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  • 1
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    Atmospheric CO2 forces abrupt vegetation shifts locally, but not globally (2012)
    Nature Publishing Group (NPG)
    Details
    Publication Date: 2012-07-06
    Description: It is possible that anthropogenic climate change will drive the Earth system into a qualitatively different state. Although different types of uncertainty limit our capacity to assess this risk, Earth system scientists are particularly concerned about tipping elements, large-scale components of the Earth system that can be switched into qualitatively different states by small perturbations. Despite growing evidence that tipping elements exist in the climate system, whether large-scale vegetation systems can tip into alternative states is poorly understood. Here we show that tropical grassland, savanna and forest ecosystems, areas large enough to have powerful impacts on the Earth system, are likely to shift to alternative states. Specifically, we show that increasing atmospheric CO2 concentration will force transitions to vegetation states characterized by higher biomass and/or woody-plant dominance. The timing of these critical transitions varies as a result of between-site variance in the rate of temperature increase, as well as a dependence on stochastic variation in fire severity and rainfall. We further show that the locations of bistable vegetation zones (zones where alternative vegetation states can exist) will shift as climate changes. We conclude that even though large-scale directional regime shifts in terrestrial ecosystems are likely, asynchrony in the timing of these shifts may serve to dampen, but not nullify, the shock that these changes may represent to the Earth system.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Higgins, Steven I -- Scheiter, Simon -- England -- Nature. 2012 Aug 9;488(7410):209-12. doi: 10.1038/nature11238.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Institut fur Physische Geographie, Goethe Universitat Frankfurt am Main, 60438 Frankfurt am Main, Germany. higgins@em.uni-frankfurt.de〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/22763447" target="_blank"〉PubMed〈/a〉
    Keywords: Africa ; Atmosphere/*chemistry ; Biomass ; Carbon/metabolism ; Carbon Dioxide/analysis/*metabolism ; Climate Change/*statistics & numerical data ; *Ecosystem ; Fires ; Geography ; History, 19th Century ; History, 20th Century ; History, 21st Century ; Hot Temperature ; Models, Biological ; Photosynthesis/physiology ; Poaceae/growth & development/metabolism ; Probability ; Rain ; Stochastic Processes ; Time Factors ; Trees/*growth & development/metabolism ; Wood
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Published by Nature Publishing Group (NPG)
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  • 2
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    Forests, savannas and grasslands: bridging the knowledge gap between ecology and Dynamic Global Vegetation Models (2014)
    Copernicus
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    Publication Date: 2014-06-17
    Description: The forest, savanna, and grassland biomes, and the transitions between them, are expected to undergo major changes in the future, due to global climate change. Dynamic Global Vegetation Models (DGVMs) are very useful to understand vegetation dynamics under present climate, and to predict its changes under future conditions. However, several DGVMs display high uncertainty in predicting vegetation in tropical areas. Here we perform a comparative analysis of three different DGVMs (JSBACH, LPJ-GUESS-SPITFIRE and aDGVM) with regard to their representation of the ecological mechanisms and feedbacks that determine the forest, savanna and grassland biomes, in an attempt to bridge the knowledge gap between ecology and global modelling. Model outcomes, obtained including different mechanisms, are compared to observed tree cover along a mean annual precipitation gradient in Africa. Through these comparisons, and by drawing on the large number of recent studies that have delivered new insights into the ecology of tropical ecosystems in general, and of savannas in particular, we identify two main mechanisms that need an improved representation in the DGVMs. The first mechanism includes water limitation to tree growth, and tree-grass competition for water, which are key factors in determining savanna presence in arid and semi-arid areas. The second is a grass-fire feedback, which maintains both forest and savanna occurrences in mesic areas. Grasses constitute the majority of the fuel load, and at the same time benefit from the openness of the landscape after fires, since they recover faster than trees. Additionally, these two mechanisms are better represented when the models also include tree life stages (adults and seedlings), and distinguish between fire-prone and shade-tolerant savanna trees, and fire-resistant and shade-intolerant forest trees. Including these basic elements could improve the predictive ability of the DGVMs, not only under current climate conditions but also and especially under future scenarios.
