Highest Importance Value Research Articles

Species Composition and Diversity of Middle-Aged Trees among Different Urban Green Space Types and Tree Age Classes in Changchun, Northeast China

Middle-aged trees refer to trees aged between 50 and 99 years, which are the reserve resources of old trees (trees ≥ 100 years of age). They are vital parts of the urban ecosystem, with important ecological, landscape, cultural, and historical value. Conservation of middle-aged trees in urban areas is important for the development of large old trees in the future. In this study, we investigated the middle-aged trees in Changchun city and analyzed the species composition and diversity characteristics of different urban green space types and tree age classes. The results showed that there were 72 species and 22,376 plants of middle-aged trees in Changchun city, and the coniferous species prevailed. The top five species with a high importance value (IV) were Pinus tabuliformis var. mukdensis, Lavix olgensis, Salix matsudana, Ulmus pumila, and Abies holophylla. Green space type and tree age were important factors influencing the richness and diversity of middle-aged trees. Tree growth spaces were relatively sufficient, and land use was stable for park green spaces (PGS) and attached green spaces (AGS), which resulted in the abundant, richer, and diverse species richness (SR) of middle-aged trees. Road green spaces (RGS) and square green spaces (SGS) had fewer trees and lower species richness, Margalef richness index (dMa), Shannon–Wiener index (He) and evenness index (Je) which could be attributed to the high intensity of human interference and poor environmental quality. The SR of middle-aged trees decreased with an increase in age class, and the values of SR in Age Class 80–89 years and Age Class 90–99 years were lower than in Age Class 50–59 years. Age Class 70–79 years had the lowest values of dMa, He, and Je, which need to be protected urgently. The results of this study can provide a basis for the conservation and management of middle-aged trees in urban areas and the choice of species for urban greening.

Genome-wide identification of the auxin response factor (ARF) gene family in Magnolia sieboldii and functional analysis of MsARF5.

Auxin plays an essential role in flowering, embryonic development, seed dormancy, and germination. Auxin response factors (ARFs) are plant-specific key transcriptional factors in mediating the gene expression network of auxin signaling. Although ARFs in model plants such as Arabidopsis had been well characterized, their identities and potential roles in non-model plants are less studied. Here, we performed genome-wide identification of ARFs in Magnolia sieboldii K. Koch, a primitive species with high taxonomic importance and medicinal values. We found 25 ARF genes in M. sieboldii, which were widely distributed across multiple chromosomes. Based on sequence similarity, the encoded proteins could be either transcriptional repressors or activators. Gene expression analysis showed a dynamic pattern for many ARFs including MsARF5 during seed germination. In addition, overexpressing of MsARF5 showed that it restores many developmental defects in the Arabidopsis mutant. Moreover, two phenotypically distinct transgenic Arabidopsis lines were obtained, indicating a link between gene expression levels and developmental phenotypes. Taken together, we provided a systematic investigation of the ARF gene family in M. sieboldii and revealed an important role of MsARF5 in mediating auxin signaling.

Diversity and Population Status of Tree Species in Bakin-Dutse of Ardo-Kola LGA, Taraba State, Nigeria

Nigerian forest resources are constantly threatened due to many anthropogenic activities and considering their importance in recycling oxygen, preventing erosion, biodiversity habitats etc. This study was carried out to determine the diversity and population status of trees. A 50km2 plot was studied using the line transect method, and the Point Centered Quartet technique was deployed to enumerate standing tree biomass. Total Height, Diameter at Breast Height and Crown cover were also measured and recorded. The results showed that 200 trees spread across fifteen (15) families and forty (40) species were identified. The Fabaceae Family had more representatives 12 (30%) while Bignoniaceae, Euphorbiaceae, Meliaceae, Sapotaceae, Rutaceae and Olecaceae had 1 (2.5%) representation each. Parkia biglobosa had highest abundance 37 (18.5%) while Anacardium ocidentale, Brachystegia eurycoma, Ceiba pentandra, Cocos nucifera, Combretum molle, Ficus thoninngii, Khaya senegalensis, Haematostaphis barterii, Lannea microcarpa, Limonia. acidissima, Mangifera indica, Mitragyna inermis, Nauclea latifolia, Newbouldia laevis, Psidium guajava and Tamarindus indica all recorded the least abundance of 1 (0.5%). Diversity indices of Hʹ=2.65 (North), Hʹ=2.49 (South), Hʹ=2.72 (East) and Hʹ=2.37 (West) were recorded. The results also showed that 90% of the tree species enumerated are in need of serious conservation efforts. Parkia biglobosa had the highest Importance Value (46.84%) while Psidium guajava recoded the least (2.21%). It was then concluded that trees in Bakin-dutse community of Ardo-kola LGA needs conserving, hence, we suggest that a concerted effort from Governmental Organizations, Non-Governmental Organization and the Local Community to curtail the rapid decline in the population of these important biodiversity resources.

