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Predicting spatiotemporal variability in radial tree growth at the continental scale with machine learning
- Paul Bodesheim, Flurin Babst, David C. Frank, Claudia Hartl, Christian S. Zang, Martin Jung, Markus Reichstein, Miguel D. Mahecha
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- Journal:
- Environmental Data Science / Volume 1 / 2022
- Published online by Cambridge University Press:
- 22 June 2022, e9
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- Article
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Tree-ring chronologies encode interannual variability in forest growth rates over long time periods from decades to centuries or even millennia. However, each chronology is a highly localized measurement describing conditions at specific sites where wood samples have been collected. The question whether these local growth variabilites are representative for large geographical regions remains an open issue. To overcome the limitations of interpreting a sparse network of sites, we propose an upscaling approach for annual tree-ring indices that approximate forest growth variability and compute gridded data products that generalize the available information for multiple tree genera. Using regression approaches from machine learning, we predict tree-ring indices in space and time based on climate variables, but considering also species range maps as constraints for the upscaling. We compare various prediction strategies in cross-validation experiments to identify the best performing setup. Our estimated maps of tree-ring indices are the first data products that provide a dense view on forest growth variability at the continental level with 0.5° and 0.0083° spatial resolution covering the years 1902–2013. Furthermore, we find that different genera show very variable spatial patterns of anomalies. We have selected Europe as study region and focused on the six most prominent tree genera, but our approach is very generic and can easily be applied elsewhere. Overall, the study shows perspectives but also limitations for reconstructing spatiotemporal dynamics of complex biological processes. The data products are available at https://www.doi.org/10.17871/BACI.248.
Chapter 3 - Changes in Climate Extremes and their Impacts on the Natural Physical Environment
- from Section III
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- By Sonia I. Seneviratne, Neville Nicholls, David Easterling, Clare M. Goodess, Shinjiro Kanae, James Kossin, Yali Luo, Jose Marengo, Kathleen McInnes, Mohammad Rahimi, Markus Reichstein, Asgeir Sorteberg, Carolina Vera, Xuebin Zhang, Matilde Rusticucci, Vladimir Semenov, Lisa V. Alexander, Simon Allen, Gerardo Benito, Tereza Cavazos, John Clague, Declan Conway, Paul M. Della-Marta, Markus Gerber, Sunling Gong, B. N. Goswami, Mark Hemer, Christian Huggel, Bart van den Hurk, Viatcheslav V. Kharin, Akio Kitoh, Albert M.G. Klein Tank, Guilong Li, Simon Mason, William McGuire, Geert Jan van Oldenborgh, Boris Orlowsky, Sharon Smith, Wassila Thiaw, Adonis Velegrakis, Pascal Yiou, Tingjun Zhang, Tianjun Zhou, Francis W. Zwiers
- Edited by Christopher B. Field, Vicente Barros, Thomas F. Stocker, Qin Dahe
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- Book:
- Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation
- Published online:
- 05 August 2012
- Print publication:
- 28 May 2012, pp 109-230
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Summary
Executive Summary
This chapter addresses changes in weather and climate events relevant to extreme impacts and disasters. An extreme (weather or climate) event is generally defined as the occurrence of a value of a weather or climate variable above (or below) a threshold value near the upper (or lower) ends (‘tails’) of the range of observed values of the variable. Some climate extremes (e.g., droughts, floods) may be the result of an accumulation of weather or climate events that are, individually, not extreme themselves (though their accumulation is extreme). As well, weather or climate events, even if not extreme in a statistical sense, can still lead to extreme conditions or impacts, either by crossing a critical threshold in a social, ecological, or physical system, or by occurring simultaneously with other events. A weather system such as a tropical cyclone can have an extreme impact, depending on where and when it approaches landfall, even if the specific cyclone is not extreme relative to other tropical cyclones. Conversely, not all extremes necessarily lead to serious impacts. [3.1]
Many weather and climate extremes are the result of natural climate variability (including phenomena such as El Niño), and natural decadal or multi-decadal variations in the climate provide the backdrop for anthropogenic climate changes. Even if there were no anthropogenic changes in climate, a wide variety of natural weather and climate extremes would still occur. [3.1]
