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Flood risk is impacted by a range of physical and socio-economic processes. Hence, the quantification of flood risk ideally considers the complete flood risk chain, from atmospheric processes through catchment and river system processes to damage mechanisms in the affected areas. Although it is generally accepted that a multitude of changes along the risk chain can occur and impact flood risk, there is a lack of knowledge of how and to what extent changes in influencing factors propagate through the chain and finally affect flood risk. To fill this gap, we present a comprehensive sensitivity analysis which considers changes in all risk components, i.e. changes in climate, catchment, river system, land use, assets, and vulnerability. The application of this framework to the mesoscale Mulde catchment in Germany shows that flood risk can vary dramatically as a consequence of plausible change scenarios. It further reveals that components that have not received much attention, such as changes in dike systems or in vulnerability, may outweigh changes in often investigated components, such as climate. Although the specific results are conditional on the case study area and the selected assumptions, they emphasize the need for a broader consideration of potential drivers of change in a comprehensive way. Hence, our approach contributes to a better understanding of how the different risk components influence the overall flood risk.
Changes in species' distributions are classically projected based on their climate envelopes. For Siberian forests, which have a tremendous significance for vegetation-climate feedbacks, this implies future shifts of each of the forest-forming larch (Larix) species to the north-east. However, in addition to abiotic factors, reliable projections must assess the role of historical biogeography and biotic interactions. Here, we use sedimentary ancient DNA and individual-based modelling to investigate the distribution of larch species and mitochondrial haplotypes through space and time across the treeline ecotone on the southern Taymyr peninsula, which at the same time presents a boundary area of two larch species. We find spatial and temporal patterns, which suggest that forest density is the most influential driver determining the precise distribution of species and mitochondrial haplotypes. This suggests a strong influence of competition on the species' range shifts. These findings imply possible climate change outcomes that are directly opposed to projections based purely on climate envelopes. Investigations of such fine-scale processes of biodiversity change through time are possible using paleoenvironmental DNA, which is available much more readily than visible fossils and can provide information at a level of resolution that is not reached in classical palaeoecology.
High Mountain Asia (HMA) is dependent upon both the amount and timing of snow and glacier meltwater. Previous model studies and coarse resolution (0.25° × 0.25°, ∼25 km × 25 km) passive microwave assessments of trends in the volume and timing of snowfall, snowmelt, and glacier melt in HMA have identified key spatial and seasonal heterogeneities in the response of snow to changes in regional climate. Here we use recently developed, continuous, internally consistent, and high-resolution passive microwave data (3.125 km × 3.125 km, 1987–2016) from the special sensor microwave imager instrument family to refine and extend previous estimates of changes in the snow regime of HMA. We find an overall decline in snow volume across HMA; however, there exist spatially contiguous regions of increasing snow volume—particularly during the winter season in the Pamir, Karakoram, Hindu Kush, and Kunlun Shan. Detailed analysis of changes in snow-volume trends through time reveal a large step change from negative trends during the period 1987–1997, to much more positive trends across large regions of HMA during the periods 1997–2007 and 2007–2016. We also find that changes in high percentile monthly snow-water volume exhibit steeper trends than changes in low percentile snow-water volume, which suggests a reduction in the frequency of high snow-water volumes in much of HMA. Regions with positive snow-water storage trends generally correspond to regions of positive glacier mass balances.
High Mountain Asia (HMA) is dependent upon both the amount and timing of snow and glacier meltwater. Previous model studies and coarse resolution (0.25° × 0.25°, ∼25 km × 25 km) passive microwave assessments of trends in the volume and timing of snowfall, snowmelt, and glacier melt in HMA have identified key spatial and seasonal heterogeneities in the response of snow to changes in regional climate. Here we use recently developed, continuous, internally consistent, and high-resolution passive microwave data (3.125 km × 3.125 km, 1987–2016) from the special sensor microwave imager instrument family to refine and extend previous estimates of changes in the snow regime of HMA. We find an overall decline in snow volume across HMA; however, there exist spatially contiguous regions of increasing snow volume—particularly during the winter season in the Pamir, Karakoram, Hindu Kush, and Kunlun Shan. Detailed analysis of changes in snow-volume trends through time reveal a large step change from negative trends during the period 1987–1997, to much more positive trends across large regions of HMA during the periods 1997–2007 and 2007–2016. We also find that changes in high percentile monthly snow-water volume exhibit steeper trends than changes in low percentile snow-water volume, which suggests a reduction in the frequency of high snow-water volumes in much of HMA. Regions with positive snow-water storage trends generally correspond to regions of positive glacier mass balances.
Terrestrial reptiles are particularly vulnerable to climate change. Their highest density and diversity can be found in hot drylands, ecosystems which demonstrate extreme climatic conditions. However, reptiles are not isolated systems but part of a large species assemblage with many trophic dependencies. While direct relations among climatic conditions, invertebrates, vegetation, or reptiles have already been explored, to our knowledge, species’ responses to direct and indirect pathways of multiple climatic and biotic factors and their interactions have rarely been examined comprehensively. We investigated direct and indirect effects of climatic and biotic parameters on the individual (body condition) and population level (occupancy) of eight abundant lizard species with different functional traits in an arid Australian lizard community using a 30‐yr multi‐trophic monitoring study. We used structural equation modeling to disentangle single and interactive effects. We then assessed whether species could be grouped into functional groups according to their functional traits and their responses to different parameters. We found that lizard species differed strongly in how they responded to climatic and biotic factors. However, the factors to which they responded seemed to be determined by their functional traits. While responses on body condition were determined by habitat, activity time, and prey, responses on occupancy were determined by habitat specialization, body size, and longevity. Our findings highlight the importance of indirect pathways through climatic and biotic interactions, which should be included into predictive models to increase accuracy when predicting species’ responses to climate change. Since one might never obtain all mechanistic pathways at the species level, we propose an approach of identifying relevant species traits that help grouping species into functional groups at different ecological levels, which could then be used for predictive modeling.
During the last few decades, the rapid separation of the Small Aral Sea from the isolated basin has changed its hydrological and ecological conditions tremendously. In the present study, we developed and validated the hybrid model for the Syr Darya River basin based on a combination of state-of-the-art hydrological and machine learning models. Climate change impact on freshwater inflow into the Small Aral Sea for the projection period 2007-2099 has been quantified based on the developed hybrid model and bias corrected and downscaled meteorological projections simulated by four General Circulation Models (GCM) for each of three Representative Concentration Pathway scenarios (RCP). The developed hybrid model reliably simulates freshwater inflow for the historical period with a Nash-Sutcliffe efficiency of 0.72 and a Kling-Gupta efficiency of 0.77. Results of the climate change impact assessment showed that the freshwater inflow projections produced by different GCMs are misleading by providing contradictory results for the projection period. However, we identified that the relative runoff changes are expected to be more pronounced in the case of more aggressive RCP scenarios. The simulated projections of freshwater inflow provide a basis for further assessment of climate change impacts on hydrological and ecological conditions of the Small Aral Sea in the 21st Century.
Recent research has shown that many cold-adapted species survived the last glacial maximum (LGM) in northern refugia. Whether this evolutionary history has had consequences for their genetic diversity and adaptive potential remains unknown. We sampled 14 populations of Carex limosa, a sedge specialized to bog ecosystems, along a latitudinal gradient from its Scandinavian core to the southern lowland range-margin in Germany. Using microsatellite and experimental common-garden data, we evaluated the impacts of global climate change along this gradient and assessed the conservation status of the southern marginal populations. Microsatellite data revealed two highly distinct genetic groups and hybrid individuals. In our common-garden experiment, the two groups showed divergent responses to increased nitrogen/phosphorus (N/P) availability, suggesting ecotypic differentiation. Each group formed genetically uniform populations at both northern and southern sampling areas. Mixed populations occurred throughout our sampling area, an area that was entirely glaciated during the LGM. The fragmented distribution implies allopatric divergence at geographically separated refugia that putatively differed in N/P availability. Molecular data and an observed low hybrid fecundity indicate the importance of clonal reproduction for hybrid populations. At the southern range-margin, however, all populations showed effects of clonality, lowered fecundity and low competitiveness, suggesting abiotic and biotic constraints to population persistence.
Organic matter characteristics in yedoma and thermokarst deposits on Baldwin Peninsula, west Alaska
(2018)
As Arctic warming continues and permafrost thaws, more soil and sedimentary organic matter (OM) will be decomposed in northern high latitudes. Still, uncertainties remain in the quality of the OM and the size of the organic carbon (OC) pools stored in different deposit types of permafrost landscapes. This study presents OM data from deep permafrost and lake deposits on the Baldwin Peninsula which is located in the southern portion of the continuous permafrost zone in west Alaska. Sediment samples from yedoma and drained thermokarst lake basin (DTLB) deposits as well as thermokarst lake sediments were analyzed for cryostratigraphical and biogeochemical parameters and their lipid biomarker composition to identify the below-ground OC pool size and OM quality of ice-rich permafrost on the Baldwin Peninsula. We provide the first detailed characterization of yedoma deposits on Baldwin Peninsula. We show that three-quarters of soil OC in the frozen deposits of the study region (total of 68 Mt) is stored in DTLB deposits (52 Mt) and one-quarter in the frozen yedoma deposits (16 Mt). The lake sediments contain a relatively small OC pool (4 Mt), but have the highest volumetric OC content (93 kgm(-3)) compared to the DTLB (35 kgm(-3)) and yedoma deposits (8 kgm(-3)), largely due to differences in the ground ice content. The biomarker analysis indicates that the OM in both yedoma and DTLB deposits is mainly of terrestrial origin. Nevertheless, the relatively high carbon preference index of plant leaf waxes in combination with a lack of a degradation trend with depth in the yedoma deposits indi-cates that OM stored in yedoma is less degraded than that stored in DTLB deposits. This suggests that OM in yedoma has a higher potential for decomposition upon thaw, despite the relatively small size of this pool. These findings show that the use of lipid biomarker analysis is valuable in the assessment of the potential future greenhouse gas emissions from thawing permafrost, especially because this area, close to the discontinuous permafrost boundary, is projected to thaw substantially within the 21st century.
