Tree Distribution Patterns Research Articles

Street tree communities reflect socioeconomic inequalities and legacy effects of colonial planning in Nairobi, Kenya

Street trees provide ecological and social benefits that sustain urban life, yet their distribution frequently mirrors socioeconomic inequalities, meaning underprivileged social groups also have fewer trees. The distribution patterns of urban trees are least documented in the cities of rapidly evolving middle-income countries. We assessed whether street tree abundance, size, condition, diversity, and composition vary across census-derived socioeconomic strata in Nairobi, Kenya. We sampled 2047 trees across 12 neighborhoods, covering 24 km of street, then used linear regression to understand how socioeconomic strata relate to street tree characteristics. We found substantial disparities in tree abundance, with affluent areas harboring 91.5 % of the trees sampled. Low-income areas and informal settlements had comparably few trees. Mean diameter and condition did not vary across socioeconomic strata, but high-income, formerly European neighborhoods had a higher proportion of small trees, indicating a bias in recent urban greening investments further benefiting these areas. Species diversity followed a similar pattern of inequality. High-income neighborhoods had over 30 % higher species richness and diversity than low-income areas. Even so, lower income neighborhoods exhibited greater differences in street tree community composition, and a higher proportion of trees that bear edible fruit or are used in traditional medicine. Overall, our results reveal pronounced spatial inequality in the distribution of street trees in Nairobi, reflecting not only socioeconomic differences but the enduring legacies of colonial planning.

Unique Plant Resources and Distribution Patterns in the Valley Forest of the Irtysh River Basin.

The river valley forests of the Irtysh River Basin are a germplasm bank of Salicaceae species and rare plant resources in China, and the distribution varies with the river and is highly distinctive. However, there is a dearth of systematic research on the characteristics of plant resources. In this study, a comprehensive investigation was conducted in the trunk stream and six tributaries with valley forest distribution in the Irtysh River Basin, and 244 quadrats were set up. The analysis focused on the composition of the flora and resource characteristics. The results reveal the following: (1) The valley forests of the Irtysh River Basin contain 256 species of plants belonging to 57 families and 178 genera, among which 19 species of trees, 23 species of shrubs, and 214 species of herbs were investigated. (2) Among the identified species, 226 (88.67%) were recognized as resource plants, with medicinal plants being the most abundant (176 species, 68.75% of the total). (3) The distribution patterns of trees, shrubs, and herbs of each resource type vary across rivers. Elevation drop, river length, and river distance all significantly affect the number of specie. This study elucidated the current status and distributional characteristics of plant resources in the valley forests of the Irtysh River Basin, which is essential for both biodiversity conservation and sustainable resource utilization.

A universal canopy gap fraction model for forests with various tree distributions based on Nilson's models considering directional overlaps among crowns

An accurate estimation of forest canopy gap fraction (GF) is a prerequisite for remote sensing retrievals of several associated canopy parameters e.g. leaf area index, fAPAR (fraction of photosynthetically active radiation absorbed by the canopy), clumping index, etc. A universal canopy GF model for forests is required for various tree distribution patterns on flat and slopping terrains, yet existing models so far do not possess all these abilities simultaneously. For example, the Neyman type-A model, the Poisson model, and the hypergeometric model are suitable only to forests with clumped, random, and regular tree distributions, respectively. In this regard, the suite of Nilson's canopy GF models developed for forests with various tree distributions have the potential to become universal models. For this purpose, this study attempts to overcome the following limitations of these models to make them be true universally applicable: (1) canopy GF calculated by the Nilson's models is mostly accurate for various tree distributions at nadir; whereas at it is either underestimated for clumped tree distributions or overestimated for regular tree distributions at off-nadir; and (2) Nilson's models were developed for flat terrains and untested for sloping terrains. Herein, two Nilson's models are modified by expanding the calculation of overlaps among crowns (OAC) at nadir to the whole hemispherical space. The results show that all canopy GF simulations in the new models (New91 and New99) show higher consistency with ray-tracing results than those in original Nilson's models in all directions, highlighting the need to consider directional OAC. The modified models (especially for New99) are validated in two RAMI forest stands and a Saihanba forest stand: the relative error in canopy GF between the modified models and a ray-tracing model is less than 10 % in all forest stands. The modified models (especially New99) are suitable for various tree distributions on flat and slopping terrains and therefore increased the universality of the original Nilson's models suitable for a wide-range of remote sensing applications. New99 can be deemed as a universal canopy GF model for forests with various tree distributions.

