Forest Farm Research Articles

Net Primary Production Simulation and Influencing Factors Analysis of Forest Ecosystem Based on a Process-Based Model

Accurate assessment of net primary production (NPP) can truly reflect the carbon budget balance of the forest ecosystem. In this study, the boreal ecosystem productivity simulation (BEPS) model was used to simulate the NPP of Saihanba mechanized forest farm in 2020, and the influencing factors of NPP were analyzed. The meteorological, forest cover, leaf area index (LAI) and other data required for the model, as well as the data for verifying, were from field surveys or downloaded from different sources. The results showed that: (1) Within the scale of the flux tower, the diurnal variation of NPP reached a maximum in June. The monthly average peak value of latent heat flux was in June, and the sensible heat flux was in March. The temperature of the understory canopy was mostly higher than that of the overstory canopy and air temperature. (2) At the regional scale, the total NPP in the study area in 2020 was 4.25 × 1011 g C a−1, with an average of 564.71 g C m−2 a−1. The annual average NPP of silver birch (Betula platyphylla) was the largest, and the total NPP of northern Chinese larch (Larix principis-ruprechtii) was the largest. (3) NPP was highly sensitive to LAI. Topographic factors had effects on NPP. The average value of NPP was relatively high in the shady slope and the gentle slope.

Employment of Ethnic Minorities Migrating from the Northern Mountains to the Central Highlands, Vietnam: A Case Study of Pleiku, Gia Lai Province

The Central Highlands includes five provinces: Lam Dong, Dak Nong, Dak Lak, Gia Lai, and Kontum. The Central Highlands is rich in resources, and fertile land is convenient for agricultural cultivation, especially industrial crops. With that great potential, after 1975, the State organized migration. It redistributed the population and owners throughout the region to the Central Highlands to establish agricultural and forestry farms, especially in the "new economic" regions. In addition to organized migration, the State's plan includes the "free migration" phenomenon of ethnic minorities from the northern mountainous provinces to the Central Highlands provinces. Unlike the original residents regarding soil, climate, and farming methods, the Central Highlands is a promising land that can bring a better life than their native homeland; they come to reclaim, establish villages, cultivate, and organize life on the new land. This paper presents the employment problem of ethnic minorities in the North who migrated to the Central Highlands, Vietnam, through a study in Pleiku City, Gia Lai Province.

Multi-Stakeholder Game Relationships in Promoting the Development of the Non-Timber Forest Product Industry by State-Owned Forest Farms

State-owned forest farms are key players in managing forestry resources worldwide, playing a pivotal role in advancing the development of the non-timber forest product industry. This paper constructs a tripartite evolutionary game model involving “government–state-owned forest farms–farmer households” to delve into how state-owned forest farms collaborate with governments and farmer households to propel the growth of the non-timber forest product industry. Additionally, it explores the interactive relationships among multiple stakeholders and their asymptotic stability. The findings reveal that (1) under certain conditions, the game model can achieve four stable equilibrium strategies: (0,0,0), (0,1,0), (0,1,1), and (1,1,1). (2) Key factors influencing the tripartite game include the political performance and administrative costs of local governments involved in the industry’s development, assessment performance and reduced management and protection expenses of state-owned forest farms, and sales revenue and planting costs of farmers’ under-forest products. (3) The market development costs shared by state-owned forest farms and government subsidies for under-forest planting should be within a reasonable range. This ensures effective promotion of farmers’ participation in under-forest planting while maintaining the willingness of state-owned forest farms and governments to actively engage. These findings provide concrete guidelines that policymakers can use to spur sustainable growth in the NTFP sector.

