Forest Tree Species Research Articles

A Spatial Assessment of Current and Future Foliar Hg Uptake Fluxes Across European Forests

AbstractAtmospheric mercury (Hg) is deposited to land surfaces mainly through vegetation uptake. Foliage stomatal gas exchange plays an important role for net vegetation Hg uptake, because foliage assimilates Hg via the stomata. Here, we use empirical relationships of foliar Hg uptake by forest tree species to produce a spatially highly resolved (1 km2) map of foliar Hg fluxes to European forests over one growing season. The modeled forest foliar Hg uptake flux is 23 ± 12 Mg Hg season−1, which agrees with previous estimates from literature. We spatially compared forest Hg fluxes with modeled fluxes of the chemical transport model GEOS‐Chem and find a good overall agreement. For European pine forests, stomatal Hg uptake was shown to be sensitive to prevailing conditions of relatively high ambient water vapor pressure deficit (VPD). We tested a stomatal uptake model for the total pine needle Hg uptake flux during four previous growing seasons (1994, 2003, 2015/2017, 2018) and two climate change scenarios (RCP 4.5 and RCP 8.5). The resulting modeled total European pine needle Hg uptake fluxes are in a range of 8.0–9.3 Mg Hg season−1 (min–max). The lowest pine forest needle Hg uptake flux to Europe (8 Mg Hg season−1) among all investigated growing seasons was associated with unusually hot and dry ambient conditions in the European summer 2018, highlighting the sensitivity of the investigated flux to prolonged high VPD. We conclude, that stomatal modeling is particularly useful to investigate changes in Hg deposition in the context of extreme climate events.

Relationships between rhizosphere microbiota and forest health conditions in Pinus pinaster stands at the Iberian Peninsula

Maritime pine (Pinus pinaster) is a Mediterranean forest tree species of great ecological importance within the European Union and the Iberian Peninsula in particular, whose presence is seriously threatened by forest decline. Knowledge of the diversity, abundance, and functionality of rhizospheric microorganisms can provide important information in the design of new strategies for sustainable forest management against forest decline. In this work, rhizospheric samples were collected from representative pine forests in the region of Castilla y León (North-western Spain) (in 10 municipalities of 5 different provinces), analyzing different physicochemical parameters and bacterial and fungal biodiversity (by metabarcoding). In addition, different variables of tree health and climatic conditions were analyzed. The main phylum of microorganisms found in the rhizosphere of P. pinaster were the Ascomycota (54.5 %) and Acidobacteria (16.4 %) in fungi and bacteria, respectively. A clear relationship was found between the presence/absence of certain bacterial and fungal groups (taxonomic and functional) and the presence/absence of healthy/sick trees. Specifically, the fungal genus Umbelopsis and the bacterial genus Paenibacillus were thought as possible control agents of decline, as their presence was related to the absence of disease. Understanding the relationships between rhizosphere microbiota and forest health parameters in Pinus pinaster can be only achieved by exploring the complex ‘ecosystem microbiome’ and its functioning using focused, integrative microbiological and ecological research performed across multiple habitats.

Predation pressure by arthropods, birds, and rodents is interactively shaped by tree species richness, vegetation structure, and season

Tree species richness, forest structure, and seasonal fluctuations between rainy and dry seasons can strongly affect trophic interactions in forest ecosystems, but the inter- and scale dependence of these variables remains unclear. Using artificial caterpillars (~18,000 replicates), we analyzed predation pressure by arthropods, birds, and rodents along a tree species richness gradient across seasons in a subtropical tree diversity experiment (BEF-China). The aim of the study was to test if forest structure, in addition to tree species richness, has an effect on predation pressure and to further specify which structural variables are important in driving predation. We assessed the effects of tree species richness and forest structure at the plot and local neighborhood levels. We also included fine-scale placement covariates, plot size, and topographical covariates of the study site. Forest structure and tree species richness independently and interactively affected predation pressure. The spatial scale was an important determinant for tree species richness and structural effects, extending from within plot scales to the overall heterogeneity of the plots’ surrounding environment. For example, the effect of branch density in the local neighborhood depended on both surrounding tree species richness and plot-level vegetation density. Similarly, visibility-enhancing factors increased attacks by arthropods (lack of branches in close surroundings) and by birds (open area), depending on the surrounding vegetation. A comparison of structural measures showed that predation pressure can be addressed in much greater detail with multiple specific structural features than with overall forest complexity. Seasonal change also affected predation pressure, with foliage being a stronger attractant in spring, but also by presumable topography-driven study plot differences in sun exposure and humidity between rainy and dry seasons. Our study demonstrates that predation pressure is not simply a function of tree species richness or structure but is shaped by the interplay of structural elements, spatial scale, and seasonal dynamics along gradients of tree species richness and forest structure. The structural and seasonal effects are important to take into account when addressing how current and future biodiversity loss may change top‐down control of herbivory and overall ecosystem functioning.

