The Dynamics of Species Composition Stand Structure and Above Ground Biomass of Undisturbed Forest in East Kalimantan

Dinamika Komposisi Spesies Struktur Pohon dan Biomasa di Hutan Terganggu di Kalimantan Timur. Kajian dinamika komposisi spesies dan biomasanya dilakukan selama 4,3 tahun (Desember 2004 - April 2009) di hutan terganggu Kalimantan Timur. Untuk melakukan kajian di gunakan 6 plot permanen (100x100 m2), yang berada di hutan penelitian Samboja. Semua pohon berdiameter > 10 cm dbh (diukur pada posisi 1,3 m diatas tanah). Pada Desember 2004,tercatat 2143 pohon tersebar di plot tersebut terdiri dari 39 famili, 82 genus dan 111 spesies. Pada pengamatan April 2009 tercatat 2466 pohon terdiri dari 40 famili, 86 genus dan 123 jenis.Sebagian besar spesies yang mendominasi adalah Garcinia nervosa dan Trigonostemon laevigatus tetapi setelah pengamatan pada tahun 2009, keduanya tidak lagi mendominasi. Selama kurun 4,3 tahun terjadi penambahan kepadatan 15,1%, basal area 12,9% dan biomasa 11,6%. Penambahan kepadatan tercatat meningkat dari 357 menjadi 411 pohon/ha. Basal area meningkat mulai dari 20,09 menjadi 22,67 m2 ha-1, sedangkan biomasa meningkat dari 286,3 menjadi 319,4 ton ha-1

Changes in the Species Composition, Stand Structure and Aboveground Biomass of a Lowland Dipterocarp Forest in Samboja, East Kalimantan

The dynamics of species composition, stand structure and aboveground biomass were studied over a 4.3-yr period (December 2004 – April 2009) in a lowland dipterocarp forest of Samboja, East Kalimantan. This study was conducted in six permanent sample plots (100 m x 100 m each) distributed over an area of 26.5 ha of Samboja Research Forest. All woody plants = 10 cm dbh (diameter at 1.3 m aboveground) were identified. In December 2004, 2.143 trees were measured in the six plots, consisting of 39 families, 82 genera and 111 species. The condition in April 2009 (after 4.3 yr) was: 2,466 trees, 40 families, 86 genera and 123 species. Most species were found in both occasions. Fourteen new species were registered, which contributed to 9.8% of a net addition of the total number of species found in the six plots. Over the 4.3-yr period, there was also an increase of 15.1% in density, 12.9% in basal area, and 11.6% in aboveground biomass, respectively. The density increased from 357 to 411 trees per ha; the basal area increased from 20.09 to 22.67 m2 ha-1; and the aboveground biomass increased from 286.3 to 319.4 ton ha. The family Dipterocarpaceae was the richest in species (more than 20 species found in both occasions), followed by Euphorbiaceae, Burseraceae, Fabaceae, and Anacardiaceae (more than five species). Most genera (80%) contained just one species, but Shorea with 13 species was the richest. Four families (Dipterocarpaceae, Fabaceae, Myrtaceae and Lauraceae) contained more than 80% of the aboveground biomass in both occasions (75% of them from Dipterocarpaceae family). The increases in species richness and density did not cause any significant differences in the diversity index and diameter distribution. This condition suggested that forest vegetation of the study site maintains its diversity composition and structural features over the period of study

Generalized Height-diameter Models for Acacia Mangium Willd. Plantations in South Sumatra

The aim of this study was to develop a generalized height-diameter model for predicting tree height of Acacia mangium plantations in South Sumatra that could account for the variability of site and stand conditions. Six commonly used non-linear growth functions (i.e. Gompertz, Chapman-Richards, Lundqvist-Korf, Weibull, modified logistic, and exponential) were selected as candidate base models and were fitted to individual tree's height-diameter data of A.mangium plantations. A total of 13,302 trees collected from permanent sample plots with various spacing , stand age, and site quality were available for this study. The data were split into two sets: one set being the majority (75%) was used to estimate model parameters and the remaining data set (25%) was used to validate the models. The results showed that the six base models produced almost identical fits with a relatively high root mean squared error (± 3.4 m) and a relatively low proportion of the total variation in obser ved tree height (52.5 - 53.4%). The Lundqvist-Korf (LK) model performed slightly better than the other models based on the goodness of fit as well as bias and standard errors of the predictions. This LK model can be fitted easily and provided more satisfactory fit when additional variables were included into the model, hence was selected as the base model. Introducing stand variables into the selected base model resulted in a significant improvement of the accuracy for predicting heights. The root mean squared error decreased by the value between 0.5564 and 1.4252 m and the proportion of variation explained by the model increased by the value between 13.88 and 33.21%. The best improvement based on fit and model validation was achieved by the generalized height-diameter model with inclusion of stand age and site index

The potential of Indonesian mangrove forests for global climate change mitigation

Mangroves provide a wide range of ecosystem services, including nutrient cycling, soil formation, wood production, fish spawning grounds, ecotourism and carbon (C) storage¹. High rates of tree and plant growth, coupled with anaerobic, water-logged soils that slow decomposition, result in large long-term C storage. Given their global significance as large sinks of C, preventing mangrove loss would be an effective climate change adaptation and mitigation strategy. It has been reported that C stocks in the Indo-Pacific region contain on average 1,023 MgC ha⁻¹ (ref. 2). Here, we estimate that Indonesian mangrove C stocks are 1,083 ± 378 MgC ha⁻¹. Scaled up to the country-level mangrove extent of 2.9 Mha (ref. 3), Indonesia’s mangroves contained on average 3.14 PgC. In three decades Indonesia has lost 40% of its mangroves⁴, mainly as a result of aquaculture development⁵. This has resulted in annual emissions of 0.07–0.21 Pg CO₂e. Annual mangrove deforestation in Indonesia is only 6% of its total forest loss⁶; however, if this were halted, total emissions would be reduced by an amount equal to 10–31% of estimated annual emissions from land-use sectors at present. Conservation of carbon-rich mangroves in the Indonesian archipelago should be a high-priority component of strategies to mitigate climate change