    Print ISSN: 1810-6277
    Electronic ISSN: 1810-6285
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 3
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    Progress in DGVMs: a comment on "Impacts of trait variation through observed trait–climate relationships on performance of an Earth system model: a conceptual analysis" by Verheijen et al. (2013) (2014)
    Copernicus
    Details
    Publication Date: 2014-03-21
    Print ISSN: 1810-6277
    Electronic ISSN: 1810-6285
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 4
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    Forests, savannas, and grasslands: bridging the knowledge gap between ecology and Dynamic Global Vegetation Models (2015)
    Copernicus
    Details
    Publication Date: 2015-03-20
    Description: The forest, savanna, and grassland biomes, and the transitions between them, are expected to undergo major changes in the future due to global climate change. Dynamic global vegetation models (DGVMs) are very useful for understanding vegetation dynamics under the present climate, and for predicting its changes under future conditions. However, several DGVMs display high uncertainty in predicting vegetation in tropical areas. Here we perform a comparative analysis of three different DGVMs (JSBACH, LPJ-GUESS-SPITFIRE and aDGVM) with regard to their representation of the ecological mechanisms and feedbacks that determine the forest, savanna, and grassland biomes, in an attempt to bridge the knowledge gap between ecology and global modeling. The outcomes of the models, which include different mechanisms, are compared to observed tree cover along a mean annual precipitation gradient in Africa. By drawing on the large number of recent studies that have delivered new insights into the ecology of tropical ecosystems in general, and of savannas in particular, we identify two main mechanisms that need improved representation in the examined DGVMs. The first mechanism includes water limitation to tree growth, and tree–grass competition for water, which are key factors in determining savanna presence in arid and semi-arid areas. The second is a grass–fire feedback, which maintains both forest and savanna presence in mesic areas. Grasses constitute the majority of the fuel load, and at the same time benefit from the openness of the landscape after fires, since they recover faster than trees. Additionally, these two mechanisms are better represented when the models also include tree life stages (adults and seedlings), and distinguish between fire-prone and shade-tolerant forest trees, and fire-resistant and shade-intolerant savanna trees. Including these basic elements could improve the predictive ability of the DGVMs, not only under current climate conditions but also and especially under future scenarios.
    Print ISSN: 1726-4170
    Electronic ISSN: 1726-4189
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 5
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    Progress in DGVMs: a comment on "Impacts of trait variation through observed trait–climate relationships on performance of an Earth system model: a conceptual analysis" by Verheijen et al. (2013) (2014)
    Copernicus
    Details
    Publication Date: 2014-08-19
    Print ISSN: 1726-4170
    Electronic ISSN: 1726-4189
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 6
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    Tree regeneration in models of forest dynamics: a key priority for further research (2024)
    In:  Ecosphere
    Details
    Publication Date: 2024-03-26
    Description: Tree regeneration is a key process in forest dynamics, particularly in the context of forest resilience and climate change. Models are pivotal for assessing long-term forest dynamics, and they have been in use for more than 50 years. However, an assessment of their ability to accurately represent tree regeneration is lacking. We assess how well current models capture the overall abundance, species composition, and mortality of tree regeneration. Using 15 models built to capture long-term forest dynamics at the stand, landscape, and global levels, we simulate tree regeneration at 200 sites representing large environmental gradients across Central Europe. The results are evaluated against comprehensive data from unmanaged forests. Most of the models overestimate regeneration levels, which is only compensated in some models by high simulated mortality rates in the early stages of individual trees dynamics. Simulated species diversity of regeneration matches the observed ranges. Models simulating higher species diversity at the stand level do not feature higher regeneration diversity. The effect of light availability on regeneration levels is captured better than the effect of temperature and soil moisture, but patterns are not consistent across models. Increasing complexity in the tree regeneration modules of the models is not related to higher accuracy of simulated tree regeneration. Furthermore, individual model design is more important than scale (stand, landscape, global) and approach (empirical, process-based) for accurately capturing tree regeneration. Despite considerable mismatches between simulation results and data, it is remarkable that most models capture the essential features of the highly complex process of tree regeneration, while not having been parameterized with such data. We conclude that much can be gained by evaluating and refining the modeling of regeneration processes. This has the potential to render long-term projections of forest dynamics under changing environmental conditions that are much more robust.
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
    Format: application/pdf
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