HPAC: a forest tree species recognition network based on multi- scale spatial enhancement in remote sensing images

ABSTRACT Forest tree species recognition is a pivotal subject in the field of remote sensing. To address this, deep learning has been extensively applied. Thus far, most classification methods have generally relied on learning certain global features, yet often overlook the characteristics of specific regions, thereby struggling to adequately handle the similarity between classes. Furthermore, due to the singular nature of features, effectively representing the attributes of tree species images becomes challenging, consequently impacting classification performance. To tackle these issues, a novel approach for forest tree species classification in remote sensing images is proposed, based on the Hollow Pyramid Attention Combination (HPAC) network. Initially, a Shallow Multi-scale Hollow Fusion (SMHF) module is introduced before the 7 × 7 convolution in the ResNet-50 network and the first residual block’s first layer. This module employs dilated convolutions to achieve varying receptive fields. Moreover, it incorporates positional feature information, significantly enhancing the shallow-level feature extraction capabilities, resulting in a richer feature representation. Subsequently, to minimize network parameters and computational workload while bolstering the capacity to recognize deep-level features, the last residual block of the ResNet-50 differentiation is substituted with a Maxpool Avgpool Fusion (MAF) module. This replacement serves to enhance classification accuracy. The classification process is ultimately concluded with a Softmax classifier. Experimental results underscore the effectiveness of the proposed method, achieving a classification accuracy of 95.89% on the PCANDVI dataset of forest tree species data (FTSD). In summary, the introduced HPAC network proves to be both feasible and effective.

Genomic and transcriptomic analyses reveal polygenic architecture for ecologically important traits in aspen (Populustremuloides Michx.).

Intraspecific genetic variation in foundation species such as aspen (Populus tremuloides Michx.) shapes their impact on forest structure and function. Identifying genes underlying ecologically important traits is key to understanding that impact. Previous studies, using single-locus genome-wide association (GWA) analyses to identify candidate genes, have identified fewer genes than anticipated for highly heritable quantitative traits. Mounting evidence suggests that polygenic control of quantitative traits is largely responsible for this "missing heritability" phenomenon. Our research characterized the genetic architecture of 30 ecologically important traits using a common garden of aspen through genomic and transcriptomic analyses. A multilocus association model revealed that most traits displayed a highly polygenic architecture, with most variation explained by loci with small effects (likely below the detection levels of single-locus GWA methods). Consistent with a polygenic architecture, our single-locus GWA analyses found only 38 significant SNPs in 22 genes across 15 traits. Next, we used differential expression analysis on a subset of aspen genets with divergent concentrations of salicinoid phenolic glycosides (key defense traits). This complementary method to traditional GWA discovered 1243 differentially expressed genes for a polygenic trait. Soft clustering analysis revealed three gene clusters (241 candidate genes) involved in secondary metabolite biosynthesis and regulation. Our work reveals that ecologically important traits governing higher-order community- and ecosystem-level attributes of a foundation forest tree species have complex underlying genetic structures and will require methods beyond traditional GWA analyses to unravel.

