by historic changes in climate, atmospheric CO₂ concentration, forest area and wood demand between 1948 and 2000, the model predicts European-scale, present-day age structure of forests, ratio of biomass removals to increment, and vegetation carbon sequestration rates that are consistent with inventory-based estimates. Alternative scenarios of climate and land-use change in the 21^st century suggest carbon sequestration in the European terrestrial biosphere during the coming decades will likely be on magnitudes relevant to climate mitigation strategies. However, the uptake rates are small in comparison to the European emissions from fossil fuel combustion, and will likely decline towards the end of the century. Uncertainty in climate change projections is a key driver for uncertainty in simulated land-atmosphere carbon fluxes and needs to be accounted for in mitigation studies of the terrestrial biosphere.

Kohlenstoffspeicherung in terrestrischen Ökosystemen reduziert derzeit die Wirkung anthropogener CO₂-Emissionen auf das Klimasystem, indem sie die Wachstumsrate der atmosphärischer CO₂-Konzentration verlangsamt. Die heutige terrestrische Kohlenstoffbilanz wird wesentlich von Klima- und Landnutzungsänderungen beeinflusst. Diese Einflussfaktoren werden sich auch in den kommenden Dekaden auf die terrestrische Biosphäre auswirken, und dabei möglicherweise zu einer positiven Rückkopplung zwischen Biosphäre und Klimasystem aufgrund von starken Bodenkohlenstoffverlusten in einem wärmeren Klima führen. Quantitative Abschätzungen der Wirkung dieser Einflussfaktoren - sowie der mit ihnen verbundenen Unsicherheit - auf die terrestrische Kohlenstoffbilanz sind daher sowohl für das Verständnis des Erdsystems, als auch für eine langfristig angelegte Klimaschutzpolitik relevant.

Um regionale Kohlenstoffbilanzen in die Zukunft zu projizieren, sind Modelle erforderlich, die die wesentlichen Prozesse des terrestrischen Kohlenstoffkreislaufes beschreiben. Die vorliegende Arbeit (1) analysiert die parameterbasierte Unsicherheit in Modellergebnissen eines der führenden globalen terrestrischen Ökosystemmodelle (LPJ-DGVM) im Vergleich mit unterschiedlichen ökosystemaren Messgrößen, sowie unter Klimawandelprojektionen, und erweitert damit bereits vorliegende Studien zu anderen Aspekten der Modelunsicherheit; (2) diskutiert unter theoretischen und experimentellen Aspekten verschiedene Hypothesen über die altersbedingte Abnahme des Waldwachstums, und implementiert die vielversprechenste Hypothese in das Model; (3) zeigt für eine europäische Fallstudie, wie Waldbestandsstatistiken erfolgreich für eine verbesserte Abschätzung von regionalen Kohlenstoffbilanzen in Wäldern durch prozessbasierten Modelle angewandt werden können; (4) untersucht die Auswirkung möglicher zukünftiger Klima- und Landnutzungsänderungen auf die europäische Kohlenstoffbilanz anhand von vier verschiedenen illustrativen Szenarien, jeweils unter Berücksichtigung von Klimawandelprojektionen vier verschiedener Klimamodelle. Eine erweiterte Version von LPJ-DGVM findet hierfür Anwendung, die eine umfassende Beschreibung der Hauptlandnutzungstypen beinhaltet.

