CABALA: a linked carbon, water and nitrogen model of forest growth for silvicultural decision support

2004 ◽  
Vol 193 (1-2) ◽  
pp. 251-282 ◽  
Author(s):  
Michael Battaglia ◽  
Peter Sands ◽  
Don White ◽  
Daryl Mummery
Keyword(s):  
Decision Support ◽  
Forest Growth ◽  
Nitrogen Model

scholarly journals Spatial Pattern of Climate Change Effects on Lithuanian Forestry

Forests ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 809 ◽  
Author(s):  
Gintautas Mozgeris ◽  
Vilis Brukas ◽  
Nerijus Pivoriūnas ◽  
Gintautas Činga ◽  
Ekaterina Makrickienė ◽  
...  
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Ecosystem Services ◽  
Forest Management ◽  
Decision Support Systems ◽  
Tree Species ◽  
Support Systems ◽  
Forest Growth ◽  
Climate Change Scenarios ◽  
Climate Change Effects

Research Highlights: Validating modelling approach which combines global framework conditions in the form of climate and policy scenarios with the use of forest decision support system to assess climate change impacts on the sustainability of forest management. Background and Objectives: Forests and forestry have been confirmed to be sensitive to climate. On the other hand, human efforts to mitigate climate change influence forests and forest management. To facilitate the evaluation of future sustainability of forest management, decision support systems are applied. Our aims are to: (1) Adopt and validate decision support tool to incorporate climate change and its mitigation impacts on forest growth, global timber demands and prices for simulating future trends of forest ecosystem services in Lithuania, (2) determine the magnitude and spatial patterns of climate change effects on Lithuanian forests and forest management in the future, supposing that current forestry practices are continued. Materials and Methods: Upgraded version of Lithuanian forestry simulator Kupolis was used to model the development of all forests in the country until 2120 under management conditions of three climate change scenarios. Selected stand-level forest and forest management characteristics were aggregated to the level of regional branches of the State Forest Enterprise and analyzed for the spatial and temporal patterns of climate change effects. Results: Increased forest growth under a warmer future climate resulted in larger tree dimensions, volumes of growing stock, naturally dying trees, harvested assortments, and also higher profits from forestry activities. Negative impacts were detected for the share of broadleaved tree species in the standing volume and the tree species diversity. Climate change effects resulted in spatially clustered patterns—increasing stand productivity, and amounts of harvested timber were concentrated in the regions with dominating coniferous species, while the same areas were exposed to negative dynamics of biodiversity-related forest attributes. Current forest characteristics explained 70% or more of the variance of climate change effects on key forest and forest management attributes. Conclusions: Using forest decision support systems, climate change scenarios and considering the balance of delivered ecosystem services is suggested as a methodological framework for validating forest management alternatives aiming for more adaptiveness in Lithuanian forestry.

scholarly journals Evaluation of the basal area growth models in the Finnish stand simulator MOTTI with data from the Estonian network of permanent forest growth plots / Soome puistukasvusimulaatori MOTTI rinnaspindala juurdekasvumudelite prognoositäpsuse hindamine Eesti metsa kasvukäigu püsiproovitükkide võrgustiku mõõtmisandmete põhjal

2011 ◽  
Vol 55 (1) ◽  
pp. 80-97
Author(s):  
Ando Lilleleht ◽  
Allan Sims ◽  
Andres Kiviste ◽  
Jari Hynynen ◽  
Mika Lehtonen
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Growth Models ◽  
Model Performance ◽  
Basal Area ◽  
Forest Growth ◽  
Tree Level ◽  
Basal Area Growth ◽  
Area Growth

Abstract Forest management has become a more complex issue than it has ever been before. Foresters need to fulfill the demands of several interest groups, often which are conflicting. Finding the balance between different management objectives can be facilitated with the use of decision support systems. Since no decision support systems have been developed in Estonia, the aim of this study is to assess the applicability of the Finnish stand growth simulator MOTTI in Estonia. The evaluation focuses on the basal area growth models; the data used originates from the Estonian network of permanent forest growth plots. Tree-level bias models were constructed for all major tree species in order to assess model performance. Also, bias was examined visually with the use of residual plots. Results show that bias levels and variables which contribute to bias differ by species. Based on the fit statistics of the bias models, Common aspen shows the highest bias level whereas the growth of Gray alder seems to be predicted most accurately. Although model performance is decent for a model that is used outside of its application limits, calibration should still be considered as a prerequisite to implement the MOTTI system in Estonian forestry practice.

Clinical decision support

2013 ◽  
Vol 46 (2) ◽  
pp. 52
Author(s):  
CHRISTOPHER NOTTE ◽  
NEIL SKOLNIK
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision
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