Species Mixing Improves Tree Growth and Timber Quality of Chinese Fir in Mixtures with Broad-Leaved Species in Central China

Mixed stands of tree species with complementary traits can modulate stand growth and timber quality. At the Fengshushan Forest Farm, mixtures of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) with Liquidambar formosana Hance, Schima superba Gardner & Champ., Elaeocarpus sylvestris (Lour.) Poir., Cinnamomum camphora (L.) Presl, and Chinese fir monoculture were established. Differences in stand growth and timber quality among these mixtures were assessed and a test was conducted to evaluate the factors influencing the mixture effects. The average diameter at breast height, tree height, stand volume, and individual tree annual increment of mixtures generally exceeded those of Chinese fir monocultures but not necessarily those of broad-leaved monocultures. When the net interaction between species was complementary, overyielding in mixtures occurred (RPfir,bl > 0), which was influenced significantly by stand density, soil properties, and timber quality. The timber quality and wood production of Chinese fir were enhanced by mixture with some broad-leaved species, with reduced slenderness and knottiness in mixtures, and notable increases in medium- (average outturn rates of 56.13%) and large-diameter (11.71%) timber in C. lanceolata/C. camphora mixture. The growth and timber quality of Chinese fir are largely promoted when grown mixed with broad-leaved species. Overyielding at the stand level occurs where Chinese fir compensates for the underperformance of broad-leaved trees.

Assessment of Changes in the Composition and Distribution of Large and Medium-Sized Mammals in Xishuangbanna, Southwest China.

Given the vulnerability of large and medium-sized mammal communities to climate change and human disturbances, understanding the spatial-temporal dynamics of these communities is essential for effective conservation planning. However, in many biodiversity hotspots, precise biological community assessments are insufficient. From 2012 to 2022, we deployed 784 camera traps in eight nature reserves (including sub-reserves) and one State Forest Farm (SFF, less strictly protected than a reserve) to study the composition and distribution of large and medium-sized mammals in tropical Xishuangbanna. The findings revealed the following: (1) Forty-three species, encompassing six orders, 17 families, and 37 genera, were documented. Among the species in historical data, nine species were not detected in this survey. (2) Smaller and more fragmented reserves lacked larger body-sized predators and herbivores, and most common species showed lower relative population abundance. Conversely, the SFF exhibited high mammal diversity. (3) The community composition of large and medium-sized mammals varied significantly across the nine sites, particularly among threatened species. Our findings highlight the uneven distribution of these mammal communities in Xishuangbanna, with rare and large-sized species facing increased vulnerability to rapid environmental changes. Moreover, the findings demonstrate the importance of considering species specificity and uniqueness in conservation planning for maintaining regional-scale biodiversity.

Seed Morphology and Tetrazolium Quick Seed Viability Test of Malabar Neem (Melia dubia Cav.) Under Laboratory Condition

Melia dubia Cav. commonly known as Malabar Neem, is an economically important fast-growing indigenous multipurpose tree species of India. It has a wide range of applications from medicinal utilities such as treating pain, fever, and infections, to agricultural and industrial uses viz., fodder, seed oil, resin, fuel wood, timber and its wood being utilized in the paper, matchbox, and plywood industries. Malabar Neem generally is distributed in tropical and sub-tropical regions of India and introduced in many countries of South Africa, the Middle East, North and South America, Brazil, Bermuda, Argentina, Southern Europe, Southeast Australia, and Asia Pacific regions. Nevertheless, it is a most promising tree species which is highly suitable for agroforestry or farm forestry with a life cycle of 8 to 12 years that gaining economic importance both in domestic and global markets and plantations in degraded lands. Consequently, the demand of Melia seedlings among Indian farmers has been increased, however the poor seed viability and very low seed germination hampered the good quality nursery production and large-scale plantations. Before seed sowing in nursery, there is need to determine the actual seed viability and to know the required seed quantity of Melia to be sown in forest nursery. Therefore, the present research study was conducted at Dr. Y. S. Parmar University of Horticulture and Forestry, Nauni, Solan, Himachal Pradesh of India to study the seed morphology and seed viability testing protocol using tetrazolium (TZ) test. The seeds of Melia species stained with 0.5, 1.0, 1.5 and 2.0 % solution of TZ and incubated at 30°C temperature for 24 hours. The tetrazolium test performed with 100 seeds in 4 replications in CRD design and analyzed with OPSTAT statistical software. The length, width and weight of fruit, drupe and seed were recorded in the range of 9.40-12.97 mm, 6.55-9.70 mm & 2.84-2.99 g; 5.84-14.32 mm, 2.76-9.72 mm & 1.672-1.798 g; and 1.2-1.98 mm, 1.02-2.98 mm & 3.12-3.74 g, respectively. The colour of fruit was yellow with oval shape having smooth surface. The result of TZ test showed that the seeds of Malabar Neem soaked in 0.5 % tetrazolium solution at 30 °C temperature for 24 hours found to be the highest seed viability percentage (40.25 %) which is recommended as a quick seed viability protocol in M. dubia. Overall, the results of the present research study fulfilled all the gaps to test quick seed viability of a seed lot before seed sowing in nursery for accurate knowledge of the seed requirement in quantity for the purpose of quality seedling production in nursery.