Using machine learning regression models to predict the pellet quality of pelleted feeds

Pelleted feeds are widely used in monogastric animal production systems because they not only improve animal performance (increasing digestibility and feed consumption) but are convenient to store and handle. However, pellet quality can be affected by many factors. While previous studies have reported the effect of a single or several factors on pellet quality, no studies have investigated how pellet quality can be affected by the large number of factors that vary during feed manufacturing. Therefore, the current study reports using machine learning regression models to predict pellet quality using commercial feed mill data. A dataset consisting of 2471 observations describing the pellet manufacturing process, the feed formulation, and environmental conditions (e.g. outdoor temperature) were collected from two feed mill lines for 8 months. Sixteen features (13 continuous, 3 categorical) were used for building the regression models, and the output was the pellet durability index (PDI) of the pelleted feeds. Twelve regression algorithms including Linear Regression (LR), Least Absolute Shrinkage and Selection Operator (LASSO) regression, Ridge Regression (RR), Support Vector Regression (SVR), Linear Support Vector Regression (LSVR), Random Forest (RF), Decision Tree (DT), Gradient Boosting Regression (GBR), Adaptive Boosting Regression (ABR), Multi-Layer Perceptron (MLP) neural network, K-Nearest Neighbor (KNN), and Stacking Regression (SR) were examined in this study. Feature importance analysis using permutation importance was performed to identify what features were most relevant for each model. Average outdoor temperature, bakery byproduct and wheat inclusion levels, as well as production line all had high permutation importance values, while the fat added into the mixer (with controls at the mill already in place to limit it) was less important than most features. The cleaned dataset was preprocessed and then split into a training (80 % of total samples, n = 1147) and a testing (20 % of total samples, n = 287) set. A 5-fold cross-validation process was applied and learning curves were used to verify the presence of overfitting for each algorithm before and after tuning the hyperparameters on the training set. The models that exhibited overfitting were excluded from the final results and only models with tuned hyperparameters were evaluated on the testing set. The SVR algorithm was selected as the best overall model for predicting PDI, as it had the lowest mean absolute and mean squared prediction errors (MAE = 3.280, MSPE = 16.192), and the second highest concordance correlation coefficient (CCC = 0.636). In conclusion, this study shows that feed mill features describing manufacturing parameters, feed formulation, and environmental data can be successfully used to build machine learning regression models for pellet quality prediction.

SPECIES DIVERSITY AND COMMUNITY STRUCTURE OF BEACH FORESTS IN SAN FERNANDO, SAN JOSE, ANTIQUE, PHILIPPINES

Beach forests play a vital role in disaster mitigation and climate change mitigation. These forests protect coastal communities against natural calamities. It has been observed that areas with less or absence of beach forests and mangrove systems were highly devastated compared to those with. However, these ecosystems were neglected due to lesser studies and baseline information about the species diversity and community structure and its role in the overall ecology of the area. The study assessed the species diversity and community structure of beach forests in San Fernando, San Jose, Antique, Philippines. The study used the transect line plots method in an area that was purposively selected. The general floristic composition was based on an ocular survey of the selected site. Characterization of community structure was done using accepted parameters. Results showed a total of sixteen (16) beach forest species that belong to twelve (12) families. Tabernaemontana pandacaqui and Jatropha gossypifolia were found to be the most frequently occurring species. The plant diversity of the area is low (mean H’ = 0.968) which is attributed to anthropogenic disturbances. The species with the highest Importance Value was Capparis micracantha (IV =61.02). Overall, beach forest in San Fernando, San Jose has a high species evenness (J’ = 0.929) which proves that conservation and preservation efforts must be increased. It is recommended that local government units must develop plans to promote awareness and strengthen values for conservation and protection of the beach forests among its people. Keywords: Beach Forest, Forest Conservation, Biodiversity, Importance Value.

