scholarly journals Environmental Effects on Normalized Gross Primary Productivity in Beech and Norway Spruce Forests

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1128
Author(s):  
Caleb Mensah ◽  
Ladislav Šigut ◽  
Milan Fischer ◽  
Lenka Foltýnová ◽  
Georg Jocher ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Environmental Conditions ◽  
Multiple Linear Regression Model ◽  
Environmental Parameters ◽  
Forest Productivity ◽  
Climatic Conditions ◽  
Gross Primary Productivity ◽  
Forest Types ◽  
Local Conditions ◽  
Diffuse Fraction

The strong effects of climate change are expected to negatively impact the long-term resilience and function of forest ecosystems, which could lead to changes in forest carbon balance and productivity. However, these forest responses may vary with local conditions and forest types. Accordingly, this study was carried out to determine gross primary productivity (GPP) sensitivity to changes in environmental parameters. Central European beech (at Štítná) and spruce species (at Bílý Kr̆íz̆ and Rájec), growing under contrasting climatic conditions, were studied. The comparative analyses of GPP were based on a five-year-long dataset of eddy covariance fluxes during the main growing season (2012–2016). Results of forest GPP responses with changes in environmental factors from a traditional Stepwise multiple linear regression model (SMLR) were used and compared with Random forest (RF) analyses. To demonstrate how actual GPP trends compare to potential GPP (GPPpot) courses expected under near-optimal environmental conditions, we computed normalized GPP (GPPnorm) with values between 0 and 1 as the ratio of the estimated daily sum of GPP to GPPpot. The study confirmed the well-known effect of total intensity of the photosynthetically active radiation and its diffuse fraction on GPPnorm across all the forest types. However, the study also showed the secondary effects of other environmental variables on forest productivity depending on the species and local climatic conditions. The reduction in forest productivity at the beech forest in Štítná was presumed to be mainly induced by edaphic drought (anisohydric behaviour). In contrast, reduced forest productivity at the spruce forest sites was presumably induced by both meteorological and hydrological drought events, especially at the moderately dry climate in Rájec. Overall, our analyses call for more studies on forest productivity across different forest types and contrasting climatic conditions, as this productivity is strongly dependent on species type and site-specific environmental conditions.

Legacy effects of drought on gross primary productivity from eddy-covariance measurements

2021 ◽  
Author(s):  
Xin Yu ◽  
René Orth ◽  
Markus Reichstein ◽  
Ana Bastos
Keyword(s):  
Eddy Covariance ◽  
Primary Productivity ◽  
Carbon Balance ◽  
Climatic Conditions ◽  
Gross Primary Productivity ◽  
Legacy Effects ◽  
Ecosystem Carbon ◽  
Ecosystem Carbon Balance ◽  
Eddy Covariance Measurements ◽  
Effects Of Drought

<p>The frequency and severity of droughts are expected to increase in the wake of climate change. Drought events not only cause direct impacts on the ecosystem carbon balance but also result in legacy effects during the following years. These legacies result from, for example, drought damage to the xylem or the crown which causes impaired growth, or from higher vulnerability to pests and diseases. To understand how droughts might affect the carbon cycle in the future, it is important to consider both direct and legacy effects. Such effects likely affect interannual variability in C fluxes but are challenging to detect in observations, and poorly represented in models. Therefore, the patterns and mechanisms inducing the legacy effects of drought on ecosystem carbon balance are necessarily needed to improve.</p><p>In this study, we analyze gross primary productivity (GPP) from eddy-covariance measurements in Germany to detect legacy effects from recent droughts. We follow a data-driven modeling approach using a random forest model trained in different sets of drought and non-drought periods. This approach allows quantifying legacy effects as deviations of observed GPP from modeled GPP in legacy years, which indicates a change in the vegetation response to hydro-climatic conditions as compared with the training period.</p>

Carbon sequestration in mixed deciduous forests: The importance of mid-storey trees for forest productivity

2021 ◽  
Author(s):  
Anne Holtmann ◽  
Andreas Huth ◽  
Felix Pohl ◽  
Corinna Rebmann ◽  
Rico Fischer
Keyword(s):  
Carbon Sequestration ◽  
Species Composition ◽  
Primary Productivity ◽  
Stand Structure ◽  
Forest Productivity ◽  
Forest Stand ◽  
Gross Primary Productivity ◽  
Small Scale ◽  
Stand Productivity ◽  
Simulation Results

<p>Forests play an important role in climate regulation due to carbon sequestration. However, a deeper understanding of forest carbon flux dynamics are often missing due to a lack of information about forest structure and species composition, especially for non-even-aged and mixed forests. In this study, we combined field inventory data of a mixed deciduous forest in Germany with an individual-based forest gap model to investigate daily carbon fluxes and to examine the role of tree size and species composition for the overall stand productivity. Simulation results show that the forest model is capable to reproduce daily eddy covariance measurements (R<sup>2</sup> of 0.73 for gross primary productivity and of 0.65 for ecosystem respiration). The simulation results showed that the forest act as a carbon sink with a net uptake of 3.2 t<sub>C</sub> ha<sup>-1</sup> yr<sup>-1</sup>  (net ecosystem productivity) and an overall gross primary productivity of 18.2  t<sub>C</sub> ha<sup>-1</sup> yr<sup>-1</sup>. At the study site, medium sized trees (30-60cm) account for the largest share (66%) of the total productivity. Small (0-30cm) and large trees (>60cm) contribute less with 8.5% and 25.5% respectively. Simulation experiments showed, that species composition showed less effect on forest productivity. Stand productivity therefore is highly depended on vertical stand structure and light climate. Hence, it is important to incorporate small scale information’s about forest stand structure into modelling studies to decrease uncertainties of carbon dynamic predictions. Experiments with such a modelling approach might help to investigate large scale mitigation strategies for climate change that takes local forest stand characteristics into account.</p>

Information support for expert evaluation of the states of the external environment

2020 ◽  
pp. 71-76
Author(s):  
Rasol Murtadha Najah
Keyword(s):  
Decision Making ◽  
Environmental Conditions ◽  
Fuzzy Inference ◽  
Environmental Parameters ◽  
Information Support ◽  
Expert Assessment ◽  
Fuzzy Variables ◽  
Decision Making Models ◽  
The Difference ◽  
State Of The Environment

This article discusses the application of methods to enhance the knowledge of experts to build a decision-making model based on the processing of physical data on the real state of the environment. Environmental parameters determine its ecological state. To carry out research in the field of expert assessment of environmental conditions, the analysis of known works in this field is carried out. The results of the analysis made it possible to justify the relevance of the application of analytical, stochastic models and models based on methods of enhancing the knowledge of experts — experts. It is concluded that the results of using analytical and stochastic objects are inaccurate, due to the complexity and poor mathematical description of the objects. The relevance of developing information support for an expert assessment of environmental conditions is substantiated. The difference of this article is that based on the analysis of the application of expert methods for assessing the state of the environment, a fuzzy logic adoption model and information support for assessing the environmental state of the environment are proposed. The formalization of the parameters of decision-making models using linguistic and fuzzy variables is considered. The formalization of parameters of decision-making models using linguistic and fuzzy variables was considered. The model’s description of fuzzy inference is given. The use of information support for environment state assessment is shown on the example of experts assessing of the land desertification stage.

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