Metagenomic Analysis Reveals the Effects of Different Land Use Types on Functional Soil Phosphorus Cycling: A Case Study of the Yellow River Alluvial Plain.

Phosphorus (P) is a crucial limiting nutrient in soil ecosystems, significantly influencing soil fertility and plant productivity. Soil microorganisms adapt to phosphorus deficiency and enhance soil phosphorus effectiveness through various mechanisms, which are notably influenced by land use practices. This study examined the impact of different land use types (long-term continuous maize farmland, abandoned evolving grassland, artificial tamarisk forests, artificial ash forests, and wetlands) on soil phosphorus-cycling functional genes within the Tanyang Forest Farm in a typical region of the Yellow River alluvial plain using macro genome sequencing technology. The gene cluster related to inorganic phosphorus solubilization and organic phosphorus mineralization exhibited the highest relative abundance across different land use types (2.24 × 10-3), followed by the gene cluster associated with phosphorus transport and uptake (1.42 × 10-3), with the lowest relative abundance observed for the P-starvation response regulation gene cluster (5.52 × 10-4). Significant differences were found in the physical and chemical properties of the soils and the relative abundance of phosphorus-cycling functional genes among various land use types. The lowest relative abundance of soil phosphorus-cycling functional genes was observed in forestland, with both forestland types showing significantly lower gene abundance compared to wetland, farmland, and grassland. Correlation analysis and redundancy analysis (RDA) revealed a significant relationship between soil physicochemical properties and soil phosphorus-cycling functional genes, with ammonium nitrogen, organic carbon, total nitrogen, and pH being the main environmental factors influencing the abundance of these genes, explaining 70% of the variation in their relative abundance. Our study reveals land use's impact on soil phosphorus-cycling genes, offering genetic insights into microbial responses to land use changes.

Variations in the root mycobiome and mycorrhizal fungi between different types of Vanilla forest farms on Réunion Island.

The mycorrhizal fungi of cultivated Vanilla spp. have mainly been studied in America, while a recent study has investigated them on Réunion Island (Indian Ocean). However, there are many different types of cultivation on Réunion, from shade-house crops to forest farms of endemic or exotic trees. Here we fill a gap in the study of the root mycobiome of Vanilla by sampling vines in forest plantations on recent lava flows in the southeast of Réunion. Specifically, we aimed to characterize the fungal communities between terrestrial and epiphytic roots, between forest farms that differ mainly in the species of trees, and between Vanilla roots and ECM-like roots of nearby trees. By sequencing fungal ITS2, we showed that the Vanilla root mycobiome is diverse and differed between the root types and forest farms. Epiphytic and terrestrial roots host endophytic fungi, while a putative rust with visible urediniospores was abundant in terrestrial roots mainly. Other pathogens were detected in epiphytic roots (Colletotrichum) with no sign of disease. Following sequencing and electron microscopy, Tulasnellaceae, characterized by imperforate parenthesomes and cell wall expansion with an amorphous matrix, were shown to be the main mycorrhizal fungi in both vanilla root types. Interestingly, the dominant Tulasnellaceae OTU was found in ECM-type roots of trees belonging to the ectomycorrhizal family Sapotaceae. Further observations are needed to confirm the ectomycorrhizal association of endemic trees with Tulasnella. Moreover, labeling experiments will be instrumental in investigating the transfer of nutrients between the trees and the Vanilla through the network of mycorrhizal associations in the soil.

