School of Agriculture, Food and Ecosystem Sciences - Research Publications

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    Sustainable management of Eucalyptus pellita plantations: A review
    Hutapea, FJ ; Weston, CJ ; Mendham, D ; Volkova, L (ELSEVIER, 2023-06-01)
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    Estimating forest above-ground biomass with terrestrial laser scanning: Current status and future directions
    Demol, M ; Verbeeck, H ; Gielen, B ; Armston, J ; Burt, A ; Disney, M ; Duncanson, L ; Hackenberg, J ; Kukenbrink, D ; Lau, A ; Ploton, P ; Sewdien, A ; Stovall, A ; Takoudjou, SM ; Volkova, L ; Weston, C ; Wortel, V ; Calders, K (Wiley Open Access, 2022-08)
    1. Improving the global monitoring of above-ground biomass (AGB) is crucial for forest management to be effective in climate mitigation. In the last decade, methods have been developed for estimating AGB from terrestrial laser scanning (TLS) data. TLS-derived AGB estimates can address current uncertainties in allometric and Earth observation (EO) methods that quantify AGB. 2. We assembled a global dataset of TLS scanned and consecutively destructively measured trees from a variety of forest conditions and reconstruction pipelines. The dataset comprised 391 trees from 111 species with stem diameter ranging 8.5 to 180.3 cm and AGB ranging 13.5–43,950 kg. 3. TLS-derived AGB closely agreed with destructive values (bias <1%, concordance correlation coefficient of 98%). However, we identified below-average performances for smaller trees (<1,000 kg) and conifers. In every individual study, TLS estimates of AGB were less biased and more accurate than those from allometric scaling models (ASMs), especially for larger trees (>1,000 kg). 4. More effort should go to further understanding and constraining several TLS error sources. We currently lack an objective method of evaluating point cloud quality for tree volume reconstruction, hindering the development of reconstruction algorithms and presenting a bottleneck for tracking down the error sources identified in our synthesis. Since quantifying AGB with TLS requires only a fraction of the efforts as compared to destructive harvesting, TLS-calibrated ASMs can become a powerful tool in AGB upscaling. TLS will be critical for calibrating/validating scheduled and launched remote sensing initiatives aiming at global AGB mapping.
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    Fire and tree species diversity in tropical peat swamp forests
    Volkova, L ; Krisnawati, H ; Qirom, MA ; Adinugroho, WC ; Imanuddin, R ; Hutapea, FJ ; McCarthy, MA ; Di Stefano, J ; Weston, CJ (ELSEVIER, 2023-02-01)
    Tropical peat swamp forests contain diverse plant communities that support many endangered flora and fauna species. These forests are increasingly threatened by disturbances such as drainage, logging, and subsequent fire, yet little is known about tree species recovery from these threats. Tree species richness and diversity were measured in peat swamp forests of Central Borneo regenerating naturally after fires from 139 chronosequence plots. Our findings indicated that two to three decades after fire, similar levels of richness and diversity to relatively undisturbed reference forest are reached within sites. However, when averaged across landscapes our modelling shows that fires of average frequency of 50 years, or even 100 years, can substantially suppress tree species richness and diversity. Thus, even rare fires can reduce the species richness and diversity of tropical peat swamp forests. Two groups of tree species drove the difference in richness and diversity between disturbed and reference forests: ‘decreasers’, occupying recently burnt forest and declining with fire exclusion, and ‘increasers’, that were only present in less disturbed forests and absent or rare in recently burnt forests. The decreasers were more common than the increasers. We conclude that peat swamp forests can recover adequately from fires through natural regeneration, and it is possible that artificial planting may speed up this process. Where possible, excluding fire from tropical peat forests will help to maintain the diversity of these threatened ecosystems and promote their recovery.
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    Using Bayesian multitemporal classification to monitor tropical forest cover changes in Kalimantan, Indonesia
    Sari, IL ; Weston, CJ ; Newnham, GJ ; Volkova, L (TAYLOR & FRANCIS LTD, 2022-12-31)
    Significant areas of native forest in Kalimantan, on the island of Borneo, have been cleared for the expansion of plantations of oil palm and rubber. In this study multisource remote sensing was used to develop a time series of land cover maps that distinguish native forest from plantations. Using a study area in east Kalimantan, Landsat images were combined with either ALOS PALSAR or Sentinel-1 images to map four land cover classes (native forest, oil palm plantation, rubber plantation, non-forest). Bayesian multitemporal classification was applied to increase map accuracy and maps were validated using a confusion matrix; final map overall accuracy was >90%. Over 18 years from 2000 to 2018 nearly half the native forests in the study area were converted to either non-forest or plantations of either rubber or oil palm, with the highest losses between 2015 and 2016. Trending upwards from 2008 large areas of degraded or cleared forests, mapped as non-forest, were converted to oil palm plantation. Conversion of native forests to plantation mainly occurred in lowland and wetland forest, while significant forest regrowth was detected in degraded peatland. These maps will help Indonesia with strategies and policies for balancing economic growth and conservation.
