Opportunities and challenges for an Indonesian forest monitoring network

© 2019, INRA and Springer-Verlag France SAS, part of Springer Nature. Key message: Permanent sampling plots (PSPs) are a powerful and reliable methodology to help our understanding of the diversity and dynamics of tropical forests. Based on the current inventory of PSPs in Indonesia, there is high potential to establish a long-term collaborative forest monitoring network. Whilst there are challenges to initiating such a network, there are also innumerable benefits to help us understand and better conserve these exceptionally diverse ecosystems

Penentuan Ukuran Plot Contoh Optimal untuk Pendugaan Luas Bidang Dasar dan Biomassa Tegakan

Luas bidang dasar dan biomassa tegakan hutan dapat dihitung dari data inventarisasi hutan yang diperoleh melalui pengukuran tegakan menggunakan plot-plot contoh dengan ukurandan jumlah tertentu. Tingkat akurasi data dan informasi yang diperoleh dari inventarisasi hutan akan sangat tergantung dari besarnya ukuran dan jumlah plot contoh tersebut. Sampai saat ini, masih sedikit studi yang mempelajari ukuran dan jumlah plot contoh untuk pelaksanaan inventarisasi hutan terutama hutan alam tropis di Indonesia. Penelitian ini bertujuan untuk menentukan ukuran dan jumlah plot contoh optimal untuk pendugaan luas bidang dasar dan biomassa tegakan dalam inventarisasi hutan pada empat jenis ekosistem hutan alam (Hutan Lahan Kering Primer/HLKP, Hutan Lahan Kering Sekunder /HLKS, Hutan Rawa Primer/HRP dan Hutan Rawa Sekunder/HRS). Data yang digunakan adalah data Petak Ukur Permanen (PUP) yang terdapat dalam klaster plot data Inventarisasi Hutan Nasional (National Forest Inventory/NFI) di Indonesia. Analisis data dilakukan untuk mendapatkan nilai koefisien variasi (CV) luas bidang dasar dan biomassa melalui simulasi berbagai ukuran plot contoh. CV menurun dengan meningkatnya ukuran plot, mengikuti tren eksponensial negatif. Ukuran plot optimal untuk HLKP, HLKS, dan HRS adalah 0,40 ha, sedangkan untuk HRP adalah 0,25 ha. Jumlah plot contoh optimal bervariasi sesuai dengan tipe ekosistem hutan dan tingkat kesalahan pengambilan sampel yang diinginkan. Studi ini menegaskan bahwa ukuran dan jumlah plot contoh harus disesuaikan pada setiap ekosistem hutan untuk memfasilitasi inventarisasi hutan yang efisien

Making sustainability work for complex forests: towards adaptive forest yield regulation

Criteria and indicators (C&I) have been worldwide accepted as a way to conceptualize and measure sustainability of forest management. Various C&I sets or standards were formulated by different organizations and processes such as ITTO, CIFOR, FSC, ATO and Montréal Process. These standards, particularly in the production aspect, underline the sustained forest yield principle and the importance of using permanent sample plot data to regulate forest yield. This principle can only be achieved when the forest yield is regulated according to its dynamics and growth which is unique for each site and unlikely to be completely known. As a result, no single yield regulation can be implemented across areas and dynamic complex interaction between forest and people. Any yield regulation practice has to be considered as a hypothesis. This hypothesis then is to be tested in the real world and to be learned for better practice in the future. This is what we call 'adaptive yield regulation’. Some simulation studies proved that this adaptive yield regulation concept meet up with the need for yield regulation schemes for small-scale forest management. In the broader sense the concept and practice of adaptive yield regulation is enfolded in adaptive management, which considers continuous and conscious learning as the only way to manage the complex forests

Allometric Models for Estimating Tree Biomass of Dryland Secondary Forest in East Halmahera

Biomass estimation of secondary forests is required to support the emission reduction of carbon dioxide through an enhancement of forest carbon stocks. Commonly, forest biomass is indirectly estimated using tree biomass allometric models that are developed based on a destructive sampling of sample trees. The availability of biomass allometric models for secondary forests in Indonesia is still limited, particularly for secondary forest ecosystems in eastern Indonesia. This study aimed to develop allometric biomass models for mixed-species trees in a secondary forest of East Halmahera, North Maluku, and to compare their accuracies with some other allometric biomass models that commonly used for estimating biomass of secondary forests. The tree biomass measurement was conducted by using a destructive sampling of 18 mixed-species trees (with diameter range of 5,4 – 36,9 cm) in a secondary forest. The samples of each tree component (stem, branch, twig, and leaf) were analyzed in a laboratory to determine the biomass of each sample tree. Allometric models were developed by using a non-linear regression analysis, which were then compared with other allometric models. This study revealed that the biomass of mixed-species trees in the study area could be estimated accurately using the M7 model that used diameter, height, and wood density variables. Such local allometric model was more accurate than other allometric models commonly used for estimating tropical forest biomass. Alternatively, the M3 model that used diameter and height variables could also be used when wood density data was not available. The local allometric models from this study can enrich the availability of biomass allometric models for secondary forest ecosystems in eastern Indonesia

