We have pragmatically but accurately evaluated the natural capital of a small northern town, Shimokawa, Hokkaido, Japan. The key industries are forestry, wood manufacturing, and agriculture. From an environmental perspective, Shimokawa was nominated as a Japanese FutureCity. Consequently, the total natural capital value (NCV) of the forest and agricultural lands was calculated to be 1.326 billion USD/year (or 24,161 USD/ha/year) and 44 million USD/year (or 19,692 USD/ha/year), respectively, in 2012. The sum of these NCVs was more than 7 times greater than the yearly gross production of the town, although the forest had a higher NCV because of the larger area (54,862 ha for forest area), compared with 2953 ha for agricultural area. This substantial NCV is mainly generated by sustainable forest management. The timber account showed that the annual tree growth was greater than the annual harvest of trees. The CO2 account derived from a one-year calculation showed that the town served as a CO2 sink at 107,249 t-CO2/year due to the large amount of annual tree growth and CO2 storage in the harvested wood products even if CO2 was emitted from industries and households. The forestry and wood manufacturing industries, as well as agriculture, created socioeconomic effects for the townspeople, ranging from job creation, study tours, and social welfare. This NCV accounting for Shimokawa town ensures the sustainable use of valuable environmental assets and will help other communities recognize their own NCV accounts.
Habitat degradation is pervasive across the tropics and is particularly acute in Southeast Asia, with major implications for biodiversity. Much research has addressed the impact of degradation on species diversity; however, little is known about how ecological interactions are altered, including those that constitute important ecosystem functions such as consumption of herbivores. To examine how rainforest degradation alters trophic interaction networks, we applied DNA metabarcoding to construct interaction networks linking forest-dwelling insectivorous bat species and their prey, comparing old-growth forest and forest degraded by logging in Sabah, Borneo. Individual bats in logged rainforest consumed a lower richness of prey than those in old-growth forest. As a result, interaction networks in logged forests had a less nested structure. These network structures were associated with reduced network redundancy and thus increased vulnerability to perturbations in logged forests. Our results show how ecological interactions change between old-growth and logged forests, with potentially negative implications for ecosystem function and network stability.
The amount of carbon stored in deadwood is equivalent to about 8 per cent of the global forest carbon stocks1. The decomposition of deadwood is largely governed by climate2-5 with decomposer groups-such as microorganisms and insects-contributing to variations in the decomposition rates2,6,7. At the global scale, the contribution of insects to the decomposition of deadwood and carbon release remains poorly understood7. Here we present a field experiment of wood decomposition across 55 forest sites and 6 continents. We find that the deadwood decomposition rates increase with temperature, and the strongest temperature effect is found at high precipitation levels. Precipitation affects the decomposition rates negatively at low temperatures and positively at high temperatures. As a net effect-including the direct consumption by insects and indirect effects through interactions with microorganisms-insects accelerate the decomposition in tropical forests (3.9% median mass loss per year). In temperate and boreal forests, we find weak positive and negative effects with a median mass loss of 0.9 per cent and -0.1 per cent per year, respectively. Furthermore, we apply the experimentally derived decomposition function to a global map of deadwood carbon synthesized from empirical and remote-sensing data, obtaining an estimate of 10.9 ± 3.2 petagram of carbon per year released from deadwood globally, with 93 per cent originating from tropical forests. Globally, the net effect of insects may account for 29 per cent of the carbon flux from deadwood, which suggests a functional importance of insects in the decomposition of deadwood and the carbon cycle.
Two new species of the gecarcinucid freshwater crab genus Arachnothelphusa are described from the Malaysian state of Sarawak in Borneo; one from Lanjak-Entimau Wildlife Sanctuary and another from Bako National Park. Arachnothelphusa rimba n. sp. is distinctive in possessing very long legs and a male first gonopod which has a cylindrical proximal part of the terminal segment, with the distal part sharply tapering to an acute tip. Arachnothelphusa bako n. sp. is superficially closest to A. kadamaiana from Sabah, but differs markedly by its narrower epistome, and proportionately shorter third maxillipeds and ambulatory legs.
