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Articles containing the keyword 'optimality'

Category : Article

article id 5546, category Article

Oliver Schabenberger, Timothy G. Gregoire. (1995). A conspectus on Estimating Function theory and its applicability to recurrent modeling issues in forest biometry. Silva Fennica vol. 29 no. 1 article id 5546. https://doi.org/10.14214/sf.a9197

Keywords: modelling; mixed models; statistical methods; longitudinal data; generalized linear models; optimality

Abstract | View details | Full text in PDF | Author Info

Much of forestry data is characterized by a longitudinal or repeated measures structure where multiple observations taken on some units of interest are correlated. Such dependencies are often ignored in favour of an apparently simpler analysis at the cost of invalid inferences. The last decade has brought to light many new statistical techniques that enable one to successfully deal with dependent observations. Although apparently distinct at first, the theory of Estimating Functions provides a natural extension of classical estimation that encompasses many of these new approaches. This contribution introduces Estimating Function Theory as a principle with potential for unification and presents examples covering a variety of modelling issues to demonstrate its applicability.

Schabenberger, E-mail: os@mm.unknown
Gregoire, E-mail: tg@mm.unknown

Category : Research article

article id 10089, category Research article

Arto Haara, Annika Kangas, Sakari Tuominen. (2019). Economic losses caused by tree species proportions and site type errors in forest management planning. Silva Fennica vol. 53 no. 2 article id 10089. https://doi.org/10.14214/sf.10089

Keywords: forest inventory; value of information; uncertainty; sub-optimality loss

Highlights: Errors in tree species proportions caused more economic losses for forest owners than site type errors; Economic losses due to sub-optimal treatments were observed from 26.5% to 31.7% of plots, depending on the remote sensing data set used; Even with the most accurate remote sensing data set, namely ALS data set, NPV losses were on average 124.4 € ha^–1 with 3% interest rate.

Abstract | Full text in HTML | Full text in PDF | Author Info

The aim of this study was to estimate economic losses, which are caused by forest inventory errors of tree species proportions and site types. Our study data consisted of ground truth data and four sets of erroneous tree species proportions. They reflect the accuracy of tree species proportions in four remote sensing data sets, namely 1) airborne laser scanning (ALS) with 2D aerial image, 2) 2D aerial image, 3) 3D and 2D aerial image data together and 4) satellite data. Furthermore, our study data consisted of one simulated site type data set. We used the erroneous tree species proportions to optimise the timing of forest harvests and compared that to the true optimum obtained with ground truth data. According to the results, the mean losses of Net Present Value (NPV) because of erroneous tree species proportions at an interest rate of 3% varied from 124.4 € ha^–1 to 167.7 € ha^–1. The smallest losses were observed using tree species proportions predicted using ALS data and largest using satellite data. In those stands, respectively, in which tree species proportion errors actually caused economic losses, they were 468 € ha^–1 on average with tree species proportions based on ALS data. In turn, site type errors caused only small losses. Based on this study, accurate tree species identification seems to be very important with respect to operational forest inventory.

Haara, Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: arto.haara@luke.fi
Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 68, FI-80101 Joensuu, Finland https://orcid.org/0000-0002-8637-5668 E-mail: annika.kangas@luke.fi
Tuominen, Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 2, FI-00791 Helsinki, Finland https://orcid.org/0000-0001-5429-3433 E-mail: sakari.tuominen@luke.fi

article id 111, category Research article

Ilona Pietilä, Annika Kangas, Antti Mäkinen, Lauri Mehtätalo. (2010). Influence of growth prediction errors on the expected losses from forest decisions. Silva Fennica vol. 44 no. 5 article id 111. https://doi.org/10.14214/sf.111

Keywords: growth prediction; uncertainty; forest information; updating; inoptimality loss

Abstract | View details | Full text in PDF | Author Info

In forest planning, forest inventory information is used for predicting future development of forests under different treatments. Model predictions always include some errors, which can lead to sub-optimal decisions and economic loss. The influence of growth prediction errors on the reliability of projected forest variables and on the treatment propositions have previously been examined in a few studies, but economic losses due to growth prediction errors is an almost unexplored subject. The aim of this study was to examine how the growth prediction errors affected the expected losses caused by incorrect harvest decisions, when the inventory interval increased. The growth models applied in the analysis were stand-level growth models for basal area and dominant height. The focus was entirely on the effects of growth prediction errors, other sources of uncertainty being ignored. The results show that inoptimality losses increased with the inventory interval. Average relative inoptimality loss was 3.3% when the inventory interval was 5 years and 11.6% when it was 60 years. Average absolute inoptimality loss was 230 euro ha^–1 when the inventory interval was 5 years and 860 euro ha^–1 when it was 60 years. The average inoptimality losses varied between development classes, site classes and main tree species.

Pietilä, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ip@nn.fi
Kangas, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: annika.kangas@helsinki.fi
Mäkinen, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: am@nn.fi
Mehtätalo, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: lm@nn.fi

article id 218, category Research article

Md. Nurul Islam, Mikko Kurttila, Lauri Mehtätalo, Arto Haara. (2009). Analyzing the effects of inventory errors on holding-level forest plans: the case of measurement error in the basal area of the dominated tree species. Silva Fennica vol. 43 no. 1 article id 218. https://doi.org/10.14214/sf.218

Keywords: inoptimality loss; dominated tree species; erroneous inventory data; forest plan

Abstract | View details | Full text in PDF | Author Info

Accurate inventory data are required for ensuring optimal net return on investment from the forest. Erroneous data can lead to the formulation of a non-optimal plan that can cause inoptimality losses. Little is known of the effect of using erroneous stand inventory data in preparing holding-level forest plans. This study reports on an approach for analyzing such inoptimality losses. Furthermore, inoptimality losses caused by measurement errors in the basal area of the dominated tree species were investigated in a case study. Based on the inventory data including routine measurements by 67 measurers, four measurer groups were created with different measurement error profiles for the basal area of the dominated tree species. This was followed by measurement error simulations for each group and by adding these to the accurate control inventory data to create erroneous data of different error profiles. Three different forest plans were then constructed by using erroneous data of each group. The plans were then analyzed and compared with plans based on correct data. The effect of measurement errors on the net present value from the whole planning period, and on the amount of remaining growing stock at the end of planning period, were analyzed and utilized in calculating the inoptimality losses. It was concluded that even errors involving dominated tree species can cause significant changes in the holding-level forest plans.

