Leaf nutrient traits of planted forests demonstrate a heightened sensitivity to environmental changes compared to natural forests

Leaf nutrient content (nitrogen, phosphorus) and their stoichiometric ratio (N/P) as key functional traits can reflect plant survival strategies and predict ecosystem productivity responses to environmental changes. Previous research on leaf nutrient traits has primarily focused on the species level with limited spatial scale, making it challenging to quantify the variability and influencing factors of forest leaf nutrient traits on a macro scale. This study, based on field surveys and literature collected from 2005 to 2020 on 384 planted forests and 541 natural forests in China, investigates the differences in leaf nutrient traits between forest types (planted forests, natural forests) and their driving factors. Results show that leaf nutrient traits (leaf nitrogen content (LN), leaf phosphorus content (LP), and leaf N/P ratio) of planted forests are significantly higher than those of natural forests (P< 0.05). The impact of climatic and soil factors on the variability of leaf nutrient traits in planted forests is greater than that in natural forests. With increasing forest age, natural forests significantly increase in leaf nitrogen and phosphorus content, with a significant decrease in N/P ratio (P< 0.05). Climatic factors are key environmental factors dominating the spatial variability of leaf nutrient traits. They not only directly affect leaf nutrient traits of planted and natural forest communities but also indirectly through regulation of soil nutrients and stand factors, with their direct effects being more significant than their indirect effects.

Climate factors affect forest biomass allocation by altering soil nutrient availability and leaf traits

Biomass in forests sequesters substantial amounts of carbon; although the contribution of aboveground biomass has been extensively studied, the contribution of belowground biomass remains understudied. Investigating the forest biomass allocation is crucial for understanding the impacts of global change on carbon allocation and cycling. Moreover, the question of how climate factors affect biomass allocation in natural and planted forests remains unresolved. Here, we addressed this question by collecting data from 384 planted forests and 541 natural forests in China. We evaluated the direct and indirect effects of climate factors on the belowground biomass proportion (BGBP). The average BGBP was 31.09% in natural forests and was significantly higher (38.75%) in planted forests. Furthermore, we observed a significant decrease in BGBP with increasing temperature and precipitation. Climate factors, particularly those affecting soil factors, such as pH, strongly affected the BGBP in natural and planted forests. Based on our results, we propose that future studies should consider the effects of forest type (natural or planted) and soil factors on BGBP.

Vascular plant taxa occurrences in exotic woodland and in natural and production forests on the Islands of São Miguel, Terceira and Pico (Azores)

Background

The data presented here originated from field expeditions carried out between 2017 and 2018, within the framework of Forest-Eco2 project: "Towards an Ecological and Economic valorisation of the Azorean Forest". The project aimed to quantify the ecological value of the Azorean forests, including carbon accumulation and to design and propose measures that could further enhance forest sustainability. For that, 90 forest plots were sampled on three Azores islands - São Miguel, Terceira and Pico - equally distributed into natural forest, exotic woodland and production forest. The aim of this report is to further expand knowledge on biodiversity trends enclosed in the different forest types present in the Azores, by providing a list of the occurrences of the 105 different vascular plant taxa together with a brief characterisation of their origin and life-form.

New information

We provide an inventory of indigenous and non-indigenous vascular plant taxa from 90 forest stands. A total of 105 taxa were identified and registered, belonging to 60 families, 91 genera, 101 species and four subspecies. A total of 35% of the taxa were endemic, 27% native and 38% non-indigenous, including 19% of invasive taxa. Endangered and vulnerable taxa were registered, including Elaphoglossumhirtum (Sw.) C.Chr., Lactucawatsoniana Trel. and others which were considered by the authors a priority for conservation (e.g. Arceuthobiumazoricum Wiens & Hawksw., Bellisazorica Hochst. ex Seub., Saniculaazorica Guthnick ex Seub., Platantheramicrantha (Hochst. ex Seub.) Schltr.). Our records provide detailed and updated knowledge of Azorean Forest flora and highlight the role of natural forests as indigenous plant diversity hotspots and exotic woodland as a source of invasive taxa within the Archipelago.