Spatial Metrics of Deforestation in Kampar and Indragiri Hulu, Riau Province

The Riau Province has been suffering from the highest deforestation rate in Sumatra, Indonesia. Many and various factors haved been discussed as causes of different deforestation types. This research is focused on evaluating the spatial pattern of deforestation in a specific location respresenting a typical deforestation in Riau. The main objective of this study was to identify spatial metrics to describe deforestation that occurred in Kampar and Indragiri Hulu regencies.The study divided the deforestation process into 3 periods of observation, e.g., 1990–2000, 2000–2010, and 2010–2014. The study based on Landsat satellite imagery aquired in 1990, 2000, 2010, and 2014 as the main data sources.  The deforestation  was detected using post-classification comparison (PCC) on the basis of 11 land cover classes developed prior to any further change detection.  The deforestation was initially derived from reclassifying the original classes into only forest and non-forest classes, and then followed by spatial pattern analysis using Fragstat software. The study shows that 2 spatial pattern of deforestation in Kampar distinctly differs from those occurred in Indragiri Hulu Regency, particularly for the period of 1990–2014. The spatial pattern of deforestation in Kampar Regency were clumped, low contiguous between patch, and high fragmentated. Meanwhile, the spatial pattern in Indragiri Hulu Regency were clumped, high contiguous between patch, and low fragmentated. Profile of deforestation in Kampar Regency was cathegorized into early deforestation and Indragiri Hulu Regency as lately deforestation

On the geometry and allometry of big-buttressed trees - a challenge for forest monitoring: new insights from 3D-modeling with terrestrial laser scanning

In many old-growth natural and close-to-natural forest types, notably in humid tropical forests, a relatively small number of very tall trees contribute considerably to stand basal area and biomass. Such trees often show distinct buttress roots with irregular non-convex shapes. Buttresses are complex structures in the lowest stem section, where most tree biomass is located. The methods used to assess the diameter of buttressed trees have a large impact on the determination of volume and biomass, as well as on the resulting estimates of the aboveground carbon stock in tropical forests. As the measurement of diameter at breast height (DBH at 1.3 m) is not feasible in such conditions, the diameter above buttress (DAB), where the cylindrical bole of the tree begins, is usually measured and included as an independent variable in biomass models. We conducted a methodological study aimed at determining the volume and biomass of individual buttressed trees belonging to several tropical species by the application of terrestrial laser scanning (TLS). The geometry and allometry of the buttresses, as well as the change with height along the stem in buttress volume and cross-sectional area were analyzed. Our results suggest that the relationship between cross-sectional areas at DAB height (ADAB) and the actual tree basal area measured at 1.3 m height is relatively strong (R² = 0.87) across a range of different species, buttress morphologies and tree dimensions. Furthermore, the change in stem cross-sectional area with tree height was surprisingly similar and smooth. Despite the small number of trees sampled, the methodological approach used in this study provided new insights on the very irregular geometry of buttressed trees. Our results may help improving the volume and biomass models for buttressed trees, that are crucial contributors to carbon stocks in tropical forests

Form Factors and Volume Models for Estimating Tree Bole Volume of Mahogany at Community Forests in Central Java

Form factors and volume models are often be used in the estimation of tree volumes. However, a few studies have developed and evaluated the accuracy of form factors and volume models for estimating tree volumes of community forests. This study aimed to formulate form factors and volume models and assess their prediction accuracy for estimating tree bole volumes of mahogany at community forests in Central Java. This study used 120 sample trees with diameters of 6–38 cm to formulate artificial and absolute form factors and to develop tree bole volume models. These form factors coupled with bole height and total height were used in simple volume equations. Regression analyses were used to develop volume models using the diameter and total height as predictors. The simple volume equations and volume models' prediction accuracy was evaluated using a cross-validation dataset and independent dataset (30 sample trees). The artificial form factor (0.68 ± 0.11) of mahogany, which was higher than the absolute form factor (0.46 ± 0.09), provided accurate estimates of tree bole volumes when it was used with the bole height instead of the total height. The volume model that uses diameter and total height produced the most accurate estimates, while the volume model that uses diameter alone provided the most practical yet reliable tool for estimating tree bole volumes of mahogany. The results of this study are useful for improving community forest management