Tree Species Groups Research Articles

Ornithogalum boucheanum (Asparagaceae) in Eastern Europe: Native and synanthropic range, habitat conditions and state of population

The geographical distribution, ecological and coenotic features of the place of growth and age structure of Ornithogalum boucheanum populations in Ukraine have been studied. In total, during the entire period of floristic research in Ukraine, 263 native sites of this species were recorded in 13 administrative regions (oblasts). Mostly these sites are concentrated in the Steppe zone, where the main part of the Eastern European fragment of the general natural range of O. boucheanum is represented. For other regions of Ukraine isolated reports of the species are known. It is noted that in addition to reduction in the number of natural habitats of O. boucheanum within the Forest-Steppe and in the southern part of Ukraine Polissya, a secondary adventive natural habitat of the species is formed, where it is part of the immigration group of foreign taxa. It was found that the natural habitats of O. boucheanum are characterized by a certain stenotopy, as the species needs some moisture and is more common in valley and balka landscapes most often in large river basins, which are not prone to drying out and can be favourable ecological corridors for long-distance migration. Favourable conditions for O. boucheanum habitats exist in floodplain and riparian forests, which have sufficient moisture, little competition from other species of grass and a sufficient amount of light in the spring. In addition, O. boucheanum can successfully master artificial and synanthropic groups of tree species, in particular being widespread in the Forest-Steppe and Steppe Robinia plantations. It was found that populations of O. boucheanum in Ukraine have different numbers: with an area of 4–6 hectares, in which there are tens and hundreds of thousands of individuals, to small populations on the northern border of distribution, in Kirovohrad and Kharkiv oblasts, which have a of young invasive character. It is possible that modern conditions have been favourable for the spread of O. boucheanum in the transition zone between the Forest-Steppe and Steppe, and that the process of forming new populations of O. boucheanum is taking place here.

A new strategy for improving the accuracy of forest aboveground biomass estimates in an alpine region based on multi-source remote sensing

ABSTRACT Spatially explicit information on the distribution of dominant tree species groups and aboveground biomass (AGB) in forested areas is essential for developing targeted forest management and biodiversity conservation measures, as well as assessing forest carbon sequestration capacity. There is a shortage of continuously updated 30-m spatial resolution products for mapping dominant tree species groups. The vast majority of remote sensing-based AGB estimation approaches have relatively low accuracy for dominant tree species groups or forest types and are unsuitable for AGB modeling. Therefore, this study aims to develop an integrated framework that considers the phenological characteristics of different tree species to improve the mapping accuracies of forest dominant tree groups and corresponding AGB estimates. Thirty-meter resolution maps of dominant tree species groups were created using machine learning algorithms and phenological parameters. Features extracted from optical and radar images and phenological characteristics were used to construct AGB estimation models in a temporally consistent manner to improve the AGB estimation accuracy and perform dynamic AGB monitoring. The proposed method accurately characterized the dynamic distribution of the dominant tree species groups in the study area. The traditional AGB model that does not consider different forest types or species had an R2 value of 0.52, whereas the proposed model that considers phenology and forest types had an R2 value of 0.67. This result indicates that incorporating information on phenology and dominant species improves the accuracy of AGB estimations. The AGB in most regions was 30–55 t/ha, showing that the majority of the forests were young or middle-aged stands, and the areal percentage of AGB greater than 30 t/ha increased during the study period, suggesting an improvement in forest quality. Furthermore, the oak AGB was the highest, indicating that oak afforestation should be encouraged to enhance the carbon sequestration capacity of future forest ecosystems. The results provide new insights for researchers and managers to understand the trends of forest development and forest health, as well as technical information and a database for formulating more rational forest management strategies.