A Multi-Scale Convolution and Multi-Layer Fusion Network for Remote Sensing Forest Tree Species Recognition

Forest tree species identification in the field of remote sensing has become an important research topic. Currently, few research methods combine global and local features, making it challenging to accurately handle the similarity between different categories. Moreover, using a single deep layer for feature extraction overlooks the unique feature information at intermediate levels. This paper proposes a remote sensing image forest tree species classification method based on the Multi-Scale Convolution and Multi-Level Fusion Network (MCMFN) architecture. In the MCMFN network, the Shallow Multi-Scale Convolution Attention Combination (SMCAC) module replaces the original 7 × 7 convolution at the first layer of ResNet-50. This module uses multi-scale convolution to capture different receptive fields, and combines it with the attention mechanism to effectively enhance the ability of shallow features and obtain richer feature information. Additionally, to make efficient use of intermediate and deep-level feature information, the Multi-layer Selection Feature Fusion (MSFF) module is employed to improve classification accuracy. Experimental results on the Aerial forest dataset demonstrate a classification accuracy of 91.03%. The comprehensive experiments indicate the feasibility and effectiveness of the proposed MCMFN network.

Exploring carbon sequestration in broad-leaved Korean pine forests: Insights into photosynthetic and respiratory processes

A comprehensive understanding of carbon assimilation and sequestration in broad-leaved Korean pine forests is crucial for accurately estimating this significant aspect of temperate forests at a regional scale. In this study, we introduced a high-temporal resolution model designed for carbon assimilation insights at the plot scale, focusing on specific parameters such as leaf area dynamics, vertical leaf distribution, photosynthetically active radiation (PAR) fluctuations, and the photosynthetic traits of tree species. The findings reveal that most tree species in broad-leaved Korean pine forests exhibit an inverted U-shaped pattern in leaf area dynamics, with shorter leaf drop periods than leaf expansion events. Leaf distribution varies significantly among different canopy heights, with approximately 80 % of the leaves above 15 m. PAR decreases as canopy height decreases, with PAR at 25 m accounting for about 60 % of the PAR above the canopy. Our framework incorporates a leaf-scale light-response curve and empirical photosynthesis-temperature relationships to estimate forest carbon assimilation on daily and hourly scales accurately. Using the model, we assess the gross primary productivity (GPP), leaf net photosynthetic assimilation (LNPA), and carbon increment (ΔC) of broad-leaved Korean pine forests from 2017 to 2020. The results demonstrate GPP, LNPA, and ΔC values of 21.4 t·ha−1·a−1, 17.4 t·ha−1·a−1, and 4.0 t·ha−1·a−1, respectively. Regarding efficiency, GPP, LNPA, and ΔC per square meter of leaf per year are 179 g, 146 g, and 33 g, respectively. Notably, tree species in the canopy layer of the forest exhibit significantly higher efficiency than those in the understory layer. This research significantly contributes to our understanding of carbon cycling and the responses of forest ecosystems to climate change. Moreover, it provides a practical tool for forest management and the development of carbon sequestration strategies.

Species-Specific Allometric Equations, Biomass Expansion Factor, and Wood Density of Native Tree Species in the Dry Afromontane Forest of Ethiopia

A forest is a storehouse of carbon released from different sources when the activities of sustainable forest management, planting, and rehabilitation exist. However, few allometric equations are present to determine its contribution to carbon reduction. The target of the study was to develop species-specific allometric equations and establish a database for biomass expansion factor and wood density for five tree species grown in the dry Afromontane forest of Ethiopia. A direct or destructive sampling method was used on 62 trees from different diameter classes. The diameter at breast height and the total height of selected trees ranged from 7 to 48 cm and 6.7 to 23.4 m, respectively. Trees were felled and divided into various biomass sections. Stem and big branch discs were sampled to determine the wood density and volume of the trees. Sample wood and foliage were oven-dried for three days and two days at 105°C and 70°C, respectively, to get their dry weight. Total above-ground biomass was regressed using diameter at breast height, total height, wood density, and average crown diameter as independent variables. R software version 4.0.1 was used to fit the biomass equations. The best biomass models were determined to have lower AIC and RSE and highest adj. R2. The biomass expansion factor and wood density of five tree species ranged from 1.19 to 1.40 and 0.53 to 0.74 g/cm−3, respectively. Species-specific allometric equations were better than both mixed species and pan tropical models for the assessment of above-ground biomass in the Chilimo dry Afromontane forest of Ethiopia.