Functional trait space and redundancy of plant communities decrease toward cold temperature at high altitudes in Southwest China

Plant communities in mountainous areas shift gradually as climatic conditions change with altitude. How trait structure in multivariate space adapts to these varying climates in natural forest stands is unclear. Studying the multivariate functional trait structure and redundancy of tree communities along altitude gradients is crucial to understanding how temperature change affects natural forest stands. In this study, the leaf area, specific leaf area, leaf carbon, nitrogen, and phosphorous content from 1,590 trees were collected and used to construct the functional trait space of 12 plant communities at altitudes ranging from 800 m to 3,800 m across three mountains. Hypervolume overlap was calculated to quantify species trait redundancy per community. First, hypervolumes of species exclusion and full species set were calculated, respectively. Second, the overlap between these two volumes was calculated to obtain hypervolume overlap. Results showed that the functional trait space significantly increased with mean annual temperature toward lower altitudes within and across three mountains, whereas species trait redundancy had different patterns between mountains. Thus, warming can widen functional trait space and alter the redundancy in plant communities. The inconsistent patterns of redundancy between mountains suggest that warming exerts varying influences on different ecosystems. Identification of climate-vulnerable ecosystems is important in the face of global warming.

Result of a year-long animal survey in a state-owned forest farm in Beijing, China

Background Artificial forest can have great potential in serving as habitat to wildlife, depending on different management methods. As the state-owned forest farms now play a new role in ecological conservation in China, the biological richness of this kind of land-use type is understudied. Once owned by a mining company, a largest state-owned forest farm, Jingxi Forest Farm, has been reformed to be a state-owned forest farm with the purpose of conservation since 2017. Although this 116.4 km² forest farm holds a near-healthy montaine ecosystem very representative in North China, a large proportion of artificial coniferous forest in the forest farm has been proven to hold less biodiversity than natural vegetation. This situation, however, provides a great opportunity for ecological restoration and biodiversity conservation. Therefore, from November 2019 to December 2020, we conducted a set of biodiversity surveys, whose results will serve as a baseline for further restoration and conservation. New information Here, we report the result of a multi-taxa fauna diversity survey conducted in Jingxi Forest Farm mainly in year 2020 with explicit spatial information. It is the first survey of its kind conducted in this area, revealing a total of 19 species of mammals, 86 birds, four reptiles, two amphibians and one fish species, as well as 101 species of insects. Four species of mammals are identified as data-poor species as they have less than 100 occurrence records with coordination in the GBIF database. One species of insect, representing one new provincial record genus of Beijing, is reported.

Identification of tree species based on the fusion of UAV hyperspectral image and LiDAR data in a coniferous and broad-leaved mixed forest in Northeast China

Rapid and accurate identification of tree species via remote sensing technology has become one of the important means for forest inventory. This paper is to develop an accurate tree species identification framework that integrates unmanned airborne vehicle (UAV)-based hyperspectral image and light detection and ranging (LiDAR) data under the complex condition of natural coniferous and broad-leaved mixed forests. First, the UAV-based hyperspectral image and LiDAR data were obtained from a natural coniferous and broad-leaved mixed forest in the Maoer Mountain area of Northeast China. The preprocessed LiDAR data was segmented using a distance-based point cloud clustering algorithm to obtain the point cloud of individual trees; the hyperspectral image was segmented using the projection outlines of individual tree point clouds to obtain the hyperspectral data of individual trees. Then, different hyperspectral and LiDAR features were extracted, respectively, and the importance of the features was analyzed by a random forest (RF) algorithm in order to select appropriate features for the single-source and multi-source data. Finally, tree species identification in the study area were conducted by using a support vector machine (SVM) algorithm together with hyperspectral features, LiDAR features and fused features, respectively. Results showed that the total accuracy for individual tree segmentation was 84.62%, and the fused features achieved the best accuracy for identification of the tree species (total accuracy = 89.20%), followed by the hyperspectral features (total accuracy = 86.08%) and LiDAR features (total accuracy = 76.42%). The optimal features for tree species identification based on fusion of the hyperspectral and LiDAR data included the vegetation indices that were sensitive to the chlorophyll, anthocyanin and carotene contents in the leaves, the partial components of the transformed independent component analysis (ICA), minimum noise fraction (MNF) and principal component analysis (PCA), and the intensity features of the LiDAR echo, respectively. It was concluded that the framework developed in this study was effective in tree species identification under the complex conditions of natural coniferous and broad-leaved mixed forest and the fusion of UAV-based hyperspectral image and LiDAR data can achieve enhanced accuracy compared the single-source UAV-based remote sensing data.