Fire and tree species diversity in tropical peat swamp forests

Tropical peat swamp forests contain diverse plant communities that support many endangered flora and fauna species. These forests are increasingly threatened by disturbances such as drainage, logging, and subsequent fire, yet little is known about tree species recovery from these threats.Tree species richness and diversity were measured in peat swamp forests of Central Borneo regenerating naturally after fires from 139 chronosequence plots. Our findings indicated that two to three decades after fire, similar levels of richness and diversity to relatively undisturbed reference forest are reached within sites. However, when averaged across landscapes our modelling shows that fires of average frequency of 50 years, or even 100 years, can substantially suppress tree species richness and diversity. Thus, even rare fires can reduce the species richness and diversity of tropical peat swamp forests.Two groups of tree species drove the difference in richness and diversity between disturbed and reference forests: ‘decreasers’, occupying recently burnt forest and declining with fire exclusion, and ‘increasers’, that were only present in less disturbed forests and absent or rare in recently burnt forests. The decreasers were more common than the increasers.We conclude that peat swamp forests can recover adequately from fires through natural regeneration, and it is possible that artificial planting may speed up this process. Where possible, excluding fire from tropical peat forests will help to maintain the diversity of these threatened ecosystems and promote their recovery.

Are allometric model parameters of aboveground biomass for trees phylogenetically constrained?

Knowledge of which biological and functional traits have, or lack, phylogenetic signal in a particular group of organisms is important to understanding the formation and functioning of biological communities. Allometric biomass models reflecting tree growth characteristics are commonly used to predict forest biomass. However, few studies have examined whether model parameters are constrained by phylogeny. Here, we use a comprehensive database (including 276 tree species) compiled from 894 allometric biomass models published in 302 articles to examine whether parameters a and b of the model W=aDb (where W stands for aboveground biomass, D is diameter at breast height) exhibit phylogenetic signal for all tree species as a whole and for different groups of tree species. For either model parameter, we relate difference in model parameter between different tree species to phylogenetic distance and to environmental distance between pairwise sites. Our study shows that neither model parameter exhibits phylogenetic signals (Pagel's λ and Blomberg's K both approach zero). This is the case regardless of whether all tree species in our data set were analyzed as a whole or tree species in different taxonomic groups (gymnosperm and angiosperm), leaf duration groups (evergreen and deciduous), or ecological groups (tropical, temperate and boreal) were analyzed separately. Our study also shows that difference in each parameter of the allometric biomass model is not significantly related to phylogenetic and environmental distances between tree species in different sites.

Mapping Dominant Boreal Tree Species Groups by Combining Area-Based and Individual Tree Crown LiDAR Metrics with Sentinel-2 Data

Airborne light detection and ranging (LiDAR) data are increasingly used to inform sustainable forest management practices. Information about species composition is needed for a range of applications; however, commonly used area-based summaries of LiDAR data are limited to accurately differentiate tree species. The objective of this study was to map dominant species groups across a large (>580,000 ha) boreal forest by combining area-based and individual tree metrics derived from single photon LiDAR data with multispectral information derived from Sentinel-2 imagery. Classification of the forest into jack pine (Pinus banksiana), black spruce (Picea mariana), mixed conifer, mixedwood, and hardwood species groups resulted in an overall accuracy of 67.8% compared with field data. A more generalized classification into softwood, hardwood, and mixedwood had an overall accuracy of 83.2%. The reflectance in the red edge region of the electromagnetic spectrum (λ = 740 nm), the area and volume of tree crowns, and the cumulative distribution of LiDAR returns in the canopy were particularly important variables to discriminate between species groups. Wall-to-wall predictions of species groups based on remotely sensed data—as derived herein—could provide a spatially-detailed alternative to stand-level species composition information traditionally derived from photo-interpreted aerial imagery.

Modelling tree diameter of less commonly planted tree species in New Zealand using a machine learning approach

Abstract A better understanding of forest growth and dynamics in a changing environment can aid sustainable forest management. Forest growth and dynamics data are typically captured by inventorying a large network of sample plots. Analysing these forest inventory datasets to make precise forecasts on growth can be challenging as they often consist of unbalanced, repeated measures data collected across large geographic areas with corresponding environmental gradients. In addition, such datasets are rarely available for less commonly planted tree species, and are often incomplete and even more unbalanced. Conventional statistical approaches are not able to deal with such datasets and identify the different factors that interactively affect forest growth. Machine learning approaches offer the potential to overcome some of the challenges with modelling complex forest dynamics in response to environmental and climatic factors, even with unbalanced inventory data. In this study, we employed a widely used machine learning algorithm (random forests) to model individual tree diameter at breast height (DBH, 1.4 m) in response to age, stocking, site and climatic factors for the following five less commonly planted tree species groups in New Zealand: Cupressus lusitanica (North Island); Cupressus macrocarpa (South Island); Eucalyptus nitens; Sequoia sempervirens; Podocarpus totara; and Leptospermum scoparium. Data to build machine learning models were extracted and combined from three national level databases, and included stand variables, information about sites and climate features. The random forest models were able to predict tree DBH with high precision for the five-tree species (R2 > 0.72 and root-mean-square error ranged from 2.79–11.42 cm). Furthermore, the random forest models were interpretable and allowed us to explore the effects of site, environmental and climate factors on forest growth. To our knowledge, this is the first attempt to utilize machine learning approaches to model tree diameter of less common planted forest tree species in New Zealand. This approach can be used to forecast more precise forest growth and carbon sequestration to help us understand how different forest types and species are affected by the changing climate.