Structure and distribution of palm tree species in Altingia excelsa planted forest in Gunung Gede Pangrango National Park, West Java, Indonesia

Abstract. Sadili A, Salamah A, Mirmanto E, Kartawinata K. 2024. Structure and distribution of palm tree species in Altingia excelsa planted forest in Gunung Gede Pangrango National Park, West Java, Indonesia. Biodiversitas 25: 249-256. Gunung Gede Pangrango National Park (GGPNP) is a conservation area consisted of natural forest and planted forest, including Altingia excelsa Noronha stands which were planted in 1925. As a result of secondary succession, various plants grow under Altingia excelsa stands, including palm tree species (Arecaceae). This research was conducted to determine the structure, population, and distribution patterns of palm trees in Altingia excelsa planted forest in Bodogol Resort, GGPNP. The data were collected by establishing a one-hectare plot divided into 100 subplots of 10 m × 10 m. Palm tree species with a Diameter at Breast Height (DBH) ?3 cm were measured, and the tree heights were estimated. Data analysis included Relative Dominance (RDo), Relative Density (RDen), Relative Frequency (RF), Importance Value Index (IVI), Shannon Wiener Diversity Index (H'), Evenness Index (E), Index of Dispersion (ID), analysis of variance values (S2) and Chi-square analysis (Q). The study results recorded four species from three genera of Arecaceae which consisted of 171 trees with a total Basal Area (BA) of 0.63 m2/ha. Pinanga coronata (Blume ex Mart.) Blume was the most dominant palm tree species with IVI of 156.89%), followed by Pinanga sp. (IVI=72.04%), Caryota rumphiana Mart. (IVI=55.77%), and Arenga pinnata (Wurmb) Merr. (IVI=15.38%). In term of diameter class distribution, Pinanga coronata and Pinanga sp. were regenerating well. Spatial distribution patterns of Arenga pinnata, Caryota rumphiana, and Pinanga sp. were regular, while Pinanga coronata was clustered. Periodical studies in the future to determine the mortality and natality of the palm trees are recommended to understand the dynamics of vegetation succession.

Species diversity and distribution pattern of venerable trees in tropical Jianfengling National Forest Park (Hainan, China)

Venerable trees are precious natural-cum-cultural heritage and an important component of regional biodiversity, with significant social, cultural and ecological values. A thorough understanding of their spatial patterns in relation to environmental factors can foster co-management for conservation and sustainable resource use. The Jianfengling National Forest Park in tropical China is a unique and rare primary tropical forest protected area with exceptionally high biodiversity and a rich endowment of venerable trees. This study evaluated the venerable tree stock regarding botanical makeup and factors shaping spatial patterns. We collected detailed tree data (species, age, dimensions, location, etc.) and environmental variables (elevation, slope and soil). The environmental variations were analyzed concerning tree abundance, species richness and tree age. The results identified 2134 venerable trees from 72 species, 55 genera and 30 families. Lithocarpus fenzelianus dominated with maximum importance value, followed by Cyclobalanopsis patelliformis, Madhuca hainanensis, Altingia obovata and Castanopsis tonkinensis. The top-ranking species were predominantly Fagaceae members. The age pattern demonstrated an inverted J-shape, with mainly 100-299 years trees and a few >500 years. DBH, tree height, and crown width displayed an approximately normal distribution. Spatial distributions by age tiers were uneven, with more in the northeast part. The altitudinal gradient significantly influenced the spatial patterns of tree abundance and species richness. The unimodal distribution marked tree and species concentration at circa 600 m mid-elevation. The findings have implications for venerable-tree conservation and management in tropical protected areas with similar threatened and remnant-tree status.