Mineral-associated organic carbon predicts the variations in microbial biomass and specific enzyme activities in a subtropical forest

Tropical and subtropical forests are critical in global carbon budgets. Although separating soil organic carbon (SOC) into particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) advances our understanding of SOC sequestration, how SOC and its fractions (POC and MAOC) interact with soil microbial traits in tropical and subtropical forests remains unclear, which is critical for improving soil C projections. Here we sampled soils beneath six stands planted with different tree species in a humid subtropical forest to assess the interactions between microbial traits (biomass and specific enzyme activities) and SOC and its fractions. We found that mineral-associated organic carbon (MAOC) accounted for 78–86% of SOC and co-varied strongly with SOC, representing the largest resource pool. There were significant relationships between microbial (especially bacteria) biomass and specific enzyme activities and SOC (especially MAOC). The results of linear mixed models indicated that SOC and particularly MAOC could significantly predict the variations in microbial (especially bacteria) biomass and specific enzyme activities. However, microbial traits failed in predicting the variation in SOC and particularly the MAOC. There were significant negative relationships between microbial biomass and specific C- and N-acquisition enzyme activities and these relationships disappeared when controlling SOC or MAOC but not when controlling particulate organic carbon (POC), suggesting that there is a tradeoff of microbial investment between biomass growth and resource acquisition, and this tradeoff is controlled by SOC, particularly the MAOC. Overall, our findings provide strong evidence for the interactions between microbial traits and soil C fractions and thus highlight that MAOC plays a critical role in regulating microbial biomass, specific enzyme activities, and their tradeoff, whereas microbial biomass and specific enzyme activity may not be important determinants of MAOC in subtropical forests.

Foliar elementome and functional traits relationships identify tree species niche in French Guiana rainforests.

Biogeochemical niche hypothesis (BN) aims to relate species/genotype elemental composition with its niche based on the fact that different elements are involved differentially in distinct plant functions. We here test the BN hypothesis through the analysis of the 10 foliar elemental concentrations and 20 functional-morphological of 60 tree species in a French Guiana tropical forest. We observed strong legacy (phylogenic+species) signals in the species-specific foliar elemental composition (elementome) and, for the first time, provide empirical evidence for a relationship between species-specific foliar elementome and functional traits. Our study thus supports the BN hypothesis and confirms the general niche segregation process through which the species-specific use of bio-elements drives the high levels of α-diversity in this tropical forest. We show that the simple analysis of foliar elementomes may be used to test for BNs of co-occurring species in highly diverse ecosystems, such as tropical rainforests. Although cause and effect mechanisms of leaf functional and morphological traits in species-specific use of bio-elements require confirmation, we posit the hypothesis that divergences in functional-morphological niches and species-specific biogeochemical use are likely to have co-evolved. This article is protected by copyright. All rights reserved.

Altitudinal Patterns of Foliar Nutrients in Dominant Tree Species: Are Central Himalayan Forests Nutrient Stressed?

In forest ecosystems nutrient availability is one of the most important drivers of tree growth and ecosystem function. We studied changes in soil and foliar nutrients (N, P & K) and leaf N and P stoichiometry in eight dominant canopy and sub-canopy forest tree species of Central Himalayan forests occurring between 300 and 2200 m asl. Nutrient (N, P & K) concentration in leaves at bud break, mature and senescent stage varied significantly across the tree species. The nutrient resorption efficiency (NRE) varied significantly across the species and found ranging for N from 48.7 - 76.8%. Both the nitrogen resorption efficiency (NRE) and phosphorus resorption efficiency (PRE) increased linearly with altitude (R2= 0.647 for NRE significant at p< 0.05; and R2 for PRE= 0.525; NS) pointing out that trees growing in temperate climate conserve nutrients more efficiently to withstand the slow mineralization due to cold climate. With the increasing altitude leaf life-span increases significantly (R2= 0.0025; p< 0.0074). ANOVA indicates that the foliar N and P and altitude were unrelated. The low N: P ratio, a measure of nutrient status of forest ecosystems at senescent leaf stage, found ranging from 9.97 in Q. floribunda to 18.8 in P. roxburghii points out that forests of the study region are nutrient stressed, partly due to low P mineralization in temperate climate, leaching of nutrients due to heavy monsoon rain, and poorly developed underlying geology. Thus, the Central Himalayan forests are characterized by high NRE and low growth rate with increasing altitude. Winter season warming might help improve the nutrient availability in the forest floor and nutrient uptake to enhance nutrient cycling and biomass productivity in these forests.