Gene expression and genetic divergence in oak species highlight adaptive genes to soil water constraints.

Drought and waterlogging impede tree growth and may even lead to tree death. Oaks, an emblematic group of tree species, have evolved a range of adaptations to cope with these constraints. The two most widely distributed European species, pedunculate (PO; Quercus robur L.) and sessile oak (SO; Quercus petraea Matt. Lieb), have overlapping ranges, but their respective distribution are highly constrained by local soil conditions. These contrasting ecological preferences between two closely related and frequently hybridizing species constitute a powerful model to explore the functional bases of the adaptive responses in oak. We exposed oak seedlings to waterlogging and drought, conditions typically encountered by the two species in their respective habitats, and studied changes in gene expression in roots using RNA-seq. We identified genes that change in expression between treatments differentially depending on species. These "species × environment"-responsive genes revealed adaptive molecular strategies involving adventitious and lateral root formation, aerenchyma formation in PO, and osmoregulation and ABA regulation in SO. With this experimental design, we also identified genes with different expression between species independently of water conditions imposed. Surprisingly, this category included genes with functions consistent with a role in intrinsic reproductive barriers. Finally, we compared our findings with those for a genome scan of species divergence and found that the expressional candidate genes included numerous highly differentiated genetic markers between the two species. By combining transcriptomic analysis, gene annotation, pathway analyses, as well as genome scan for genetic differentiation among species, we were able to highlight loci likely involved in adaptation of the two species to their respective ecological niches.

Community structure of phyllosphere fungi associated with dominant tree species in a broad-leaved Korean pine forest of Changbai Mountain, Northeast China

Forest is the main component of terrestrial ecosystems that harbors about 40% of the existing species on the earth. As a vital component of biodiversity, phyllosphere microbes in the canopy play a critical and unique role in maintaining plant health, improving host resistance, and influencing global biogeochemical cycle. However, the studies on the community structure of phyllosphere fungi in natural forests are scarce as compared to that on rhizosphere microbes. Consequently, we know litter about how phyllosphere fungi associates with leaf traits. In this study, we analyzed fungal community composition of canopy leaves of six dominant tree species (i.e., Pinus koraiensis, Tilia amurensis, Quercus mongolica, Acer mono, Fraxinus mandshurica, and Ulmus japonica), in a broad-leaved Korean pine forest of Changbai Mountain Nature Reserve in Jilin Province, using high-throughput sequencing. We compared the differences of phyllosphere fungal community structure and functional groups of different dominant tree species. Moreover, 14 key leaf functional traits of their host trees were measured to investigate the relationships between fungal community composition and leaf functional traits. We found that the dominant phyla and class of phyllosphere fungi were Ascomycota and Basidiomycota, and Dothideomycetes and Taphrinomycetes, respectively. Results of LEfSe analysis indicated that all the tree species except Ulmus japonica had significant biomarkers, such as the Eurotiomycetes of Pinus koraiensis and the Ascomycetes of Quercus mongolica. The main functional groups of phyllosphere fungi were pathotroph. The results of redundancy and envfit analysis showed that functional traits related to plant nutrient acquisition as well as resistance to diseases and pests were the main factors influencing the community structure of phyllosphere fungi.