Mapping of Rubber Forest Growth Models Based on Point Cloud Data

The point cloud-based 3D model of forest helps to understand the growth and distribution pattern of trees, to improve the fine management of forestry resources. This paper describes the process of constructing a fine rubber forest growth model map based on 3D point clouds. Firstly, a multi-scale feature extraction module within the point cloud column is used to enhance the PointPillars learning capability. The Swin Transformer module is employed in the backbone to enrich the contextual semantics and acquire global features with the self-attention mechanism. All of the rubber trees are accurately identified and segmented to facilitate single-trunk localisation and feature extraction. Then, the structural parameters of the trunks calculated by RANSAC and IRTLS cylindrical fitting methods are compared separately. A growth model map of rubber trees is constructed. The experimental results show that the precision and recall of the target detection reach 0.9613 and 0.8754, respectively, better than the original network. The constructed rubber forest information map contains detailed and accurate trunk locations and key structural parameters, which are useful to optimise forestry resource management and guide the enhancement of mechanisation of rubber tapping.

Species Composition and Diversity of Plants along Human-Induced Disturbances in Tropical Moist Sal Forests of Eastern Ghats, India

Plant biodiversity data are prerequisites for the sustainable management of a forest. We used quantitative ecological tools to determine the species composition, diversity (richness and evenness), population structure, distribution patterns, and regeneration status of trees in a Tropical Moist Sal Forest of Eastern Ghats, India. For this purpose, a field inventory was conducted during 2020–2022 in sixteen 1.0 ha forest stands along a human-induced disturbance gradient. A total of 161 species (61 trees, 40 shrubs, 60 herbs) belonging to 77 families and 143 genera were recorded in the 16.0 ha of forest area. The results revealed a significant (p < 0.01) decrease in the tree and shrub species density, basal area, species richness, and diversity along the gradient of disturbance. However, in the case of herbs, the Shannon–Weiner diversity index increased significantly (p < 0.01) with increasing disturbance levels. Irrespective of forest types and disturbance levels, the tree diameter class (10–30 cm) accounted for the highest stem density in the forest. A mixed trend was found in the case of the basal area; the >41 cm diameter class constituted the highest basal area in the Pure Sal Forest while the 10–30 cm class was in the Moist Deciduous Forest without Sal. Tree species richness was found higher in lower diameter classes. Disturbances impacted the distribution pattern of trees; in the Pure Sal Forest, the contagious distribution of trees were 61.54%, 40%, and 12.5% in undisturbed, low-disturbed, and moderately disturbed sites, respectively. The percent of trees showing random and regular distribution increased with the increased level of disturbance in all forest types. The number of tree species having good regeneration decreased with the increased disturbance intensity in all forest types. Frequent grazing, repeated forest fires, and poor soil seed banks at the Moderately Disturbed site were the main reasons for the poor/no regeneration of Pterocarpus marsupium, Adina cordifolia, Terminalia bellerica, and some other economical species. Significant changes in structural attributes of the tree community revealed the impact of human-induced disturbances in the Moist Sal Forests of Eastern Ghats. The disturbance mosaics promoted the growth of many invasive weed species and lianas, depleting the number of valuable species in the forest. This study suggests the adaption of sustainable biodiversity conservation approaches through the active participation of the tribal so that the remnants the Moist Sal Forests of Eastern Ghats can be controlled to prevent further degradation.

Distribution of giant trees in the urban areas and western suburbs of Tokyo, Japan

ABSTRACT Giant trees reflect site environmental conditions and to elucidate the distribution pattern of the giant trees, we investigated relationships between giant tree locations and landforms. On the basis of elevation, the landforms of Tokyo were divided into four types (lowland, plateau, hill, and mountain), and tree distribution patterns were divided into five groups, including three sub-types, with occurrence patterns of representative species [I: Frequently lowlands, often plateaux and mountain type (Machilus thunbergi); II: Frequently plateaux, often lowland, hill, or mountain type (Quercus acuta, Prunus speciosa, Taxodium distichum, Liriodendron tulipifera, Cedrus deodara, Aphananthe aspera, and Prunus × yedoensis “Somei-yoshino”) with two subtypes, II-1: Typically plateaux (Cinnamomum camphora, Castanopsis sieboldii, and Ginkgo biloba) and II-2: Frequently plateaux and hills (Zelkova serrata); III: Typically plateaux and hill type (Certis sinensis var. japonica, Torreya nucifera, Carpinus tschonoskii, Quercus myrsinifolia, and Quercus serrata) with one subtype, Frequently plateaux (Prunus jamasakura); IV: Mountains often with plateaux or hill type (Acer pictum subsp. mono, Aesculus turbinate, Abies firma, Cryptomeria japonica, and Cercidiphyllum japonicum); and V: Mountain-limited type (Castanea crenata, Pterocarya rhoifolia, and Fraxinus platypoda)]. Some giant trees, including Quercus crispula, Fagus japonica, Fagus crenata, and Tsuga sieboldii, were distributed in mountainous areas but not on plateaux, hills, or in lowlands. Some unique giant trees (Aphananthe aspera, Certis sinensis var. japonica, and Carpinus tschonoskii) are self-seeding in the wild and found in plateau areas but not mountainous or hilly areas. These results suggest that the distribution of giant trees is influenced by site ecological characteristics, tree physiology, and human management and land-use.

