Wetlands through time – modeling changes in area and greenhouse gas budgets from the past to the future

The accelerated burning of fossil fuels and the large-scale transformation of forests into agricultural land since the industrial revolution have led to rapid climate warming which, if not mitigated, is threatening human life on Earth. The field of climate science strives to better understand the complex climate system and its internal feedbacks and with that be able to provide reliable projections of future changes. These depend most and foremost on societal and political dynamics. In the Paris Agreement, the global community has committed to limit warming below 2◦ C, which requires global net-zero greenhouse gas emissions until the year 2050. However, global efforts to reduce emissions are still by far insufficient to reach the agreed target. Although climate science long has identified immediate emission reduction as the most important mitigation strategy, a multitude of internal feedbacks and processes are still poorly understood. This creates the need for further investigations into potential impacts of past and future emissions, not only on the climate but also on the global biosphere, including potential irreversible tipping points or mitigation opportunities. One important sub-system of the global climate system and carbon cycle that is expected to see increased pressures from anthropogenic disturbance and climate warming are global wetlands. Wetlands are sources of methane, an important greenhouse gas, and thus hold the potential to contribute to future warming. A special type of wetlands, peatlands, also act as long-term carbon stores and thus could both help to remove anthropogenic carbon from the atmosphere on long timescales or lead to large additional release of carbon into the atmosphere. This thesis presents model investigations of wetland dynamics, using the dynamic global vegetation model LPX-Bern, which is developed and maintained at the University of Bern. LPX-Bern is used to investigate changes in wetland area and greenhouse gas budgets from the past to the future, with a particular focus on peatlands. Chapter 1 gives an introduction to the key concepts discussed in this thesis. First, the global carbon cycle and its different components are introduced. Then wetlands, the main subject of this thesis, are defined and discussed in detail. Wetlands are a key component of the global carbon cycle as they function both as large carbon stores and sources of methane. The history of wetlands and their reconstruction through proxy evidence is discussed in the context of past climate variability. The past and potential future effects of human activities on wetlands are examined. Finally, the world of wetland modeling is introduced, giving an overview of the historic model development and different model complexities. Chapter 2 then introduces the LPX-Bern and presents model adjustments that were implemented during this thesis. The modules representing peatlands and wetlands are discussed in detail, including the formulation for the dynamic calculation of wetland and peatland area and the new treatment of dynamic peatland area in case of prescribed land-use change. The discussion of the methane module includes the emission calculation for different types of wetlands, the implementation of methane emissions from fires, and the description of a re-calibration of key emission factors in preparation for the different modeling studies presented in the following chapters. In chapter 3, a modeling study published in Biogeosciences is presented which investigates the transient history of peatlands from the Last Glacial Maximum (LGM), about 21,000 years ago, to the present. Transient LPX-Bern simulations suggest that peatland area was highly dynamic in the past and changes in area were driven mostly by changes in precipitation and temperature. The study argues that to determine the net peat carbon balance, the full history of peatlands has to be considered, including peatlands that vanished over time. The simulated transient evolution of today’s northern peatlands is compared to data reconstructions and large model-data mismatches are found concerning the inception of peat in northern Asia. However, the simulated peatland distribution and carbon storage at present-day compare well to literature estimates. Additional time-slice simulations at the LGM show that uncertainties in the prescribed climate forcing propagate to large uncertainties in peatland variables. Chapter 4 presents a follow-up study published in Biogeosciences which directly builds on results from the study presented in chapter 3. The transient simulation from the LGM to the present is taken as the basis for future projections of peatland dynamics. Different future climate and land-use scenarios are used to investigate potential future short-term and long-term changes in peatland area and carbon storage. The results suggest likely future losses of global peatland area and carbon, even under present-day climate, with large parts of today’s northern peatlands at risk. Losses in response to future climate and land-use change are expected to increase with increasing future emissions. Uncertainties connected to uncertain climate anomalies are quantified by using output from a climate model ensemble as forcing. In chapter 5, model investigations into past wetland methane emissions are presented. Results from transient LPX-Bern simulations from the LGM to the present are compared to the methane ice-core record. Large model-data mismatches are found, most notably the absence of a simulated increase in emissions from the LGM to the pre-industrial period (PI). Driver attribution reveals a small temperature sensitivity and large sea-level driven tropical wetland loss as potential sources of the small LGM-PI methane emission increase. Preliminary investigations into model adjustments, addressing the temperature dependence of methane production and the dynamic wetland model, show potential to increase the LGM-PI methane emission rise, but alone are not sufficient to close the model-date gap. Furthermore, the discussed model changes could worsen model performance in other respects which would need to be addressed. Chapter 6 presents a selection of two collaborative studies for which LPX-Bern model output was provided. First, simulations that contributed to the Global Methane Budget, a community publication that is part of the Global Carbon Project, are discussed in detail, with a focus on comparing wetland methane emissions between LPX-Bern simulations with prescribed and dynamically calculated wetland area. Emissions are found to be globally comparable, but with regional biases in wetland prediction translating into large regional differences in simulated emissions. In the second part, simulations are presented that contributed to a model-intercomparison project investigating projected future changes in peatland net carbon balance and methane emissions under different scenarios. The LPX-Bern simulations in this study, where the peatland area is prescribed, are compared to similar LPX-Bern simulations from chapter 4, where the peatland area is calculated dynamically. Future peatland area loss is found to mostly lead to larger predicted carbon loss but also smaller peatland methane emissions than if peatland area is held constant. Finally, Chapter 7 gives an outlook over potential future model investigations and model development, progressing and building on the work presented in this thesis. An additional appendix describes the implementation of a new transient land-sea-ice mask for paleo simulations into the LPX-Bern, which however was not used in any simulations presented in the main text. The new implementation increases the update time-step and allows for variable grid cell land fractions