Bryophytes of conservation concern decline and traits change in retention patches during two decades following forest harvest

Setting aside tree retention patches at final harvest is a common forest conservation measure, but the long-term responses of species of conservation concern to different types of forest retention remain unknown. This is the first long-term study of the dynamics of bryophytes of conservation concern and associated traits in small forest retention patches (0.01–0.53 ha) over almost two decades and in relation to environmental drivers. We applied joint species distribution models to compare how bryophytes changed in terms of occurrence, abundance, species richness and traits between year 2000, 2006 and 2018, and in relation to five different retention patch types, patch area, retained living tree volume per hectare, structural heterogeneity, and surrounding habitat openness. Bryophytes responded mostly negatively to the long-term environmental change, although with considerable variation depending on retention patch type. Only negative trends were detected for individual species. Still, no regional extinctions (loss of species from all local patches) occurred and there was a tendency for recovery of a few species. Bryophytes with predominantly asexual reproductive modes and small colony size (<100 cm2) increased in occurrence probability over time, indicating that these traits were beneficial for the long-term persistence of species in small and exposed forest patches. We recommend forest managers to create large (preferably up to 0.5 ha) and variable retention patches, both in terms of patch type (i.e. buffer zones and free-standing groups of different dominant tree species and ground moisture) and structural heterogeneity (i.e. living tree volumes, large and small trees, and deadwood).

Defining functional groups of tree species according to rural stakeholder perceptions in Central Mali

In the dry areas of western Africa, the over-exploitation of forestry resources and the lack of tree regeneration lead to the degradation of agroforestry parklands. Such parklands could be better managed if the multiple services provided by the trees were well identified and valorized. However, there is little information on the local knowledge of' tree species regarding their functions, uses and services. Likewise, local stakeholders' perceptions of the relation between the species aptness for the above functions and uses and their functional traits is not well known. This study focuses on local knowledge of tree species in parklands of the Segou region in Mali, in order to identify specific uses or multifunctionalities that could be highlighted in improving agroforestry systems. Qualitative surveys have been carried out to identify users' perceptions of tree functions and functional traits. Findings show the possibility of classifying species by relevant functional groups, i.e. woody/timber trees, fruit/cash crop trees and trees related to livestock. Functional traits were not easily identified by farmers and the related information was difficult to analyze. Moreover, the perception of functions and traits depended on user groups (craftsmen, crop farmers, livestock farmers, traditional health practitioners, women etc.) and on agro-environmental and socio-economic contexts (activities, knowledge, means and practices). Therefore, scientific databases composed of lists of functions and traits for a given species have no generic value and must be valued depending on the context which may or may not enhance the substitutions between species for each use.

Comparison of Variable Selection Methods among Dominant Tree Species in Different Regions on Forest Stock Volume Estimation

The forest stock volume (FSV) is one of the crucial indicators to reflect the quality of forest resources. Variable selection methods are usually used for FSV estimated models. However, few studies have explored which variable selection methods can make the selected data set have better explanatory and robustness for the same dominant tree species in different regions after the feature variables were filtered by the feature selection methods. In this study, we chose six dominant tree species from Lin’an District, Anji County, and a part of Longquan City. The tree species include broad-leaved, coniferous, Masson pine, Chinese fir, coniferous and broad-leaved mixed forest, and all tree species which include the above five groups of tree species. The last two tree species were represented by mixed and all, respectively. Then, the satellite images, terrain factors, and forest inventory data were selected by six variable selection methods (least absolute shrinkage and selection operator (LASSO), recursive feature elimination (RFE), stepwise regression (Step-Reg), permutation importance (PI), mean decrease impurity (MDI), and SelectFromModel based on LightGBM (SFM)), according to different dominant tree types in different regions. The selected variables were formed into a new dataset divided by different dominant trees. Besides, extreme gradient boosting (XGBoost) was used, combined with variable selection methods to estimate the FSV. The performed results are as follows: In the feature selection of coniferous, RFE performed better both in the average and in the separate regions. In the feature selection of Chinese fir and all, PI performed better both in the average and in the separate regions. In the feature selection of Masson pine, MDI performed better both in the average and in the separate regions. In the feature selection of mixed, MDI performed better in the average while RFE performed better in the separate regions comprehensively. The results showed that not only in separate regions, but the average result two factors, RFE, MDI, and PI all performed well to select variables to estimate the FSV. Furthermore, we selected the top five high feature-importance factors of different tree types, and the results showed that tree age and canopy density were both of great importance to the estimation of FSV. Besides, in the exhibited results of feature selection methods, compared with no variable selection, the research also found that variable selection can improve the performance of the model. Additionally, from the results of different tree types in different regions, we also found that small-scale and diversity of dominant tree types may lead to the instability and unreliability of experimental results. The study provides some insight into the application the optimal variable selection methods of the same dominant tree type in different regions. This study will help the development of variable selection methods to estimate FSV.