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.

Modeling tree species richness patterns and their environmental drivers across Hyrcanian mountain forests

Perception of the way tree species richness distribution varies along the elevational gradient is necessary for applying conservation strategies in favor of biodiversity hotspots. Hyrcanian Mountain Forests of Iran are among the most biodiverse forests in the world and are inscribed in the United Nations Educational, Scientific, and Cultural Organization (UNESCO) World Heritage List. Here, the Bayesian Additive Regression Tree (BART) and Stack-Species Distribution Model (S-SDMs) were used to understand tree diversity patterns of the Hyrcanian Mountain Forests. For all the tree species, we implemented the BART model with nine environmental variables, including six bioclimatic and three topographic variables, to create a habitat suitability map. We used the area under the curve (AUC), True skill statistic (TSS), type I error, and type II error to evaluate the BART model for each tree species. All models were then stacked to estimate tree species richness. Important variables affecting the distribution of tree species in northern Iran were different for each species but, in general, topographic variables such as slope and altitude played a very important role. BART model mapped all the 29 tree species distribution effectively with AUC 0.83–0.98, TSS 0.51–0.92; and low type I and type II errors. A very important point was the high ability of this model to predict species with low presence data. The achievement of this study was identifying the biodiversity hotspots based on the tree distribution pattern along the elevational gradient. We mapped regional richness at 1 km spatial resolution and it was the first effort to predict macroecological patterns in the Hyrcanian forests of Iran. The hotspots were mainly scattered from sea level and areas with 1000 m elevation, which were close to residential areas. In conclusion, these results help forest manager to plan new conservation strategies based on tree richness hotspots.

Automatic registration framework for multi-platform point cloud data in natural forests

ABSTRACT The use of light detection and ranging (LiDAR) for investigating forest parameters has gained attention in recent years. However, the occlusion of trees in natural forests makes it difficult for LiDAR on a single platform to capture complete point clouds of trees. In order to solve this problem, it is crucial to combine multi-platform LiDAR data. Because of the complexity of natural forests and the small difference between the geometric characteristics of trees, current multi-platform LiDAR data fusion remains an ongoing challenge in natural forests. In this paper, an automatic registration framework for multi-platform point cloud data in natural forests based on tree distribution pattern was proposed. It consists of five steps, namely segmenting trees, generating feature descriptors, matching trees and registering coarsely and finely. The proposed registration framework can determine the same and accurate location information of matching trees from multi-platform LiDAR data, and a large number of correct matching trees can be obtained through two rounds of a single tree matching process. The proposed framework was validated by fusing airborne laser scanner (ALS) and backpack laser scanner (BLS) data in natural forest. According to experimental results, the proposed framework has a high registration accuracy (root-mean-square error (RMSE) = 0.133 m, mean absolute error (MAE) = 0.126 m). In addition, when the single tree segmentation accuracy exceeds 0.85, the proposed framework is less affected by segmentation errors. In natural forests, the proposed framework can effectively improve the accuracy and efficiency of multi-platform LiDAR data registration.