Climate impacts on transocean dispersal and habitat in gray whales from the Pleistocene to 2100
(2015)
Arctic animals face dramatic habitat alteration due to ongoing climate change. Understanding how such species have responded to past glacial cycles can help us forecast their response to today's changing climate. Gray whales are among those marine species likely to be strongly affected by Arctic climate change, but a thorough analysis of past climate impacts on this species has been complicated by lack of information about an extinct population in the Atlantic. While little is known about the history of Atlantic gray whales or their relationship to the extant Pacific population, the extirpation of the Atlantic population during historical times has been attributed to whaling. We used a combination of ancient and modern DNA, radiocarbon dating and predictive habitat modelling to better understand the distribution of gray whales during the Pleistocene and Holocene. Our results reveal that dispersal between the Pacific and Atlantic was climate dependent and occurred both during the Pleistocene prior to the last glacial period and the early Holocene immediately following the opening of the Bering Strait. Genetic diversity in the Atlantic declined over an extended interval that predates the period of intensive commercial whaling, indicating this decline may have been precipitated by Holocene climate or other ecological causes. These first genetic data for Atlantic gray whales, particularly when combined with predictive habitat models for the year 2100, suggest that two recent sightings of gray whales in the Atlantic may represent the beginning of the expansion of this species' habitat beyond its currently realized range.
Flooding is an imminent natural hazard threatening most river deltas, e.g. the Mekong Delta. An appropriate flood management is thus required for a sustainable development of the often densely populated regions. Recently, the traditional event-based hazard control shifted towards a risk management approach in many regions, driven by intensive research leading to new legal regulation on flood management. However, a large-scale flood risk assessment does not exist for the Mekong Delta. Particularly, flood risk to paddy rice cultivation, the most important economic activity in the delta, has not been performed yet. Therefore, the present study was developed to provide the very first insight into delta-scale flood damages and risks to rice cultivation. The flood hazard was quantified by probabilistic flood hazard maps of the whole delta using a bivariate extreme value statistics, synthetic flood hydrographs, and a large-scale hydraulic model. The flood risk to paddy rice was then quantified considering cropping calendars, rice phenology, and harvest times based on a time series of enhanced vegetation index (EVI) derived from MODIS satellite data, and a published rice flood damage function. The proposed concept provided flood risk maps to paddy rice for the Mekong Delta in terms of expected annual damage. The presented concept can be used as a blueprint for regions facing similar problems due to its generic approach. Furthermore, the changes in flood risk to paddy rice caused by changes in land use currently under discussion in the Mekong Delta were estimated. Two land-use scenarios either intensifying or reducing rice cropping were considered, and the changes in risk were presented in spatially explicit flood risk maps. The basic risk maps could serve as guidance for the authorities to develop spatially explicit flood management and mitigation plans for the delta. The land-use change risk maps could further be used for adaptive risk management plans and as a basis for a cost-benefit of the discussed land-use change scenarios. Additionally, the damage and risks maps may support the recently initiated agricultural insurance programme in Vietnam.
Many semi-arid regions are characterised by water scarcity and vulnerability of natural resources, pronounced climatic variability and social stress. Integrated studies including climatotogy, hydrology, and socio-econornic studies are required both for analysing the dynamic natural conditions and to assess possible strategies to make semi-arid regions Less vulnerable to the present and changing climate. The model introduced here dynamically describes the retationships between climate forcing, water availability, agriculture and selected societal processes. The model has been tailored to simulate the rather complex situation in the semi-and north-eastern Brazil in a quantitative manner including the sensitivity to external forcing, such as climate change. The selected results presented show the general functioning of the integrated model, with a primary focus on climate change impacts. It becomes evident that due to Large differences in regional climate scenarios, it is still impossible to give quantitative values for the most probable development, e.g., to assign probabilities to the simulated results. However, it becomes clear that water is a very crucial factor, and that an efficient and ecologically sound water management is a key question for the further development of that semi-arid region. The simulation results show that, independent of the differences in climate change scenarios, rain-fed farming is more vulnerable to drought impacts compared to irrigated farming. However, the capacity of irrigation and other water infrastructure systems to enhance resilience in respect to climatic fluctuations is significantly constrained given a significant negative precipitation trend. (c) 2005 Elsevier B.V. All rights reserved.
Rock glaciers are permafrost or glacial landforms of debris and ice that deform under the influence of gravity. Recent estimates hold that, in the semiarid Chilean Andes for example, active rock glaciers store more water than glaciers. However, little is known about how many rock glaciers might decay because of global warming and how much this decay might contribute to water and sediment release. We investigated an inventory of >6500 rock glaciers in the Argentinian Andes, spanning the climatic gradient from the Desert Andes to cold-temperate Tierra del Fuego. We used active rock glaciers as a diagnostic of permafrost, assuming that the toes mark the 0 degrees C isotherm in climate scenarios for the twenty-first century and their impact on freezing conditions near the rock glacier toes. We find that, under future worst case warming, up to 95% of rock glaciers in the southern Desert Andes and in the Central Andes will rest in areas above 0 degrees C and that this freezing level might move up more than twice as much (similar to 500 m) as during the entire Holocene (similar to 200 m). Many active rock glaciers are already well below the current freezing level and exemplify how local controls may confound regional prognoses. A Bayesian Multifactor Analysis of Variance further shows that only in the Central Andes are the toes of active rock glaciers credibly higher than those of inactive ones. Elsewhere in the Andes, active and inactive rock glaciers occupy indistinguishable elevation bands, regardless of aspect, the formation mechanism, or shape of rock glaciers. The state of rock glacier activity predicts differences in elevations of toes to 140 m at best so that regional inference of the distribution of discontinuous permafrost from rock-glacier toes cannot be more accurate than this in the Argentinian Andes. We conclude that the Central Andes-where rock glaciers are largest, cover the most area, and have a greater density than glaciers-is likely to experience the most widespread disturbance to the thermal regime of the twenty-first century. (C) 2018 Elsevier B.V. All rights reserved.
Polyunsaturated fatty acids (PUFA), especially long-chain (i.e., >= 20 carbons) polyunsaturated fatty acids (LC-PUFA), are fundamental to the health and survival of marine and terrestrial organisms. Therefore, it is imperative that we gain a better understanding of their origin, abundance, and transfer between and within these ecosystems. We evaluated the natural variation in PUFA distribution and abundance that exists between and within these ecosystems by amassing and analyzing, using multivariate and analysis of variance (ANOVA) methods, >3000 fatty acid (FA) profiles from marine and terrestrial organisms. There was a clear dichotomy in LC-PUFA abundance between organisms in marine and terrestrial ecosystems, mainly driven by the C-18 PUFA in terrestrial organisms and omega-3 (n-3) LC-PUFA in marine organisms. The PUFA content of an organism depended on both its biome (marine vs terrestrial) and taxonomic group. Within the marine biome, the PUFA content varied among taxonomic groups. PUFA content of marine organisms was dependent on both geographic zone (i.e., latitude, and thus broadly related to temperature) and trophic level (a function of diet). The contents of n-3 LC-PUFA were higher in polar and temperate marine organisms than those from the tropics. Therefore, we conclude that, on a per capita basis, high latitude marine organisms provide a disproportionately large global share of these essential nutrients to consumers, including terrestrial predators. Our analysis also hints at how climate change, and other anthropogenic stressors, might act to negatively impact the global distribution and abundance of n-3 LC-PUFA within marine ecosystems and on the terrestrial consumers that depend on these subsidies.
Climate change is expected to exacerbate the current threats to freshwater ecosystems, yet multifaceted studies on the potential impacts of climate change on freshwater biodiversity at scales that inform management planning are lacking. The aim of this study was to fill this void through the development of a novel framework for assessing climate change vulnerability tailored to freshwater ecosystems. The three dimensions of climate change vulnerability are as follows: (i) exposure to climate change, (ii) sensitivity to altered environmental conditions and (iii) resilience potential. Our vulnerability framework includes 1685 freshwater species of plants, fishes, molluscs, odonates, amphibians, crayfish and turtles alongside key features within and between catchments, such as topography and connectivity. Several methodologies were used to combine these dimensions across a variety of future climate change models and scenarios. The resulting indices were overlaid to assess the vulnerability of European freshwater ecosystems at the catchment scale (18 783 catchments). The Balkan Lakes Ohrid and Prespa and Mediterranean islands emerge as most vulnerable to climate change. For the 2030s, we showed a consensus among the applied methods whereby up to 573 lake and river catchments are highly vulnerable to climate change. The anthropogenic disruption of hydrological habitat connectivity by dams is the major factor reducing climate change resilience. A gap analysis demonstrated that the current European protected area network covers <25% of the most vulnerable catchments. Practical steps need to be taken to ensure the persistence of freshwater biodiversity under climate change. Priority should be placed on enhancing stakeholder cooperation at the major basin scale towards preventing further degradation of freshwater ecosystems and maintaining connectivity among catchments. The catchments identified as most vulnerable to climate change provide preliminary targets for development of climate change conservation management and mitigation strategies.
Arctic and alpine treelines worldwide differ in their reactions to climate change. A northward advance of or densification within the treeline ecotone will likely influence climate-vegetation feedback mechanisms. In our study, which was conducted in the Taimyr Depression in the North Siberian Lowlands, w present a combined field-and model-based approach helping us to better understand the population processes involved in the responses of the whole treeline ecotone, spanning from closed forest to single-tree tundra, to climate warming. Using information on stand structure, tree age, and seed quality and quantity from seven sites, we investigate effects of intra-specific competition and seed availability on the specific impact of recent climate warming on larch stands. Field data show that tree density is highest in the forest-tundra, and average tree size decreases from closed forest to single-tree tundra. Age-structure analyses indicate that the trees in the closed forest and forest-tundra have been present for at least similar to 240 yr. At all sites except the most southerly ones, past establishment is positively correlated with regional temperature increase. In the single-tree tundra, however, a change in growth form from krummholz to erect trees, beginning similar to 130 yr ago, rather than establishment date has been recorded. Seed mass decreases from south to north, while seed quantity increases. Simulations with LAVESI (Larix Vegetation Simulator) further suggest that relative density changes strongly in response to a warming signal in the forest-tundra while intra-specific competition limits densification in the closed forest and seed limitation hinders densification in the single-tree tundra. We find striking differences in strength and timing of responses to recent climate warming. While forest-tundra stands recently densified, recruitment is almost non-existent at the southern and northern end of the ecotone due to autecological processes. Palaeo-treelines may therefore be inappropriate to infer past temperature changes at a fine scale. Moreover, a lagged treeline response to past warming will, via feedback mechanisms, influence climate change in the future.