Forest Land Encroachment in Kehmil Forest Division of Kupwara District: Dimensions, Causes and Consequences.

This research aims to identify the areas under encroachment and its causes and consequences in the Kehmil forest division of the district of Kupwara in Jammu and Kashmir. The survey was conducted for two consecutive years during September 2020 to November 2020 and September 2021 to November 2021. The study area is dominated by (Himalayan dry-temperate to subalpine forest types). Cedrus deodar, Pinus excelsa, and Abies pindrow are the species in the Kupwara region with the highest importance value (IV). For data collection, direct observations of the encroached site, interviews and opinion of the locals, literature studies and analysis were done. The study area of 546.89 hectare land was encroached by 2178 encroachers. It was determined that the encroached area's agricultural system is a dry land one with horticultural crops as its primary plant types. The main reason for forest encroachment by the population is relatively huge such as rise in population and unemployment, restrictions on agricultural land and forest guard forces. Due to forest encroachment, the abolition of forest plant species in study area has altered the expected ranking of tree species identified in the undisturbed forest. Based on the present study, it is concluded that there is a need of extensive land-use regulations at the national and municipal levels to stop future deforestation by well-built protections for the remaining forest land in the Kehmil forest division.

Study on key technology of identification of mine water inrush source by PSO-LightGBM

Abstract Mine water inrush is a major type of disaster in coal mine production in China. It causes heavy casualties and serious economic losses and threatens coal mine safety. To quickly and accurately identify mine water inrush source, according to the hydrochemical characteristics of different aquifers in the Donghuantuo mining area, this paper systematically analyzes the hydraulic connection of the aquifers in main coal mining areas before and after mining activities. Four types of hydrochemical data were collected: No. 5 coal seam roof water, No. 8 coal seam roof water, No. 122 coal seam floor water, and No. 1214 coal seam aquifer water in the Donghuantuo mining area. In addition, based on the hydrochemical data, the parameter selection of LightGBM was optimized by Particle Swarm Optimization (PSO) and constructed the PSO-LightGBM water inrush source identification model. The recognition accuracy of PSO-LightGBM model was compared with LightGBM model, classification regression tree (CART) model, and random forest (RF) model. The results showed that coal mining activities would have a significant impact on the water quality characteristics of the roof sandstone fissure water of No. 5 coal mine. Mining activities had a certain impact on the accuracy of the identification model. In addition, compared with the four recognition models, PSO-LightGBM model had the highest recognition accuracy of 97.22%. It showed that the model had high accuracy, stability, generalization ability, and important reference value for the identification of mine water inrush source.

Enhancing User Experience of Eye-Controlled Systems: Design Recommendations on the Optimal Size, Distance and Shape of Interactive Components from the Perspective of Peripheral Vision.

For special populations with motor impairments, eye-controlled interaction may be the only way for them to communicate with the outside world. Because of the dominance of vision in the motor mechanism, eye-controlled interaction has high usability and important research value. During eye-controlled interaction, the visual channel needs to receive information from the graphical user interface (GUI) and transmit the user’s eye-controlled instructions, which overburdens the visual channel and reduces the efficiency of eye-controlled interaction. This study presents an ergonomic experiment to study how to design interactive GUI components in an eye-controlled user interface. The experiments were conducted based on the shape, size, and distance (from the object to the center of the screen) of the visual interactive components. The experiment comprised three parts: (1) the pre-experiment determined the evaluation index and selected the icon material; (2) the formal experiment was a three-factor within-subjects experiment, which included a search task using participants’ peripheral vision; and (3) after the experiment, subjective evaluations were conducted using a questionnaire. The results showed that the shape, size, and distance of the interactive object significantly affected the reaction time, and the size factor significantly affected the movement time of the eye-controlled interaction. Finally, combined with the results of the subjective evaluation, we concluded that the recommended sizes of the interactive components were 2.889°, 3.389°, and 3.889°, and the recommended distances were 5.966° and 8.609°. Additionally, designers should utilize components with simple concrete shapes as much as possible to improve user recognition efficiency. Our study provides enlightening recommendations on how to design components in eye-controlled interactive interfaces, and has great guiding significance for building design standards of the eye-controlled systems.