Fine roots constitute a significant component of the net primary productivity (NPP) of forest ecosystems but are much less studied than aboveground NPP. Comparisons across sites and regions are also hampered by inconsistent methodologies, especially in tropical areas. Here, we present a novel dataset of fine root biomass, productivity, residence time, and allocation in tropical old-growth rainforest sites worldwide, measured using consistent methods, and examine how these variables are related to consistently determined soil and climatic characteristics. Our pantropical dataset spans intensive monitoring plots in lowland (wet, semi-deciduous, and deciduous) and montane tropical forests in South America, Africa, and Southeast Asia (n = 47). Large spatial variation in fine root dynamics was observed across montane and lowland forest types. In lowland forests, we found a strong positive linear relationship between fine root productivity and sand content, this relationship was even stronger when we considered the fractional allocation of total NPP to fine roots, demonstrating that understanding allocation adds explanatory power to understanding fine root productivity and total NPP. Fine root residence time was a function of multiple factors: soil sand content, soil pH, and maximum water deficit, with longest residence times in acidic, sandy, and water-stressed soils. In tropical montane forests, on the other hand, a different set of relationships prevailed, highlighting the very different nature of montane and lowland forest biomes. Root productivity was a strong positive linear function of mean annual temperature, root residence time was a strong positive function of soil nitrogen content in montane forests, and lastly decreasing soil P content increased allocation of productivity to fine roots. In contrast to the lowlands, environmental conditions were a better predictor for fine root productivity than for fractional allocation of total NPP to fine roots, suggesting that root productivity is a particularly strong driver of NPP allocation in tropical mountain regions.
Reliable and accurate prediction model capturing the changes in solar radiation is essential in the power generation and renewable carbon-free energy industry. Malaysia has immense potential to develop such an industry due to its location in the equatorial zone and its climatic characteristics with high solar energy resources. However, solar energy accounts for only 2-4.6% of total energy utilization. Recently, in developed countries, various prediction models based on artificial intelligence (AI) techniques have been applied to predict solar radiation. In this study, one of the most recent AI algorithms, namely, boosted decision tree regression (BDTR) model, was applied to predict the changes in solar radiation based on collected data in Malaysia. The proposed model then compared with other conventional regression algorithms, such as linear regression and neural network. Two different normalization techniques (Gaussian normalizer binning normalizer), splitting size, and different input parameters were investigated to enhance the accuracy of the models. Sensitivity analysis and uncertainty analysis were introduced to validate the accuracy of the proposed model. The results revealed that BDTR outperformed other algorithms with a high level of accuracy. The funding of this study could be used as a reliable tool by engineers to improve the renewable energy sector in Malaysia and provide alternative sustainable energy resources.
Arbuscular mycorrhizal (AM) and ectomycorrhizal (EcM) associations are critical for host-tree performance. However, how mycorrhizal associations correlate with the latitudinal tree beta-diversity remains untested. Using a global dataset of 45 forest plots representing 2,804,270 trees across 3840 species, we test how AM and EcM trees contribute to total beta-diversity and its components (turnover and nestedness) of all trees. We find AM rather than EcM trees predominantly contribute to decreasing total beta-diversity and turnover and increasing nestedness with increasing latitude, probably because wide distributions of EcM trees do not generate strong compositional differences among localities. Environmental variables, especially temperature and precipitation, are strongly correlated with beta-diversity patterns for both AM trees and all trees rather than EcM trees. Results support our hypotheses that latitudinal beta-diversity patterns and environmental effects on these patterns are highly dependent on mycorrhizal types. Our findings highlight the importance of AM-dominated forests for conserving global forest biodiversity.