A changing climate leads to changes in the frequency, intensity, spatial extent, duration, and timing of weather and climate extremes, and can result in unprecedented extremes. Changes in extremes can also be directly related to changes in mean climate, because mean future conditions in some variables are projected to lie within the tails of present-day conditions. Nevertheless, changes in extremes of a climate or weather variable are not always related in a simple way to changes in the mean of the same variable, and in some cases can be of opposite sign to a change in the mean of the variable. Changes in phenomena such as the El Nino-Southern Oscillation or monsoons could affect the frequency and intensity of extremes in several regions simultaneously. [3.1]
3 - Experimental design: scaling up in time and space, and its statistical considerations
- Edited by Werner L. Kutsch, Max-Planck-Institut für Biogeochemie, Jena, Michael Bahn, Leopold-Franzens-Universität Innsbruck, Austria, Andreas Heinemeyer
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- Book:
- Soil Carbon Dynamics
- Published online:
- 11 May 2010
- Print publication:
- 07 January 2010, pp 34-48
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Summary
INTRODUCTION
Accurate measurement of the soil CO2 efflux is critical for the assessment of the carbon budget of terrestrial ecosystems, since it is the main pathway for assimilated carbon to return to the atmosphere, and only small changes in the soil CO2 efflux rate might have important implications on the net ecosystem carbon balance. Due to this central role in the terrestrial carbon cycle, soil CO2 efflux has been measured throughout all biomes, and covering all principal vegetation types. Using simplified regressions of soil CO2 efflux measurements reported in the scientific literature, the total amount of carbon emitted as CO2 by soils worldwide has been estimated at approximately 68–80 Pg (1995; Raich et al., 2002), representing the second largest carbon flux between ecosystems and the atmosphere. This amount is more than ten times the current rate of fossil fuel combustion and indicates that each year around 10% of the atmosphere's CO2 cycles through the soil (Prentice et al., 2001). Thus, even a small change in soil respiration could significantly intensify, or mitigate, current atmospheric increases of CO2, with potential feedbacks to climate change. In fact, soils store more than twice as much carbon globally than the atmosphere (Bolin, 2000) and consequently contain a large long-term potential for the carbon cycle climate feedback. Applying results from small-scale experiments to larger areas is necessary in order to understand the potential role of soils in sequestering or releasing carbon under changed climatic conditions, and to inform management and policy makers about likely consequences of land-use changes on carbon fluxes and stocks in specific regions.
11 - Semi-empirical modelling of the response of soil respiration to environmental factors in laboratory and field conditions
- Edited by Werner L. Kutsch, Max-Planck-Institut für Biogeochemie, Jena, Michael Bahn, Leopold-Franzens-Universität Innsbruck, Austria, Andreas Heinemeyer
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- Book:
- Soil Carbon Dynamics
- Published online:
- 11 May 2010
- Print publication:
- 07 January 2010, pp 207-220
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Summary
INTRODUCTION
Soil respiration, globally 68–80 Pg C y−1, represents the second largest carbon flux between ecosystems and the atmosphere (Schimel et al., 1996; Raich et al., 2002). This is more than ten times the current rate of fossil fuel combustion and indicates that each year around 10% of the atmosphere's CO2 cycles through the soil. Thus, even a small change in soil respiration could significantly intensify – or mitigate – current atmospheric increases of CO2, with potential feedbacks to climate change. Despite this global significance and the considerable scientific commitment to its study over the last decades, there is still limited comprehensive understanding of the factors controlling temporal and across-ecosystem variability of soil respiration.
This understanding is largely hampered by the fact that studies are often conducted and compared at different temporal and spatial scales that are not compatible. Since, particularly in large-scale studies, factors influencing soil respiration often correlate with each other, responses of soil respiration to those factors are confounded and only apparent relationships are obtained.
For the purpose of this chapter, methods (and their associated problems) for analyzing soil respiration data from different scales are reviewed and jointly interpreted with emphasis on the temperature dependence of soil respiration.
MODELLING SOIL RESPIRATION: AN OVERVIEW
General modelling approaches
Soil respiration – defined as the CO2 efflux from the soil surface – originates from the metabolic activity of roots (autotrophic respiration), micro-organisms (bacteria, actinomycetes and fungi) and soil meso- and macro-fauna (heterotrophic respiration).