Reiner Zimmermann | University of Hohenheim, Stuttgart (original) (raw)

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Papers by Reiner Zimmermann

Oecologia, 2002

... CO2 as-similation (A) to daily transpiration (E) was independent of lysimeter size, leaf area... more ... CO2 as-similation (A) to daily transpiration (E) was independent of lysimeter size, leaf area and pre-dawn water potential, ... H. Heilmeier (✉) · A. Wartinger · M. Erhard · R. Zimmermann E.-D. Schulze Lehrstuhl Pflanzenökologie, Universität Bayreuth, 95440 Bayreuth, Germany R ...

Ecological Studies, 2008

Lösch (2001) concluded that information on the ecophysiology of tropical mountain trees — key com... more Lösch (2001) concluded that information on the ecophysiology of tropical mountain trees — key components for the understanding of the functional role of vegetation in these ecosystems — is entirely missing; therefore we concentrate on transpiration. Available knowledge on stands is almost exclusively from catchment studies (e.g. Bruijnzeel and Proctor 1995; see Chapter 12 in this volume), but types of “gully”, “slope” and “stunted” forests are found everywhere. To evaluate their contribution to water consumption and buffering in the landscape it is essential to characterize these forest types individually, here via up-scaling from sap flow measurements on individual trees to plot-scale. In this context it is important to know whether sap flow varies species-specifically (then many species have to be studied) or whether the size of individual plants, their life-forms, and associations with functional groups are more important (then only a few representative individuals need to be investigated).

Oecologia, 1988

Two equations in our paper were inverted. These were the weights for empirical logistic regressio... more Two equations in our paper were inverted. These were the weights for empirical logistic regression reported on the bottom of page 212 and top of page 213. The corrected weight from the bottom of page 212 is:

2010 Ieee International Geoscience and Remote Sensing Symposium, Jul 25, 2010

The mapping of freeze/thaw state of the landscape is one of the main objectives of NASA's upcomin... more The mapping of freeze/thaw state of the landscape is one of the main objectives of NASA's upcoming SMAP (Soil Moisture Active and Passive) mission. This study applies ALECTRA (Alaska Ecological Transect) biophysical network and QuikSCAT scatterometer data to evaluate some of the validation issues regarding the SMAP freeze/thaw measurements. Although the QuikSCAT data is at Ku-band frequency, rather than the L-band of the SMAP instrument, the data is utilized due to its uniquely high temporal resolution over the ALECTRA sites. The results show that multiple temperature measurements representative of individual landscape (soil, snow cover, vegetation and atmosphere) elements and spatial heterogeneity within the satellite field-of-view are important for understanding the radar backscatter process and aggregate freeze/thaw signal. The backscatter temporal dynamics and relative contribution of these landscape elements to the freeze-thaw signal varies with land cover type, seasonal weather and climate conditions. Index Terms -Freeze/thaw state, SMAP, QuikSCAT, ALECTRA

TURKISH JOURNAL OF AGRICULTURE AND FORESTRY, 2016

       ... more                                                                                                                                                  

Trees Struct Funct, 1999

Using constant heat sap flow sensors, xylem water fluxes in ten tree species and two liana specie... more Using constant heat sap flow sensors, xylem water fluxes in ten tree species and two liana species were monitored for 5-10 days during the beginning of the wet season in May, 1993. For a subset of the trees, a branch was also monitored at the top of the crown for 5 days. Xylem flux (J S ) was related diurnally in all plants to vapor pressure deficit (D) measured within the upperthird of the canopy, and to incoming shortwave radiation R S above the canopy. Cross-correlation analysis was used to estimate time lags between diurnal patterns of J S and D or R S , and between J S in stems and branches. The maximum correlation coefficient from cross-correlation of J S with R S (range=0.57-0.92) was often higher than the maximum of J S with D (range=0.43-0.89), indicating that diurnal J S was more dependent on R S than D. Time lags (lag corresponding to maximum correlation) of J S at stem-base with D was shorter (0-45 min) than with radiation (5-115 min), highly variable within a species, and uncorrelated to the height or exposure of tree crowns or liana in the canopy. On a stand level, not accounting for the diel lag between stem sap flux and canopy flux resulted in errors in estimated canopy transpiration of up to 30%.

