File Name: physiological ecology of forest production principles processes and models .zip
Models of trees and stands exist since many decades, what nowadays has changed is our focus towards integrated forest ecosystem functioning. Managing forests in the 21 st century requires efforts that go beyond empiricism. It is a textbook for graduates and scientists interested in process-based models of stand dynamics, growth and forest management. Models represent valuable tools for tackling issues like ecosystem carbon sequestration, helping us understand the economic implications of silvicultural interventions and providing insights on the impacts of climate change on forests.
The textbook is a compendium of applied research that non-pure mathematicians can understand, interiorize and take advantage of for getting precious knowledge on forest functioning.
Models of tree and stand dynamics. Springer Nature, Cham, Switzerland, pp. Forests play a relevant role in the global carbon cycle and this mitigation potential - that lies in the accumulated stock of forest ecosystem carbon - has dynamics we either ignore or we are not able to predict completely right now.
Could we forecast forest productivity on large geographical areas, under several climate change scenarios? Will forests react to changing environmental conditions? If so, how? If these questions sound rather familiar, it seems we are aware about the key role of forests and what the challenges in managing forests in the 21 st century are.
What some might not know, is that none of these issues could ever be faced without models. This is not the first book addressing forest modelling see  ,  ,  , but is certainly the first one integrating an extensive documentation of theory and concepts and their translation into source codes for a prompt computer programming and testing. Thus, this is not a merely descriptive book and coherently the authors stated that the description of the plethora of existing forest models can be found elsewhere.
As a premise, the book aims at bridging the gap between empirical and process-based models using mathematical tools and numerical estimations and it perfectly does so by covering a wide range of examples with a rich set of R-codes at the end of each chapter and including solutions, which were much appreciated. The same, the reader should not be too much concerned about sinking into complex equations, but rather the logic behind is easily comprehensible even from non-pure mathematicians.
The focus is immediately stated: the book mainly covers process-based models that incorporate mechanism, hybridisation, or optimisation, singly or in combination. Yet why? Because our common understanding of stand dynamics, growth and management lacks and is generally limited by a predetermined set of empirical data which we try to rely on.
Chapter 6 deals with individual tree and stand-level competition thus focusing on the challenging issue of resource limitation to total growth and productivity.
Applications of evolutionary optimisation to tree structure and consequent carbon allocation are introduced in chapter 7 altogether with examples of models that use this approach to derive plant structure and carbon allocation e. How does forest production vary regionally? Is climate change going to increase or decrease productivity and carbon sequestration? To tackle these issues, go to Chapter 8 which outlines some general ideas and overall accepted theories about linking models with data, moving to input quantification for model applications by introducing different methods of parameterisation for a chosen model Chapter 5.
Data assimilation is widely used in other rather different fields such as engineering, meteorology and physical oceanography… but it surprisingly happens in forestry research, too. In chapter 9 some basic concepts - central to model calibration - are illustrated, followed by some examples of Bayesian calibration as used in ecological modelling, in comparison with conventional statistical parameter calibration.
Two examples of calibrated models for predicting forest growth and estimating carbon balance are also shown. Worth noting, a clear definition and distinction of what state variables, parameters and driving or forcing variables, including model hierarchical organizations, is provided. What sounds obvious in the theory not often reflects in the practice, and this is even a practical textbook.
There is an increasing demand by national forest policies to assess sustainable harvest levels, forest potential for climate change mitigation, or the supply of roundwood and biomass to the global markets and far more.
In this sense, forest modelling represents a valuable toolbox to inspect pressing issues like ecosystem carbon sequestration, economic implications of different silvicultural interventions and policies.
In chapter 10 some sound applications of modelling frameworks are provided. In conclusion, we know that models of trees and stands have existed for hundreds of years, but what has changed now is our focus towards integrated ecosystem functioning rather than single tree growth. Quo vadis then? Forest management recommendations in many countries are based on economical optimization studies that assess the impact of intervention on economic revenue and costs , trying to find appropriate strategies that are beneficial for the stakeholders.
Consequentially, standard optimization studies in forestry are centred and based on empirical growth models. And that is often the case in forest management. It is crucial to bridge empirical and process-based data assimilation methods that combine research-based ecological measurements with standard forestry data.
Another useful application of process-based stand-level models relies on the possibility to estimate forest productivity in areas not subject to forest inventory. In this case, we should also consider incorporating air-borne measurement methods such as LiDAR, drones, and different varieties of satellite-derived vegetational indexes to drive our models.
Nevertheless, the biggest challenge in nowadays forest models - at any level of spatial and temporal resolution - is to make reliable predictions under climate change, especially when not all has been or can be accounted for. These are our new quantum leaps, hic sunt dracones. Marano G, Collalti A Total Article Views: from publication date up to now. Web Metrics Days since publication: Overall contacts: Avg. Article citations are based on data periodically collected from the Clarivate Web of Science web site last update: Feb Local ecological niche modelling to provide suitability maps for 27 forest tree species in edge conditions.
Spatio-temporal modelling of forest monitoring data: modelling German tree defoliation data collected between and for trend estimation and survey grid examination using GAMMs. Dynamic modelling of target loads of acidifying deposition for forest ecosystems in Flanders Belgium.
Some refinements on species distribution models using tree-level National Forest Inventories for supporting forest management and marginal forest population detection. A comparison of models for quantifying growth and standing carbon in UK Scots pine forests. Artificial intelligence associated with satellite data in predicting energy potential in the Brazilian savanna woodland area.
Modeling forest trees and stands. CrossRef Gscholar. Landsberg J, Sands P Physiological ecology of forest production: principles, processes and models Vol. A quantitative analysis of plant form - the pipe model theory. Basic analysis. Japanese Journal of Ecology Online Gscholar.
Further evidence of the theory and its application in forest ecology. Forest ecosystems, analysis at multiple scales 3rd edn. Academic Press, S. Corresponding author. Alessio Collalti alessio. Breakdown by View Type Waiting for server response Page Top none References. Related Contents. Download Reference. Citation Marano G, Collalti A RIS Zotero. Nature and Landscape Conservation.
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Models of trees and stands exist since many decades, what nowadays has changed is our focus towards integrated forest ecosystem functioning. Managing forests in the 21 st century requires efforts that go beyond empiricism. It is a textbook for graduates and scientists interested in process-based models of stand dynamics, growth and forest management. Models represent valuable tools for tackling issues like ecosystem carbon sequestration, helping us understand the economic implications of silvicultural interventions and providing insights on the impacts of climate change on forests. The textbook is a compendium of applied research that non-pure mathematicians can understand, interiorize and take advantage of for getting precious knowledge on forest functioning.
Process-based models open the way to useful predictions of the future growth rate of forests and provide a means of assessing the probable effects of variations in climate and management on forest productivity. As such they have the potential to overcome the limitations of conventional forest growth and yield models, which are based on mensuration data and assume that climate and atmospheric CO2 concentrations will be the same in the future as they are now.