Empirical Models for Estimating the Stand Biomass of Teak Plantations in Java, Indonesia(&lt;Special Issue&gt;Multipurpose Forest Management)

Tiryana, Tatang; Tatsuhara, Satoshi; Shiraishi, Norihiko

doi:10.20659/jfp.16.special_issue_177

Cited by 10 publications

(9 citation statements)

References 16 publications

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“…By following the methods of Fujikake (2003), Hiroshima (2006), andTiryana et al (2011), and considering Eqs. 1 and 2, we can describe the likelihood function (L) of the observation as follows:…”

Section: Survival Analysis Of Target Treesmentioning

confidence: 99%

Survival analyses of individual tree populations in natural forest stands to evaluate the maturity of forest stands: A case study ofpreserved forests in Northern Japan

Wijenayake

Hiroshima

2022

JFP

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Most survival analyses in forest science have been applied to planted forests where tree age usually had no dispersal on one stand, while there have been few reports about the age-based survival analyses in natural forests. The purpose of this study was to perform survival analyses of individual tree populations in natural forest stands to evaluate the matured states of forest stands. We used a combination of tree-ring and census data from the three preserved permanent plots in pan-mixed and sub-boreal natural forests, Hokkaido, northern Japan. All the living trees (diameter at breast height ≥ 5 cm in 1989) were targeted to identify tree ages using a RESISTOGRAPH. Periodical tree age data with a 10-year age class were used during the observation periods of 1989-1999, 1999-2009, and 2009-2019, and all the changes (i.e., death and new ingrowth) during the periods were recorded. In the analyses, first, we applied survival analyses to find out multi-temporal age distributions and non-parametric estimates. Secondly, we applied parametric Weibull distributions to calculate age-related metrics such as mean lifetime and mean age of stands. Finally, we evaluated these calculated metrics from the viewpoints of matured states of forest stands. The results of non-parametric survival analyses showed the age distribution of multi-modal and exponential shapes. We also found the differences in survival probabilities among periods were not significant except for one plot. We also compared the relationship among estimated mean lifetime, biological lifetime, and mean age of stands derived from parametric survival analyses with the Weibull distribution and evaluated the matured states of stands considering all these aspects. It was implied that the study stands might not get enough matured yet, but some plots showed further progress toward the matured state than others.

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Section: Survival Analysis Of Target Treesmentioning

confidence: 99%

Survival analyses of individual tree populations in natural forest stands to evaluate the maturity of forest stands: A case study ofpreserved forests in Northern Japan

Wijenayake

Hiroshima

2022

JFP

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“…Akar rata-rata kuadrat simpangan (RMSE) menunjukkan ketepatan dari pendugaan (Freund et al, 2010;Sumadi & Siahaan, 2010;. Model terbaik adalah model dengan RMSE terendah (Tiryana et al, 2011;Qirom, 2018). SR merupakan rata-rata jumlah dari nilai mutlak selisih antara volume dugaan dan volume aktual, proporsional terhadap jumlah volume dugaan (Riady, 2011).…”

Section: Pemilihan Model Terbaikunclassified

Timber Volume Estimation Model for Commercial Tree Species in the Logging Area Concession of PT. Tunas Timber Lestari in Boven Digul, Papua

Hutapea

2019

JWAS

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Model penduga volume pohon merupakan salah satu komponen penting dalam mewujudkan pengelolaan hutan lestari. Saat ini, berbagai model telah disusun untuk berbagai tipe hutan di Indonesia. Namun demikian, model-model tersebut belum mewakili tipe ekosistem hutan di Papua. Oleh sebab itu, berbagai studi masih sangat diperlukan untuk menyusun model penduga volume pohon untuk berbagai tipe ekosistem di Papua. Penelitian ini bertujuan untuk menyusun model penduga volume pohon jenis komersial di areal PT. Tunas Timber Lestari di Distrik Sesnukt, Kabupaten Boven Digul, Provinsi Papua. Sebanyak 164 pohon contoh dipilih untuk menyusun model penduga volume pohon dan 50 pohon contoh untuk validasi model. Hasil penelitian menunjukkan bahwa diameter dan tinggi pohon tidak memiliki korelasi yang kuat. Oleh sebab itu, model penduga harus disusun berdasarkan kombinasi diameter dengan tinggi pohon. Model terbaik pada tahapan penyusunan model dipilih berdasarkan nilai koefisien determinasi (R 2), kesalahan standar estimasi (SEE), dan Fhitung. Sementara model terbaik pada tahap validasi model dipilih berdasarkan nilai bias (e), rata-rata kuadrat simpangan (RMSE), simpangan rata-rata (SR), simpangan agregatif (SA), dan χ 2 hitung. Model terbaik untuk menduga volume pohon jenis komersial di PT.

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“…The cost is low and it can be done quickly, flexibly, and accurately [11,12]. Variables that are easily obtained in estimating stand biomass are basal area and age [13]. The Bitterlich method is more accurate and efficient in estimating basal area and volume of pine stands [14].…”

Section: Introductionmentioning

confidence: 99%

Application of Point Sampling Method in Estimation of Stand Basal Area in Community Forest

Mulyana

Rohman

Purwanto

2018

j. sylva indonesiana

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Estimation of the potency of community forest is usually done with the census approach for each forest. Sampling methods to estimate the potency of community forest are still rare. The size of community forest is relatively small, scatter, and less irregular shape, therefore the estimation of community forest potency using sampling plot is difficult to apply. The approach of sampling without a plot (plotless/ point sampling) was cheaper and faster compare to the method of sample plots and direct measurement (census) in predicting basal area. The objective of this research is determining the difference in the average value of basal area using direct measurement of stand (census) and point sampling methods. The research was carried out for 4 months in 30 community forests at Kemuning Village, Gunungkidul District. Materials used to estimate basal area with point sampling method were Spiegel Relascope and Bitterlich Stick with the value of Basal Area Factor 1. Parameters measured were diameter at breast high (dbh) for census method and the number of trees were categorized in or border for point sampling method. The result was analyzed statistically using unpaired t-student. The result showed that the average of basal area of tree in community forest with point sampling method were no significantly different from the average of basal area with census method (α = 1%). Therefore, the point sampling method can be considered as a tool in inventory at community forest

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Empirical Models for Estimating the Stand Biomass of Teak Plantations in Java, Indonesia(<Special Issue>Multipurpose Forest Management)

Cited by 10 publications

References 16 publications

Survival analyses of individual tree populations in natural forest stands to evaluate the maturity of forest stands: A case study ofpreserved forests in Northern Japan

Survival analyses of individual tree populations in natural forest stands to evaluate the maturity of forest stands: A case study ofpreserved forests in Northern Japan

Timber Volume Estimation Model for Commercial Tree Species in the Logging Area Concession of PT. Tunas Timber Lestari in Boven Digul, Papua

Application of Point Sampling Method in Estimation of Stand Basal Area in Community Forest

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