Dendroclimatological study of ancient trees integrating non-destructive techniques.

Based on the need to protect previous ancient trees and the development of dendroclimatology, the use of non-destructive technologies in tree-ring research has gained increasing attention. This study focuses on the ancient Pinus tabulaeformis in Yu Xiang Forest Farm in Henan Province. Firstly, samples were collected using the traditional Increment borers and the Resistograph, a non-destructive method. Subsequently, the peak-valley analysis was used to filter the data obtained by the Resistograph to extract the tree ring width sequence, and the data's accuracy was verified by correlation analysis with tree ring width sequence by the Increment borers. Then, the optimal filtering method and an appropriate comprehensive threshold were determined, and tree ring width and density sequences were successfully extracted. Following that, the growth trend and residual resistance in the measurement process were corrected using linear fitting and Ensemble Empirical Mode Decomposition (EEMD) technology, thereby establishing the tree-ring width and density index series, which were further validated through correlation analysis and t-tests. Finally, analysis of the correlation with climatic factors, identified the main limiting factors for tree growth, and the accuracy of the tree-ring information extracted by the Resistograph was further verified. The results showed that spite of certain differences between the tree-ring width indices extracted by the Resistograph and the Increment borer, they were generally reliable. The radial growth of the ancient P.tabulaeformis in Yu Xiang Forest Farm is primarily influenced by temperature, with the maximum density of the tree rings responding more significantly to the mean maximum temperature, while the minimum density of the tree rings responded more significantly to the mean minimum temperature. These results not only provide a scientific and accurate age for the protection of ancient trees and verify the reliability of the data obtained by the Resistograph, but also facilitate the use of non-destructive technology for in-depth study of ancient trees, therefore enhancing our understanding of how climate change affects tree growth and provide valuable insights for the future protection and management of these ancient trees.

Different habitat condition proportions on farms affect the structure and diversity of dung beetle (Coleoptera, Scarabaeidae, Scarabaeinae) communities

The continuous changes and increase of land use into ranching and agriculture have caused shifts in the composition and structure of dung beetle communities due to the modification of vegetation structure. The impact of these changes can be approached using dung beetles as ecological indicators. Agricultural, ranching, and forestry are often integrated into the same farm in different proportions (landscape level), and their degree of integration with habitats changes over time and space. We assessed if different habitat proportions of crop, pasture, and forest land on three farms affect the structure and diversity of dung beetle (Coleoptera: Scarabaeinae) communities. Farms included from three to four habitat conditions each (plantations of timber species, banana-coffee plantation, living fences, pastures, secondary and riparian forest). Pitfall traps with dung and carrion as bait were placed across each habitat condition of each farm during three different sampling periods. Across all samplings, 1,198 dung beetle individuals belonging to 21 species were captured. Species diversity and composition vary according to the type of farm and the main factor that modifies this tendency is the proportion of pasture land composing the farm. Farms with a lower proportion of grazing land (11.96% for forestry farms and 32.19% for agricultural farms) and denser vegetation canopy, which cast more shadows, had greater beetle diversity. Conversely, farms having a greater proportion of grazing land had low diversity and a dominant tendency in the species abundance curve. Umbraphile species dominated the forest farm, indicating a strong affinity for shaded environments such as the one provided there, while species displaying no habitat preference exhibited higher abundance in the ranching farm. Additionally, a notable prevalence of small-sized species was observed in the ranching farm, contrasting with a relatively even distribution of sizes in the remaining landscapes. These tendencies suggest that shade positively influences biodiversity conservation. Riparian vegetation, living fences, and banana-coffee plantations are important connectivity elements in agricultural landscapes for shade-adapted dung beetle species.