Tree Diversity in Home Gardens in the Bogor Regency, West Java

We used the point-centered quarter method for trees and quadrats for saplings in home gardens of 42 hamlets within 40 districts in the Bogor Regency, West Java, to investigate the floristic composition and structure of home garden tree communities. We found a diverse range of fruit trees. A total of 64 fruit tree species were identified accounting for 93.2% of all tree species. Artocarpus heterophyllus and Nephelium lappaceum were the two species with the highest importance value, frequency, and degree of association. The Artocarpus heterophyllus–Nephelium lappaceum association or in the local names Nangka– Rambutan association is justified based on these species’ characteristics. The distributional patterns of tree species support categorizing them into six groups: very common, common, rather common, rather rare, rare, and very rare. Annona squamosa, Phyllanthus acidus, Syzygium polyanthum, Glochidion borneense, Mangifera foetida, and Diospyros philippensis were the fruit tree species that made up the extremely rare group. Nephelium lappaceum, Artocarpus heterophyllus, and Lansium domesticum, had the highest importance value (40%) at the tree level, whereas Punica granatum, Annona muricata, and Averrhoa bilimbi at the sapling stage. Species diversity indices for trees and saplings in the sampled home gardens fell into the H' = 1 to 3 categories, while similarity indices among the home gardens species composition were quite low (IS 64%). The fruit tree species had a low ability to regenerate.

Machine learning of microvolt-level 12-lead electrocardiogram can help distinguish takotsubo syndrome and acute anterior myocardial infarction

BackgroundQualitative differences in 12-lead electrocardiograms (ECG) at onset have been reported in patients with takotsubo syndrome (TTS) and acute anterior myocardial infarction (Ant-AMI). We aimed to distinguish these diseases by machine learning (ML) approach of microvolt-level quantitative measurements.MethodsWe enrolled 56 consecutive patients with sinus rhythm TTS (median age, 77 years; 16 men), and 1-to-1 random matching was performed based on age and sex of the patients. The ECG in the emergency room was evaluated using an automated system (ECAPs12c; Nihon-Koden). Statistical and ML predictive models for TTS were constructed using clinical features and ECG parameters.ResultsStatistically significant differences were observed in 25 parameters; the V1 ST level at the J point (V1 STJ) showed the lowest P value (P < .001). V1 STJ ≤+18 μV showed the highest accuracy for TTS (0.773). The highest area under the receiver operating characteristic curve (AUROC) was shown in the aVR ST level at 1/16th of the preceding R-R interval after the J point (aVR STmid: 0.727). Conversely, the light gradient boosting machine (model_LGBM) and extra tree classifier (model_ET) indicated higher accuracy (model_LGBM: 0.842, model_ET: 0.831) and AUROC (model_LGBM: 0.868, model_ET 0.896) than other statistical models. V1 STJ had high feature importance and Shapley additive explanation values in the 2 ML models.ConclusionML applied to automated microvolt-level ECG measurements showed the possibility of distinguishing between TTS and Ant-AMI, which may be a clinically useful ECG-based discriminator.

Disentangling the Factors That Contribute to the Growth of Betula spp. and Cunninghami lanceolata in China Based on Machine Learning Algorithms

Forests are indispensable materials and spiritual foundations for promoting ecosystem circulation and human survival. Exploring the environmental impact mechanism on individual-tree growth is of great significance. In this study, the effects of biogeoclimate, competition, and topography on the growth of Betula spp. and Cunninghamia lanceolata (Lamb.) Hook., two tree species with high importance value in China, were explored by gradient boosting regression tree (GBRT), k-nearest neighbor (KNN), and random forest (RF) machine learning (ML) algorithms. The results showed that the accuracy of RF was better than KNN, which was better than GBRT. All ML algorithms performed well for future diameter at breast height (DBH) predictions; the Willmott’s indexes of agreement (WIA) of each ML algorithm in predicting the future DBH were all higher than 0.97, and the R2 was higher than 0.98 and 0.90, respectively. The individual tree annual growth rate is mainly affected by the single-tree size, and the external environment can promote or inhibit tree growth. Climate and stand structure variables were relatively more important for tree growth than the topographic factors. Lower temperature and precipitation, higher stand density, and canopy closure were more unfavorable for their growth. In afforestation, the following factors should be considered in order: geographic location, meteorological climate, stand structure, and topography.