Committed and projected future changes in global peatlands – continued transient model simulations since the Last Glacial Maximum

Peatlands are diverse wetland ecosystems distributed mostly over the northern latitudes and tropics. Globally they store a large portion of the global soil organic carbon and provide important ecosystem services. The future of these systems under continued anthropogenic warming and direct human disturbance has potentially large impacts on atmospheric CO2 and climate. We performed global long-term projections of peatland area and carbon over the next 5000 years using a dynamic global vegetation model forced with climate anomalies from 10 models of the Coupled Model Intercomparison Project (CMIP6) and three standard future scenarios. These projections are seamlessly continued from a transient simulation from the Last Glacial Maximum to the present to account for the full transient history and are continued beyond 2100 with constant boundary conditions. Our results suggest short to long-term net losses of global peatland area and carbon, with higher losses under higher-emission scenarios. Large parts of today's active northern peatlands are at risk, whereas peatlands in the tropics and, in case of mitigation, eastern Asia and western North America can increase their area and carbon stocks. Factorial simulations reveal committed historical changes and future rising temperature as the main driver of future peatland loss and increasing precipitations as the driver for regional peatland expansion. Additional simulations forced with climate anomalies from a subset of climate models which follow the extended CMIP6 scenarios, transient until 2300, show qualitatively similar results to the standard scenarios but highlight the importance of extended transient future scenarios for long-term carbon cycle projections. The spread between simulations forced with different climate model anomalies suggests a large uncertainty in projected peatland changes due to uncertain climate forcing. Our study highlights the importance of quantifying the future peatland feedback to the climate system and its inclusion into future earth system model projections

An Empirical Analysis of the Perceived Usefulness of Digital Governance Tools among Heterogeneous Swiss Municipalities

Digital governance tools have the potential to enable more efficient and less error-prone governance processes. However, the heterogeneity among municipalities might affect their willingness and purposes to use such tools, for which we have limited evidence. This study analyzes results from a survey among Swiss municipalities with different population sizes, focusing on their evaluation and prioritization of digital governance tools. The results show that for some governance areas, such as strategy formation & monitoring and project portfolio management, the perceived usefulness of these tools increases with municipality size, while the perceived use of them for data collection is generally lower. Smaller municipalities are more likely to reject new digital governance tools, with a general skepticism of the usefulness and the financial situation indicated as the most common reasons. Medium to large municipalities show additional reasons for the rejection, rooted in their more prevalent previous or current use of digital tools

Efficient Neural Ranking using Forward Indexes and Lightweight Encoders

Dual-encoder-based dense retrieval models have become the standard in IR. They employ large Transformer-based language models, which are notoriously inefficient in terms of resources and latency. We propose Fast-Forward indexes -- vector forward indexes which exploit the semantic matching capabilities of dual-encoder models for efficient and effective re-ranking. Our framework enables re-ranking at very high retrieval depths and combines the merits of both lexical and semantic matching via score interpolation. Furthermore, in order to mitigate the limitations of dual-encoders, we tackle two main challenges: Firstly, we improve computational efficiency by either pre-computing representations, avoiding unnecessary computations altogether, or reducing the complexity of encoders. This allows us to considerably improve ranking efficiency and latency. Secondly, we optimize the memory footprint and maintenance cost of indexes; we propose two complementary techniques to reduce the index size and show that, by dynamically dropping irrelevant document tokens, the index maintenance efficiency can be improved substantially. We perform evaluation to show the effectiveness and efficiency of Fast-Forward indexes -- our method has low latency and achieves competitive results without the need for hardware acceleration, such as GPUs.Comment: Accepted at ACM TOIS. arXiv admin note: text overlap with arXiv:2110.0605

The global methane budget 2000–2017

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning

A strong mitigation scenario maintains climate neutrality of northern peatlands

Northern peatlands store 300–600 Pg C, of which approximately half are underlain by permafrost. Climate warming and, in some regions, soil drying from enhanced evaporation are progressively threatening this large carbon stock. Here, we assess future CO2 and CH4 fluxes from northern peatlands using five land surface models that explicitly include representation of peatland processes. Under Representative Concentration Pathways (RCP) 2.6, northern peatlands are projected to remain a net sink of CO2 and climate neutral for the next three centuries. A shift to a net CO2 source and a substantial increase in CH4 emissions are projected under RCP8.5, which could exacerbate global warming by 0.21°C (range, 0.09–0.49°C) by the year 2300. The true warming impact of peatlands might be higher owing to processes not simulated by the models and direct anthropogenic disturbance. Our study highlights the importance of understanding how future warming might trigger high carbon losses from northern peatlands

Interaktive Visualisierung zeigt, wie National- und Ständerat zusammen arbeiten

Im Herbst stehen die Nationalratswahlen bevor. Höchste Zeit also Bilanz zu ziehen und mal einen Blick hinter die Kulissen des Parlaments zu werfen: Arbeiten die verschiedenen Parteien eigentlich gegeneinander oder miteinander? Und zu welchen Themen? Und wer sind die aktivsten oder faulsten Ratsmitglieder? Diese und viele weitere Fragen lassen sich nun auf spielerische Art und in Eigenregie erforschen – dank einer interaktiven Visualisierung des Instituts Public Sector Transformation der BFH