Variability in forest tree species composition and diversity in different aged cocoa agroforests of Ghana

Variability in forest tree species composition and diversity in different aged cocoa agroforests of Ghana

Assessment of Soil Quality in the Transformation from Pure Chinese Fir Plantation to Mixed Broad-Leaved and Cunninghamia lanceolata Plantation in Subtropical China

To assess the alterations in soil properties resulting from the interplanting of broad-leaved tree species within coniferous forests, we conducted an investigation into soil quality in a mixed Chinese fir and broad-leaved forest, as well as in a Chinese fir pure forest (used as a control) in subtropical China. A total of 15 soil physicochemical properties were assessed across three soil depths—0–15 cm, 15–30 cm, and 30–45 cm—for the two forest types in the experimental study. Principal component analysis in conjunction with the Norm value was employed to create a minimal data set (MDS) for assessing six indicators, including bulk density (BD), total nitrogen (TN), total phosphate (TP), available potassium (AK), soil pH, and catalase (CAT). The soil quality index (SQI) was calculated for both forest types. The results demonstrated that following the interplanting of broad-leaved tree species in the Chinese fir forest, all soil physicochemical indicators were significantly improved compared to the control, and significant differences were also observed in the 0–15 cm and 15–30 cm soil layers (p < 0.05). The overall average of the SQI of the mixed forest (0.8523, 0.6636) was significantly higher than that of the control (0.4477, 0.3823) (p < 0.05) in the 0–15 cm and 15–30 cm soil layers, respectively. However, there was no significant difference in the SQI in the 30–45 cm soil layer (p > 0.05) between the two forest types. The results indicated that the SQI based on the minimal dataset (MDS) can reflect the SQI of the total dataset (TDS) when assessing soil quality in forests. Our research provides valuable scientific insights into soil science and an understanding of the relationships between soil properties, forest structure, and species composition in sustainable forest management.

Adaptive Relationships in Hemi-Boreal Forests: Tree Species Responses to Competition, Stress, and Disturbance.

European Union forest policy calls for closer-to-nature forest management, but natural disturbances and forest succession are ecological phenomena that are difficult to characterize and integrate into sustainable forest management practices. Therefore, the aim of this study is to explore the adaptive properties of Lithuania's hemi-boreal forest ecosystems. To accomplish this, we first reviewed (i) the potential natural forest communities, (ii) the successional dynamics, and (iii) adaptive strategies of forest trees, and second, we synthesised the adaptive relationships using these three reviews. The results firstly identified that Lithuania's potential natural forests are broadly divided into two climatically based zonal formations: (i) mesophytic and hygromesophytic coniferous and broadleaved forests and (ii) mesophytic deciduous broadleaved and coniferous-broadleaved forests. Secondly, the review of successional dynamics showed that each tree species can be categorised into various end communities and plant functional groups. Using the differences in tree establishment and phenological development modes we identified four forest dynamic types of tree adaptive strategies: stress-resistant ruderals, competitive stress-sensitive ruderals, ruderal stress-sensitive competitors, and stress-resistant competitors. Such functional redundancy leads to a variety of tree responses to competition, stress, and disturbance, which reduces the risk of loss of forest ecosystem functioning. Finally, the synthesised review on the adaptive relationships of each forest tree community shows both the niche position of each hemi-boreal forest tree species and how they should be managed in the organization of plant communities. We believe that this research can serve as a guide for future relevant research and the development of appropriate methods for sustainable forest management.

Urban forests – Different ownership translates to greater diversity of trees

Urban forests are recognized for their multiple benefits to society, and increasingly so with climate change. However, they too are threatened by increased heat, pollution, and higher risks of pest outbreaks. Increasing the diversity of tree species in urban forests is crucial for enhancing their resilience by reducing the risk of mass tree losses. Yet, we lack the most important ingredient to act: knowledge. Traditionally, urban tree inventories only include trees on public land. This study describes the first urban forest research plot established in Montreal, Canada, encompassing 1567 trees on public and private (residential and institutional) lands from 84 species and 43 genera. Our paper significantly contributes to the existing body of knowledge by providing empirical data that enhances our understanding and provides a clearer picture of urban forests, particularly concerning total tree diversity, across public and private lands. We found that tree abundance and diversity differed depending on land ownership: the public urban forest included more trees and was slightly more diverse than the private urban forest. Acer emerged as the most abundant genus, and small trees dominated all ownership categories. Importantly, the species composition of trees in public and private spaces differed, increasing the overall diversity. Of particular interest was the presence of three species on private property that were not recorded in the larger public tree inventory. Developing inventory practices that include private trees can provide insight to strategically enhance tree diversity where needed and maximize the benefits that diverse urban forests provide.