Soil respiration is the largest carbon efflux from the terrestrial ecosystem to the atmosphere, and selective logging influences soil respiration via changes in abiotic (temperature, moisture) and biotic (biomass, productivity, quantity and quality of necromass inputs) drivers. Logged forests are a predominant feature of the tropical forest landscape, their area exceeding that of intact forest. We quantified both total and component (root, mycorrhiza, litter, and soil organic matter, SOM) soil respiration in logged (n = 5) and old-growth (n = 6) forest plots in Malaysian Borneo, a region which is a global hotspot for emission from forest degradation. We constructed a detailed below-ground carbon budget including organic carbon inputs into the system via litterfall and root turnover. Total soil respiration was significantly higher in logged forests than in old-growth forests (14.3 ± 0.23 and 12.7 ± 0.60 Mg C ha-1 year-1 , respectively, p = 0.037). This was mainly due to the higher SOM respiration in logged forests (55 ± 3.1% of the total respiration in logged forests vs. 50 ± 3.0% in old-growth forests). In old-growth forests, annual SOM respiration was equal to the organic carbon inputs into the soil (difference between SOM respiration and inputs 0.18 Mg C ha-1 year-1 , with 90% confidence intervals of -0.41 and 0.74 Mg C ha-1 year-1 ), indicating that the system is in equilibrium, while in logged forests SOM respiration exceeded the inputs by 4.2 Mg C ha-1 year-1 (90% CI of 3.6 and 4.9 Mg C ha-1 year-1 ), indicating that the soil is losing carbon. These results contribute towards understanding the impact of logging on below-ground carbon dynamics, which is one of the key uncertainties in estimating emissions from forest degradation. This study demonstrates how significant perturbation of the below-ground carbon balance, and consequent net soil carbon emissions, can persist for decades after a logging event in tropical forests.
In high-voltage (HV) insulation, electrical trees are an important degradation phenomenon strongly linked to partial discharge (PD) activity. Their initiation and development have attracted the attention of the research community and better understanding and characterization of the phenomenon are needed. They are very damaging and develop through the insulation material forming a discharge conduction path. Therefore, it is important to adequately measure and characterize tree growth before it can lead to complete failure of the system. In this paper, the Gaussian mixture model (GMM) has been applied to cluster and classify the different growth stages of electrical trees in epoxy resin insulation. First, tree growth experiments were conducted, and PD data captured from the initial to breakdown stage of the tree growth in epoxy resin insulation. Second, the GMM was applied to categorize the different electrical tree stages into clusters. The results show that PD dynamics vary with different stress voltages and tree growth stages. The electrical tree patterns with shorter breakdown times had identical clusters throughout the degradation stages. The breakdown time can be a key factor in determining the degradation levels of PD patterns emanating from trees in epoxy resin. This is important in order to determine the severity of electrical treeing degradation, and, therefore, to perform efficient asset management. The novelty of the work presented in this paper is that for the first time the GMM has been applied for electrical tree growth classification and the optimal values for the hyperparameters, i.e., the number of clusters and the appropriate covariance structure, have been determined for the different electrical tree clusters.
Leaf litter and its breakdown products represent an important input of organic matter and nutrients to mangrove sediments and adjacent coastal ecosystems. It is commonly assumed that old-grown stands with mature trees contribute more to the permanent sediment organic matter pool than younger stands. However, neither are interspecific differences in leaf decay rates taken into account in this assumption nor is our understanding of the underlying mechanisms or drivers of differences in leaf chemistry sufficient. This study examines the influence of different plant species and ontogenetic stage on the microbial decay of mangrove leaf litter. A litterbag experiment was conducted in the Matang Mangrove Forest Reserve, Malaysia, to monitor leaf litter mass loss, and changes in leaf litter chemistry and microbial enzyme activity. Four mangrove species of different morphologies were selected, namely the trees Rhizophora apiculata and Bruguiera parviflora, the fern Acrostichum aureum and the shrub Acanthus ilicifolius. Decay rates of mangrove leaf litter decreased from A. ilicifolius to R. apiculata to B. parviflora to A. aureum. Leaf litter mass, total phenolic content, protein precipitation capacity and phenol oxidase activity were found to decline rapidly during the early stage of decay. Leaf litter from immature plants differed from that of mature plants in total phenolic content, phenolic signature, protein precipitating capacity and protease activity. For R. apiculata, but not of the other species, leaf litter from immature plants decayed faster than the litter of mature plants. The findings of this study advance our understanding of the organic matter dynamics in mangrove stands of different compositions and ages and will, thus, prove useful in mangrove forest management.
