scholarly journals Effects of Temperature and Water Availability on Northern European Boreal Forests

Author(s):  
Guiomar Ruiz-Pérez ◽  
Giulia Vico
2018 ◽  
Vol 165 (3) ◽  
pp. 511-523 ◽  
Author(s):  
Patricia L. Sáez ◽  
Betsy K. Rivera ◽  
Constanza F. Ramírez ◽  
Valentina Vallejos ◽  
Lohengrin A. Cavieres ◽  
...  

2014 ◽  
Vol 11 (7) ◽  
pp. 10917-11025
Author(s):  
M. Forkel ◽  
N. Carvalhais ◽  
S. Schaphoff ◽  
W. v. Bloh ◽  
M. Migliavacca ◽  
...  

Abstract. Existing dynamic global vegetation models (DGVMs) have a~limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer term vegetation dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help to revise current modelling approaches and thus to enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a~new phenology model within the LPJmL (Lund Potsdam Jena managed lands) DGVM and integrated several observational data sets to improve the ability of the model in reproducing satellite-derived time series of vegetation greenness. Specifically, we optimized LPJmL parameters against observational time series of the fraction of absorbed photosynthetic active radiation (FAPAR), albedo and gross primary production to identify the main environmental controls for seasonal vegetation greenness dynamics. We demonstrated that LPJmL with new phenology and optimized parameters better reproduces seasonality, inter-annual variability and trends of vegetation greenness. Our results indicate that soil water availability is an important control on vegetation phenology not only in water-limited biomes but also in boreal forests and the arctic tundra. Whereas water availability controls phenology in water-limited ecosystems during the entire growing season, water availability co-modulates jointly with temperature the beginning of the growing season in boreal and arctic regions. Additionally, water availability contributes to better explain decadal greening trends in the Sahel and browning trends in boreal forests. These results emphasize the importance of considering water availability in a new generation of phenology modules in DGVMs in order to correctly reproduce observed seasonal to decadal dynamics of vegetation greenness.


2019 ◽  
Vol 25 (10) ◽  
pp. 3462-3471 ◽  
Author(s):  
Xianliang Zhang ◽  
Rubén D. Manzanedo ◽  
Loïc D'Orangeville ◽  
Tim T. Rademacher ◽  
Junxia Li ◽  
...  

2021 ◽  
Vol 9 (7) ◽  
pp. 1409
Author(s):  
Igor A. Kazartsev ◽  
Georgy R. Lednev

The distribution and genetic diversity of 91 of Beauveria isolates collected during a long-term survey in boreal forests of northern European Russia was studied. Based on morphological and sequence analysis of TEF and Bloc loci, three Beauveria spp. were identified: B. pseudobassiana, B. bassiana, and B. caledonica, with abundance of 81, 11, and 8%, respectively. Through multilocus sequencing, four haplotypes of B. bassiana and two haplotypes of B. caledonica were detected. Twelve haplotypes of B. pseudobassiana with non-random distribution were identified. Two haplotypes of B. pseudobassiana were the most abundant and widespread occurring across the whole study area, whereas others tended to be more specific to either the north or south of the study area, indicating the presence of different subpopulations. For further analysis of these putative subpopulations, southern and northern areas were separated along the boundary of the Köppen–Geiger climate zones (dfb and dfc), and the genetic structure was examined by analysis of molecular variance and spatial autocorrelation. Molecular evidence of intraspecific recombination of B. pseudobassiana and B. bassiana across northern European Russia area was indicated.


2014 ◽  
Vol 11 (23) ◽  
pp. 7025-7050 ◽  
Author(s):  
M. Forkel ◽  
N. Carvalhais ◽  
S. Schaphoff ◽  
W. v. Bloh ◽  
M. Migliavacca ◽  
...  

Abstract. Existing dynamic global vegetation models (DGVMs) have a limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer-term vegetation dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help to revise current modelling approaches and thus enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a new phenology model within the LPJmL (Lund Potsdam Jena managed lands) DGVM and integrated several observational data sets to improve the ability of the model in reproducing satellite-derived time series of vegetation greenness. Specifically, we optimized LPJmL parameters against observational time series of the fraction of absorbed photosynthetic active radiation (FAPAR), albedo and gross primary production to identify the main environmental controls for seasonal vegetation greenness dynamics. We demonstrated that LPJmL with new phenology and optimized parameters better reproduces seasonality, inter-annual variability and trends of vegetation greenness. Our results indicate that soil water availability is an important control on vegetation phenology not only in water-limited biomes but also in boreal forests and the Arctic tundra. Whereas water availability controls phenology in water-limited ecosystems during the entire growing season, water availability co-modulates jointly with temperature the beginning of the growing season in boreal and Arctic regions. Additionally, water availability contributes to better explain decadal greening trends in the Sahel and browning trends in boreal forests. These results emphasize the importance of considering water availability in a new generation of phenology modules in DGVMs in order to correctly reproduce observed seasonal-to-decadal dynamics of vegetation greenness.


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