A Community Response to Tourism Focusing on the Home Stay Program in Goriganga Valley Munsyari , Pithoragarh Uttarakhand , India

In most mountainous regions of the world, people have limited possibilities for generating income. Agriculture forestry, animal husbandry Home stay back bone of local economics, The Himalayan Mountain in all its length adnbreath has been a famous destination as well as international tourist. Its snowy peaks, glaciers, passes, alpine grasslands, its wilderness, might river and many there unsurpassed natural constructs have been inspiring the adventure and explorers. The tourism industry in India has grown enormously and is becoming a major source of economic growth in India. Is paper focuses on studying the possibilities of home- stay programs and the willingness of the residents in Uttarakhand on such programs. Considering the tourism perspective of India, home-stay programs are rather unusual. Only Ladakh Autonomous Region in Jammu and Kashmir are the two examples. is research is a combination of qualitative and quantitative approaches through household survey, an average treatment, community economic development analysis, observations, interpretative analysis, and ethnographic understanding of Johar valley, Munsyari Pithoragarh District, Uttarakhand. E results show that the tourism industry has not brought economic benefits for the households involved in the industry; however, this could be owing to the community not being involved in tourism development. In addition, most of the villagers considered that the home-stay program could create opportunities for jobs and improve the income of the local community. In the mountain tourism industry, tourist guides, dhabawals are the main successful tourism operations. In the study area, we found private entrepreneurship, but the home-stay program has not yet been developed. is research paper expects to assist making decisions to initiate an extensive home-stay program under the “Endogenous Tourism” program with some re-evaluations of not only the previously mentioned village of Uttarakhand, but also other remote locations in India, considering the colorful and cultural-rituals of rural living in India.

Assessment of forest disturbance and soil erosion in wind farm project using satellite observations

The construction of wind farms, involving road construction and wind turbine installation, severely disrupts natural landscapes. Wind energy expansion in global forested areas has unclear impacts on local forests and ecosystem services. Due to a lack of information on internal road distribution and deployment dates, few studies have assessed forest disturbances caused by wind farms. Environmental issues like vegetation destruction and soil erosion may be overlooked. To address this, we integrated multi-source spaceborne observations to identify deployment dates and road distributions of forest wind farms and mapped related forest disturbances and soil erosion changes. Six global locations were tested, showing over 80 % accuracy. Disturbance intensity ranged from 1.5 to 6.5 ha/MW, with NDVI decreasing by 0.03 to 0.33 in disturbed forest regions. The average soil erosion increase per unit area due to road construction ranged from 24.74 to 274.33 t/hm−1a−1, while wind turbine construction caused an average soil erosion increase ranging from 26.52 to 26.52 to 263.46 t/hm−1a−1. Road construction is the primary cause of forest disturbance, with greater soil erosion increases in mountainous than in plain forests. This method enhances monitoring and understanding of wind farms' environmental impacts.

Site-based climate-smart tree species selection for forestation under climate change