When Darwin visited the Galapagos archipelago, he observed that, in spite of the islands' physical similarity, members of species that had dispersed to them recently were beginning to diverge from each other. He postulated that these divergences must have resulted primarily from interactions with sets of other species that had also diverged across these otherwise similar islands. By extrapolation, if Darwin is correct, such complex interactions must be driving species divergences across all ecosystems. However, many current general ecological theories that predict observed distributions of species in ecosystems do not take the details of between-species interactions into account. Here we quantify, in sixteen forest diversity plots (FDPs) worldwide, highly significant negative density-dependent (NDD) components of both conspecific and heterospecific between-tree interactions that affect the trees' distributions, growth, recruitment, and mortality. These interactions decline smoothly in significance with increasing physical distance between trees. They also tend to decline in significance with increasing phylogenetic distance between the trees, but each FDP exhibits its own unique pattern of exceptions to this overall decline. Unique patterns of between-species interactions in ecosystems, of the general type that Darwin postulated, are likely to have contributed to the exceptions. We test the power of our null-model method by using a deliberately modified data set, and show that the method easily identifies the modifications. We examine how some of the exceptions, at the Wind River (USA) FDP, reveal new details of a known allelopathic effect of one of the Wind River gymnosperm species. Finally, we explore how similar analyses can be used to investigate details of many types of interactions in these complex ecosystems, and can provide clues to the evolution of these interactions.
Metarhizium anisopliae (Metchnikoff) Sorokin, a pathogenic fungus to insects, infects the subterranean termite, Coptotermes curvignathus Holmgren, a devastating pest of plantation trees in the tropics. Electron microscopy and proteomics were used to investigate the infection and developmental process of M. anisopliae in C. curvignathus. Fungal infection was initiated by germ tube penetration through the host's cuticle as observed at 6 h post-inoculation (PI), after which it elongated into the host's integumental tissue. The colonization process continued as seen from dissemination of blastospores in the hemocoel at 96 h PI. At this time point, the emergent mycelia had mummified the host and forty-eight hours later, new conidia were dispersed on the termites' body surface. Meanwhile, hyphal bodies were observed in abundance in the intercellular space in the host's body. The proteomes of the pathogen and host were isolated separately using inoculated termite samples withdrawn at each PI-time point and analyzed in two-dimensional electrophoresis (2-DE) gels. Proteins expressed in termites showed evidence of being related to cell regulation and the immune response, while those expressed in M. anisopliae, to transportation and fungal virulence. This study provides new information on the interaction between termites and its entomopathogen, with potential utilization for developing future biopesticide to control the termite population.
Tropical peat swamp forest is a global store of carbon in a water-saturated, anoxic and acidic environment. This ecosystem holds diverse prokaryotic communities that play a major role in nutrient cycling. A study was conducted in which a total of 24 peat soil samples were collected in three forest types in a tropical peat dome in Sarawak, Malaysia namely, Mixed Peat Swamp (MPS), Alan Batu (ABt), and Alan Bunga (ABg) forests to profile the soil prokaryotic communities through meta 16S amplicon analysis using Illumina Miseq. Results showed these ecosystems were dominated by anaerobes and fermenters such as Acidobacteria, Proteobacteria, Actinobacteria and Firmicutes that cover 80-90% of the total prokaryotic abundance. Overall, the microbial community composition was different amongst forest types and depths. Additionally, this study highlighted the prokaryotic communities' composition in MPS was driven by higher humification level and lower pH whereas in ABt and ABg, the less acidic condition and higher organic matter content were the main factors. It was also observed that prokaryotic diversity and abundance were higher in the more oligotrophic ABt and ABg forest despite the constantly waterlogged condition. In MPS, the methanotroph Methylovirgula ligni was found to be the major species in this forest type that utilize methane (CH4), which could potentially be the contributing factor to the low CH4 gas emissions. Aquitalea magnusonii and Paraburkholderia oxyphila, which can degrade aromatic compounds, were the major species in ABt and ABg forests respectively. This information can be advantageous for future study in understanding the underlying mechanisms of environmental-driven alterations in soil microbial communities and its potential implications on biogeochemical processes in relation to peatland management.
