forest meteorology
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2021 ◽  
Author(s):  
Timm Waldau ◽  
Frank-M. Chmielewski

<p>Eine direkte Auswirkung des rezenten Klimawandels auf die Vegetation ist die Verfrühung phänologischer Stadien, besonders im Frühjahr (WALDAU & CHMIELEWSKI, 2018; CHMIELEWSKI et al., 2004; WOLFE et al., 2005). Diese Trends wurden weltweit beobachtet und sind hauptsächlich auf den Anstieg der Lufttemperatur zurückzuführen, was den engen Zusammenhang zwischen Pflanzenentwicklung und Temperatur belegt. Dieser stetige Temperaturanstieg wird sich in Zukunft fortsetzen und zu zeitlichen und räumlichen Verschiebungen in der Vegetationsentwicklung führen. Um diese Veränderungen abschätzen zu können, sind plausible phänologische Modelle erforderlich, wobei das Kältebedürfnis, das für die Überwindung der Dormanz erforderlich ist, hierbei eine der Schlüsselgrößen ist. <br />Ziel dieser Studie war es die zukünftigen Auswirkungen des Klimawandels auf die natürliche Vegetation in Deutschland abzuschätzen. In einer dreijährigen Studie (Winter 2015/16 – 2017/18) wurde der Zeitpunkt der Dormanzbrechung für verschiedene Baumarten experimentell in Klimakammerversuchen bestimmt. Im Rahmen dieses Vortrages sollen die Ergebnisse für die Schwarzerle (Alnus glutinosa) dargestellt werden. Nach der Ermittlung des für den Blattaustrieb der Schwarzerle notwendigen Kältereizes wurde ein Chilling/Forcing Modell parametrisiert und anschließend an den phänologischen Beobachtungdaten des Deutschen Wetterdienstes (1951-2015) validiert. Für die Abschätzung der künftigen klimatischen Entwicklung wurde ein Klimaensemble aus sieben verschieden Klimamodellrechnungen für zwei Klimaszenarien (RCP 2.6 & 8.5) verwendet. Für den Zeitraum 2010-2100 werden neben den zeitlichen Trends der Lufttemperatur und der Phänologie zusätzlich die regionalen Unterschiede in Deutschland (Nord-Ost/Nord-West/Süd-Ost/Süd-West) aufgezeigt.</p> <p> </p> <p>Literatur:</p> <p>CHMIELEWSKI, F. M., MÜLLER, A. & BRUNS, E. (2004): Climate changes and trends in phenology of fruit trees and field crops in Germany, 1961–2000. Agricultural and Forest Meteorology 121 (1), 69-DOI: https://doi.org/10.1016/S0168-1923(03)00161-8.</p> <p>WALDAU, T. & CHMIELEWSKI, F. M. (2018): Spatial and temporal changes of spring temperature, thermal growing season and spring phenology in Germany 1951–2015. Meteorol. Z. 27 (4), 335-342.DOI: https://doi.org/10.1127/metz/2018/0923.</p> <p>WOLFE, D. W., SCHWARTZ, M. D., LAKSO, A. N., OTSUKI, Y., POOL, R. M. & SHAULIS, N. J. (2005): Climate change and shifts in spring phenology of three horticultural woody perennials in northeastern USA. International Journal of Biometeorology 49 (5), 303-309. DOI: https://doi.org/10.1007/s00484-004-0248-9.</p>


2021 ◽  
Vol 9 ◽  
Author(s):  
P. L. Vidale ◽  
G. Egea ◽  
P. C. McGuire ◽  
M. Todt ◽  
W. Peters ◽  
...  

Current land surface schemes in weather and climate models make use of the so-called coupled photosynthesis–stomatal conductance (A–gs) models of plant function to determine the surface fluxes that govern the terrestrial energy, water and carbon budgets. Plant physiology is controlled by many environmental factors, and a number of complex feedbacks are involved, but soil moisture control on root water uptake is primary, particularly in sub-tropical to temperate ecosystems. Land surface models represent plant water stress in different ways, but most implement a water stress factor, β, which ranges linearly (more recently also curvilinearly) between β = 1 for unstressed vegetation and β = 0 at the wilting point, expressed in terms of volumetric water content (θ).  β is most commonly used to either limit A or gs, and hence carbon and water fluxes, and a pertinent research question is whether these treatments are in fact interchangeable. Following Egea et al. (Agricultural and Forest Meteorology, 2011, 151 (10), 1,370–1,384) and Verhoef et al. (Agricultural and Forest Meteorology, 2014, 191, 22–32), we have implemented new β treatments, reflecting higher levels of biophysical complexity in a state-of-the-art LSM, Joint UK Land Environment Simulator, by allowing root zone soil moisture to limit plant function non-linearly and via individual routes (carbon assimilation, stomatal conductance, or mesophyll conductance) as well as any (non-linear) combinations thereof. The treatment of β does matter to the prediction of water and carbon fluxes: this study demonstrates that it represents a key structural uncertainty in contemporary LSMs, in terms of predictions of gross primary productivity, energy fluxes and soil moisture evolution, both in terms of climate means and response to a number of European droughts, including the 2003 heat wave. Treatments allowing ß to act on vegetation fluxes via stomatal and mesophyll routes are able to simulate the spatiotemporal variability in water use efficiency with higher fidelity during the growing season; they also support a broader range of ecosystem responses, e.g., those observed in regions that are radiation limited or water limited. We conclude that current practice in weather and climate modelling is inconsistent, as well as too simplistic, failing to credibly simulate vegetation response to soil water stress across the typical range of variability that is encountered for current European weather and climate conditions, including extremes of land surface temperature and soil moisture drought. A generalized approach performs better in current climate conditions and promises to be, based on responses to recently observed extremes, more trustworthy for predicting the impacts of climate change.


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