Correcting the Results of CHM-Based Individual Tree Detection Algorithms to Improve Their Accuracy and Reliability

Individual tree detection algorithms (ITD) are used to obtain accurate information about trees. Following the process of individual tree detection, it is possible to use additional processing tools to determine tree parameters such as tree height, crown base height, crown volume, or stem volume. However, many of the methods developed so far have focused on parameterising the algorithms based on the study area, height structure or tree species analysed. Applying the parameters of the method can be challenging in areas with dense and heterogeneous forests with a diverse stand structure. Therefore, this work aimed to develop a method to correct the results of ITD algorithms to identify individual trees more reliably, taking into account different ITD methods based on the Canopy Height Model. In the present study, we proposed a three-step approach to correct segmentation errors. In the first step, erroneous (under- and over-segmentation errors) and correct segments were classified. After classification, the second step was to refine the under-segmentation errors. The final step was to merge segments from the over-segmentation class with correct segments based on the specified conditions. The study was conducted in one of the most complex and diverse forest communities in Europe, making tree identification a major challenge. The accuracy of the segmentation improvements varied depending on the method applied and tree species group examined. Thus, based on the results, the paper advocates for the correction method due to its efficiency in mixed forest stands. Therefore, the present study offers a possible solution to reduce segmentation errors by considering different forest types and different CHM-based ITD methods for identifying individual trees.

The Effect of Stand Density, Biodiversity, and Spatial Structure on Stand Basal Area Increment in Natural Spruce-Fir-Broadleaf Mixed Forests

Forest trees exhibit a large variation in the basal area increment (BAI), and the variation is attributed to the stand density, biodiversity, and stand spatial structure. Studying and quantifying the effect of these above variables on tree growth is vital for future forest management. However, the stand spatial structure based on neighboring trees has rarely been considered, especially in the mixed forests. This study adopted the random-forest (RF) algorithm to model and interpret BAI based on stand density, biodiversity, and spatial structure. Fourteen independent variables, including two stand density predictors, four biodiversity predictors, and eight spatial structure predictors, were evaluated. The RF model was trained for the whole stand, three tree species groups (gap, neutral, and shade_tolerant), and two tree species (spruce and fir). A 10-fold blocked cross-validation was then used to optimize the hyper-parameters and evaluate the models. The squared correlation coefficients (R2) for the six groups were 0.233 for the whole stand, 0.575 for fir, 0.609 for shade_tolerant, 0.622 for neutral, 0.722 for gap, and 0.730 for spruce. The Stand Density Index (SDI) was the most-important predictor, suggesting that BAI is primarily restricted by competition. BAI and species biodiversity were positively correlated for the whole stand. The stands were expected to be randomly distributed based on the relationship between the uniform angle index (W) and growth. The relationship between dominance (U) and BAI indicated that small trees should be planted around the light-demanding tree species and vice versa. Of note, these findings emphasize the need to consider the three types of variables in mixed forests, especially the spatial structure factors. This study may help make significant advances in species composition, spatial arrangement, and the sustainable development of mixed forests.

Urbanization intensifies tree sap flux but divergently for different tree species groups in China.