Allometric relationships between stem diameter, height and crown area of associated trees of cocoa agroforests of Ghana

Allometric models which are used to describe the structure of trees in agroforestry systems are usually extrapolated from models developed for trees in forest ecosystems. This makes quantitative assessment of the functions of shade trees in agroforestry systems challenging since increased availability of light and space in these systems may induce structural differences from those growing under forest conditions. We addressed this issue by providing species-specific allometric information on the structural characteristics of associated shade trees on cocoa agroforestry systems and assessed if allometries conformed to theoretical predictions. At the plot level, stand and soil characteristics affecting tree structural characteristics were assessed. The study was conducted in cocoa agroforestry systems at Suhum, Ghana. The height-diameter at breast height (H-DBH) allometry had the best fits (R2 = 53–89%), followed by the crown area (CA)-DBH allometry (R2 = 27–87%) and then the CA-H allometry (R2 = 22–73%). In general, the scaling exponents of the CA-DBH, H-CA and H-DBH allometries conformed to the metabolic scaling theory (MST). However, both the CA-DBH and H-DBH allometries diverged from the geometric similarity model. Though forest tree species had similar crown areas as fruit trees, they were slenderer than fruit trees. Tree slenderness coefficients were positively correlated with soil P, Ca, Cu and the ratios (Ca + Mg):K, (Ca + Mg):(K + Na) and Ca:Mg, but not C:N while DBH and H were correlated with soil P and C:N ratio. Our results show that critical soil nutrients and their ratios affects shade tree structural attributes (e.g. slenderness and CA), which possibly restrict variations in species-specific allometries to a narrow range on cocoa systems. Furthermore, shade tree species richness and density are better predictors of relative canopy projection area (a proxy for shade intensity) than tree species diversity. In conclusion, the results have implications for shade tree species selection, monitoring of woody biomass and maintenance of biodiversity.

Altitudinal shifting of major forest tree species in Italian mountains under climate change

Climate change has profound implications for global ecosystems, particularly in mountainous regions where species distribution and composition are highly sensitive to changing environmental conditions. Understanding the potential impacts of climate change on native forest species is crucial for effective conservation and management strategies. Despite numerous studies on climate change impacts, there remains a need to investigate the future dynamics of climate suitability for key native forest species, especially in specific mountainous sections. This study aims to address this knowledge gap by examining the potential shifts in altitudinal range and suitability for forest species in Italy's mountainous regions. By using species distribution models, through MaxEnt we show the divergent impacts among species and scenarios, with most species experiencing a contraction in their altitudinal range of suitability whereas others show the potential to extend beyond the current tree line. The Northern and North-Eastern Apennines exhibit the greatest and most widespread impacts on all species, emphasizing their vulnerability. Our findings highlight the complex and dynamic nature of climate change impacts on forest species in Italy. While most species are projected to experience a contraction in their altitudinal range, the European larch in the Alpine region and the Turkey oak in the Apennines show potential gains and could play significant roles in maintaining wooded populations. The tree line is generally expected to shift upward, impacting the European beech—a keystone species in the Italian mountain environment—negatively in the Alpine arc and Northern Apennines, while showing good future suitability above 1,500 meters in the Central and Southern Apennines. Instead, the Maritime pine emerges as a promising candidate for the future of the Southern Apennines. The projected impacts on mountain biodiversity, particularly in terms of forest population composition, suggest the need for comprehensive conservation and management strategies. The study emphasizes the importance of using high-resolution climate data and considering multiple factors and scenarios when assessing species vulnerability. The findings have implications at the local, regional, and national levels, emphasizing the need for continued efforts in producing reliable datasets and forecasts to inform targeted conservation efforts and adaptive management strategies in the face of climate change.