The cultural role played by the ethnomycological knowledge of wild mushrooms for the peoples of highlands and lowlands in Tlaltenango, Zacatecas, Mexico

ABSTRACT The greatest diversity of culturally relevant fungi in Mexico has been recorded in temperate forests. Likewise, it has been proven that people who live in such environments possess greater ethnomycological knowledge, compared with people in the lowlands. In this study, we investigated whether the uses and perceptions of fungi were different between people living near forests in highlands and those living in lowlands near grasslands and subtropical scrublands. We selected seven communities from the municipality of Tlaltenango, Zacatecas, Mexico, where we conducted guided tours, 35 semistructured interviews, and free lists to 420 people. Since highlands surrounded by temperate forests give rise to high species diversity, we expected that the inhabitants, in comparison with those of the lowlands where there is less diversity, would recognize a larger number of fungi. To test this hypothesis, we employed discriminant function analysis, principal coordinate analysis, Mann-Whitney U test, and linear regression. The cultural importance of each species was calculated based on the frequency with which it was mentioned and the first principal coordinate. Although the highlanders have a deeper knowledge of mushrooms, lowlanders and highlanders had similar fungal backgrounds and preferred the same species, regardless of the fungi surrounding their territory. The lack of differences among communities was due in part to the fact that the most culturally important species were those that grew in grasslands and subtropical scrub areas. Agaricus campestris was the most culturally prevalent and only commercialized species both in the highlands and lowlands, followed by Pleurotus djamor and Volvariella bombycina. None of the mushrooms growing in the pine-oak forest had a high cultural importance value, even for the communities living in the vicinity of this forest, forcing them to travel long distances to collect Agaricus campestris. Further investigations are needed in order to assess the relevance of sociocultural factors, and their potential influence in the preference for particular mushrooms in this region.

Ethnoecology of The Slamet Mountain Slope Community (SMSC) in Paguyangan District, Brebes Regency, Central Java

The local communities have local knowledge in utilizing and managing landscape units. The threat of modernization has led to the degradation of local knowledge, including the Javanese community on Mt. Slamet. This study aimed to analyze the plant diversity characteristics of landscape units and determine the important value of landscape units and plant species used by the community. This research was conducted in the Ragatunjung, Cipetung, and Pandansari village, Paguyangan District, Brebes Regency, Central Java. Semi-structured interviews collected Ethnoecological data with eight key informants and 83 respondents selected by purposive sampling and snowball sampling. Data on the level of landscape utilization were analyzed using the Local User's Value Index (LUVI). The community recognizes nine types of landscape units, such as perawisan (yard), wanah (production forest), Majegan (gardens), Sabin (rice fields), Kubang buyut (protected forest plan), tea plantations, Telaga Ranjeng Nature Reserve, Tanah Bengkok and tuk (water sources). Wanah was the most important landscape unit in the community in Ragatunjung (31.27), Cipetung (53.55), and Pandansari (28.17). Oryza sativa had the highest importance value in Sabin (22) and wanah (12) of Ragatunjung. In contrast, Syzygium aromaticum had the highest in Majegan (6.68). Brassica oleracea has the highest importance value in the two landscape units of Cipetung, namely, Majegan (4.20) and settlements (3.5), while in the wanah is Zea mays (11.38). Solanum tuberosum had the highest value in each landscape unit in Pandansari, both in wanah (10.33), Majegan (6.80), and Protection Forest Plan (PFP) (4.13). Categorizing landscapes and their utilization by maintaining certain landscapes, such as the Telaga Ranjeng Nature Reserve and Kubang buyut, directly impact the sustainability and integrity of ecosystems and natural resources in and around the area.