Overhunting reduces important plant-animal interactions such as vertebrate seed dispersal and seed predation, thereby altering plant regeneration and even above-ground biomass. It remains unclear, however, if non-hunted species can compensate for lost vertebrates in defaunated ecosystems. We use a nested exclusion experiment to isolate the effects of different seed enemies in a Bornean rainforest. In four of five tree species, vertebrates kill many seeds (13-66%). Nonetheless, when large mammals are excluded, seed mortality from insects and fungi fully compensates for the lost vertebrate predation, such that defaunation has no effect on seedling establishment. The switch from seed predation by generalist vertebrates to specialist insects and fungi in defaunated systems may alter Janzen-Connell effects and density-dependence in plants. Previous work using simulation models to explore how lost seed dispersal will affect tree species composition and carbon storage may require reevaluation in the context of functional redundancy within complex species interactions networks.
Large vertebrates are rarely considered important drivers of conspecific negative density-dependent mortality (CNDD) in plants because they are generalist consumers. However, disturbances like trampling and nesting also cause plant mortality, and their impact on plant diversity depends on the spatial overlap between wildlife habitat preferences and plant species composition. We studied the impact of native wildlife on a hyperdiverse tree community in Malaysia. Pigs (Sus scrofa) are abnormally abundant at the site due to food subsidies in nearby farmland and they construct birthing nests using hundreds of tree saplings. We tagged 34 950 tree saplings in a 25 ha plot during an initial census and assessed the source mortality by recovering tree tags from pig nests (n = 1672 pig-induced deaths). At the stand scale, pigs nested in flat dry habitats, and at the local neighbourhood scale, they nested within clumps of saplings, both of which are intuitive for safe and efficient nest building. At the stand scale, flat dry habitats contained higher sapling densities and higher proportions of common species, so pig nesting increased the weighted average species evenness across habitats. At the neighbourhood scale, pig-induced sapling mortality was associated with higher heterospecific and especially conspecific sapling densities. Tree species have clumped distributions due to dispersal limitation and habitat filtering, so pig disturbances in sapling clumps indirectly caused CNDD. As a result, Pielou species evenness in 400 m2 quadrats increased 105% more in areas with pig-induced deaths than areas without disturbances. Wildlife induced CNDD and this supported tree species evenness, but they also drove a 62% decline in sapling densities from 1996 to 2010, which is unsustainable. We suspect pig nesting is an important feature shaping tree composition throughout the region.
Many lowland rainforests in Southeast Asia are severely altered by selective logging and there is a need for rapid assessment methods to identify characteristic communities of old growth forests and to monitor restoration success in regenerating forests. We have studied the effect of logging on the diversity and composition of lichen communities on trunks of trees in lowland rainforests of northeast Borneo dominated by Dipterocarpaceae. Using data from field observations and vouchers collected from plots in disturbed and undisturbed forests, we compared a taxonomy-based and a taxon-free method. Vouchers were identified to genus or genus group and assigned to functional groups based on sets of functional traits. Both datasets allowed the detection of significant differences in lichen communities between disturbed and undisturbed forest plots. Bark type diversity and the proportion of large trees, particularly those belonging to the family Dipterocarpaceae, were the main drivers of lichen community structure. Our results confirm the usefulness of a functional groups approach for the rapid assessment of tropical lowland rainforests in Southeast Asia. A high proportion of Dipterocarpaceae trees is revealed as an essential element for the restoration of near natural lichen communities in lowland rainforests of Southeast Asia.
