Simulating effects of fire disturbance and climate change on boreal forest productivity and evapotranspiration

2006 ◽  
Vol 362 (1-3) ◽  
pp. 85-102 ◽  
Author(s):  
Sinkyu Kang ◽  
John S. Kimball ◽  
Steven W. Running
Ecosystems ◽  
2021 ◽  
Author(s):  
Theresa S. Ibáñez ◽  
David A. Wardle ◽  
Michael J. Gundale ◽  
Marie-Charlotte Nilsson

AbstractWildfire disturbance is important for tree regeneration in boreal ecosystems. A considerable amount of literature has been published on how wildfires affect boreal forest regeneration. However, we lack understanding about how soil-mediated effects of fire disturbance on seedlings occur via soil abiotic properties versus soil biota. We collected soil from stands with three different severities of burning (high, low and unburned) and conducted two greenhouse experiments to explore how seedlings of tree species (Betula pendula, Pinus sylvestris and Picea abies) performed in live soils and in sterilized soil inoculated by live soil from each of the three burning severities. Seedlings grown in live soil grew best in unburned soil. When sterilized soils were reinoculated with live soil, seedlings of P. abies and P. sylvestris grew better in soil from low burn severity stands than soil from either high severity or unburned stands, demonstrating that fire disturbance may favor post-fire regeneration of conifers in part due to the presence of soil biota that persists when fire severity is low or recovers quickly post-fire. Betula pendula did not respond to soil biota and was instead driven by changes in abiotic soil properties following fire. Our study provides strong evidence that high fire severity creates soil conditions that are adverse for seedling regeneration, but that low burn severity promotes soil biota that stimulates growth and potential regeneration of conifers. It also shows that species-specific responses to abiotic and biotic soil characteristics are altered by variation in fire severity. This has important implications for tree regeneration because it points to the role of plant–soil–microbial feedbacks in promoting successful establishment, and potentially successional trajectories and species dominance in boreal forests in the future as fire regimes become increasingly severe through climate change.


2021 ◽  
Vol 193 (4) ◽  
Author(s):  
Stefan Erasmi ◽  
Michael Klinge ◽  
Choimaa Dulamsuren ◽  
Florian Schneider ◽  
Markus Hauck

AbstractThe monitoring of the spatial and temporal dynamics of vegetation productivity is important in the context of carbon sequestration by terrestrial ecosystems from the atmosphere. The accessibility of the full archive of medium-resolution earth observation data for multiple decades dramatically improved the potential of remote sensing to support global climate change and terrestrial carbon cycle studies. We investigated a dense time series of multi-sensor Landsat Normalized Difference Vegetation Index (NDVI) data at the southern fringe of the boreal forests in the Mongolian forest-steppe with regard to the ability to capture the annual variability in radial stemwood increment and thus forest productivity. Forest productivity was assessed from dendrochronological series of Siberian larch (Larix sibirica) from 15 plots in forest patches of different ages and stand sizes. The results revealed a strong correlation between the maximum growing season NDVI of forest sites and tree ring width over an observation period of 20 years. This relationship was independent of the forest stand size and of the landscape’s forest-to-grassland ratio. We conclude from the consistent findings of our case study that the maximum growing season NDVI can be used for retrospective modelling of forest productivity over larger areas. The usefulness of grassland NDVI as a proxy for forest NDVI to monitor forest productivity in semi-arid areas could only partially be confirmed. Spatial and temporal inconsistencies between forest and grassland NDVI are a consequence of different physiological and ecological vegetation properties. Due to coarse spatial resolution of available satellite data, previous studies were not able to account for small-scaled land-cover patches like fragmented forest in the forest-steppe. Landsat satellite-time series were able to separate those effects and thus may contribute to a better understanding of the impact of global climate change on natural ecosystems.


2017 ◽  
Vol 106 (3) ◽  
pp. 977-990 ◽  
Author(s):  
Yan Boulanger ◽  
Anthony R. Taylor ◽  
David T. Price ◽  
Dominic Cyr ◽  
Guillaume Sainte-Marie
Keyword(s):  

2020 ◽  
Author(s):  
Marion Jourdan ◽  
Christian Piedallu ◽  
Jonas Baudry ◽  
Xavier Morin

ABSTRACTClimate change modifies ecosystem processes directly through its effect on environmental conditions, but also indirectly by changing community composition. Theoretical studies and grassland experiments suggest that diversity may increase and stabilize communities’ productivity over time. Few recent studies on forest ecosystems suggested the same pattern but with a larger variability between the results. In this paper, we aimed to test stabilizing diversity effect for two kinds of mixtures (Fagus sylvatica - Quercus pubescens and Fagus sylvatica - Abies alba), and to assess how climate may affect the patterns. We used tree ring data from forest plots distributed along a latitudinal gradient across French Alps. We found that diversity effect on stability in productivity varies with stand composition. Most beech–fir stands showed a greater stability in productivity over time than monocultures, while beech–oak stands showed a less stable productivity. Considering non-additive effects, no significant trends were found, regardless the type of mixed stands considered. We further highlighted that these patterns could be partially explained by asynchrony between species responses to annual climatic conditions (notably to variation in temperature or precipitation), overyielding, and climatic conditions. We also showed that the intensity of the diversity effect on stability varies along the ecological gradient, consistently with the stress gradient hypothesis for beech-oak forests, but not for beech-fir forests. This study showed the importance of the species identity on the relationships between diversity, climate and stability of forest productivity. Better depicting diversity and composition effects on forest ecosystem functioning appears to be crucial for forest managers to promote forest adaptation and maintain timber resource in the context of on-going climate change.


2006 ◽  
Vol 82 (2) ◽  
pp. 159-176 ◽  
Author(s):  
R J Hall ◽  
F. Raulier ◽  
D T Price ◽  
E. Arsenault ◽  
P Y Bernier ◽  
...  

Forest yield forecasting typically employs statistically derived growth and yield (G&Y) functions that will yield biased growth estimates if changes in climate seriously influence future site conditions. Significant climate warming anticipated for the Prairie Provinces may result in increased moisture deficits, reductions in average site productivity and changes to natural species composition. Process-based stand growth models that respond realistically to simulated changes in climate can be used to assess the potential impacts of climate change on forest productivity, and hence can provide information for adapting forest management practices. We present an application of such a model, StandLEAP, to estimate stand-level net primary productivity (NPP) within a 2700 km2 study region in western Alberta. StandLEAP requires satellite remote-sensing derived estimates of canopy light absorption or leaf area index, in addition to spatial data on climate, topography and soil physical characteristics. The model was applied to some 80 000 stand-level inventory polygons across the study region. The resulting estimates of NPP correlate well with timber productivity values based on stand-level site index (height in metres at 50 years). This agreement demonstrates the potential to make site-based G&Y estimates using process models and to further investigate possible effects of climate change on future timber supply. Key words: forest productivity, NPP, climate change, process-based model, StandLEAP, leaf area index, above-ground biomass


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