There is growing empirical evidence that anthropogenic climate change will substantially affect the electric sector. Impacts will stem both from the supply sidethrough the mitigation of greenhouse gasesand from the demand sidethrough adaptive responses to a changing environment. Here we provide evidence of a polarization of both peak load and overall electricity consumption under future warming for the worlds third-largest electricity marketthe 35 countries of Europe. We statistically estimate country-level doseresponse functions between daily peak/total electricity load and ambient temperature for the period 2006-2012. After removing the impact of nontemperature confounders and normalizing the residual load data for each country, we estimate a common doseresponse function, which we use to compute national electricity loads for temperatures that lie outside each countrys currently observed temperature range. To this end, we impose end-of-century climate on todays European economies following three different greenhouse-gas concentration trajectories, ranging from ambitious climate-change mitigationin line with the Paris agreementto unabated climate change. We find significant increases in average daily peak load and overall electricity consumption in southern and western Europe (similar to 3 to similar to 7% for Portugal and Spain) and significant decreases in northern Europe (similar to-6 to similar to-2% for Sweden and Norway). While the projected effect on European total consumption is nearly zero, the significant polarization and seasonal shifts in peak demand and consumption have important ramifications for the location of costly peak-generating capacity, transmission infrastructure, and the design of energy-efficiency policy and storage capacity.
The 2008-2010 food crisis might have been a harbinger of fundamental climate-induced food crises with geopolitical implications. Heat-wave-induced yield losses in Russia and resulting export restrictions led to increases in market prices for wheat across the Middle East, likely contributing to the Arab Spring. With ongoing climate change, temperatures and temperature variability will rise, leading to higher uncertainty in yields for major nutritional crops. Here we investigate which countries are most vulnerable to teleconnected supply-shocks, i.e. where diets strongly rely on the import of wheat, maize, or rice, and where a large share of the population is living in poverty. We find that the Middle East is most sensitive to teleconnected supply shocks in wheat, Central America to supply shocks in maize, and Western Africa to supply shocks in rice. Weighing with poverty levels, Sub-Saharan Africa is most affected. Altogether, a simultaneous 10% reduction in exports of wheat, rice, and maize would reduce caloric intake of 55 million people living in poverty by about 5%. Export bans in major producing regions would put up to 200 million people below the poverty line at risk, 90% of which live in Sub-Saharan Africa. Our results suggest that a region-specific combination of national increases in agricultural productivity and diversification of trade partners and diets can effectively decrease future food security risks.
Meteorological extreme events have great potential for damaging railway infrastructure and posing risks to the safety of train passengers. In the future, climate change will presumably have serious implications on meteorological hazards in the Alpine region. Hence, attaining insights on future frequencies of meteorological extremes with relevance for the railway operation in Austria is required in the context of a comprehensive and sustainable natural hazard management plan of the railway operator. In this study, possible impacts of climate change on the frequencies of so-called critical meteorological conditions (CMCs) between the periods 1961-1990 and 2011-2040 are analyzed. Thresholds for such CMCs have been defined by the railway operator and used in its weather monitoring and early warning system. First, the seasonal climate change signals for air temperature and precipitation in Austria are described on the basis of an ensemble of high-resolution Regional Climate Model (RCM) simulations for Europe. Subsequently, the RCM-ensemble was used to investigate changes in the frequency of CMCs. Finally, the sensitivity of results is analyzed with varying threshold values for the CMCs. Results give robust indications for an all-season air temperature rise, but show no clear tendency in average precipitation. The frequency analyses reveal an increase in intense rainfall events and heat waves, whereas heavy snowfall and cold days are likely to decrease. Furthermore, results indicate that frequencies of CMCs are rather sensitive to changes of thresholds. It thus emphasizes the importance to carefully define, validate, andif neededto adapt the thresholds that are used in the weather monitoring and warning system of the railway operator. For this, continuous and standardized documentation of damaging events and near-misses is a pre-requisite.
Climate science today makes use of a variety of red globes to explore and communicate findings. These transform the iconography which informs this image: the idealised, even mythical vision of the blue, vulnerable and perfect marble is impaired by the application of the colours yellow and red. Since only predictions that employ a lot of red seem to exist, spectators are confronted with the message that the future Earth that might turn out as envisaged here is undesirable. Here intuitively powerful narrations of the end of the world may connect. By employing methods of art history and visual analysis, and building on examples from current Intergovernmental Panel on Climate Change reports and future scenario maps, this article explores how burning world images bear - intentionally or not - elements of horror and shock. My question explored here is as follows: should 'burning world' images be understood as a new and powerful cosmology?
Damage due to tropical cyclones accounts for more than 50% of all meteorologically-induced economic losses worldwide. Their nominal impact is projected to increase substantially as the exposed population grows, per capita income increases, and anthropogenic climate change manifests. So far, historical losses due to tropical cyclones have been found to increase less than linearly with a nation's affected gross domestic product (GDP). Here we show that for the United States this scaling is caused by a sub-linear increase with affected population while relative losses scale super-linearly with per capita income. The finding is robust across a multitude of empirically derived damage models that link the storm's wind speed, exposed population, and per capita GDP to reported losses. The separation of both socio-economic predictors strongly affects the projection of potential future hurricane losses. Separating the effects of growth in population and per-capita income, per hurricane losses with respect to national GDP are projected to triple by the end of the century under unmitigated climate change, while they are estimated to decrease slightly without the separation.
Strong waves in the mid-latitude circulation have been linked to extreme surface weather and thus changes in waviness could have serious consequences for society. Several theories have been proposed which could alter waviness, including tropical sea surface temperature anomalies or rapid climate change in the Arctic. However, so far it remains unclear whether any changes in waviness have actually occurred. Here we propose a novel meandering index which captures the maximum waviness in geopotential height contours at any given day, using all information of the full spatial position of each contour. Data are analysed on different time scale (from daily to 11 day running means) and both on hemispheric and regional scales. Using quantile regressions, we analyse how seasonal distributions of this index have changed over 1979-2015. The most robust changes are detected for autumn which has seen a pronounced increase in strongly meandering patterns at the hemispheric level as well as over the Eurasian sector. In summer for both the hemisphere and the Eurasian sector, significant downward trends in meandering are detected on daily timescales which is consistent with the recently reported decrease in summer storm track activity. The American sector shows the strongest increase in meandering in the warm season: in particular for 11 day running mean data, indicating enhanced amplitudes of quasi-stationary waves. Our findings have implications for both the occurrence of recent cold spells and persistent heat waves in the mid-latitudes.
This dissertation investigates the impact of the economic and fiscal crisis starting in 2008 on EU climate policy-making. While the overall number of adopted greenhouse gas emission reduction policies declined in the crisis aftermath, EU lawmakers decided to introduce new or tighten existing regulations in some important policy domains. Existing knowledge about the crisis impact on EU legislative decision-making cannot explain these inconsistencies. In response, this study develops an actor-centred conceptual framework based on rational choice institutionalism that provides a micro-level link to explain how economic crises translate into altered policy-making patterns. The core theoretical argument draws on redistributive conflicts, arguing that tensions between ‘beneficiaries’ and ‘losers’ of a regulatory initiative intensify during economic crises and spill over to the policy domain. To test this hypothesis and using social network analysis, this study analyses policy processes in three case studies: The introduction of carbon dioxide emission limits for passenger cars, the expansion of the EU Emissions Trading System to aviation, and the introduction of a regulatory framework for biofuels. The key finding is that an economic shock causes EU policy domains to polarise politically, resulting in intensified conflict and more difficult decision-making. The results also show that this process of political polarisation roots in the industry that is the subject of the regulation, and that intergovernmental bargaining among member states becomes more important, but also more difficult in times of crisis.
The Himalayas are a region that is most dependent, but also frequently prone to hazards from changing meltwater resources. This mountain belt hosts the highest mountain peaks on earth, has the largest reserve of ice outside the polar regions, and is home to a rapidly growing population in recent decades. One source of hazard has attracted scientific research in particular in the past two decades: glacial lake outburst floods (GLOFs) occurred rarely, but mostly with fatal and catastrophic consequences for downstream communities and infrastructure. Such GLOFs can suddenly release several million cubic meters of water from naturally impounded meltwater lakes. Glacial lakes have grown in number and size by ongoing glacial mass losses in the Himalayas. Theory holds that enhanced meltwater production may increase GLOF frequency, but has never been tested so far. The key challenge to test this notion are the high altitudes of >4000 m, at which lakes occur, making field work impractical. Moreover, flood waves can attenuate rapidly in mountain channels downstream, so that many GLOFs have likely gone unnoticed in past decades. Our knowledge on GLOFs is hence likely biased towards larger, destructive cases, which challenges a detailed quantification of their frequency and their response to atmospheric warming. Robustly quantifying the magnitude and frequency of GLOFs is essential for risk assessment and management along mountain rivers, not least to implement their return periods in building design codes.