Effects of 21 Years of Simulated Acidic Deposition on Tree Growth and Species Composition in an Aggrading Appalachian Hardwood Forest

Abstract The long-term effects of soil acidification on the development of a young aggrading Appalachian forest were examined after 21 years of continuous treatment. Beginning with a clearcut harvest in 1997, annual ammonium sulfate (N+S) and ammonium sulfate with lime (N+S+LIME) treatments were aerially applied to a developing forest. The lime treatment was designed to counteract the acidification of the nitrogen and sulfur amendments. After 21 years, the N+S and N+S+LIME treatments had little impact on total woody biomass accumulation relative to the control. There were significant differences among species and treatment responses with respect to woody biomass accumulation, however. Biomass of Prunus pensylvanica was about twice as much as any other species in N+S and N+S+LIME treatments but was similar to Liriodendron tulipifera and Betula lenta on control areas. Treatment effects were not significant for average tree diameter or stem density, although both varied among the six tree species with the highest importance values. The importance value of P. pensylvanica decreased by almost half in the last 6 years due to mortality, but this was not associated with either the N+S or N+S+LIME treatments. The dynamic nature of this short-lived tree species is potentially masking any effects of the N+S or N+S+LIME treatments to date. Study Implications: We examined the long-term impact of nitrogen and sulfur additions with and without lime on forest stand development. After 21 years, the forest showed little change in aboveground woody biomass, although the distribution of biomass among species was affected by the treatments. Prunus pensylvanica (pin cherry) accumulated the greatest biomass on N+S and N+S+LIME treatments relative to the untreated areas. However, P. pensylvanica is a short-lived species, and our data show it is declining. It is unclear whether the treatments are having minimal impacts or they are being masked by the early dominance and subsequent mortality of P. pensylvanica.

Woody plant community structure and composition of an urban riparian forest in Monterrey metropolitan area, Northeast Mexico1

This work details the structure and composition of the woody plant community of a gallery forest located in the La Silla River, between Monterrey and Guadalupe urban areas in Nuevo León, Mexico. For the analysis, the woody vegetation was categorized into upper and lower strata. The upper stratum maximum height was 38 m, and the canopy cover was 100%. The canopy consisted of 22 species from 16 families, of which seven species represented 82.3% of the importance value index (IV); Taxodium huegelii had the highest IV (34.32%). The lower stratum maximum height was 2.5 m, and the cover was 48%. Thirteen species from 10 families were identified, five of which reached 81.3% of the IV; Ricinus communis had the highest IV (23.42%). The plant community diversity was 3.8 and 2.29, based on Margalef and Shannon indices, respectively. As one finding in the present study, it can be stated that the main threat is the presence of widely distributed exotic species such as Ricinus communis and Leucaena leucocephala, with high importance values. However, the presence of a well-established tree stratum, as well as the presence of species typical of the gallery forest, suggest a good state of conservation of this gallery forest. The present results highlight the importance of studying the composition, structure, and diversity, taking into consideration the flora of floristic provinces, as an analytic strategy for the diagnosis of riparian lentic community health.

Diversity of Tree Species in Syiah Kuala University

This research was conducted from April 2020 to October 2020 entitled "Diversity of Tree Species at Syiah Kuala University". The data collection technique was performed through a survey of 21 observation plots including faculties, office units, worship facilities, health facilities and other supporting facilities. The data analysis includes the Important Value (NP) and Species Diversity Index (H'). The results showed that the species composition of trees growing on the campus of Syiah Kuala University were 46 species belonging to 27 families. Six tree species that had relatively high importance value compared to others, namely Pterocarpus indicus (19.61%), Swietenia mahagon i (19.56%), Polyathia longifolia (12.76%), Mimusops elengi (12.48%), Roystonia regia (12.27%), and Samanea saman (10.176%). The Diversity Index (H') of those tree species ranged from 1.549 to 2.634. The conclusion is that the tree species composition was relatively limited when compared to the Cronquist classification, and the tree species diversity index was in the medium category.

Tree Species Diversity in a Semi-Conserved Beach Forest in Southern Philippines

Beach forest is a unique type of ecosystem, a mixed group of littoral creepers, shrubs, and trees above the high tide level. In Sarangani Province, beach forest is not well studied even though it experienced various environmental threats due to the increase of coastal development and tourism. This study aimed to determine the composition and diversity of beach forest species in Barangay Kling, Kiamba, Sarangani Province and relate it to the whole coastal area of the municipality by producing a profile. Specifically, the study sought to determine the species composition of beach forest in the sampling areas; assess the beach forest diversity of at least three sampling areas in Barangay Kling. Using transect-quadrat method, species were identified through identification guides. Data analysis includes relative density, relative frequency, relative dominance, species diversity index and species importance value. Results of the assessment of species composition and community structure showed that a total of 39 beach forest species distributed among 23 families are present on the site, and another ten (10) species were observed outside of the transects. Milletia pinnata has the highest importance value with a rating of 79.04, followed by Terminalia catappa (65.54) and Barringtonia asiatica (44.04). The results show that the area has a huge potential for development into a beach forest park considering the diversity and maturity of the stand. In addition, management, protection, and rehabilitation of beach forest are also highly recommended to maximize their potential as climate change mitigators and their role in coastal protection.