Modelling the Geographical Distribution Pattern of Apple Trees on the Loess Plateau, China

The Loess Plateau, known for its fragile ecosystems, is one of the traditional apple-producing regions in China. Although some management measures are needed to enhance sustainable agriculture in response to the rising pressure of climate change, the geographic distribution of apple trees considering multiple variables has not been considered. In this study, we used three software (the maximum entropy model, IDRISI, and ArcGIS) to simulate the potential distribution of suitable habitats and range shifts of apple trees in the near present and near future (i.e., the 2030s and the 2050s) under two climate scenarios (the Shared Socioeconomic Pathways (SSP)1-26 and SSP5-85), while taking a variety of environmental factors into account (e.g., temperature, precipitation, and terrain). After optimization, the class unsuitable habitat (CUH) changed the potential distribution pattern of apple trees on the Loess Plateau. Currently, the areas of lowly suitable habitat (LSH), moderately suitable habitat (MSH), highly suitable habitat (HSH), and CUH were 7.66 × 104, 2.80 × 104, 0.23 × 104, and 18.05 × 104 km2, respectively. Compared to the centroid estimated under the climate of 1970–2000, the suitability range of apple trees was displaced to the northwest in both the 2030s and the 2050s in SSP5-85 (i.e., 63.88~81.30 km), causing a larger displacement in distance than SSP1-26 (i.e., 40.05~50.32 km). This study demonstrates the possible changes in the spatial distribution of apple trees on the Loess Plateau in the near future and may provide a strong basis for future policy making.

NEAREST NEIGHBOR PATTERNS OF DOMINANT TREE SPECIES IN TROPICAL FORESTS, PHOU KHAO KHOUAY NATIONAL PARK, LAOS

Target-tree management is a silviculture technique that aims to achieve sustainable forest management by considering the spatial structure of forests. In this study, a new quantitative method was used to analyze the spatial structure of natural forest stands in the Phou Khao Khouay national park in Laos. The method involved mapping and measuring all individual trees with a diameter at breast height (DBH) greater than or equal to 5 cm in 32 permanent plots of 50 m × 50 m. The analysis focused on four spatial structural parameters: uniform angle index, species mingling, height dominance, and crowding. The results showed that (1) the dominant species in the three forest types had a species mingling degree ranging from medium to complete mixture; (2) the target trees were found to have a dominant height compared to their nearest neighbors; (3) the distribution patterns of trees in the stands varied from regular to clumped; and (4) the crowding index indicated a distribution density of trees from sparse to dense. Dispersal limitation and competition among neighboring trees were the main mechanisms driving the forest's spatial structure in the study area. The findings of the present study provide valuable information for proposing silvicultural measures that promote sustainable forest management in Phou Khao Khouay National Park. By understanding the spatial structure of forests, target-tree management can be used to improve forest health, increase biodiversity, and enhance the ecosystem services provided by forests.

Environmental Factors Driving the Spatial Distribution Pattern of Venerable Trees in Sichuan Province, China.

Venerable trees are important natural resources and cultural heritage, offering historical, ecological, social and economic value. However, global warming and anthropogenic activities have threatened their welfare and survival. A comprehensive understanding of their current and future spatial patterns, vis-á-vis environmental conditions, can inform the co-management of sustainable resource use and conservation. We employed the existing spatial occurrence data and environmental variables (bioclimate and elevation) to simulate the optimal habitats for venerable trees in China's Sichuan Province. We evaluated the current and future climate scenarios of 2100 with double CO2 concentration. The BIOCLIM and QGIS spatial analyses assessed the primary factors of geographical distribution. The results identified 10,720 venerable trees from 123 species, 81 genera and 42 families. Cupressus funebris dominated, with the maximum importance value, followed by Ginkgo biloba, Ficus virens var. sublanceolata, and Phoebe zhennan. The elevation distribution of tree abundance and species richness demonstrated a unimodal pattern, skewing to the low-elevation end, with a concentration in the 600-1500 m low-medium altitude. The majority of trees and excellent habitats were found in eastern Sichuan with a less harsh terrain and climate. The bio3 (isothermality) and bio7 (temperature annual range) factors significantly influenced tree occurrence. Temperature imposed a greater effect on distribution than moisture under the current climate scenario. For the future climate-change scenario, the suitable habitats were predicted to maintain an overall stable pattern, with largely contiguous expansions of better habitats. However, climate warming would shrink the excellent habitats on the plains. The findings can inform strategies and guidelines for venerable-tree conservation in Sichuan. Furthermore, vulnerable areas could be identified. The future range expansion sites could be enlisted to cultivate new trees to replenish the venerable-tree pool. Habitat patches that remain sustainable could provide refugia with the potential for protected-area designation.