Motivated by this limited knowledge of GLOF frequency and hazard, I developed an algorithm that efficiently detects GLOFs from satellite images. In essence, this algorithm classifies land cover in 30 years (~1988–2017) of continuously recorded Landsat images over the Himalayas, and calculates likelihoods for rapidly shrinking water bodies in the stack of land cover images. I visually assessed such detected tell-tale sites for sediment fans in the river channel downstream, a second key diagnostic of GLOFs. Rigorous tests and validation with known cases from roughly 10% of the Himalayas suggested that this algorithm is robust against frequent image noise, and hence capable to identify previously unknown GLOFs. Extending the search radius to the entire Himalayan mountain range revealed some 22 newly detected GLOFs. I thus more than doubled the existing GLOF count from 16 previously known cases since 1988, and found a dominant cluster of GLOFs in the Central and Eastern Himalayas (Bhutan and Eastern Nepal), compared to the rarer affected ranges in the North. Yet, the total of 38 GLOFs showed no change in the annual frequency, so that the activity of GLOFs per unit glacial lake area has decreased in the past 30 years. I discussed possible drivers for this finding, but left a further attribution to distinct GLOF-triggering mechanisms open to future research.
This updated GLOF frequency was the key input for assessing GLOF hazard for the entire Himalayan mountain belt and several subregions. I used standard definitions in flood hydrology, describing hazard as the annual exceedance probability of a given flood peak discharge [m3 s-1] or larger at the breach location. I coupled the empirical frequency of GLOFs per region to simulations of physically plausible peak discharges from all existing ~5,000 lakes in the Himalayas. Using an extreme-value model, I could hence calculate flood return periods. I found that the contemporary 100-year GLOF discharge (the flood level that is reached or exceeded on average once in 100 years) is 20,600+2,200/–2,300 m3 s-1 for the entire Himalayas. Given the spatial and temporal distribution of historic GLOFs, contemporary GLOF hazard is highest in the Eastern Himalayas, and lower for regions with rarer GLOF abundance. I also calculated GLOF hazard for some 9,500 overdeepenings, which could expose and fill with water, if all Himalayan glaciers have melted eventually. Assuming that the current GLOF rate remains unchanged, the 100-year GLOF discharge could double (41,700+5,500/–4,700 m3 s-1), while the regional GLOF hazard may increase largest in the Karakoram.
To conclude, these three stages–from GLOF detection, to analysing their frequency and estimating regional GLOF hazard–provide a framework for modern GLOF hazard assessment. Given the rapidly growing population, infrastructure, and hydropower projects in the Himalayas, this thesis assists in quantifying the purely climate-driven contribution to hazard and risk from GLOFs.
A contemporary challenge in Ecology and Evolutionary Biology is to anticipate the fate of populations of organisms in the context of a changing world. Climate change and landscape changes due to anthropic activities have been of major concern in the contemporary history. Organisms facing these threats are expected to respond by local adaptation (i.e., genetic changes or phenotypic plasticity) or by shifting their distributional range (migration). However, there are limits to their responses. For example, isolated populations will have more difficulties in developing adaptive innovations by means of genetic changes than interconnected metapopulations. Similarly, the topography of the environment can limit dispersal opportunities for crawling organisms as compared to those that rely on wind. Thus, populations of species with different life history strategy may differ in their ability to cope with changing environmental conditions. However, depending on the taxon, empirical studies investigating organisms’ responses to environmental change may become too complex, long and expensive; plus, complications arising from dealing with endangered species. In consequence, eco-evolutionary modeling offers an opportunity to overcome these limitations and complement empirical studies, understand the action and limitations of underlying mechanisms, and project into possible future scenarios. In this work I take a modeling approach and investigate the effect and relative importance of evolutionary mechanisms (including phenotypic plasticity) on the ability for local adaptation of populations with different life strategy experiencing climate change scenarios. For this, I performed a review on the state of the art of eco-evolutionary Individual-Based Models (IBMs) and identify gaps for future research. Then, I used the results from the review to develop an eco-evolutionary individual-based modeling tool to study the role of genetic and plastic mechanisms in promoting local adaption of populations of organisms with different life strategies experiencing scenarios of climate change and environmental stochasticity. The environment was simulated through a climate variable (e.g., temperature) defining a phenotypic optimum moving at a given rate of change. The rate of change was changed to simulate different scenarios of climate change (no change, slow, medium, rapid climate change). Several scenarios of stochastic noise color resembling different climatic conditions were explored. Results show that populations of sexual species will rely mainly on standing genetic variation and phenotypic plasticity for local adaptation. Population of species with relatively slow growth rate (e.g., large mammals) – especially those of small size – are the most vulnerable, particularly if their plasticity is limited (i.e., specialist species). In addition, whenever organisms from these populations are capable of adaptive plasticity, they can buffer fitness losses in reddish climatic conditions. Likewise, whenever they can adjust their plastic response (e.g., bed-hedging strategy) they will cope with bluish environmental conditions as well. In contrast, life strategies of high fecundity can rely on non-adaptive plasticity for their local adaptation to novel environmental conditions, unless the rate of change is too rapid. A recommended management measure is to guarantee interconnection of isolated populations into metapopulations, such that the supply of useful genetic variation can be increased, and, at the same time, provide them with movement opportunities to follow their preferred niche, when local adaptation becomes problematic. This is particularly important for bluish and reddish climatic conditions, when the rate of change is slow, or for any climatic condition when the level of stress (rate of change) is relatively high.
Cities to the rescue?
(2017)
Despite the proliferation and promise of subnational climate initiatives, the institutional architecture of transnational municipal networks (TMNs) is not well understood. With a view to close this research gap, the article empirically assesses the assumption that TMNs are a viable substitute for ambitious international action under the United Nations Framework Convention on Climate Change (UNFCCC). It addresses the aggregate phenomenon in terms of geographical distribution, central players, mitigation ambition and monitoring provisions. Examining thirteen networks, it finds that membership in TMNs is skewed toward Europe and North America while countries from the Global South are underrepresented; that only a minority of networks commit to quantified emission reductions and that these are not more ambitious than Parties to the UNFCCC; and finally that the monitoring provisions are fairly limited. In sum, the article shows that transnational municipal networks are not (yet) the representative, ambitious and transparent player they are thought to be.
The unprecedented increase in atmospheric concentrations of carbon dioxide (CO2) and other greenhouse gases (GHG) by anthropogenic activities since the Industrial Revolution impacts on various earth system processes, commonly referred to as `climate change´ (CC). CC faces aquatic ecosystems with extreme abiotic perturbations that potentially alter the interrelations between functional autotrophic and heterotrophic plankton groups. These relations, however, modulate biogeochemical cycling and mediate the functioning of aquatic ecosystems as C sources or sinks to the atmosphere. The aim of this thesis was therefore to investigate how different aspects of CC influence community composition and functioning of pelagic heterotrophic bacteria. These organisms constitute a major component of biogeochemical cycling and largely determine the balance between autotrophic and heterotrophic processes.
Due to the vast amount of potential CC impacts, this thesis focuses on the following two aspects: (1) Increased exchange of CO2 across the atmosphere-water interface and reaction of CO2 with seawater leads to profound shifts in seawater carbonate chemistry, commonly termed as `ocean acidification´ (OA), with consequences for organism physiology and the availability of dissolved inorganic carbon (DIC) in seawater. (2) The increase in atmospheric GHG concentration impacts on the efficiency with which the Earth cools to space, affecting global surface temperature and climate. With ongoing CC, shifts in frequency and severity of episodic weather events, such as storms, are expected that in particular might affect lake ecosystems by disrupting thermal summer stratification. Both aspects of CC were studied at the ecosystem-level in large-volume mesocosm experiments by using the Kiel Off-shore Mesocosms for Future Ocean Simulations (KOSMOS) deployed at different coastal marine locations, and the LakeLab facility in Lake Stechlin.
We evaluated the impact of OA on heterotrophic bacterial metabolism in a brackish coastal ecosystem during low-nutrient summer months in the Baltic Sea. There are several in situ experiments that already assessed potential OA-induced changes in natural plankton communities at diverse spatial and seasonal conditions. However, most studies were performed at high phytoplankton biomass conditions, partly provoked by nutrient amendments. Our study highlights potential OA effects at low-nutrient conditions that are representative for most parts of the ocean and of particular interest in current OA research. The results suggest that during extended periods at low-nutrient concentrations, increasing pCO2 levels indirectly impact the growth balance of heterotrophic bacteria via trophic bacteria-phytoplankton interactions and shift the ecosystem to a more autotrophic system.
Further work investigated how OA affects heterotrophic bacterial dissolved organic matter (DOM) transformation in two mesocsom studies, performed at different nutrient conditions. We observed similar succession patterns for individual compound pools during a phytoplankton bloom and subsequent accumulation of these compounds irrespective of the pCO2 treatment. Our results indicate that OA-induced changes in the dynamics of bacterial DOM transformation and potential impacts on DOM quality are unlikely. In addition, there have been no indications that in dependence of nutrient conditions, different amounts of photosynthetic organic matter are channelled into the more recalcitrant DOM pool. This provides novel insights into the general dynamics of the marine DOM pool.
A fourth enclosure experiment in oligo-mesotrophic Lake Stechlin assessed the impact of a severe summer storm on lake bacterial communities during thermal stratification by artificially mixing. Mixing disrupted and lowered the thermocline, increasing the upper mixed layer and substantially changed water physical-chemical variables. Deep water entrainment and associated changes in water physical-chemical variables significantly affected relative bacterial abundances for about one week. Afterwards a pronounced cyanobacterial bloom developed in response to mixing which affected community assembly of heterotrophic bacteria. Colonization and mineralization of senescent phytoplankton cells by heterotrophic bacteria largely determined C-sequestration to the sediment. About six weeks after mixing, bacterial communities and measured activity parameters converged to control conditions. As such, summer storms have the potential to affect bacterial communities for a prolonged period during summer stratification. The results highlight effects on community assembly and heterotrophic bacterial metabolism that are associated to entrainment of deep water into the mixed water layer and assess consequences of an episodic disturbance event for the coupling between bacterial metabolism and autochthonous DOM production in large volume clear-water lakes.
Altogether, this doctoral thesis reveales substantial sensitivities of heterotrophic bacterial metabolism and community structure in response to OA and a simulated summer storm event, which should be considered when assessing the impact of climate change on marine and lake ecosystems.