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    Developing Multi-Source Indices to Discriminate between Native Tropical Forests, Oil Palm and Rubber Plantations in Indonesia
    Sari, IL ; Weston, CJ ; Newnham, GJ ; Volkova, L (MDPI, 2022-01)
    Over the last 18 years, Indonesia has experienced significant deforestation due to the expansion of oil palm and rubber plantations. Accurate land cover maps are essential for policymakers to track and manage land change to support sustainable forest management and investment decisions. An automatic digital processing (ADP) method is currently used to develop land cover change maps for Indonesia, based on optical imaging (Landsat). Such maps produce only forest and non-forest classes, and often oil palm and rubber plantations are misclassified as native forests. To improve accuracy of these land cover maps, this study developed oil palm and rubber plantation discrimination indices using the integration of Landsat-8 and synthetic aperture radar Sentinel-1 images. Sentinel-1 VH and VV difference (>7.5 dB) and VH backscatter intensity were used to discriminate oil palm plantations. A combination of Landsat-8 NDVI, NDMI with Sentinel-1 VV and VH were used to discriminate rubber plantations. The improved map produced four land cover classes: native forest, oil palm plantation, rubber plantation, and non-forest. High-resolution SPOT 6/7 imagery and ground truth data were used for validation of the new classified maps. The map had an overall accuracy of 92%; producer’s accuracy for all classes was higher than 90%, except for rubber (65%), and user’s accuracy was over 80% for all classes. These results demonstrate that indices developed from a combination of optical and radar images can improve our ability to discriminate between native forest and oil palm and rubber plantations in the tropics. The new mapping method will help to support Indonesia’s national forest monitoring system and inform monitoring of plantation expansion.
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    Recovery of Carbon and Vegetation Diversity 23 Years after Fire in a Tropical Dryland Forest of Indonesia
    Adinugroho, WC ; Prasetyo, LB ; Kusmana, C ; Krisnawati, H ; Weston, CJ ; Volkova, L (MDPI, 2022-06)
    Understanding the recovery rate of forest carbon stocks and biodiversity after disturbance, including fire, is vital for developing effective climate-change-mitigation policies and actions. In this study, live and dead carbon stocks aboveground, belowground, and in the soil to a 30 cm depth, as well as tree and shrub species diversity, were measured in a tropical lowland dry forest, 23 years after a fire in 1998, for comparison with adjacent unburned reference forests. The results showed that 23 years since the fire was insufficient, in this case, to recover live forest carbon and plant species diversity, to the level of the reference forests. The total carbon stock, in the recovering 23-year-old forest, was 199 Mg C ha−1 or about 90% of the unburned forest (220 Mg C ha−1), mainly due to the contribution of coarse woody debris and an increase in the 5–10 cm soil horizon’s organic carbon, in the burned forest. The carbon held in the live biomass of the recovering forest (79 Mg C ha−1) was just over half the 146 Mg C ha−1 of the reference forest. Based on a biomass mean annual increment of 6.24 ± 1.59 Mg ha−1 yr−1, about 46 ± 17 years would be required for the aboveground live biomass to recover to equivalence with the reference forest. In total, 176 plant species were recorded in the 23-year post-fire forest, compared with 216 in the unburned reference forest. The pioneer species Macaranga gigantea dominated in the 23-year post-fire forest, which was yet to regain the similar stand structural and compositional elements as those found in the adjacent unburned reference forest.