In recent years, positive and negative effects of urbanization on forest ecosystem have been reported by many studies, while some uncertainties about the impact of urbanization-induced spatial heterogeneity of environmental factors on forest systems still remain unclear. In this study, we analyzed the urbanization effects on sap flux of a common subtropical evergreen tree species Schima superba along an urban-rural gradient in Guangdong Province, South China, and identified the consistency of these results among different groups (evergreen, deciduous, and coniferous species) using data from 83 previously published studies in China. The mean sap flux density (Fd) of S. superba in Xiaoqingshan (XQS), Heshan (HS), Dinghushan (DHS), and Shimentai (SMT), along the urban-rural gradient was 40.9gm-2s-1, 32.1gm-2s-1, 17.0gm-2s-1, and 17.5gm-2s-1, respectively, presenting a decreasing trend with the diminishing urbanization. This pattern in Fd tended to enlarge with tree size and was well confirmed by the enhanced leaf transpiration rate (by 119%) and photosynthetic rate (by 8.8%) for the S. superba in another urbanization gradient from the urban (Hangzhou, denoted as "HZ") to rural sites (Jiande, denoted as "JD") in Zhejiang Province, East China, which has similar climatic condition and urbanization with Guangdong Province. We attributed such positive effects to the decreased sapwood density and specific leaf area (SLA), as well as the increased Huber value (sap wood area/leaf area) and the sap wood specific hydraulic conductivity (KS). We also found that pollutant emission exerted more impact on Fd than climatic factors change, since the variation of the latter was not large enough to cause significant change of Fd under the same climatic zone. In addition, we conducted a principal component analysis (PCA) based on the published 83 studies. Results showed Fd of evergreen tree species was related positively to principle 1 and negatively to principle 2, respectively, whereas the Fd of deciduous broadleaf and coniferous tree species was positively and negatively related to both principles, respectively. This study demonstrated the potential impact of urbanization-related pollutant emission changes on water use of forest trees and the growth among different groups.

特大干旱对树木死亡的影响——以美国德克萨斯州东部森林为例

美国德克萨斯州在2011年经历了史上最严重的干旱，这一事件造成约3亿多株树木死亡。在大时空尺度上（面积约9×10⁶ hm²，时间跨度近20年），基于近1800个森林样地，4次周期性调查中的约209663株树木，使用主成份分析（PCA）和广义线性混合效应模型（GLM）回归，对树木死亡的时空差异及其干旱强度与长度对树木死亡造成的中长期复杂影响进行了研究。采用树木密度、树木基面积、林地年龄、样地调查时间间隔作为树木间的竞争指标，分析了造成大旱前后周期水平和年度水平上的样地树木死亡差异的原因。综合分析了不同地理区域、树木种组、胸径大小和林地起源的4个划分标准下树木死亡对死亡率的相对贡献。结果表明：松属树木的死亡率最低（7.92%）；高度低、胸径小的树木的死亡率较大，分别为29.79%和26.00%。人工林的树木死亡率（10.26%）低于天然林（13.47%）；西海湾平原生态区树木的死亡率在干旱后达到最大（22.27%）；西南区的树木死亡率在干旱后也达到最大（13.78%）；海拔和纬度对树木死亡率影响不明显。德州东部森林整体死亡格局形成原因较为复杂，各地理区域、林地起源、树木大小和不同树种，对森林死亡的贡献率各不相同。四个区域中死亡贡献率较大的为天然林；无论是天然林还是人工林，其死亡贡献率最大的为小树；干旱对天然林的影响比人工林更显著；天然林和人工林中死亡贡献率情况各不相同，在天然林中松属和枫香属树种死亡贡献率低于人工林，其他种则是人工林高于天然林。林地密度和树木死亡的回归分析表明二者之间无显著关系。PCA结果显示干旱对树木死亡影响大于树木竞争和其它自然干扰的影响，干旱强度和干旱长度对树木死亡的影响基本相当。;In 2011, Texas experienced the most severe drought in its 100 years history, resulting in the death of more than 300 million trees. On a large spatial and temporal scale (an area of 9×10⁶ ha, a time span of nearly 20 years), this study is based on 1800 forest plots, with about 209,663 trees from four periodic surveys. This study utilized Principal component Analysis (PCA) and Generalized Linear Models (GLM) to characterize the spatio-temporal difference of tree mortality and drought severity and length effects. The causes of the differential tree mortality at cycle and annual level before and after the 2011 drought were analyzed using tree density, basal area, stand age, and survey interval as the competition indexes among trees. The relative contribution of tree death to mortality was analyzed according to four classification criteria, geographic region, tree species group, tree sizes (height and diameter at breast height-DBH) and forest stand origin. The results showed that the Pinus trees suffered the least, with a mortality rate of 7.92%. The mortality rates of trees with low height and small DBH were 29.79% and 26.00%, respectively. Natural forest trees witnessed a higher mortality rate (13.47%) than plantation forests (10.26%). The mortality rate of trees in the Western Gulf Coastal Plains ecological region and southwest region reached the highest after drought with a mortality rate of 22.27% and 13.78%. The effects of elevation and latitude on tree mortality were not apparent. The causes of overall tree mortality patterns in eastern Texas are complex, and differential mortality rates were observed across geographical regions, stand origin, tree sizes and different tree species. Among the four regions, the natural forest had a higher death contribution rate. Small trees contributed the most to the death in both natural and plantation forests. The effect of drought on the natural forest was more significant than that on plantation forests. The death contribution rates in natural forests and plantation forests are different. In the natural forests, the death contribution rates of Pinus and Liquidambar species were lower than those in the plantations. Regression analysis of forest density and tree mortality did not show a significant statistical relationship between them, suggesting tree mortality was triggered by density-independent factors. The results of PCA showed that the effect of drought on tree mortality was greater than that of tree competition and other natural disturbances, and the effect of drought severity and drought length on tree death was similar.