Climate change, along with socio-economic development, will increase the economic impacts of floods. While the factors that influence flood risk to private property have been extensively studied, the risk that natural disasters pose to public infrastructure and the resulting implications on public sector budgets, have received less attention. We address this gap by developing a two-staged model framework, which first assesses the flood risk to public infrastructure in Austria. Combining exposure and vulnerability information at the building level with inundation maps, we project an increase in riverine flood damage, which progressively burdens public budgets. Second, the risk estimates are integrated into an insurance model, which analyzes three different compensation arrangements in terms of the monetary burden they place on future governments' budgets and the respective volatility of payments. Formalized insurance compensation arrangements offer incentives for risk reduction measures, which lower the burden on public budgets by reducing the vulnerability of buildings that are exposed to flooding. They also significantly reduce the volatility of payments and thereby improve the predictability of flood damage expenditures. These features indicate that more formalized insurance arrangements are an improvement over the purely public compensation arrangement currently in place in Austria.
The politics of zoom
(2019)
Following the mandate in the Paris Agreement for signatories to provide “climate services” to their constituents, “downscaled” climate visualizations are proliferating. But the process of downscaling climate visualizations does not neutralize the political problems with their synoptic global sources—namely, their failure to empower communities to take action and their replication of neoliberal paradigms of globalization. In this study we examine these problems as they apply to interactive climate‐visualization platforms, which allow their users to localize global climate information to support local political action. By scrutinizing the political implications of the “zoom” tool from the perspective of media studies and rhetoric, we add to perspectives of cultural cartography on the issue of scaling from our fields. Namely, we break down the cinematic trope of “zooming” to reveal how it imports the political problems of synopticism to the level of individual communities. As a potential antidote to the politics of zoom, we recommend a downscaling strategy of connectivity, which associates rather than reduces situated views of climate to global ones.
The politics of zoom
(2019)
Following the mandate in the Paris Agreement for signatories to provide “climate services” to their constituents, “downscaled” climate visualizations are proliferating. But the process of downscaling climate visualizations does not neutralize the political problems with their synoptic global sources—namely, their failure to empower communities to take action and their replication of neoliberal paradigms of globalization. In this study we examine these problems as they apply to interactive climate‐visualization platforms, which allow their users to localize global climate information to support local political action. By scrutinizing the political implications of the “zoom” tool from the perspective of media studies and rhetoric, we add to perspectives of cultural cartography on the issue of scaling from our fields. Namely, we break down the cinematic trope of “zooming” to reveal how it imports the political problems of synopticism to the level of individual communities. As a potential antidote to the politics of zoom, we recommend a downscaling strategy of connectivity, which associates rather than reduces situated views of climate to global ones.
Climate change affects societies across the globe in various ways. In addition to gradual changes in temperature and other climatic variables, global warming is likely to increase intensity and frequency of extreme weather events.
Beyond biophysical impacts, these also directly affect societal and economic activity. Additionally, indirect effects can occur; spatially, economic losses can spread along global supply-chains; temporally, climate impacts can change the economic development trajectory of countries.
This thesis first examines how climate change alters river flood risk and its local socio-economic implications. Then, it studies the global economic response to river floods in particular, and to climate change in general.
Changes in high-end river flood risk are calculated for the next three decades on a global scale with high spatial resolution. In order to account for uncertainties, this assessment makes use of an ensemble of climate and hydrological models as well as a river routing model, that is found to perform well regarding peak river discharge. The results show an increase in high-end flood risk in many parts of the world, which require profound adaptation efforts. This pressure to adapt is measured as the enhancement in protection level necessary to stay at historical high-end risk. In developing countries as well as in industrialized regions, a high pressure to adapt is observed - the former to increase low protection levels, the latter to maintain the low risk levels perceived in the past.
Further in this thesis, the global agent-based dynamic supply-chain model acclimate is developed. It models the cascading of indirect losses in the global supply network. As an anomaly model its agents - firms and consumers - maximize their profit locally to respond optimally to local perturbations. Incorporating quantities as well as prices on a daily basis, it is suitable to dynamically resolve the impacts of unanticipated climate extremes.
The model is further complemented by a static measure, which captures the inter-dependencies between sectors across regions that are only connected indirectly. These higher-order dependencies are shown to be important for a comprehensive assessment of loss-propagation and overall costs of local disasters.
In order to study the economic response to river floods, the acclimate model is driven by flood simulations. Within the next two decades, the increase in direct losses can only partially be compensated by market adjustments, and total losses are projected to increase by 17% without further adaptation efforts. The US and the EU are both shown to receive indirect losses from China, which is strongly affected directly. However, recent trends in the trade relations leave the EU in a better position to compensate for these losses.
Finally, this thesis takes a broader perspective when determining the investment response to the climate change damages employing the integrated assessment model DICE. On an optimal economic development path, the increase in damages is anticipated as emissions and consequently temperatures increase. This leads to a significant devaluation of investment returns and the income losses from climate damages almost double.
Overall, the results highlight the need to adapt to extreme weather events - local physical adaptation measures have to be combined with regional and global policy measures to prepare the global supply-chain network to climate change.
In a changing world facing several direct or indirect anthropogenic challenges the freshwater resources are endangered in quantity and quality. An excessive supply of nutrients, for example, can cause disproportional phytoplankton development and oxygen deficits in large rivers, leading to failure of the aims requested by the Water Framework Directive (WFD). Such problems can be observed in many European river catchments including the Elbe basin, and effective measures for improving water quality status are highly appreciated.
In water resources management and protection, modelling tools can help to understand the dominant nutrient processes and to identify the main sources of nutrient pollution in a watershed. They can be effective instruments for impact assessments investigating the effects of changing climate or socio-economic conditions on the status of surface water bodies, and for testing the usefulness of possible protection measures. Due to the high number of interrelated processes, ecohydrological model approaches containing water quality components are more complex than the pure hydrological ones, and their setup and calibration require more efforts. Such models, including the Soil and Water Integrated Model (SWIM), still need some further development and improvement.
Therefore, this cumulative dissertation focuses on two main objectives: 1) the approach-related objectives aiming in the SWIM model improvement and further development regarding nutrient (nitrogen and phosphorus) process description, and 2) the application-related objectives in meso- to large-scale Elbe river basins to support adaptive river basin management in view of possible future changes. The dissertation is based on five scientific papers published in international journals and dealing with these research questions.
Several adaptations were implemented in the model code to improve the representation of nutrient processes including a simple wetland approach, an extended by ammonium nitrogen cycle in the soils, as well as a detailed in-stream module, simulating algal growth, nutrient transformation processes and oxygen conditions in the river reaches, mainly driven by water temperature and light. Although this new approaches created a highly complex ecohydrological model with a large number of additional calibration parameters and rising uncertainty, the calibration and validation of the SWIM model enhanced by the new approaches in selected subcatchment and the entire Elbe river basin delivered satisfactory to good model results in terms of criteria of fit. Thus, the calibrated and validated model provided a sound base for the assessment of possible future changes and impacts in climate, land use and management in the Elbe river (sub)basin(s).
The new enhanced modelling approach improved the applicability of the SWIM model for the WFD related research questions, where the ability to consider biological water quality components (such as phytoplankton) is important. It additionally enhanced its ability to simulate the behaviour of nutrients coming mainly from point sources (e.g. phosphate phosphorus). Scenario results can be used by decision makers and stakeholders to find and understand future challenges and possible adaptation measures in the Elbe river basin.
Extreme weather events like heatwaves and floods severely affect societies with impacts ranging from economic damages to losses in human lifes. Global warming caused by anthropogenic greenhouse gas emissions is expected to increase their frequency and intensity, particularly in the warm season. Next to these thermodynamic changes, climate change might also impact the large scale atmospheric circulation.Such dynamic changes might additionally act on the occurence of extreme weather events, but involved mechanisms are often highly non-linear. Therefore, large uncertainty exists on the exact nature of these changes and the related risks to society. Particularly in the densely populated mid-latitudes weather patterns are governed by the large scale circulation like the jet-streams and storm tracks. Extreme weather in this region is often related to persistent weather systems associated with a strongly meandering jet-stream. Such meanders are called Rossby waves. Under specific conditions they can become slow moving, stretched around the entire hemisphere and generate simultaneaous heat- and rainfall extremes in far-away regions.
This thesis aims at enhancing the understanding of synoptic-scale, circumglobal Rossby waves and the associated risks of dynamical changes to society. More specific, the analyses investigate their relation to extreme weather, regions at risk, under which conditions they are generated, and the influence of anthropogenic climate change on those conditions now, in the past and in the future.
I find that circumglobal Rossby waves promoted simultaneous occuring weather extremes across the northern hemisphere in several recent summers. Further, I present evidence that they are often linked to quasiresonant-amplification of planetary waves. These events include the 2003 European heatwave and the Moscow heatwave of 2010. This non-linear mechanism acts on the upper level flow through trapping and amplification of stationary synoptic scale waves. I show that this resonance mechanism acts in both hemispheres and is related to extreme weather. A main finding is that circumglobal Rossby waves primarily occur as two specific teleconnection patterns associated with a wave 5 and wave 7 pattern in the northern hemisphere, likely due to the favourable longitudinal distance of prominent mountain ridges here. Furthermore, I identify those regions which are particularly at risk: The central United States, western Europe and the Ukraine/Russian region. Moreover, I present evidence that the wave 7 pattern has and extreme weather in these regions. My results suggest that the increase in frequency can be linked to favourable changes in large scale temperature gradients, which I show to be largely underestimated by model simulations. Using surface temperature fingerprint as proxy for investigating historic and future model ensembles, evidence is presented that anthropogenic warming has likely increased the probability for the occurence of circumglobal Rossby waves. Further it is shown that this might lead to a doubling of such events until the end of the century under a high-emission scenario.
Overall, this thesis establishes several atmosphere-dynamical pathways by which changes in large scale temperature gradients might link to persistent boreal summer weather. It highlights the societal risks associated with the increasing occurence of a newly discovered Rossby wave teleconnection pattern, which has the potential to cause simultaneaous heat-extremes in the mid-latitudinal bread-basket regions. In addition, it provides further evidence that the traditional picture by which quasi-stationary Rossby waves occur only in the low wavenumber regime, should be reconsidered.