Global climate change threatens ecosystem functions and resilience, prompting large-scale planting initiatives to mitigate its impacts. To ensure new plantations are adaptive to future climates, it is crucial to consider climate mismatches resulting from climate change when selecting tree species. However, current research is all species-based, which is not effective for species selection across species at specific plantation sites. Our research developed a novel site-based approach that can identify optimal tree species for specific planting sites under projected future climates. We evaluated the feasibility and effectiveness of this method across 10 representative sites in diverse climatic zones in China based on climate niche projections for 100 key tree species. Our findings demonstrated the necessity and effectiveness of this approach, which can select a suit of suitable tree species tailored for any potential planting site across China under different climate change scenarios. For instance, at Tibet Dongjiu Forest farm, Aibes densa and Quercus pannosa currently showed high suitability scores above 0.8 (on a scale of 0–1). However, by the 2080s, Aibes densa's suitability was projected to drop to 0.25, while Quercus pannosa was expected to maintain its suitability. Conversely, Quercus aquifolioides currently had a low suitability of 0.08, but it was projected to increase to 0.74 by the 2080s. These findings demonstrate the importance of using this approach to avoid selecting the wrong species or overlooking potentially suitable species. In addition, our simulation analysis suggests that a dataset of 40–50 species is necessary to ensure that most planting sites can identify 2–3 suitable species. This advancement significantly enhances the precision and effectiveness of tree species selection strategies for local practitioners, offering vital insights for forestry, conservation, and ecological restoration projects. These results highlight the tremendous potential and practical applicability of our site-based approach in enhancing forestry adaptation and ecological functions in response to global climate change.

Impacts of oyster farms on sediment-associated mercury and methylmercury concentrations and health risks in an estuarine, mangrove forest, Zhanjiang Bay, China

Estuarine sediments serve as significant reservoirs for mercury (Hg) and methylmercury(MeHg), which can also interconvert in the external environment. The release of Hg in response to human activities raises concerns about its potential ecological and human health effects. Sediment samples were collected in December 2021 from four locations (sites), and Hg cycling by measuring the concentrations of, and controls on, the spatial distribution of total Hg (THg) and methylmercury (MeHg) in high-tidal zone (HTZ) and mid-tidal zone (MTZ) sediments of a mangrove forest (MF) and oyster farm (OF) was examined in northwestern Zhanjiang Bay, including simultaneous determination of sediment particle size, oxidation-reduction potential (Eh), pH, total organic carbon (TOC), sulfide concentration (S2-), and sulfate reducing bacteria (SRB). The research results indicated that concentrations of both THg and MeHg ranged between 20.0–104.0 ng/g and 0.011–0.277 ng/g in the sediments, respectively. The highest methylation potentials within the MF and OF were in sediments located approximately 10–15 cm below the surface. MeHg in the HTZ of the OF was likely derived from exogenous inputs as Hg methylation appears limited, and the formation of MeHg depended not only on the amount of inorganic mercury available for methylation in SRB, but also on the TOC, pH, Eh and S2- content in the sediment. A risk assessment of MeHg during the anthropogenic disturbance of this estuaries conducted on individuals eating oysters demonstrated that health risks are low.

The advantage of afforestation using native tree species to enhance soil quality in degraded forest ecosystems

Different vegetation restoration methods have improved soil quality to varying degrees. This study, focused on the forest–grassland–desert transition zone in the Hebei–Inner Mongolia border region, and employed a systematic grid sampling method to establish fixed monitoring plots in the Saihanba Mechanized Forest Farm and the Ulan Buh Grassland. The differences in soil quality evolution across various vegetation restoration methods under the same climatic and soil historical conditions were analyzed, elucidating the roles of these vegetation restoration methods in degraded forest ecosystems, with the aim of providing a reference for ecological restoration under similar land conditions. This study used a grid method to establish sample points in the forest–grassland–desert transitional zone and assessed five methods of vegetation restoration sites: artificial forest composed of native species of Larix principis-rupprechtii (FL), artificial forest composed of exotic Pinus sylvestris var. mongolica (FP), natural secondary broad-leaved forest (FN), open grassland (GO), and enclosed grassland (GC). The differences in soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), total potassium (TK), alkaline hydrolysis nitrogen (AN), rapidly available phosphorus (AP) and rapidly available potassium (AK) among the different vegetation restoration sites were compared via variance analysis, and the soil quality index (SQI) was calculated to assess the soil quality at the sample points. The SOC, TN, and AN contents of forest soil were significantly greater than those of grassland, and the TN, TP, AN, AK, and SOC contents of FL, FN, and GC were significantly greater than those of FP and GO. Among them, the TN, TP, and SOC contents were the highest in the FL, reaching 2.74, 0.39, and 47.27 g kg−1, respectively. In terms of ecological stoichiometric characteristics, the average N:P ratio in the study area was 6.68, indicating a serious lack of N in the study area. Among the different types of restoration sites, the effect was stronger in the FP than in the FL, and the TN and AN contents were only 1.48 g kg−1 and 116.69 mg kg−1, respectively. The SQI in the FL was not significantly different from that in the FN or GC, but it was significantly greater than that in the FP and GO. These findings indicate that native tree species restoration in degraded forest ecosystems significantly improved soil quality, while the introduction of exotic tree species for afforestation had a minimal effect on improving soil quality.