Islam, University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland E-mail: nurul.islam@joensuu.fi
Kurttila, Finnish Forest Research Institute, Joensuu Research Unit, FI-80101 Joensuu, Finland E-mail: mk@nn.fi
Mehtätalo, University of Helsinki, Dept. of Forest Resource Management, FI-00014 University of Helsinki, Finland E-mail: lm@nn.fi
Haara, University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland E-mail: ah@nn.fi

article id 531, category Research article

Thomas N. Buckley, Jeffrey M. Miller, Graham D. Farquhar. (2002). The mathematics of linked optimisation for water and nitrogen use in a canopy. Silva Fennica vol. 36 no. 3 article id 531. https://doi.org/10.14214/sf.531

Keywords: stomatal conductance; optimality theory; nitrogen allocation; NUE; WUE

Abstract | View details | Full text in PDF | Author Info

We develop, and discuss the implementation of, a mathematical framework for inferring optimal patterns of water and nitrogen use. Our analysis is limited to a time scale of one day and a spatial scale consisting of the green canopy of one plant, and we assume that this canopy has fixed quantities of nitrogen and water available for use in photosynthesis. The efficiencies of water and nitrogen use, and the interactions between the two, are strongly affected by physiological and physical properties that can be modeled in different ways. The thrust of this study is therefore to discuss these properties and how they affect the efficiencies of nitrogen and water use, and to demonstrate, qualitatively, the effects of different model assumptions on inferred optimal strategies. Preliminary simulations suggest that the linked optimisation of nitrogen and water use is particularly sensitive to the level of detail in canopy light penetration models (e.g., whether sunlit and shaded fractions are pooled or considered independently), and to assumptions regarding nitrogen and irradiance gradients within leaves (which determine how whole-leaf potential electron transport rate is calculated from leaf nitrogen content and incident irradiance).

Buckley, Environmental Biology Group, Research School of Biological Sciences, The Australian National University, GPO Box 475, Canberra City, ACT 2601, Australia and Cooperative Research Centre for Greenhouse Accounting, RSBS, ANU E-mail: tom_buckley@alumni.jmu.edu
Miller, Environmental Biology Group, Research School of Biological Sciences, The Australian National University, GPO Box 475, Canberra City, ACT 2601, Australia E-mail: jmm@nn.au
Farquhar, Environmental Biology Group, Research School of Biological Sciences, The Australian National University, GPO Box 475, Canberra City, ACT 2601, Australia and Cooperative Research Centre for Greenhouse Accounting, RSBS, ANU E-mail: gdf@nn.au

article id 530, category Research article

Graham D. Farquhar, Thomas N. Buckley, Jeffrey M. Miller. (2002). Optimal stomatal control in relation to leaf area and nitrogen content. Silva Fennica vol. 36 no. 3 article id 530. https://doi.org/10.14214/sf.530

Keywords: stomatal conductance; optimal leaf area; optimality theory; resource substitution

Abstract | View details | Full text in PDF | Author Info

We introduce the simultaneous optimisation of water-use efficiency and nitrogen-use efficiency of canopy photosynthesis. As a vehicle for this idea we consider the optimal leaf area for a plant in which there is no self-shading among leaves. An emergent result is that canopy assimilation over a day is a scaled sum of daily water use and of photosynthetic nitrogen display. The respective scaling factors are the marginal carbon benefits of extra transpiration and extra such nitrogen, respectively. The simple approach successfully predicts that as available water increases, or evaporative demand decreases, the leaf area should increase, with a concomitant reduction in nitrogen per unit leaf area. The changes in stomatal conductance are therefore less than would occur if leaf area were not to change. As irradiance increases, the modelled leaf area decreases, and nitrogen/leaf area increases. As total available nitrogen increases, leaf area also increases. In all the examples examined, the sharing by leaf area and properties per unit leaf area means that predicted changes in either are less than if predicted in isolation. We suggest that were plant density to be included, it too would further share the response, further diminishing the changes required per unit leaf area.

Farquhar, Cooperative Research Centre for Greenhouse Accounting and Environmental Biology Group, Research School of Biological Sciences, Australian National University, ACT 2601, Australia E-mail: farquhar@rsbs.anu.edu.au
Buckley, Cooperative Research Centre for Greenhouse Accounting and Environmental Biology Group, Research School of Biological Sciences, Australian National University, ACT 2601, Australia E-mail: tnb@nn.au
Miller, Research School of Biological Sciences, Australian National University, ACT 2601, Australia E-mail: jmm@nn.au

Category : Review article

article id 535, category Review article

Thomas J. Givnish. (2002). Adaptive significance of evergreen vs. deciduous leaves: solving the triple paradox. Silva Fennica vol. 36 no. 3 article id 535. https://doi.org/10.14214/sf.535

Keywords: deciduous trees; phenology; evergreens; optimality models; leaf longevity

Abstract | View details | Full text in PDF | Author Info

Givnish, Dept of Botany, University of Wisconsin, Madison, WI 53706, USA E-mail: givnish@facstaff.wisc.edu

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