This is a cumulative dissertation comprising three original studies (one published, one in revision, one submitted; Effective December 2017) investigating how reptile species in arid Australia respond to various climatic parameters at different spatial scales and analysing the two potential main underlying mechanisms: thermoregulatory behaviour and species interactions. This dissertation combines extensive individual-based field data across trophic levels, selected field experiments, statistical analyses, and predictive modelling techniques. Mechanisms and processes detected in this dissertation can now be used to predict potential future changes in the community of arid-zone lizards. This knowledge will help improving our fundamental understanding of the consequences of global change and thereby prevent biodiversity loss in a vulnerable ecosystem.
John Birks
(2015)
We describe the career of John Birks as a pioneering scientist who has, over a career spanning five decades, transformed palaeoecology from a largely descriptive to a rigorous quantitative science relevant to contemporary questions in ecology and environmental change. We review his influence on students and colleagues not only at Cambridge and Bergen Universities, his places of primary employment, but also on individuals and research groups in Europe and North America. We also introduce the collection of papers that we have assembled in his honour. The papers are written by his former students and close colleagues and span many of the areas of palaeoecology to which John himself has made major contributions. These include the relationship between ecology and palaeoecology, late-glacial and Holocene palaeoecology, ecological succession, climate change and vegetation history, the role of palaeoecological techniques in reconstructing and understanding the impact of human activity on terrestrial and freshwater ecosystems and numerical analysis of multivariate palaeoecological data.
In the wake of 21st century, humanity witnessed a phenomenal raise of urban agglomerations as powerhouses for innovation and socioeconomic growth. Driving much of national (and in few instances even global) economy, such a gargantuan raise of cities is also accompanied by subsequent increase in energy, resource consumption and waste generation. Much of anthropogenic transformation of Earth's environment in terms of environmental pollution at local level to planetary scale in the form of climate change is currently taking place in cities. Projected to be crucibles for entire humanity by the end of this century, the ultimate fate of humanity predominantly lies in the hands of technological innovation, urbanites' attitudes towards energy/resource consumption and development pathways undertaken by current and future cities. Considering the unparalleled energy, resource consumption and emissions currently attributed to global cities, this thesis addresses these issues from an efficiency point of view. More specifically, this thesis addresses the influence of population size, density, economic geography and technology in improving urban greenhouse gas (GHG) emission efficiency and identifies the factors leading to improved eco-efficiency in cities. In order to investigate the in uence of these factors in improving emission and resource efficiency in cities, a multitude of freely available datasets were coupled with some novel methodologies and analytical approaches in this thesis.
Merging the well-established Kaya Identity to the recently developed urban scaling laws, an Urban Kaya Relation is developed to identify whether large cities are more emission efficient and the intrinsic factors leading to such (in)efficiency. Applying Urban Kaya Relation to a global dataset of 61 cities in 12 countries, this thesis identifed that large cities in developed regions of the world will bring emission efficiency gains because of the better technologies implemented in these cities to produce and utilize energy consumption while the opposite is the case for cities in developing regions. Large cities in developing countries are less efficient mainly because of their affluence and lack of efficient technologies. Apart from the in uence of population size on emission efficiency, this thesis identified the crucial role played by population density in improving building and on-road transport sector related emission efficiency in cities. This is achieved by applying the City Clustering Algorithm (CCA) on two different gridded land use datasets and a standard emission inventory to attribute these sectoral emissions to all inhabited settlements in the USA. Results show that doubling the population density would entail a reduction in the total CO2 emissions in buildings and on-road sectors typically by at least 42 %. Irrespective of their population size and density, cities are often blamed for their intensive resource consumption that threatens not only local but also global sustainability. This thesis merged the concept of urban metabolism with benchmarking and identified cities which are eco-efficient. These cities enable better socioeconomic conditions while being less burden to the environment. Three environmental burden indicators (annual average NO2 concentration, per capita waste generation and water consumption) and two socioeconomic indicators (GDP per capita and employment ratio) for 88 most populous European cities are considered in this study. Using two different non-parametric ranking methods namely regression residual ranking and Data Envelopment Analysis (DEA), eco-efficient cities and their determining factors are identified. This in-depth analysis revealed that mature cities with well-established economic structures such as Munich, Stockholm and Oslo are eco-efficient. Further, correlations between objective eco-efficiency ranking with each of the indicator rankings and the ranking of urbanites' subjective perception about quality of life are analyzed. This analysis revealed that urbanites' perception about quality of life is not merely confined to the socioeconomic well-being but rather to their combination with lower environmental burden.
In summary, the findings of this dissertation has three general conclusions for improving emission and ecological efficiency in cities. Firstly, large cities in emerging nations face a huge challenge with respect to improving their emission efficiency. The task in front of these cities is threefold: (1) deploying efficient technologies for the generation of electricity and improvement of public transportation to unlock their leap frogging potential, (2) addressing the issue of energy poverty and (3) ensuring that these cities do not develop similar energy consumption patterns with infrastructure lock-in behavior similar to those of cities in developed regions. Secondly, the on-going urban sprawl as a global phenomenon will decrease the emission efficiency within the building and transportation sector. Therefore, local policy makers should identify adequate fiscal and land use policies to curb urban sprawl. Lastly, since mature cities with well-established economic structures are more eco-efficient and urbanites' perception re ects its combination with decreasing environmental burden; there is a need to adopt and implement strategies which enable socioeconomic growth in cities whilst decreasing their environment burden.
More than a billion people rely on water from rivers sourced in High Mountain Asia (HMA), a significant portion of which is derived from snow and glacier melt. Rural communities are heavily dependent on the consistency of runoff, and are highly vulnerable to shifts in their local environment brought on by climate change. Despite this dependence, the impacts of climate change in HMA remain poorly constrained due to poor process understanding, complex terrain, and insufficiently dense in-situ measurements.
HMA's glaciers contain more frozen water than any region outside of the poles. Their extensive retreat is a highly visible and much studied marker of regional and global climate change. However, in many catchments, snow and snowmelt represent a much larger fraction of the yearly water budget than glacial meltwaters. Despite their importance, climate-related changes in HMA's snow resources have not been well studied.
Changes in the volume and distribution of snowpack have complex and extensive impacts on both local and global climates. Eurasian snow cover has been shown to impact the strength and direction of the Indian Summer Monsoon -- which is responsible for much of the precipitation over the Indian Subcontinent -- by modulating earth-surface heating. Shifts in the timing of snowmelt have been shown to limit the productivity of major rangelands, reduce streamflow, modify sediment transport, and impact the spread of vector-borne diseases. However, a large-scale regional study of climate impacts on snow resources had yet to be undertaken.
Passive Microwave (PM) remote sensing is a well-established empirical method of studying snow resources over large areas. Since 1987, there have been consistent daily global PM measurements which can be used to derive an estimate of snow depth, and hence snow-water equivalent (SWE) -- the amount of water stored in snowpack. The SWE estimation algorithms were originally developed for flat and even terrain -- such as the Russian and Canadian Arctic -- and have rarely been used in complex terrain such as HMA.
This dissertation first examines factors present in HMA that could impact the reliability of SWE estimates. Forest cover, absolute snow depth, long-term average wind speeds, and hillslope angle were found to be the strongest controls on SWE measurement reliability. While forest density and snow depth are factors accounted for in modern SWE retrieval algorithms, wind speed and hillslope angle are not. Despite uncertainty in absolute SWE measurements and differences in the magnitude of SWE retrievals between sensors, single-instrument SWE time series were found to be internally consistent and suitable for trend analysis.
Building on this finding, this dissertation tracks changes in SWE across HMA using a statistical decomposition technique. An aggregate decrease in SWE was found (10.6 mm/yr), despite large spatial and seasonal heterogeneities. Winter SWE increased in almost half of HMA, despite general negative trends throughout the rest of the year. The elevation distribution of these negative trends indicates that while changes in SWE have likely impacted glaciers in the region, climate change impacts on these two pieces of the cryosphere are somewhat distinct.
Following the discussion of relative changes in SWE, this dissertation explores changes in the timing of the snowmelt season in HMA using a newly developed algorithm. The algorithm is shown to accurately track the onset and end of the snowmelt season (70% within 5 days of a control dataset, 89% within 10). Using a 29-year time series, changes in the onset, end, and duration of snowmelt are examined. While nearly the entirety of HMA has experienced an earlier end to the snowmelt season, large regions of HMA have seen a later start to the snowmelt season. Snowmelt periods have also decreased in almost all of HMA, indicating that the snowmelt season is generally shortening and ending earlier across HMA.
By examining shifts in both the spatio-temporal distribution of SWE and the timing of the snowmelt season across HMA, we provide a detailed accounting of changes in HMA's snow resources. The overall trend in HMA is towards less SWE storage and a shorter snowmelt season. However, long-term and regional trends conceal distinct seasonal, temporal, and spatial heterogeneity, indicating that changes in snow resources are strongly controlled by local climate and topography, and that inter-annual variability plays a significant role in HMA's snow regime.
Understanding the distribution of species is fundamental for biodiversity conservation, ecosystem management, and increasingly also for climate impact assessment. The presence of a species in a given site depends on physiological limitations (abiotic factors), interactions with other species (biotic factors), migratory or dispersal processes (site accessibility) as well as the continuing
effects of past events, e.g. disturbances (site legacy). Existing approaches to predict species distributions either (i) correlate observed species occurrences with environmental variables describing abiotic limitations, thus ignoring biotic interactions, dispersal and legacy effects (statistical species distribution model, SDM); or (ii) mechanistically model the variety of processes determining species distributions (process-based model, PBM). SDMs are widely used due to their easy applicability and ability to handle varied data qualities. But they fail to reproduce the dynamic response of species distributions to changing conditions. PBMs are expected to be superior in this respect, but they need very specific data unavailable for many species, and are often more complex and require more computational effort. More recently, hybrid models link the two approaches to combine their respective strengths.