Die vorliegende Arbeit stellt einen Ansatz vor, um Unsicherheiten in der prozessbasierten Abschätzung von terrestrischen Kohlenstoffbilanzen auf regionaler Skala zu untersuchen und zu reduzieren. Die Ergebnisse dieser Arbeit zeigen, dass der Nettokohlenstoffaustausch zwischen terrestrischer Biosphäre und Atmosphäre unter heutigen klimatischen Bedingungen relativ sicher abgeschätzt werden kann, obwohl erhebliche Unsicherheit über die modelbasierte terrestrische Nettoprimärproduktion existiert. Prozessbasierte Modellierung und Waldbestandsstatistiken wurden erfolgreich kombiniert, um verbesserte Abschätzungen von regionalen Kohlenstoffvorräten und ihrer Änderung mit der Zeit zu ermöglichen. Die Anwendung des angepassten Modells in 77 europäischen Regionen zeigt, dass modellbasierte Abschätzungen des Biomasseaufwuchses in Wäldern weitgehend mit inventarbasierten Abschätzungen für verschiede Baumarten übereinstimmen. Unter Berücksichtigung von historischen Änderungen in Klima, atmosphärischem CO₂-Gehalt, Waldfläche und Holzernte (1948-2000) reproduziert das Model auf europäischer Ebene die heutigen, auf Bestandsstatistiken beruhenden, Abschätzungen von Waldaltersstruktur, das Verhältnis von Zuwachs und Entnahme von Biomasse, sowie die Speicherungsraten im Kohlenstoffspeicher der Vegetation. Alternative Szenarien von zukünftigen Landnutzungs- und Klimaänderungen legen nahe, dass die Kohlenstoffaufnahme der europäischen terrestrischen Biosphäre von relevanter Größenordnung für Klimaschutzstrategien sind. Die Speicherungsraten sind jedoch klein im Vergleich zu den absoluten europäischen CO₂-Emissionen, und nehmen zudem sehr wahrscheinlich gegen Ende des 21. Jahrhunderts ab. Unsicherheiten in Klimaprojektionen sind eine Hauptursache für die Unsicherheiten in den modellbasierten Abschätzungen des zukünftigen Nettokohlenstoffaustausches und müssen daher in Klimaschutzanalysen der terrestrischen Biosphäre berücksichtigt werden.

Es gibt zwei Hauptpfade, über die der Mensch die terrestrische Biosphäre verändert: 1) direkt durch Landnutzungswandel (LNW) und 2) indirekt durch Klimawandel (KW), welcher seinerseits zu Ökosystemveränderungen führt. Die vorliegende Dissertation unternimmt den Versuch, die vom Menschen über beide diese Pfade verursachten Veränderungen konsistent und quantitativ zu bestimmen. Die Analyse basiert auf einem integrierten Indikator für makro-skalige Veränderungen der biogeochemikalischen Eigenschaften und der Ökosystemstruktur. Große Verschiebungen bei diesen grundlegenden Bausteinen der Biosphäre bedeuten ein Risiko für komplexere Ökosystemeigenschaften, da sie möglicherweise lange bestehende biotische Interaktionen unterbrechen. Die Arbeit stützt sich auf Simulationen mit dem dynamischen globalen Vegetations-, Agrar- und Hydrologiemodell LPJmL, um zu bestimmen, wie biogeochemische Eigenschaften und die Ökosystemstruktur auf historischen LNW und KW reagiert haben. Für die Zukunftsprojektionen wird LPJmL mit einer großen Anzahl an Klima- und Landnutzungsszenarien angetrieben. Laut den Simulationsergebnissen haben sich schwere Ökosystemveränderungen durch LNW und KW von lediglich 0,5% um 1700 auf 25-31% der Landoberfläche heute ausgedehnt. Landnutzung war in der Vergangenheit der wichtigste anthropogene Treiber schwerer Ökosystemveränderungen. Für das 21. Jahrhundert zeigen die Ergebnisse, dass KW voraussichtlich in allen außer den ambitioniertesten Mitigationsszenarien den Platz als Haupttreiber schwerer Ökosystemveränderungen übernehmen wird. Einige Landnutzungsszenarien nehmen an, dass zukünftige Effizienzsteigerungen trotz Bevölkerungswachtum eine Verringerung der landwirtschaftlichen Fläche ermöglichen. Doch auch verminderte LNW-Auswirkungen werden wahrscheinlich nicht ausreichen, um die Zunahme von Klimafolgen zu kompensieren, so dass die vom Menschen verursachte Transformation der Biosphäre in diesem Jahrhundert wahrscheinlich unabhängig vom Szenario wachsen wird.