Peatland core domain sets: building consensus on what should be measured in research and monitoring

It is often difficult to compile and synthesise evidence across multiple studies to inform policy and practice because different outcomes have been measured in different ways or datasets and models have not been fully or consistently reported. In the case of peatlands, a critical terrestrial carbon store, this lack of consistency hampers the evidence-based decisions in policy and practice that are needed to support effective restoration and conservation. This study adapted methods pioneered in the medical community to reach consensus over peatland outcomes that could be consistently measured and reported to improve the synthesis of data and reduce research waste. Here we report on a methodological framework for identifying, evaluating and prioritising the outcomes that should be measured. We discuss the subsequent steps to standardise methods for measuring and reporting outcomes in peatland research and monitoring. The framework was used to identify and prioritise sets of key variables (known as core domain sets) for UK blanket and raised bogs, and for tropical peat swamps. Peatland experts took part in a structured elicitation and prioritisation process, comprising two workshops and questionnaires, that focused on climate (32 and 18 unique outcomes for UK and tropical peats, respectively), hydrology (26 UK and 16 tropical outcomes), biodiversity (8 UK and 22 tropical outcomes) and fire-related outcomes (13, for tropical peatlands only). Future research is needed to tackle the challenges of standardising methods for data collection, management, analysis, reporting and re-use, and to extend the approach to other types of peatland. The process reported here is a first step towards creating datasets that can be synthesised to inform evidence-based policy and practice, and contribute towards the conservation, restoration and sustainable management of this globally significant carbon store. evidence-based policy and practice, evidence synthesis, outcomes, standardisationpublishedVersio

The Forest Observation System, building a global reference dataset for remote sensing of forest biomass

International audienceForest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (aGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. aGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. all plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities

MODELLING NATURAL MORTALITY OF TROPICAL PLANTATION SPECIES Acacia mangium Willd.

Natural mortality of trees is extremely variable due to the uncertainty and complexity of the functioning of forest ecosystems. The objective of this study was to develop a stand-level mortality model for Acacia mangium species by relating mortality to stand variables that affect the natural mortality process. The model was developed using data from l97 permanent sample plots measured periodically at 1-yr time intervals from 2-4 years until 8-11 years after planting in South Sumatra, Indonesia. The model consists of two complementary equations. The first equation is a logistic function predicting the probability of mortality incidence depending on stand density, site index and stand age. The second equation estimates the reduction in the number of surviving stems observed in a stand where natural mortality occurs. Nine equations were fitted using data from permanent sample plots where trees died over the time period and the best model was selected. Estimates from this second model were then adjusted by a factor equal to the probability of mortality applying three different approaches: probabilistic two-step, deterministic threshold and stochastic. All methods revealed no significant difference between the observed and the predicted number of surviving stems per ha. The probabilistic two-step approach, however, produced more consistent and the most accurate estimates. This method should provide reliable prediction when it is to be used in forest productivity prediction and management system for the species

A COMPATIBLE ESTIMATION MODEL OF STEM VOLUME AND TAPER FOR Acacia mangium Willd. PLANTATIONS

This study describes the establishment of a compatible volume estimation model for Acacia mangium Willd on the basis of 279 felled sample trees collected from the A. mangium plantation stands in South Sumatra, Indonesia. The model comprises of a total volume model and a stem taper model, which is compatible in the sense of the total volume obtained by integration of the taper model being equal to that computed by the total volume model. Several well-known total volume functions were evaluated including constant form factor, combined variable, generalized combine variable, logarithmic, generalized logarithmic and Honer transformed variables. A logarithmic model was determined to be the best and was then used as the basis for deriving the taper model. Appropriate statistical procedures were used in model fitting to account for the problems of heteroscedasticity and autocorrelation that are associated with the construction of volume and taper functions. The simultaneous fitting method of the Seemingly Unrelated Regression (SUR) improved the parameter estimates and goodness-of-fit statistics while ensuring numeric consistency among the component models and reducing the total squared error obtained by an independent fitting method. The developed model can be used to estimate total stem volume, merchantable volume to any merchantability diameter limit at any height, and (possibly) height of any diameter based on only easily measurable parameters such as diameter at breast height and total tree height for the species analysed

Modelling Natural Mortality of Tropical Plantation Species Acacia Mangium Willd.

Natural mortality of trees is extremely variable due to the uncertainty and complexity of the functioning of forest ecosystems. To overcome this uncertainty, a two-step mortality model was applied for unthinned stands of Acacia mangium species. The model was developed using data from l97 permanent sample plots measured periodically at 1-yr time intervals from 2-4 years until 8-11 years after planting in South Sumatra, Indonesia. The model consists of two complementary equations. The first equation is a logistic function predicting the probability of mortality incidence depending on stand density, site index and stand age. The second equation estimates the reduction in the number of surviving stems observed in a stand where natural mortality occurs. Nine equations were fitted using data from permanent sample plots where trees died over the time period and the best model was selected. Estimates from this second model were then adjusted by a factor equal to the probability of mortality applying three different approaches: probabilistic two-step, deterministic threshold and stochastic. All methods revealed no significant difference between the observed and the predicted number of surviving stems per ha. The probabilistic two-step approach, however, produced more consistent and the most accurate estimates. This method should provide reliable prediction when it is to be used in forest productivity prediction and management system for the species