Avian species functional diversity and habitat use: The role of forest structural attributes and tree diversity in the Midlands Mistbelt Forests of KwaZulu-Natal, South Africa.

Forest transformation has major impacts on biodiversity and ecosystem functioning. Identifying the influence of forest habitat structure and composition on avian functional communities is important for conserving and managing forest systems. This study investigated the effect of forest structure and composition characteristics on bird species community structure, habitat use and functional diversity in 14 Mistbelt Forest patches of the Midlands of KwaZulu-Natal in South Africa. We surveyed bird communities using point counts. We quantified bird functional diversity for each forest patch using three diversity indices: functional richness, functional evenness and functional divergence. We further assessed species-specific responses by focussing on three avian forest specialists, orange ground-thrush Geokichla gurneyi, forest canary Crithagra scotops and Cape parrot Poicephalus robustus. We found that bird community and forest-specialist species responses to forest structure and tree species diversity differed. Also, forest structural complexity, canopy cover and tree species richness were the main forest characteristics better at explaining microhabitat influence on bird functional diversity. Forest patches with relatively high structural complexity and tree species richness had higher functional richness. Different structural characteristics influenced habitat use by the three forest specialists. Tree species diversity influenced C. scotops and G. gurneyi positively, while P. robustus responded negatively to forest patches with high tree species richness. Our study showed that site-scale forest structure and composition characteristics are important for bird species richness and functional richness. Forest patches with high tree species diversity and structural complexity should be maintained to conserve forest specialists, bird species richness and functional richness.

Modeling the initial development dynamics for two native Brazilian forest tree species

Abstract Development models are used to quantify the dynamics and rate of initial development, the seedling phase duration, and global warming impacts on forest species. Such models relate the physiological age of the plant, through air temperature functions, to its morphological appearance, given by the cumulative leaf number on the main stem. Despite their potential, studies on initial development dynamics are still scarce, especially for native forest species. Thus, this study calibrated and evaluated the performance of two development models—Phyllochron and Wang and Engel—in estimating the cumulative leaf number and seedling phase duration of two Brazilian native forest species—Cybistax antisyphilitica (Mart.) Mart. (Bignoniaceae) and Platycyamus regnellii Benth. (Fabaceae). Cumulative leaf number and seedling phase duration data from outdoor experiments carried out during the 2017 and 2018 growing seasons with 12 sowing dates in Itajubá, Minas Gerais, Brazil, were used. These experiments provided a rich dataset for calibrating and evaluating the Phyllochron and Wang and Engel development models. Both development models were capable of predicting cumulative leaf number with low and acceptable errors for both species and produced less accurate estimates for seedling phase duration. For C. antisyphilitica, both models were remarkably similar in estimating cumulative leaf number and seedling phase duration, with a root-mean-square error of 3.3 leaves and 25 days, respectively. For P. regnellii, the Wang and Engel model was slightly better than the Phyllochron, with an error of fewer than 2.06 leaves and 13.1 days. Using the coefficients calibrated in this study and, preferably, the Wang and Engel model, it is possible to project the development of both forest species under climate change scenarios.

KEANEKARAGAMAN JENIS DAN POLA PENYEBARAN POHON DI HUTAN LINDUNG GUNUNG EGON DUSUN BLIDIT KECAMATAN WAIGETE KABUPATEN SIKKA

This study aims to determine the diversity of species and distribution patterns of trees in the protected forest of Mount Egon, Blidit Hamlet, Waigete District, Sikka Regency and is expected to be useful for the development of science and technology, especially in the field of forestry and plantations. This research was carried out for one month from February 13 to 13. March 2023. The research used was scientific research using survey and transect methods with an observation plot size of 10 x 10. The results obtained from the study found twelve tree species, namely, Hibiscus tiliaceus, Schleichera oleosa, Santalum Album, Dimocarpus longan, Ficus carica, terminalia catappa toona sinensis, averrhoa bilimbi, canarium indicum, shorea spp, dendrocalamus asper, ficus benjamina, with a diversity index of 2,340 with criteria 1<H'<3, the diversity of tree species in the protected forest of Mount Egon is classified as moderate and the distribution pattern with IM< 1 then the distribution pattern is uniform.