There are two major pathways of human interference with the terrestrial biosphere: 1) directly through land use change (LUC) and 2) indirectly through anthropogenic climate change (CC) which in turn drives ecosystem change. This dissertation presents an attempt to assess human-induced biosphere change through both these pathways in a consistent and quantitative way. The analysis is based on an integrated indicator of macro-scale changes in biogeochemical characteristics and ecosystem structure. Large shifts in these basic building blocks of the biosphere are taken to indicate a risk to more complex ecosystem properties as they potentially disrupt long-standing biotic interactions. This dissertation relies on simulations with the dynamic global vegetation, agriculture and hydrology model LPJmL to quantify how biogeochemical characteristics and ecosystem structure have responded to historical LUC and CC. For future projections LPJmL is driven by a large number of CC and LUC scenarios, using the same indicator to measure the impact on the biosphere. Simulation results show that major impacts on the biosphere from CC and LUC have expanded from merely 0.5% of the land surface in 1700 to 25-31% of the land surface today. Land use has been the main anthropogenic driver causing major ecosystem change in the past. For the future, results show that CC is expected to take over as the main anthropogenic driver of major ecosystem change during this century in all but the most ambitious climate mitigation scenarios. Despite a growing world population, some land use scenarios project that future efficiency improvements will allow for a reduction of agricultural land and hence a reduction of the impact of LUC on the terrestrial biosphere. Yet, results also show that reduced LUC impacts will likely not be able to compensate for the increase in CC impacts, and human-induced transformation of the biosphere is likely to grow during this century regardless of the considered scenario.

Increasing atmospheric CO2 and other greenhouse gasses coupled to the accelerated rate of global warming puts plants and ecosystems under the strain of a rapidly changing abiotic environment. Understanding the impacts of changing global climate is a strong focus of plant science and the establishment of more resilient crop variants is an important goal for breeding programs. Our understanding of plant responses and acclimation to abiotic conditions has improved substantially over the last decades but the combination of a complex abiotic environment and high biological diversity, both on molecular as well as on species level, leaves us still with a lot of uncertainties. The aim of this doctoral thesis was to establish a link between plant thermal responses and the carbon-nitrogen balance of plants. The work in this thesis focused on ecologically significant species of the boreal region: Picea abies, Pinus sylvestris and Betula pendula; and Betula utilis, which is one of the prominent tree species in the high altitudes of the Himalayas. The results presented demonstrate that sub-optimal temperatures combined with other abiotic factors can have additive effects that are not easily deducible from the effect of the two factors separately. Low nitrogen availability enhanced the negative effect of low temperature, while elevated CO2 enhanced plant growth under moderate increases in temperatures but under a more extreme temperature increase it exacerbated the negative effect of heat. I also show evidence that species, despite being grouped into the same functional group or inhabiting the same biome can have different thresholds to temperature and to shifts in the C/N balance of their environment and that these differences can, to some extent, be explained by their differential growth strategies. Furthermore, I demonstrate results supporting the hypothesis that the C-N fluxes between mycorrhizal fungi and tree are strongly dependent on the C and N in the environment, highlighting the significance of the tree-mycorrhiza associations in the C sequestration capacity of the boreal region. In this thesis I also present a generalised empirically based mathematical model that can describe the respiration-temperature response of plant functional types or biomes with high precision, giving a more accurate estimate of NPP when implemented in global climate models, and has the potential to incorporate the thermal acclimation of respiration, further increasing the precision of estimating carbon fluxes under future warming temperatures. My results provide novel insights into the interactive temperature-carbon-nitrogen responses of plants, taking a step towards better understanding the response of plants and forests to future climates.