In this thesis, I apply and compare statistical and process-based approaches to predict species distributions, and I discuss their respective limitations, specifically for applications in changing environments. Detailed analyses of SDMs for boreal tree species in Finland reveal that nonclimatic predictors - edaphic properties and biotic interactions - are important limitations at the treeline, contesting the assumption of unrestricted, climatically induced range expansion. While the estimated SDMs are successful within their training data range, spatial and temporal model transfer fails. Mapping and comparing sampled predictor space among data subsets identifies spurious extrapolation as the plausible explanation for limited model transferability. Using these findings, I analyze the limited success of an established PBM (LPJ-GUESS) applied to the same problem. Examination of process representation and parameterization in the PBM identifies implemented processes to adjust (competition between species, disturbance) and missing processes that are crucial in boreal forests (nutrient limitation, forest management). Based on climatic correlations shifting over time, I stress the restricted temporal transferability of bioclimatic limits used in LPJ-GUESS and similar PBMs. By critically assessing the performance of SDM and PBM in this application, I demonstrate the importance of understanding the limitations of the
applied methods.
As a potential solution, I add a novel approach to the repertoire of existing hybrid models. By simulation experiments with an individual-based PBM which reproduces community dynamics resulting from biotic factors, dispersal and legacy effects, I assess the resilience of coastal vegetation to abrupt hydrological changes. According to the results of the resilience analysis, I then modify temporal SDM predictions, thereby transferring relevant process detail from PBM to
SDM. The direction of knowledge transfer from PBM to SDM avoids disadvantages of current hybrid models and increases the applicability of the resulting model in long-term, large-scale applications. A further advantage of the proposed framework is its flexibility, as it is readily extended to other model types, disturbance definitions and response characteristics.
Concluding, I argue that we already have a diverse range of promising modelling tools at hand, which can be refined further. But most importantly, they need to be applied more thoughtfully. Bearing their limitations in mind, combining their strengths and openly reporting underlying assumptions and uncertainties is the way forward.
Model-Based attribution of high-resolution streamflow trends in two alpine basins of Western Austria
(2017)
Several trend studies have shown that hydrological conditions are changing considerably in the Alpine region. However, the reasons for these changes are only partially understood and trend analyses alone are not able to shed much light. Hydrological modelling is one possible way to identify the trend drivers, i.e., to attribute the detected streamflow trends, given that the model captures all important processes causing the trends. We modelled the hydrological conditions for two alpine catchments in western Austria (a large, mostly lower-altitude catchment with wide valley plains and a nested high-altitude, glaciated headwater catchment) with the distributed, physically-oriented WaSiM-ETH model, which includes a dynamical glacier module. The model was calibrated in a transient mode, i.e., not only on several standard goodness measures and glacier extents, but also in such a way that the simulated streamflow trends fit with the observed ones during the investigation period 1980 to 2007. With this approach, it was possible to separate streamflow components, identify the trends of flow components, and study their relation to trends in atmospheric variables. In addition to trends in annual averages, highly resolved trends for each Julian day were derived, since they proved powerful in an earlier, data-based attribution study. We were able to show that annual and highly resolved trends can be modelled sufficiently well. The results provide a holistic, year-round picture of the drivers of alpine streamflow changes: Higher-altitude catchments are strongly affected by earlier firn melt and snowmelt in spring and increased ice melt throughout the ablation season. Changes in lower-altitude areas are mostly caused by earlier and lower snowmelt volumes. All highly resolved trends in streamflow and its components show an explicit similarity to the local temperature trends. Finally, results indicate that evapotranspiration has been increasing in the lower altitudes during the study period.
Meteorological extreme events have great potential for damaging railway infrastructure and posing risks to the safety of train passengers. In the future, climate change will presumably have serious implications on meteorological hazards in the Alpine region. Hence, attaining insights on future frequencies of meteorological extremes with relevance for the railway operation in Austria is required in the context of a comprehensive and sustainable natural hazard management plan of the railway operator. In this study, possible impacts of climate change on the frequencies of so-called critical meteorological conditions (CMCs) between the periods 1961-1990 and 2011-2040 are analyzed. Thresholds for such CMCs have been defined by the railway operator and used in its weather monitoring and early warning system. First, the seasonal climate change signals for air temperature and precipitation in Austria are described on the basis of an ensemble of high-resolution Regional Climate Model (RCM) simulations for Europe. Subsequently, the RCM-ensemble was used to investigate changes in the frequency of CMCs. Finally, the sensitivity of results is analyzed with varying threshold values for the CMCs. Results give robust indications for an all-season air temperature rise, but show no clear tendency in average precipitation. The frequency analyses reveal an increase in intense rainfall events and heat waves, whereas heavy snowfall and cold days are likely to decrease. Furthermore, results indicate that frequencies of CMCs are rather sensitive to changes of thresholds. It thus emphasizes the importance to carefully define, validate, andif neededto adapt the thresholds that are used in the weather monitoring and warning system of the railway operator. For this, continuous and standardized documentation of damaging events and near-misses is a pre-requisite.
Climate change is acting on several aspects of plant life cycles, including the sexual reproductive stage, which is considered amongst the most sensitive life-cycle phases. In temperate forests, it is expected that climate change will lead to a compositional change in community structure due to changes in the dominance of currently more abundant forest tree species. Increasing our understanding of the effects of climate change on currently secondary tree species recruitment is therefore important to better understand and forecast population and community dynamics in forests. Here, we analyse the interactive effects of rising temperatures and soil moisture reduction on germination, seedling survival and early growth of two important secondary European tree species, Acer pseudoplatanus and A.platanoides. Additionally, we analyse the effect of the temperature experienced by the mother tree during seed production by collecting seeds of both species along a 2200-km long latitudinal gradient. For most of the responses, A.platanoides showed higher sensitivity to the treatments applied, and especially to its joint manipulation, which for some variables resulted in additive effects while for others only partial compensation. In both species, germination and survival decreased with rising temperatures and/or soil moisture reduction while early growth decreased with declining soil moisture content. We conclude that although A.platanoides germination and survival were more affected after the applied treatments, its initial higher germination and larger seedlings might allow this species to be relatively more successful than A.pseudoplatanus in the face of climate change.
BACKGROUND Central European outbreak populations of the bank vole (Myodes glareolus Schreber) are known to cause damage in forestry and to transmit the most common type of Hantavirus (Puumala virus, PUUV) to humans. A sound estimation of potential effects of future climate scenarios on population dynamics is a prerequisite for long-term management strategies. Historic abundance time series were used to identify the key weather conditions associated with bank vole abundance, and were extrapolated to future climate scenarios to derive potential long-term changes in bank vole abundance dynamics.
RESULTS Classification and regression tree analysis revealed the most relevant weather parameters associated with high and low bank vole abundances. Summer temperatures 2 years prior to trapping had the highest impact on abundance fluctuation. Extrapolation of the identified parameters to future climate conditions revealed an increase in years with high vole abundance.
CONCLUSION Key weather patterns associated with vole abundance reflect the importance of superabundant food supply through masting to the occurrence of bank vole outbreaks. Owing to changing climate, these outbreaks are predicted potentially to increase in frequency 3-4-fold by the end of this century. This may negatively affect damage patterns in forestry and the risk of human PUUV infection in the long term. (c) 2014 Society of Chemical Industry
Climate impacts on transocean dispersal and habitat in gray whales from the Pleistocene to 2100
(2015)
Arctic animals face dramatic habitat alteration due to ongoing climate change. Understanding how such species have responded to past glacial cycles can help us forecast their response to today's changing climate. Gray whales are among those marine species likely to be strongly affected by Arctic climate change, but a thorough analysis of past climate impacts on this species has been complicated by lack of information about an extinct population in the Atlantic. While little is known about the history of Atlantic gray whales or their relationship to the extant Pacific population, the extirpation of the Atlantic population during historical times has been attributed to whaling. We used a combination of ancient and modern DNA, radiocarbon dating and predictive habitat modelling to better understand the distribution of gray whales during the Pleistocene and Holocene. Our results reveal that dispersal between the Pacific and Atlantic was climate dependent and occurred both during the Pleistocene prior to the last glacial period and the early Holocene immediately following the opening of the Bering Strait. Genetic diversity in the Atlantic declined over an extended interval that predates the period of intensive commercial whaling, indicating this decline may have been precipitated by Holocene climate or other ecological causes. These first genetic data for Atlantic gray whales, particularly when combined with predictive habitat models for the year 2100, suggest that two recent sightings of gray whales in the Atlantic may represent the beginning of the expansion of this species' habitat beyond its currently realized range.
Climate forecasts project further increases in extremely high-temperature events. These present threats to biodiversity, as they promote population declines and local species extinctions. This implies that ecological communities will need to rely more strongly on recovery processes, such as recolonization from a meta-community context. It is poorly understood how differences in extreme event intensity change the outcome of subsequent community reassembly and if such extremes modify the biotic environment in ways that would prevent the successful re-establishment of lost species. We studied replicated aquatic communities consisting of algae and herbivorous rotifers in a design that involved a control and two different heat wave intensity treatments (29 degrees C and 39 degrees C). Animal species that suffered heat-induced extinction were subsequently re-introduced at the same time and density, in each of the two treatments. The 39 degrees C treatment led to community closure in all replicates, meaning that a previously successful herbivore species could not re-establish itself in the postheat wave community. In contrast, such closure never occurred after a 29 degrees C event. Heat wave intensity determined the number of herbivore extinctions and strongly affected algal relative abundances. Re-introduced herbivore species were thus confronted with significantly different food environments. This ecological legacy generated by heat wave intensity led to differences in the failure or success of herbivore species re-introductions. Reassembly was significantly more variable, and hence less predictable, after an extreme heat wave, and was more canalized after a moderate one. Our results pertain to relatively simple communities, but they suggest that ecological legacies introduced by extremely high-temperature events may change subsequent ecological recovery and even prevent the successful re-establishment of lost species. Knowing the processes promoting and preventing ecological recovery is crucial to the success of species re-introduction programs and to our ability to restore ecosystems damaged by environmental extremes.