The diversity of native tree species from Bung Jagoi community forests, Bau, Sarawak and their potential for reforestation

ABSTRACT The study focuses on the diversity of native species from which can be selected potential species in Bung Jagoi community forests for reforestation. Multi-aged regeneration survey using nested plot design was carried out on four types of forest in Bung Jagoi community forests. The findings indicate that the intact and undisturbed primary forests are more diverse and hold a number of species with higher importance value than the disturbed forests. Bung Jagoi community forests also have abundant potential native species for reforestation.

Stable Isotope Ratio Analysis for the Comparison of Timber From Two Forest Concessions in Gabon

Consumers are becoming increasingly aware of the environmental impacts caused by deforestation and illegal logging and there is an increasing demand for supply chain transparency and traceability of wood products. Many importing and exporting nations have implemented regulations which aim to control the origin and species of traded timbers of high ecological importance and economic value. However, despite growing interest in method development for timber authentication purposes, many studies have been limited by insufficient numbers of authentic timber reference samples. Our aim was to address the differences in stable isotope ratio profile of bulk, homogenized wood samples collected from living or recently felled trees in two FSC concessions in Gabon, which are approximately 240 km apart, for the purposes of origin classification and protecting valuable forest commodities. Forty-seven timber samples comprising 10 genera of tropical trees were obtained using a Pickering Punch sampling device or chainsaw from two forest concessions in Gabon (Precious Woods Group and Compagnie des Bois du Gabon) during July 2019. Samples were subject to δ18O, δ2H, δ13C, δ15N, and δ34S stable isotope analysis using elemental analysis-isotope ratio mass spectrometry (EA-IRMS). Results show that significant differences are evident in the stable isotope ratios of Aucoumea klaineana between Precious Woods Group and Compagnie des Bois du Gabon forest concessions. Relationships are evident between climatic and geological variables and the stable isotope ratios of the samples suggesting that further degrees of origin classification may be achievable in Gabon. For other species, insufficient numbers meant the possibility to determine discriminating factors between the two concessions was limited though data from these samples may prove useful to contribute to the understanding of stable isotope variability in tropical timber. The data presented establish a basis for evaluating origin claims of forest products and timber from the Compagnie des Bois du Gabon and Precious Woods Group concessions and lay a foundation for future development of timber tracking technologies in Gabon. The technique can be used for purposes of due diligence or forensic investigation by law enforcement as part of demand-side regulations such as the EU Timber Regulation, Illegal Logging Prevention Act, or the Lacey Act.

Impacts of Temporal Changes in Land Use/Cover on the Remaining Historical Forests in Guiyang, China

The remaining historical forests are crucial for maintaining biodiversity in urban areas. However, the integrity and stability of historical forests are affected by land-use/cover change. A better understanding of these impacts can help prioritize protection and restoration. In this study, we estimated the loss of area and levels of threats and analyzed the importance of critical areas for historical forests in the built-up area of a rapidly urbanizing city—Guiyang, China. We used the threat indicator, morphological spatial pattern analysis, and probability of connectivity based on InVEST, GuidosToolbox, and Conefor software. The results based on remote sensing image classification showed that 1988.46 ha of historical forestlands was transformed into other land-use/cover types. The mean value of the threat index of all the historical forest patches increased by 33% compared to the baseline year. The area of cores and bridges, considered as key nodes and links for the connectivity of forest networks, decreased by 193.32 and 353.61 ha, respectively. Most of the critical areas with high importance values for connectivity were located in the central part of the city and were severely threatened by the surrounding areas. We recommend that effective measures be implemented to control the further loss of historical forests and to increase the connectivity and buffering capacity of the remaining forests by creating tree belts and corridors in key locations.