Ökande atmosfäriskt CO2 och andra växthusgaser kopplade till den accelererande globala uppvärmningen utsätter växter och ekosystem för stressen av en snabbt förändrande abiotisk miljö. Att förstå påverkan av ett globalt klimat i förändring står i fokus inom växtforskning och utvecklandet av mer motståndskraftiga grödor är ett viktigt mål inom programmen för växtförädling. Vår förståelse av växters responser och acklimatisering till abiotiska förhållanden har förbättrats avsevärt under de senaste decennierna, men på grund av kombinationen av en komplex abiotisk miljö och stor biologisk mångfald, både på molekylär nivå såväl som på art-nivå, kvarstår en del frågetecken. Syftet med denna avhandling var att upprätta ett samband mellan växters responser på temperaturförändringar och kol-kvävebalansen hos växter. Arbetet i denna avhandling inriktades på ekologiskt betydande arter i den boreala regionen, Picea abies, Pinus sylvestris and Betula pendula; samt Betula utilis som är en av de framträdande trädarterna på höga höjder i Himalaya. Resultaten som presenteras visar att suboptimala temperaturer i kombination med andra abiotiska faktorer kan ha additiva effekter som inte enkelt kan härledas från effekten av de två faktorerna var för sig. Låg kvävetillgänglighet ökade den negativa effekten av låg temperatur, medan förhöjd CO2-halt förbättrade planttillväxt under måttliga temperaturökningar, men under en mer extrem temperaturökning förvärrades dock den negativa effekten av värme. Jag framför även bevis på att arter, trots att de grupperas i samma funktionella grupp eller finns inom samma biom, kan ha olika tröskelvärden beträffande temperatur och förskjutningar i C/N-balansen i sin miljö och att dessa skillnader, i viss utsträckning, kan förklaras av deras olika tillväxtstrategier. Vidare visar jag resultat som stöder hypotesen att C-N - flöden mellan mykorrhiza och träd är starkt beroende av C och N i miljön. Detta belyser i sin tur betydelsen av samarbetet mellan träd och mykorrhiza gällande kolbindningskapaciteten i den boreala regionen. I denna avhandling presenterar jag även en generaliserad empiriskt baserad matematisk modell som med hög precision kan beskriva respiration-temperatur svar av växtfunktionella typer eller biom, vilken ger en mer exakt uppskattning av NPP i globala klimatmodeller. Mina resultat åstadkommer nya insikter i de interaktiva temperatur-kol-kväve-responserna hos växter, och tar ett steg mot bättre förståelse för växters och skogars reaktion på framtida klimat.

The Swedish Nuclear Fuel and Waste Management Co., (SKB), pursues site investigations for the final repository for spent nuclear fuel at two sites in the south eastern part of Sweden, the Forsmark- and the Laxemar site (figure 1). Data from the two site investigations are used to build site descriptive models of the areas. These models describe the bedrock and surface system properties important for designing the repository, the environmental impact assessment, and the long-term safety, i.e. up to 100,000 years, in a safety assessment. In this paper we discuss the methodology, and the interim results for, the landscape model, used in the safety assessment to populate the Forsmark site in the numerical dose models. The landscape model is built upon ecosystem types, e.g. a lake or a mire, (Biosphere Objects) that are connected in the landscape via surface hydrology. Each of the objects have a unique set of properties derived from the site description. The objects are identified by flow transport modeling, giving discharge points at the surface for all possible flow paths from the hypothetical repository in the bedrock. The landscape development is followed through time by using long-term processes e.g. shoreline displacement and sedimentation. The final landscape model consists of a number of maps for each chosen time period and a table of properties that describe the individual objects which constitutes the landscape. The results show a landscape that change over time during 20,000 years. The time period used in the model equals the present interglacial and can be used as an analogue for a future interglacial. Historically, the model area was covered by sea, and then gradually changes into a coastal area and, in the future, into a terrestrial inland landscape. Different ecosystem types are present during the landscape development, e.g. sea, lakes, agricultural areas, forest and wetlands (mire). The biosphere objects may switch from one ecosystem type to another during the modeled time period, from sea to lake, and from lake to mire and finally, some objects are transformed into agricultural area due to favorable farming characteristics.