       ... more                                                                                                                                                  

Supported by the "Deutsche Forschungsgemeinschaft", Bonn

Earth Interactions, Dec 1, 2004

Evidence is presented from the satellite microwave remote sensing record that the timing of seaso... more Evidence is presented from the satellite microwave remote sensing record that the timing of seasonal thawing and subsequent initiation of the growing season in early spring has advanced by approximately 8 days from 1988 to 2001 for the pan-Arctic basin and Alaska. These trends are highly variable across the region, with North America experiencing a larger advance relative to Eurasia and the entire region. Interannual variability in the timing of spring thaw as detected from the remote sensing record corresponded directly to seasonal anomalies in mean atmospheric CO 2 concentrations for the region, including the timing of the seasonal draw down of atmospheric CO 2 from terrestrial net primary productivity (NPP) in spring, and seasonal maximum and minimum CO 2 concentrations. The timing of the seasonal thaw for a given year was also found to be a significant (P , 0.01) predictor of the seasonal amplitude of atmospheric CO 2 for the following year. These results imply that the timing of seasonal thawing in spring has a major impact on terrestrial NPP and net carbon exchange at high latitudes. The initiation of the growing season has also been occurring earlier, on average, over the time period addressed in this study and may be a major mechanism driving observed atmospheric CO 2 seasonal cycle advances, vegetation greening, and enhanced productivity for the northern high latitudes.

... Variations from case to case associated with variations in mean DSD characteristics were more... more ... Variations from case to case associated with variations in mean DSD characteristics were more ... Ulbrich, CW, and D. Atlas, 1984: Assessment of the contribution of differential polarization to ... Zahrai, A., and DS Zrnić, 1993: The 10 cm-wavelength polarimetric weather radar at ...

Oecologia, 2002

... CO2 as-similation (A) to daily transpiration (E) was independent of lysimeter size, leaf area... more ... CO2 as-similation (A) to daily transpiration (E) was independent of lysimeter size, leaf area and pre-dawn water potential, ... H. Heilmeier (✉) · A. Wartinger · M. Erhard · R. Zimmermann E.-D. Schulze Lehrstuhl Pflanzenökologie, Universität Bayreuth, 95440 Bayreuth, Germany R ...

Ecological Studies, 2008

Lösch (2001) concluded that information on the ecophysiology of tropical mountain trees — key com... more Lösch (2001) concluded that information on the ecophysiology of tropical mountain trees — key components for the understanding of the functional role of vegetation in these ecosystems — is entirely missing; therefore we concentrate on transpiration. Available knowledge on stands is almost exclusively from catchment studies (e.g. Bruijnzeel and Proctor 1995; see Chapter 12 in this volume), but types of “gully”, “slope” and “stunted” forests are found everywhere. To evaluate their contribution to water consumption and buffering in the landscape it is essential to characterize these forest types individually, here via up-scaling from sap flow measurements on individual trees to plot-scale. In this context it is important to know whether sap flow varies species-specifically (then many species have to be studied) or whether the size of individual plants, their life-forms, and associations with functional groups are more important (then only a few representative individuals need to be investigated).