The structure of Leguminosae-Detarioideae dominant rain forest in Korup National Park, Cameroon

Background and aims – We studied a cluster of trees in the Leguminosae subfamily Detarioideae, to: (1) determine the size, structure, and tree species composition of this cluster; (2) map the size, shape, and structure of groups of individual Detarioideae tree species in the cluster.Location – Lowland rain forest in southern Korup National Park, in the Southwest Region of Cameroon.Material and methods – Trees in permanent plots were recorded using standard plot enumeration techniques. Outside plots, single-species tree groups were recorded by a rapid technique. From this data, detailed maps of groups of trees were prepared.Key results – Detarioideae tree species occur co-dominant in a cluster of at least 32 km2 with an irregular shape. The cluster contained at least 42 Detarioideae tree species; at least 29 of these occurred in groups ranging in size from 50 to 4000 m across, depending on the species. Groups usually had circular shapes, caused by ballistic seed dispersal. In a group, trees were always mixed with trees of several other Detarioideae species. Every area within the cluster contained a specific set of Detarioideae species. The percentage of Detarioideae trees ≥ 60 cm stem diameter on 50 ha was up to 76% in Detarioideae-rich forest, to 6% in Detarioideae-poor forest. Of all trees in the centre of the cluster, 2.8% belonged to pioneer forest species, which indicates that disturbance levels were low during the past generations of trees.Discussion – The forests in the Detarioideae cluster have not been subject to substantial human and natural impacts in historic or prehistoric times. Such forests are exceptional in Africa. Detarioideae clusters may indicate glacial age forest refuges, especially clusters that contain both many different Detarioideae species and some Detarioideae species endemic to the cluster.

Factors influencing the rate of formation of tree‐related microhabitats and implications for biodiversity conservation and forest management

Abstract The retention of trees bearing tree‐related microhabitats (TreMs) has become an important means of conserving biodiversity in production forests. However, we lack estimates of TreM formation rates and evidence on factors driving TreM formation. Based on the observation of 80,099 living trees from 19 species groups in Europe and Iran, we estimated the probability of TreM occurrence on trees and the associated rate of first TreM formation as a function of tree DBH, management, tree species group and random site effects. We built a separate model for each of 11 TreM groups. The hazard rate of first TreM formation (defined as the probability of formation of a first TreM forming on a tree that is known to have none, during an infinitesimal DBH increment) increased with DBH for some TreM groups like breeding‐woodpecker‐hole, rot‐hole or root‐concavity, indicating an acceleration in TreM formation during tree growth. However, it decreased with DBH for TreM groups like bark‐loss or dendrotelm, indicating slower formation on very large trees. Most TreM groups had reduced formation rates in managed forests (last logging less than 100 years ago) compared to unmanaged forests (no logging for at least 100 years), with the exception of dendrotelms. No general difference appeared between broadleaves and conifers, but early‐successional species tended to have different TreMs than mid‐ and late‐successional species. Abies, Alnus, Betula, Fagus, Prunus, Quercus, Sorbus, Tilia and Ulmus displayed high formation rates for six TreM groups or more. Variability among sites was considerable. Synthesis and applications. The rate of formation of tree‐related microhabitats (TreMs) varies greatly among TreM groups, tree species, locations, tree diameters at breast height and forest management. The high rate of formation of some TeM groups on small trees implies that tree retention for biodiversity should concern trees of all sizes and start as soon as thinning operations have occurred. Biodiversity conservation should value not only forest stands and trees that already have many TreMs but also those where the likelihood of future TreM formation is high due to species, maturity or local environmental conditions. The addition of quantitative models of TreM formation to forest stand dynamics simulators is necessary to better take into account biodiversity conservation in forest management.