Bacteria associated with decomposing dead wood in a natural temperate forest

Dead wood represents an important pool of organic matter in forests and is one of the sources of soil formation. It has been shown to harbour diverse communities of bacteria, but their roles in this habitat are still poorly understood. Here, we describe the bacterial communities in the dead wood of Abies alba, Picea abies and Fagus sylvatica in a temperate natural forest in Central Europe. An analysis of environmental factors showed that decomposing time along with pH and water content was the strongest drivers of community composition. Bacterial biomass positively correlated with N content and increased with decomposition along with the concurrent decrease in the fungal/bacterial biomass ratio. Rhizobiales and Acidobacteriales were abundant bacterial orders throughout the whole decay process, but many bacterial taxa were specific either for young (<15 years) or old dead wood. During early decomposition, bacterial genera able to fix N2 and to use simple C1 compounds (e.g. Yersinia and Methylomonas) were frequent, while wood in advanced decay was rich in taxa typical of forest soils (e.g. Bradyrhizobium and Rhodoplanes). Although the bacterial contribution to dead wood turnover remains unclear, the community composition appears to reflect the changing conditions of the substrate and suggests broad metabolic capacities of its members.

Habitat preferences of Boros schneideri (Coleoptera: Boridae) in the natural tree stands of the Białowieża Forest

We analyzed habitat requirements of Boros schneideri (Panzer, 1796) (Coleoptera: Boridae) in the natural forests of the continental biogeographical region, using data collected in the Białowieża Forest. This species has been found on the six host trees, but it preferred dead, standing pine trees, characterized by large diameter, moderately moist and moist phloem but avoided trees in sunny locations. It occurred mostly in mesic and wet coniferous forests. This species demonstrated preferences for old tree stands (over 140-yr old), and its occurrence in younger tree-stand age classes (minimum 31-40-yr old) was not significantly different from random distribution. B. schneideri occupied more frequently locations distant from the forest edge, which were less affected by logging. Considering habitat requirements, character of occurrence, and decreasing number of occupied locations in the whole range of distribution, this species can be treated as relict of primeval forests.

Regional factors rather than forest type drive the community structure of soil living oribatid mites (Acari, Oribatida)

Most European forests are managed by humans. However, the manner and intensity of management vary. While the effect of forest management on above-ground communities has been investigated in detail, effects on the below-ground fauna remain poorly understood. Oribatid mites are abundant microarthropods in forest soil and important decomposers in terrestrial ecosystems. Here, we investigated the effect of four forest types (i.e., managed coniferous forests; 30 and 70 years old managed beech forests; natural beech forests) on the density, diversity and community structure of oribatid mites (Acari). The study was replicated at three regions in Germany: the Swabian Alb, the Hainich and the Schorfheide. To relate changes in oribatid mite community structure to environmental factors, litter mass, pH, C and N content of litter, fine roots and C content of soil were measured. Density of oribatid mites was highest in the coniferous forests and decreased in the order 30 years old, 70 years old, and natural beech forests. Mass of the litter layer and density of oribatid mites were strongly correlated indicating that the litter layer is an important factor regulating oribatid mite densities. Diversity of oribatid mites was little affected by forest type indicating that they harbor similar numbers of niches. Species composition differed between the forest types, suggesting different types of niches. The community structure of oribatid mites differed more strongly between the three regions than between the forest types indicating that regional factors are more important than effects associated with forest type.