Oecologia, 1988

Two equations in our paper were inverted. These were the weights for empirical logistic regressio... more Two equations in our paper were inverted. These were the weights for empirical logistic regression reported on the bottom of page 212 and top of page 213. The corrected weight from the bottom of page 212 is:

2010 Ieee International Geoscience and Remote Sensing Symposium, Jul 25, 2010

The mapping of freeze/thaw state of the landscape is one of the main objectives of NASA's upcomin... more The mapping of freeze/thaw state of the landscape is one of the main objectives of NASA's upcoming SMAP (Soil Moisture Active and Passive) mission. This study applies ALECTRA (Alaska Ecological Transect) biophysical network and QuikSCAT scatterometer data to evaluate some of the validation issues regarding the SMAP freeze/thaw measurements. Although the QuikSCAT data is at Ku-band frequency, rather than the L-band of the SMAP instrument, the data is utilized due to its uniquely high temporal resolution over the ALECTRA sites. The results show that multiple temperature measurements representative of individual landscape (soil, snow cover, vegetation and atmosphere) elements and spatial heterogeneity within the satellite field-of-view are important for understanding the radar backscatter process and aggregate freeze/thaw signal. The backscatter temporal dynamics and relative contribution of these landscape elements to the freeze-thaw signal varies with land cover type, seasonal weather and climate conditions. Index Terms -Freeze/thaw state, SMAP, QuikSCAT, ALECTRA

TURKISH JOURNAL OF AGRICULTURE AND FORESTRY, 2016

       ... more                                                                                                                                                  

Trees Struct Funct, 1999

Using constant heat sap flow sensors, xylem water fluxes in ten tree species and two liana specie... more Using constant heat sap flow sensors, xylem water fluxes in ten tree species and two liana species were monitored for 5-10 days during the beginning of the wet season in May, 1993. For a subset of the trees, a branch was also monitored at the top of the crown for 5 days. Xylem flux (J S ) was related diurnally in all plants to vapor pressure deficit (D) measured within the upperthird of the canopy, and to incoming shortwave radiation R S above the canopy. Cross-correlation analysis was used to estimate time lags between diurnal patterns of J S and D or R S , and between J S in stems and branches. The maximum correlation coefficient from cross-correlation of J S with R S (range=0.57-0.92) was often higher than the maximum of J S with D (range=0.43-0.89), indicating that diurnal J S was more dependent on R S than D. Time lags (lag corresponding to maximum correlation) of J S at stem-base with D was shorter (0-45 min) than with radiation (5-115 min), highly variable within a species, and uncorrelated to the height or exposure of tree crowns or liana in the canopy. On a stand level, not accounting for the diel lag between stem sap flux and canopy flux resulted in errors in estimated canopy transpiration of up to 30%.

       ... more                                                                                                                                                  

Supported by the "Deutsche Forschungsgemeinschaft", Bonn

Earth Interactions, Dec 1, 2004

Evidence is presented from the satellite microwave remote sensing record that the timing of seaso... more Evidence is presented from the satellite microwave remote sensing record that the timing of seasonal thawing and subsequent initiation of the growing season in early spring has advanced by approximately 8 days from 1988 to 2001 for the pan-Arctic basin and Alaska. These trends are highly variable across the region, with North America experiencing a larger advance relative to Eurasia and the entire region. Interannual variability in the timing of spring thaw as detected from the remote sensing record corresponded directly to seasonal anomalies in mean atmospheric CO 2 concentrations for the region, including the timing of the seasonal draw down of atmospheric CO 2 from terrestrial net primary productivity (NPP) in spring, and seasonal maximum and minimum CO 2 concentrations. The timing of the seasonal thaw for a given year was also found to be a significant (P , 0.01) predictor of the seasonal amplitude of atmospheric CO 2 for the following year. These results imply that the timing of seasonal thawing in spring has a major impact on terrestrial NPP and net carbon exchange at high latitudes. The initiation of the growing season has also been occurring earlier, on average, over the time period addressed in this study and may be a major mechanism driving observed atmospheric CO 2 seasonal cycle advances, vegetation greening, and enhanced productivity for the northern high latitudes.

... Variations from case to case associated with variations in mean DSD characteristics were more... more ... Variations from case to case associated with variations in mean DSD characteristics were more ... Ulbrich, CW, and D. Atlas, 1984: Assessment of the contribution of differential polarization to ... Zahrai, A., and DS Zrnić, 1993: The 10 cm-wavelength polarimetric weather radar at ...