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    Estimating land cover map accuracy and area uncertainty using a confusion matrix: A case study in Kalimantan, Indonesia
    Sari, IL ; Weston, CJ ; Newnham, GJ ; Volkova, L (IOP Publishing, 2021-11-26)
    Abstract Remote sensing is widely used to generate land cover maps, but the maps derived from remote sensing often produce accuracy below expectations for map error. Therefore, quantifying map accuracy is essential for reporting the precision of an estimated area. This study describes a simple framework for assessing map accuracy and estimating land cover area uncertainty for a land cover changes map for Kalimantan in 2012-2018. This study compared simple random sampling and stratified random sampling to determine suitable procedures for estimating accuracy and area uncertainty. The validation relies on the visual assessment of high spatial resolution images such as SPOT 6/7 and high-resolution temporal images from Open Foris Collect Earth. Our results showed that the land cover change map assessed using random sampling had an overall accuracy of 74% while using stratified random sampling had an overall accuracy of 75%. Thus, for tropical regions with high cloud cover, we recommend using stratified random sampling. The major source of map error was in differentiating between native forest and plantation areas. Future map improvement requires more accurate differentiation between forest and plantation to better support national forest monitoring systems for sustainable forest management.
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    Loss and Recovery of Carbon in Repeatedly Burned Degraded Peatlands of Kalimantan, Indonesia
    Volkova, L ; Adinugroho, WC ; Krisnawati, H ; Imanuddin, R ; Weston, CJ (MDPI, 2021-12)
    Although accurate estimates of biomass loss during peat fires, and recovery over time, are critical in understanding net peat ecosystem carbon balance, empirical data to inform carbon models are scarce. During the 2019 dry season, fires burned through 133,631 ha of degraded peatlands of Central Kalimantan. This study reports carbon loss from surface fuels and the top peat layer of 18.5 Mg C ha−1 (3.5 from surface fuels and 15.0 from root/peat layer), releasing an average of 2.5 Gg (range 1.8–3.1 Gg) carbon in these fires. Peat surface change measurements over one month, as the fires continued to smolder, indicated that about 20 cm of the surface was lost to combustion of peat and fern rhizomes, roots and recently incorporated organic residues that we sampled as the top peat layer. Time series analysis of live green vegetation (NDVI trend), combined with field observations of vegetation recovery two years after the fires, indicated that vegetation recovery equivalent to fire-released carbon is likely to occur around 3 years after fires.
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    Ground-Based Field Measurements of PM2.5 Emission Factors From Flaming and Smoldering Combustion in Eucalypt Forests
    Reisen, F ; Meyer, CP ; Weston, CJ ; Volkova, L (AMER GEOPHYSICAL UNION, 2018-08-16)
    Abstract In fire‐prone areas such as southern Australia and parts of the United States, prescribed burning is a common fire management tool to reduce fuel load for wildfire suppression purposes. The burns are typically undertaken during calm and stable conditions when the burn extent and duration can be carefully controlled. This often coincides with poor atmospheric ventilation, leading to a buildup of smoke, which can impact air quality and human health. The low intensity of these burns also means that the plume is less buoyant and the main impact on local populations is due to emissions during the slow and prolonged smoldering combustion of heavy fuels. This study presents emission measurements of PM2.5 at prescribed burns in eucalypt forests of southern Australia using a smoke collection method suitable for both flaming combustion of fine fuels and residual smoldering combustion of heavy fuels and logs. The median PM2.5 emission factors (EFs) measured were 16.9‐g/kg fuel during flaming combustion and 38.8‐g/kg fuel during smoldering combustion. The correlation between PM2.5 EFs and modified combustion efficiency highlights two distinct trends at low modified combustion efficiency, attributed to the distinct combustion processes of glowing char combustion and pyrolysis. Hence, two distinct relationships were developed that best fitted the measurements and that can be used to extrapolate measured EFs to a wider range of fuel and burning conditions. The results from this study addressed a gap in our knowledge of particle emissions during burns in eucalypt forests under different burning conditions and help to better forecast and manage air quality impacts from prescribed burns on nearby communities.
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    Potential for forest thinning to reduce risk and increase resilience to wildfire in Australian temperate Eucalyptus forests
    Keenan, RJ ; Weston, CJ ; Volkova, L (Elsevier BV, 2021-10)
    Unprecedented wildfires in south-eastern Australia in 2019–2020 focused attention on forest management to reduce their risks and impacts. These fires mostly burnt dry eucalypt forests. In this short review, we found evidence from international studies that thinning combined with fuel reduction can reduce wildfire risks and impacts in dry forests compared with no treatment or thinning alone. In Australia, studies so far demonstrate mixed outcomes, indicating that more landscape-scale experiments are required to better assess the use of thinning in dry Eucalyptus forests to reduce fire risks in a rapidly changing climate.