The relationship between resource abundance and insect herbivory on islands.

We examined the relationship between resource abundance and the feeding activity of phytophagous insects on three common island plants. The aim was to investigate the correlation between phytophagous insects' abundance and availability of food and island geography. We collected 30,835 leaves from three tree species groups (Mallotus japonicus, Prunus species, and Quercus species) on 18 islands in southwest Korea. The number of plant resources for herbivores varied: the number of leaves per shoot was the highest in Mallotus, leaf weight and the water content per leaf was significantly lower in Quercus species. External feeding was higher for Prunus and Quercus species, whereas the internal feeding type was significantly higher for Quercus species. Geography (area and distance), elevation and food resource (elevation, number of plant species, and the forest cover rate) had a variable effect on phytophagous insects feeding activities: distance and the number of plant species were more explainable to the external feeding guild. In contrast, area and forest cover were more to the internal feeding guild.

Farm Rejuvenation-Induced Changes in Tree Spatial Pattern and Live Biomass Species of Cocoa Agroforests in Central Cameroon: Insights for Tree Conservation Incentives in Cocoa Landscapes

Cocoa agroforests sustain ecosystem services (ESs) to varying degrees. These services are otherwise mostly provided by other non-cocoa shade or companion trees. However, the density of shade trees is associated with services and/or disservices that drive farm-specific tree management successions. Considering the growing impacts of climate crisis on farm productivity and the need for adaptation strategies, the ESs are increasingly provisional and contingent on the prevailing vegetation, land tenure, and management successions, amongst others social and ecological factors. To assess the temporal changes in shade management, we surveyed an age gradient of “family farms” in cocoa agroforests created from forest (fCAFS) and savannah (sCAFS) land cover. We evaluated the temporal changes in farm structure, relative tree abundance, and live aboveground biomass of the major canopy strata. We used a spatial point process and linear mixed effect analysis to assess the contributions of associated perennial trees (AsT) on farm rejuvenation patterns. The density of cocoa trees was inconsistent with farm age; this was significantly high on farms in sCAFS (1544 trees ha−1) with spatially random configuration across farm age. On farms in fCAFS, we observed a transition of the cocoa tree configuration in the order regular, random, and clustering from young (with highest density of 1114 trees ha−1) to old farms. On a temporal scale, there is no clear distinction of farm structure and biomass between fCAFS and sCAFS. However, the cycle of tree species and structural composition of the canopy strata are dissimilar; the live biomass allocation for the considered use groups of tree species was different with farm age. The observed dynamics in canopy tree structure and live biomass provide insights into farmers’ temporal allocation of uses and prioritization of different tree species with farm age. We recommend the consideration of such landscape-specific, tree management dynamics in proposing on-farm tree conservation incentives. Our results are also conducive to reliable estimates of the ecosystem services from CAFS in the national implementation of conservation mechanisms such as REDD+.

What level of native beetle diversity can be supported by forestry plantations? A global synthesis

AbstractForestry plantations have been established globally to meet timber demands, often leading to the conversion of natural to artificial forests. Forestry plantations may support natural elements of forest biodiversity, but understanding their role in the maintenance of biodiversity is a crucial question.We performed a meta‐analysis of 48 studies to determine how forestry plantations relative to natural forests influence the species richness and abundance of three important coleopteran groups (i.e., ground beetles, rove beetles, and dung beetles), given their essential role in ecosystem functioning.We assessed whether beetle responses depended on taxonomic group, geographical location, native or exotic character of the planted tree species, and associated management characteristics (i.e., composition, size, age, and connectivity of the plantations).We found that forestry plantations negatively affected coleopteran species richness and abundance compared to natural forests. The negative impact was most severe in plantations with exotic tree species and located in tropical biomes.Species richness and abundance of beetles significantly increased with plantation age in native plantations but decreased in exotic ones. Also, small plantations close to native forest had higher beetle species richness and abundance than ones located far away from native forest.Stopping the conversion of natural forests to plantations, promoting the use of native tree species, and lengthening rotations are critical for allowing biodiversity recovery in forestry plantations, combined with a robust conservation strategy to protect threatened biodiversity and ecosystem functioning.