Enhancing monitoring of mangrove spatiotemporal tree diversity and distribution patterns

AbstractSpatiotemporal information on mangrove species assemblage of natural, disturbed, and rehabilitated is an essential prerequisite for effective strategies for biodiversity conservation and management. However, appropriate field‐based sampling strategies of spatial heterogeneity still hamper the detection of the species distribution and its temporal development. An increasing amount of remote sensing data seems the perfect way to tackle these challenges. With this article, we fill this gap by presenting a review of the challenges and limitations to assess the current status of species diversity. We conclude that species discrimination based on remote sensing techniques is still limited by atmospheric contamination and tidal fluctuations. The lack of accurate information on the spatiotemporal development of species diversity and forest structure further curtails an understanding of functional indicators and the predictive power of modeling approaches. Nevertheless, multi‐source remote‐sensing techniques could seemingly capture the landscape heterogeneity and support systematic sampling designs. Spatially balanced (systematic) training and validation data are necessary to compile robust spatiotemporal information, supporting reliable predictions for optimizing restoration efforts. A systematic sampling of spatiotemporal ecological information is vital to derive the historical state of mangroves, detecting their degradation, and predicting future patterns of species distribution that are generally crucial for restoration, and particularly to rehabilitate species diversity.

Population Structure and Spatial Distribution of Tree Species in Lower Montane Forest, Doi Suthep-Pui National Park, Northern Thailand

Plant diversity is important for sustainable development, particularly in watershed areas. This study explored tree population and diversity in a lower montane forest (LMF). A 16-ha permanent plot was established in LMF at Huai Kogma sub-watershed, northern Thailand. All trees with a diameter at breast height ≥ 2 cm were tagged, measured, identified, and their coordinates were mapped. The results showed that 220 species in 139 genera from 63 plant families were found. The dominant families based on species numbers and tree density were Fagaceae, Lauraceae, and Theaceae. The most dominant species were Castanopsis acuminatissima, Schima wallichii, Castanopsis armata, and Styrax benzoides. Diameter classes for climax species frequently followed negative exponential distributions, indicating their populations could be maintained into the future. By contrast, pioneer species, such as Macaranga indica, Morus macroura, and Rhus javanica, had discontinuous distribution, and were mostly found in gap areas, indicating successful regeneration may require high light intensity. Spatial distribution patterns based on Morisita’s index showed that most of the selected species had clumped patterns, particularly those in the Fagaceae family, which were predominantly distributed along the mountain ridge. Tree distribution patterns can affect ecological dynamics, thus reinforcing patterns dependent on local interactions such as the abundance of and distance to available resources. Our finding can aid evaluations of forest sustainability, and support the biodiversity conservation plans. In particular, the selection of suitable species for LMF restoration programs where mixed plantings of pioneer and climax species are planned.

Differential characteristics and driving forces of the spatial distribution of heritage trees in Luoyang, an ancient capital of China

Heritage trees have important historical, landscape, and ecological value. Exploring the spatial distribution pattern of heritage trees is of great importance to the construction of ecological civilization and the connotation of regional history and culture. This paper took 5,216 heritage trees in Luoyang, an ancient capital of China, as the research object and used geospatial analysis methods and a geographically weighted regression model to analyze the differences and driving forces of the spatial distribution of heritage trees. Results show that 1) the heritage trees in Luoyang were primarily Gleditsia sinensis, Sophora japonica, and Platycladus orientalis, and more than half of these trees were under 300 years old; 2) the high-density area formed a distribution pattern of “three cores, one ring, and two belts,” and the distribution of heritage trees had a positive spatial autocorrelation; 3) different driving factors in different regions had complex influences on the spatial distribution of heritage trees, and the order of influence was as follows: area of forest and orchard land > elevation > number of POIs (points of interest) > distance to the nearest river > slope > number of immovable relics. The results could provide a comprehensive understanding of the spatial distribution of heritage trees to protect the ecological function of heritage trees and mine the cultural value of heritage trees.