Extreme droughts, heat waves, frosts, precipitation, wind storms and other climate extremes may impact the structure, composition and functioning of terrestrial ecosystems, and thus carbon cycling and its feedbacks to the climate system. Yet, the interconnected avenues through which climate extremes drive ecological and physiological processes and alter the carbon balance are poorly understood. Here, we review the literature on carbon cycle relevant responses of ecosystems to extreme climatic events. Given that impacts of climate extremes are considered disturbances, we assume the respective general disturbance-induced mechanisms and processes to also operate in an extreme context. The paucity of well-defined studies currently renders a quantitative meta-analysis impossible, but permits us to develop a deductive framework for identifying the main mechanisms (and coupling thereof) through which climate extremes may act on the carbon cycle. We find that ecosystem responses can exceed the duration of the climate impacts via lagged effects on the carbon cycle. The expected regional impacts of future climate extremes will depend on changes in the probability and severity of their occurrence, on the compound effects and timing of different climate extremes, and on the vulnerability of each land-cover type modulated by management. Although processes and sensitivities differ among biomes, based on expert opinion, we expect forests to exhibit the largest net effect of extremes due to their large carbon pools and fluxes, potentially large indirect and lagged impacts, and long recovery time to regain previous stocks. At the global scale, we presume that droughts have the strongest and most widespread effects on terrestrial carbon cycling. Comparing impacts of climate extremes identified via remote sensing vs. ground-based observational case studies reveals that many regions in the (sub-)tropics are understudied. Hence, regional investigations are needed to allow a global upscaling of the impacts of climate extremes on global carbon-climate feedbacks.
Carbon storage capacity of semi-arid grassland soils and sequestration potentials in northern China
(2015)
Organic carbon (OC) sequestration in degraded semi-arid environments by improved soil management is assumed to contribute substantially to climate change mitigation. However, information about the soil organic carbon (SOC) sequestration potential in steppe soils and their current saturation status remains unknown. In this study, we estimated the OC storage capacity of semi-arid grassland soils on the basis of remote, natural steppe fragments in northern China. Based on the maximum OC saturation of silt and clay particles <20m, OC sequestration potentials of degraded steppe soils (grazing land, arable land, eroded areas) were estimated. The analysis of natural grassland soils revealed a strong linear regression between the proportion of the fine fraction and its OC content, confirming the importance of silt and clay particles for OC stabilization in steppe soils. This relationship was similar to derived regressions in temperate and tropical soils but on a lower level, probably due to a lower C input and different clay mineralogy. In relation to the estimated OC storage capacity, degraded steppe soils showed a high OC saturation of 78-85% despite massive SOC losses due to unsustainable land use. As a result, the potential of degraded grassland soils to sequester additional OC was generally low. This can be related to a relatively high contribution of labile SOC, which is preferentially lost in the course of soil degradation. Moreover, wind erosion leads to substantial loss of silt and clay particles and consequently results in a direct loss of the ability to stabilize additional OC. Our findings indicate that the SOC loss in semi-arid environments induced by intensive land use is largely irreversible. Observed SOC increases after improved land management mainly result in an accumulation of labile SOC prone to land use/climate changes and therefore cannot be regarded as contribution to long-term OC sequestration.
The response of surface processes to climatic forcing is fundamental for understanding the impacts of climate change on landscape evolution. In the Himalaya, most large rivers feature prominent fill terraces that record an imbalance between sediment supply and transport capacity, presumably due to past fluctuations in monsoon precipitation and/or effects of glaciation at high elevation. Here, we present volume estimates, chronological constraints, and Be-10-derived paleo-erosion rates from a prominent valley fill in the Yamuna catchment, Garhwal Himalaya, to elucidate the coupled response of rivers and hillslopes to Pleistocene climate change. Although precise age control is complicated due to methodological problems, the new data support formation of the valley fill during the late Pleistocene and its incision during the Holocene. We interpret this timing to indicate that changes in discharge and river-transport capacity were major controls. Compared to the present day, late Pleistocene hillslope erosion rates were higher by a factor of similar to 2-4, but appear to have decreased during valley aggradation. The higher late Pleistocene erosion rates are largely unrelated to glacial erosion and could be explained by enhanced sediment production on steep hillslopes due to increased periglacial activity that declined as temperatures increased. Alternatively, erosion rates that decrease during valley aggradation are also consistent with reduced landsliding from threshold hillslopes as a result of rising base levels. In that case, the similarity of paleo-erosion rates near the end of the aggradation period with modern erosion rates might imply that channels and hillslopes are not yet fully coupled everywhere and that present-day hillslope erosion rates may underrepresent long-term incision rates. (C) 2015 Elsevier B.V. All rights reserved.
Anthropogenic carbon emissions lock in long-term sea-level rise that greatly exceeds projections for this century, posing profound challenges for coastal development and cultural legacies. Analysis based on previously published relationships linking emissions to warming and warming to rise indicates that unabated carbon emissions up to the year 2100 would commit an eventual global sea-level rise of 4.3-9.9 m. Based on detailed topographic and population data, local high tide lines, and regional long-term sea-level commitment for different carbon emissions and ice sheet stability scenarios, we compute the current population living on endangered land at municipal, state, and national levels within the United States. For unabated climate change, we find that land that is home to more than 20 million people is implicated and is widely distributed among different states and coasts. The total area includes 1,185-1,825 municipalities where land that is home to more than half of the current population would be affected, among them at least 21 cities exceeding 100,000 residents. Under aggressive carbon cuts, more than half of these municipalities would avoid this commitment if the West Antarctic Ice Sheet remains stable. Similarly, more than half of the US population-weighted area under threat could be spared. We provide lists of implicated cities and state populations for different emissions scenarios and with and without a certain collapse of the West Antarctic Ice Sheet. Although past anthropogenic emissions already have caused sea-level commitment that will force coastal cities to adapt, future emissions will determine which areas we can continue to occupy or may have to abandon.
The amount of terrestrial particulate organic matter (t-POM) entering lakes is predicted to increase as a result of climate change. This may especially alter the structure and functioning of ecosystems in small, shallow lakes which can rapidly shift from a clear-water, macrophyte-dominated into a turbid, phytoplankton-dominated state. We used the integrative ecosystem model PCLake to predict how rising t-POM inputs affect the resilience of the clear-water state. PCLake links a pelagic and benthic food chain with abiotic components by a number of direct and indirect effects. We focused on three pathways (zoobenthos, zooplankton, light availability) by which elevated t-POM inputs (with and without additional nutrients) may modify the critical nutrient loading thresholds at which a clear-water lake becomes turbid and vice versa. Our model results show that (1) increased zoobenthos biomass due to the enhanced food availability results in more benthivorous fish which reduce light availability due to bioturbation, (2) zooplankton biomass does not change, but suspended t-POM reduces the consumption of autochthonous particulate organic matter which increases the turbidity, and (3) the suspended t-POM reduces the light availability for submerged macrophytes. Therefore, light availability is the key process that is indirectly or directly changed by t-POM input. This strikingly resembles the deteriorating effect of terrestrial dissolved organic matter on the light climate of lakes. In all scenarios, the resilience of the clear-water state is reduced thus making the turbid state more likely at a given nutrient loading. Therefore, our study suggests that rising t-POM input can add to the effects of climate warming making reductions in nutrient loadings even more urgent.
The weather in Eurasia, Australia, and North and South America is largely controlled by the strength and position of extratropical storm tracks. Future climate change will likely affect these storm tracks and the associated transport of energy, momentum, and water vapour. Many recent studies have analyzed how storm tracks will change under climate change, and how these changes are related to atmospheric dynamics. However, there are still discrepancies between different studies on how storm tracks will change under future climate scenarios. Here, we show that under global warming the CMIP5 ensemble of coupled climate models projects only little relative changes in vertically averaged mid-latitude mean storm track activity during the northern winter, but agree in projecting a substantial decrease during summer. Seasonal changes in the Southern Hemisphere show the opposite behaviour, with an intensification in winter and no change during summer. These distinct seasonal changes in northern summer and southern winter storm tracks lead to an amplified seasonal cycle in a future climate. Similar changes are seen in the mid-latitude mean Eady growth rate maximum, a measure that combines changes in vertical shear and static stability based on baroclinic instability theory. Regression analysis between changes in the storm tracks and changes in the maximum Eady growth rate reveal that most models agree in a positive association between the two quantities over mid-latitude regions.
Cellulose delta O-18 is an index of leaf-to-air vapor pressure difference (VPD) in tropical plants
(2011)
Cellulose in plants contains oxygen that derives in most cases from precipitation. Because the stable oxygen isotope composition, delta O-18, of precipitation is associated with environmental conditions, cellulose delta O-18 should be as well. However, plant physiological models using delta O-18 suggest that cellulose delta O-18 is influenced by a complex mix of both climatic and physiological drivers. This influence complicates the interpretation of cellulose delta O-18 values in a paleo-context. Here, we combined empirical data analyses with mechanistic model simulations to i) quantify the impacts that the primary climatic drivers humidity (e(a)) and air temperature (T-air) have on cellulose delta O-18 values in different tropical ecosystems and ii) determine which environmental signal is dominating cellulose delta O-18 values. Our results revealed that e(a) and T-air equally influence cellulose delta O-18 values and that distinguishing which of these factors dominates the delta O-18 values of cellulose cannot be accomplished in the absence of additional environmental information. However, the individual impacts of e(a) and T-air on the delta O-18 values of cellulose can be integrated into a single index of plant-experienced atmospheric vapor demand: the leaf-to-air vapor pressure difference (VPD). We found a robust relationship between VPD and cellulose delta O-18 values in both empirical and modeled data in all ecosystems that we investigated. Our analysis revealed therefore that delta O-18 values in plant cellulose can be used as a proxy for VPD in tropical ecosystems. As VPD is an essential variable that determines the biogeochemical dynamics of ecosystems, our study has applications in ecological-, climate-, or forensic-sciences.