Tree species classification based on PointNet++ deep learning and true- colour point cloud

ABSTRACT Accurate identification of tree species is the foundation of forest resource surveys and an important research field in forestry remote sensing. The introduction of the PointNet++ deep learning network to point cloud processing provides a new approach for tree species identification. This network can directly compute and train unordered point clouds, greatly reducing the manual selection and extraction process of feature data. However, how to establish a high-quality single tree point cloud dataset is a key issue to be solved. In this study, a 2.5-ha temperate coniferous broad-leaved mixed forest located in Mao’er Mountain Experimental Forest Farm in Heilongjiang Province, China, was investigated. The unmanned aerial vehicle (UAV) RGB image and LiDAR synchronous observation system were used to obtain the true-colour point clouds of the forest. Combining upsampling and downsampling methods, a dataset containing coordinates, normal vectors, RGB, and intensity information was constructed from the original point cloud. Comparative experiments were designed based on resampling algorithms, number of sampling points, feature information, and time cost to find the optimal feature information and processing methods for tree species classification. The results showed that the accuracy of tree species classification by using PointNet++ was greatly improved after adding RGB and point cloud intensity information. The classification accuracy was about 5% higher than that using only coordinate data sets. In addition, the combination of PU-Net downsampling network based on point cloud completion and geometric upsampling method achieved the highest classification accuracy (OA = 0.944) when the number of single trees point cloud was 3072. The algorithm also took a relatively shorter running time. This study demonstrated that the introduction of multi-feature information and the optimization of resampling method can provide new solutions for tree species classification based on the PointNet++ deep learning network.

Sustainable Management Practices of State-Owned Forest Farms in Subtropical Regions: Case Study of S Forest Farm in China

Sustainable Management Practices of State-Owned Forest Farms in Subtropical Regions: Case Study of S Forest Farm in China

Multi-objective optimization of forest structure for broadleaf mixed forest under different CMIP5 scenarios

Climate change is an important global research topic and one of the most pressing issues facing the world today. It significantly impacts forest distribution, species composition, stand structure, growth, and other functions, therefore, it is crucial to simulate the dynamic changes of forest structure under future climate change and develop optimized solutions to adapt to it. Combined with the various stand structural parameters, based on the equal or unequal weights of each parameter at the stand level, to establish a dynamic stand spatial structure multi-objective optimization index (L-index) under different climate changes, and to implement broadleaf mixed forest spatial structure optimization research in Yanan Forest Farm under RCP 2.6, RCP 4.5, RCP 8.5 climate scenarios after 5 years. The results indicated that the L-index showed an increase ranging from 13.8 % to 35.7 % under equal weights in different climate scenarios. Additionally, the optimal harvesting intensity ranged from 13.2 % to 20.5 %, with the highest intensity observed in the RCP4.5 climate scenario; compared to the RCP4.5 and RCP8.5 climate scenarios, the RCP2.6 scenario shows the largest trend and magnitude of change in the indicators, suggesting that the state of stand growth is more sensitive under the RCP2.6 scenario. The L-index showed an increase ranging from 13.7 % to 34.4 % under the unequal weights in different climate scenarios, in which the optimal harvesting intensity ranged from 14.6 % to 19.8 %. More importantly, it should be noted that the values of the increases in the L-index and the relative increased proportion (RIP) were both higher than those when unequal weights were employed. Moreover, it should be highlighted that the increments in the L-index and RIP were both greater than those observed when unequal weights were applied for all three plots under different climate scenarios. Overall, the adjusted the complete mixing degree index (Mc) increased, angle index (W), dominance ratio index (U), and Hegyi competition index (CI) decreased compared to before optimizing with the equal or unequal weights of the stand structural variable, which is evident that the adjustments made to the stand’s structure have resulted in a significant improvement. Thus, the multi-objective optimization for forest spatial dynamics constructed is both reasonable and effective, and it more scientific forest management under different climatic scenarios.

