Dynamics and management of Alaska boreal forest: An all-aged multi-species matrix growth model

Liang, Jingjing

doi:10.1016/j.foreco.2010.04.040

Cited by 31 publications

(23 citation statements)

References 25 publications

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“…From the computational and analytical viewpoint, matrix models are actually simpler by structure than empirical-statistical individual tree models [1], and they essentially require handling of less information [8]. With respect to accuracy, matrix models have been shown to predict tree growth accurately-both in the short term [34] and long term [18,22]. This paper introduces a new time-dependent transition matrix model for predicting pine growth in northern Finland, in which the time-dependency originates from modelling the basal area evolving in time.…”

Section: Discussionmentioning

confidence: 99%

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Introducing a Non-Stationary Matrix Model for Stand-Level Optimization, an Even-Aged Pine (Pinus Sylvestris L.) Stand in Finland

Pyy

Ahtikoski

Laitinen

et al. 2017

Forests

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Abstract:In general, matrix models are commonly applied to predict tree growth for size-structured tree populations, whereas empirical-statistical models are designed to predict tree growth based on a vast amount of field observations. From the theoretical point of view, matrix models can be considered to be more generic since their dependency on ad hoc growth conditions is far less prevalent than that of empirical-statistical models. On the other hand, the main pitfall of matrix models is their inability to include variation among the individuals within a size class, occasionally resulting in less accurate predictions of tree growth compared to empirical-statistical models. Thus, the relevant question is whether a matrix model can capture essential tree-growth dynamics/characteristics so that the model produces accurate stand projections which can further be applied in practical decision-making. Such a dynamic characteristic in our model is the basal area of trees, which causes nonlinearity in time. Therefore, our matrix model is a nonlinear model. The empirical data for models was based on 20 sample plots representing 8360 tree records. Further, according to the model, stand projections were produced for three Scots pine (Pinus sylvestris L.) sapling stands (age of 25 years, stand density fluctuating from 850 to 1400 stems ha −1 ). Then, (even-aged) stand management was optimized by applying sequential quadratic programming (SQP) among those growth predictions. The objective function of the optimization task was to maximize the net present value (NPV) of the ongoing rotation. The stands were located in Northern Ostrobothnia, Finland, on nutrient-poor soil type. The results indicated that initial stand density had an effect on optimal solutions-optimal stand management varied with respect to thinnings (timing and intensity) as well as to optimal rotation. Further, an increasing discount rate shortened considerably the optimal rotation period, and relaxing the minimum thinning removal to 30 m 3 ha −1 resulted in an increase both in number of thinnings and in the maximum net present value.

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Section: Discussionmentioning

confidence: 99%

“…The time dependency introduced in this paper contributes to the current literature on matrix growth models (e.g., [1,11,18,22]). …”

Section: The Growth Modelmentioning

confidence: 99%

Introducing a Non-Stationary Matrix Model for Stand-Level Optimization, an Even-Aged Pine (Pinus Sylvestris L.) Stand in Finland

Pyy

Ahtikoski

Laitinen

et al. 2017

Forests

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“…From the initial fixed-parameter transition matrix (Buongiorno and Michie, 1980) to the recent models which account for site and demographic factors (e.g. Liang, 2010;Picard et al, 2010) as well as geospatial variability (e.g. Liang and Zhou, 2010;Liang, in preparation), matrix models have been substantially improved for applications in five continents worldwide.…”

Section: Introductionmentioning

confidence: 99%

“…With a growing interest in timber and wood-based energy in the region, Liang (2010) has developed a conventional matrix model to facilitate studies and management of the Alaska boreal forest, but this model is susceptible to bias when applied to stands outside the sample area or to large regions where spatial patterns are not accounted for (Liang, 2010). To this end, a controlled trend surface (CTS) matrix model (Liang and Zhou, 2010) has been developed for improved regional accuracy.…”

Section: Introductionmentioning

confidence: 99%

Mapping forest dynamics under climate change: A matrix model

Liang

Zhou

Verbyla

et al. 2011

Forest Ecology and Management

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“…Pengelolaan hutan berkelanjutan sangat membutuhkan informasi pertumbuhan dan hasil (Krisnawati, Suhendang, & Parthama, 2008;Lhotka & Loewenstein, 2011;Liang, 2010;Pukkala, Lähde, & Laiho, 2009). Namun ketersediaan informasi tersebut masih sangat terbatas dan sangat sedikit mengingat sangat bervariasinya kondisi hutan tropis di Indonesia.…”

Section: Pendahuluanunclassified

Growth Model of Remmant Stands in Selectively Logged Forest, Papua

Kuswandi

2017

JPTH

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ABSTRAKPengelolaan hutan berkelanjutan sangat membutuhkaninformasi pertumbuhan yang mengintegrasikan fungsifungsi ingrowth, upgrowth, dan mortality. Penelitian dilakukan pada areal Ijin Usaha Pemanfaatan Hasil hutan Kayu (IUPHHK) PT. Tunas Timber Lestari (TTL), PT. Wapoga Mutiara Timber (WMT) dan PT. Manokwari Mandiri Lestari (MML) di Papua. Tujuan dari penelitian ini adalah untuk menghasilkan model pertumbuhan tegakan untuk hutan alam bekas tebangan berdasarkan data petak ukur permanen di Papua. Model Hasil penelitian menunjukkan bahwa karakteristik tegakan (luas bidang dasar, jumlah pohon dan ukuran/diameter pohon) berpengaruh berbeda terhadap model ingrowth, upgrowth, dan mortalitytegakan pada masing-masing lokasi. Pada PT WMT karakterisitik tegakan berpengaruh nyata terhadap model ingrowth, upgrowth, dan mortality yang ditunjukan dengan nilai koefisien determinasi yang tinggi >80% dan Pval<0,05, walaupun pengaruh karakterisik tegakan tidak secara bersamaan berlaku pada setiap model. Pada PT MML yang berpengaruh nyata hanya model ingrowth dan upgrowth, sedangkan pada PT. TTL hanya model ingrowth. Kata kunci: model seluruh tegakan, model linier, hutan bekas tebangan, Papua

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Dynamics and management of Alaska boreal forest: An all-aged multi-species matrix growth model

Cited by 31 publications

References 25 publications

Introducing a Non-Stationary Matrix Model for Stand-Level Optimization, an Even-Aged Pine (Pinus Sylvestris L.) Stand in Finland

Introducing a Non-Stationary Matrix Model for Stand-Level Optimization, an Even-Aged Pine (Pinus Sylvestris L.) Stand in Finland

Mapping forest dynamics under climate change: A matrix model

Growth Model of Remmant Stands in Selectively Logged Forest, Papua

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