Enhancing forest resilience: Advances in Ontario’s wild tree seed transfer policy

Climate is a critical driver in shaping patterns of tree distribution and productivity in Canadian forests. Canada’s climate is changing and, as a result, tree populations may become maladapted to the climate at their current growing locations. In 2020, Ontario updated its tree seed transfer policy to respond to the evolving natural, operational, scientific, and policy environments, including a changing climate. Collaboration among federal and provincial science, operations, and policy staff was essential to update the policy, which involved a custom climate similarity analysis, a related assessment of critical seed transfer distances, various engagement efforts to assess end-user receptivity, and the development of an online interactive tool to allow users to explore seed transfer options under climate change. Here we describe several factors considered during the policy update, major steps in the update process, and highlights of the outcome. The intent of this effort is to support other jurisdictions considering similar changes and to emphasize the need for a changing culture in seed procurement and management.

Spatial Distribution and Species Association of Dominant Tree Species in Huangguan Plot of Qinling Mountains, China

The spatial distribution pattern and population structure of trees are shaped by multiple processes, such as species characteristics, environmental factors, and intraspecific and interspecific interactions. Studying the spatial distribution patterns of species, species associations, and their relationships with environmental factors is conducive to uncovering the mechanisms of biodiversity maintenance and exploring the underlying ecological processes of community stability and succession. This study was conducted in a 25-ha Qinling Huangguan forest (warm-temperate, deciduous, broad-leaved) dynamic monitoring plot. We used univariate and bivariate g(r) functions of the point pattern analysis method to evaluate the spatial distribution patterns of dominant tree species within the community, and the intra- and interspecific associations among different life-history stages. Complete spatial randomness and heterogeneous Poisson were used to reveal the potential process of community construction. We also used Berman’s test to determine the effect of three topographic variables on the distribution of dominant species. The results indicated that all dominant species in this community showed small-scale aggregation distribution. When we excluded the influence of environmental heterogeneity, the degree of aggregation distribution of each dominant species tended to decrease, and the trees mainly showed random or uniform distribution. This showed that environmental heterogeneity significantly affects the spatial distribution of tree species. Dominant species mainly showed positive associations with one another among different life-history stages, while negative associations prevailed among different tree species. Furthermore, we found that the associations between species were characterized by interspecific competition. Berman’s test results under the assumption of complete spatial randomness showed that the distribution of each dominant species was mainly affected by slope and convexity.

Neighbours consistently influence tree growth and survival in a frequently burned open oak landscape

Abstract Successful management of fire‐prone woody ecosystems is challenging and requires knowledge of the spatial arrangement of the trees and how the tree distribution patterns influence the nature and consequences of subsequent fires. In open tree landscapes, trees are often aggregated, and the ability of trees within the clumps to survive fires plays a significant role in determining subsequent landscape dynamics. If positive interactions exist among neighbouring trees, this will help maintain the patterns of clumped trees. However, the tree‐aggregated landscape will continue to exist only if the positive neighbour interactions persist consistently over time. In cases where disturbances are episodic, detecting these interactions is only possible through long‐term studies. Data reported here are from a 25‐year study involving the annual tree censusing of a large grid‐plot in a frequently burned open oak landscape dominated by Quercus macrocarpa and Quercus ellipsoidallis. The results showed that while having neighbours reduced tree growth, neighbours consistently facilitated survival, irrespective as to whether the neighbours were conspecifics or heterospecifics. Trees of all sizes in close proximity to neighbours were considerably more likely to survive fire throughout the study. This neighbour facilitation is likely the result of a reduction of both herbaceous and woody fuel within clumps. Synthesis. This is the first study to document consistent neighbour facilitation among trees experiencing repeated stressors over an extended time period. Our findings support the literature documenting positive neighbour effects among plants in stressful and highly disturbed environments, in accordance with the stress‐gradient hypothesis. While aggregated tree regeneration is typically viewed as the primary cause for the development of tree clumps in fire‐prone ecosystems, our study showed that aggregated tree survival, by itself, can also be an important driver of post‐fire tree clumping. Our results support the growing literature emphasizing the importance of landscape heterogeneity as a driver of resilience in fire‐prone tree ecosystems, and the value of maintaining or creating this heterogeneity during forest management.