Prediction model for the quantity and density of first-order branches of Larix kaempferi in eastern area of Liaoning Province, China.

As an important branch characteristic factor, the quantity of branches could influence crown structure, tree growth, and wood quality. Taking Larix kaempferi plantation in Dagujia Forest Farm, Qingyuan County, Liao-ning Province as the research object, we developed a mixed effect prediction model of the first-order branches quantity of L. kaempferi including sprouting branches based on the negative binomial distribution model, and a mixed effect prediction model of the first-order branches density of L. kaempferi including sprouting branches based on the negative exponential model. The results showed that the mixed effect model considering sample level as the random effect effectively decreased the heteroscedasticity and autocorrelation. The fitting goodness was better than the traditional model. The quantity of the first-order branches increased with increasing crown ratio. The mixed effect model with the basic model intercept of the first-order branches quantity as the random effect parameter was determined as the optimal model, with Ra2=0.552 and the RMSE=7.242. As for the density of the first-order branches, the heteroscedasticity and autocorrelation were also reduced when the random effect was added. The density of the first-order increased with increasing crown ratio. The mixed effect model with the basic model intercept of the first-order branches density model and branch depth as random effects was determined as the optimal model, with Ra2=0.792 and the RMSE=4.447. The model for branch quantity and density of L. kaempferi constructed would lay an important foundation for making scientific forest management plans and improving wood quality.

Soil fauna changing in after‐pine harvesting's areas along a temporal gradient of Atlantic Forest regeneration

AbstractMonoculture of pine alters the soil fauna community structure, but forest farms, mixed with natural areas, are restoring the original vegetation to protect, the diversity and ecosystem functions. In restoration initiatives it is necessary to consider the soil fauna. Thus, the aim of this study was to investigate how the process of restoration of the soil community occurs over time in areas after pine harvesting. Areas in natural regeneration with 4 and 10 years, pine plantations adjacent to these areas (representing previous use), and areas of natural forest (reference) were evaluated, it was evaluated three areas per treatment, with six sampling points spaced 30 m apart, totalling 18 sampling points for each treatment (n = 18). Soil mesofauna and macrofauna were collected through soil monoliths and pitfall traps. The comparison of the statistical analysis was to check for changes in the soil fauna over time (4 and 10 years) compared with that observed in secondary forest areas. The study showed that, along the natural regeneration time (4 and 10 years), it was observed increments in the diversity and evenness of the soil community and a reduction in the dominance of groups like Formicidae and increases in the community structure complexity with the resurgence of micropredators/regulators (Collembola and Acari), litter transformers (Oligochaeta, Diplopoda, Blattodea, Coleoptera (Larva), Diptera (Larva) and Coleoptera) and predators (Pseudoscorpiones, Opiliones, Symphyla and Coleoptera) after 10 years of natural regeneration, the areas have already recovered groups with important ecosystem functions, but are not yet at the level of abundance, functional diversity and community structure of native forest areas. The 4‐ and 10‐year regeneration areas present major number of soil fauna groups of native forest (20 groups in regeneration areas and 17 in the native forest areas). Even so, the forest showed a major complexity of soil fauna community structure, evidenced by the diversity. This study contributes to the understanding of natural regeneration for soil fauna along a temporal gradient and these findings can guide the conservation of regional soil fauna diversity.