Mitragyna speciosa (Korth.) Havil. or locally known as ketum/daun sebiak/biak-biak belongs to Rubiaceae family and generally occurs in secondary forest or disturbed areas in tropical and subtropical region. This research enumerated the characterisation of Mitragyna speciosa leaf anatomy and micromorphology features which is still not well documented. This medium to large sized tree species characterised with opposite arrangement, ovate-acuminate leaf and with 12-17 pairs of veins. Transverse sections of petioles showed that this species has petiole outlines with slightly convex at the middle of the adaxial part and 'U'-shaped on abaxial side. Results also showed that this species has paracytic and hypostomatic stomata, combination of non-glandular (majority) and glandular trichomes (minority), with observation on the secretory cells present in petiole and midrib parenchyma cells. Cuticle on the abaxial and adaxial epidermal surfaces showed the presence granule and wax films with periclinal and anticlinal walls can be differentiated clearly. The results obtained in this study can be used to providing additional systematics information of Mitragyna speciosa with the documentation of the leaf anatomy and micromorphology characters.
Resource allocation within trees is a zero-sum game. Unavoidable trade-offs dictate that allocation to growth-promoting functions curtails other functions, generating a gradient of investment in growth versus survival along which tree species align, known as the interspecific growth-mortality trade-off. This paradigm is widely accepted but not well established. Using demographic data for 1,111 tree species across ten tropical forests, we tested the generality of the growth-mortality trade-off and evaluated its underlying drivers using two species-specific parameters describing resource allocation strategies: tolerance of resource limitation and responsiveness of allocation to resource access. Globally, a canonical growth-mortality trade-off emerged, but the trade-off was strongly observed only in less disturbance-prone forests, which contained diverse resource allocation strategies. Only half of disturbance-prone forests, which lacked tolerant species, exhibited the trade-off. Supported by a theoretical model, our findings raise questions about whether the growth-mortality trade-off is a universally applicable organizing framework for understanding tropical forest community structure.
The complexity of forest structures plays a crucial role in regulating forest ecosystem functions and strongly influences biodiversity. Yet, knowledge of the global patterns and determinants of forest structural complexity remains scarce. Using a stand structural complexity index based on terrestrial laser scanning, we quantify the structural complexity of boreal, temperate, subtropical and tropical primary forests. We find that the global variation of forest structural complexity is largely explained by annual precipitation and precipitation seasonality (R² = 0.89). Using the structural complexity of primary forests as benchmark, we model the potential structural complexity across biomes and present a global map of the potential structural complexity of the earth´s forest ecoregions. Our analyses reveal distinct latitudinal patterns of forest structure and show that hotspots of high structural complexity coincide with hotspots of plant diversity. Considering the mechanistic underpinnings of forest structural complexity, our results suggest spatially contrasting changes of forest structure with climate change within and across biomes.
Electromyography (EMG) signal is one of the extensively utilised biological signals for predicting human motor intention, which is an essential element in human-robot collaboration platforms. Studies on motion intention prediction from EMG signals have often been concentrated on either classification and regression models of muscle activity. In this study, we leverage the information from the EMG signals, to detect the subject's intentions in generating motion commands for a robot-assisted upper limb rehabilitation platform. The EMG signals are recorded from ten healthy subjects' biceps muscle, and the movements of the upper limb evaluated are voluntary elbow flexion and extension along the sagittal plane. The signals are filtered through a fifth-order Butterworth filter. A number of features were extracted from the filtered signals namely waveform length (WL), mean absolute value (MAV), root mean square (RMS), standard deviation (SD), minimum (MIN) and maximum (MAX). Several different classifiers viz. Linear Discriminant Analysis (LDA), Logistic Regression (LR), Decision Tree (DT), Support Vector Machine (SVM) and k-Nearest Neighbour (k-NN) were investigated on its efficacy to accurately classify the pre-intention and intention classes based on the significant features identified (MIN and MAX) via Extremely Randomised Tree feature selection technique. It was observed from the present investigation that the DT classifier yielded an excellent classification with a classification accuracy of 100%, 99% and 99% on training, testing and validation dataset, respectively based on the identified features. The findings of the present investigation are non-trivial towards facilitating the rehabilitation phase of patients based on their actual capability and hence, would eventually yield a more active participation from them.