Forest Successional Stages Research Articles

All boreal forest successional stages needed to maintain the full suite of soil biodiversity, community composition, and function following wildfire

Wildfire is a natural disturbance in boreal forest systems that has been predicted to increase in frequency, intensity, and extent due to climate change. Most studies tend to assess the recovery of one component of the community at a time but here we use DNA metabarcoding to simultaneously monitor soil bacteria, fungi, and arthropods along an 85-year chronosequence following wildfire in jack pine-dominated ecosites. We describe soil successional and community assembly processes to better inform sustainable forest management practices. Soil taxa showed different recovery trajectories following wildfire. Bacteria shared a large core community across stand development stages (~ 95–97% of their unique sequences) and appeared to recover relatively quickly by crown closure. By comparison fungi and arthropods shared smaller core communities (64–77% and 68–69%, respectively) and each stage appeared to support unique biodiversity. We show the importance of maintaining a mosaic ecosystem that represents each stand development stage to maintain the full suite of biodiversity in soils following wildfire, especially for fungi and arthropods. These results will provide a useful baseline for comparison when assessing the effects of human disturbance such as harvest or for assessing the effects of more frequent wildfire events due to climate change.

Estimation of forest above‐ground biomass in Guangxi, China, by integrating forest age and stack learning

AbstractWith the implementation of large‐scale ecological restoration projects, Southwest China has become one of the fastest forest growth areas in the world in terms of vegetation cover and above‐ground biomass (AGB). It is expected to be a potential area for achieving the carbon neutrality target in China. Accurate estimation of forest AGB is becoming an increasingly urgent necessity for carbon neutrality and forest management. However, due to the complex geological background, there is significant uncertainty in estimating forest AGB in the southwestern region, which generally results in underestimating carbon sinks from forest restoration. To address the issue, we propose a method by incorporating forest age information and stack learning technique to estimate forest AGB. Based on remote sensing, forest inventory and in situ forest biomass data, three fundamental methods (Multiple regression, Random forest and Support vector machine) are employed and compared to build the AGB estimation model with vegetation indices, texture feature factors and forest age. Optimal basic models are further enhanced by integration learning to improve the estimation performance and then applied to the study area Guangxi to obtain regional AGB information of different forest types. The results show that: (1) forest age plays a vital role in reducing the uncertainty of AGB estimation. By incorporating forest age information, R2 of AGB estimation is improved by 0.07–0.27 and RMSE is decreased by 16.35%–47.47% for different forest types; (2) with R2 value >0.78, random forest model outperforms support vector machine and multiple linear regression models. Compared with the single optimal model, integration model by stack learning further enhances R2 of estimation by 0.02–0.03 and decreases RMSE by 5.20%–14.89%. (3) The total forest AGB in Guangxi is 988.17 Tg and the average forest AGB level is 73.30 t/ha. Natural broadleaf forest has the highest AGB level (86.75 t/ha), followed by natural coniferous forest (81.19 t/ha), planted coniferous forest (63.23 t/ha) and planted eucalyptus forest (49.71 t/ha). AGB level in karst areas is lower than that in non‐karst areas due to soil and water constraints. The majority of plantation forests in Guangxi is in the early and middle stages of forest succession, with the rapid growth of forest AGB, and has hence significant potential as carbon sinks. This study indicates that stack learning and incorporation of forest age could significantly decrease the uncertainty of forest AGB estimation. Our study helps to provide more accurate AGB information for karst ecological project management and regional carbon neutrality assessment.

Mapping the Age of Subtropical Secondary Forest Using Dense Landsat Time Series Data: An Ensemble Model

Quantifying secondary forest age (SFA) is essential to evaluate the carbon processes of forest ecosystems at regional and global scales. However, the successional stages of secondary forests remain poorly understood due to low-frequency thematic maps. This study aimed to estimate SFA with higher frequency and more accuracy by using dense Landsat archives. The performances of four time-series change detection algorithms—moving average change detection (MACD), Continuous Change Detection and Classification (CCDC), LandTrendr (LT), and Vegetation Change Tracker (VCT)—for detecting forest regrowth were first evaluated. An ensemble model was then developed to determine more accurate timings for forest regrowth based on the evaluation results. Finally, after converting the forest regrowth year to the SFA, the spatiotemporal and topographical distributions of the SFA were analyzed. The proposed ensemble model was validated in Jiangxi province, China, which is located in a subtropical region and has experienced drastic forest disturbances, artificial afforestation, and natural regeneration. The results showed that: (1) the developed ensemble model effectively determined forest regrowth time with significantly decreased omission and commission rates compared to the direct use of the four single algorithms; (2) the optimal ensemble model combining the independent algorithms obtained the final SFA for Jiangxi province with the lowest omission and commission rates in the spatial domain (14.06% and 24.71%) and the highest accuracy in the temporal domain (R2 = 0.87 and root mean square error (RMSE) = 3.17 years); (3) the spatiotemporal and topographic distribution from 1 to 34 years in the 2021 SFA map was analyzed. This study demonstrated the feasibility of using change detection algorithms for estimating SFA at regional to national scales and provides a data foundation for forest ecosystem research.

Response Characteristics of Soil Organic Carbon Pool and Its Chemical Composition During Secondary Forest Succession in the Loess Plateau

In order to explore the characteristics of the soil organic carbon(SOC)pool and its chemical composition during the succession of secondary forests in the Loess Plateau, samples of the primary stage (Populus davidiana forest), transition stage (Populus davidiana and Quercus wutaishansea mixed forest), and top stage (Quercus wutaishansea forest) of secondary forest succession in the Huanglong Mountain forest area of the Loess Plateau in Northern Shaanxi were selected as the research object. The variation characteristics of SOC content, storage, and its chemical composition at different soil depths (0-10, 10-20, 20-30, 30-50, and 50-100 cm) were analyzed. The results showed that:① the contents and storage of SOC increased significantly with the secondary forest succession process (P<0.05). The content of SOC decreased significantly with the increase in soil depth, and the storage of SOC increased from 64.8 Mg·hm-2 in the primary stage to 129.2 Mg·hm-2 in the top stage, with an increase of 99%. ② During the succession of secondary forests, in the surface (0-30 cm) soil organic carbon, the relative content of aliphatic carbon components that have a simple structure and can be decomposed more easily decreased, and the relative content of aromatic carbon components that have a complex structure and cannot be decomposed easily increased, indicating that the chemical composition of organic carbon stability of surface-layer soil increased significantly with the process of secondary forest succession. However, the stability of the chemical composition of SOC in the deep layer (30-100 cm) first increased and then decreased, that is, the transition stage>the top stage>the primary stage. ③In the process of secondary forest succession, the stability of SOC chemical composition in the primary stage and transition stage increased significantly with the increase in soil depth. The top stage tended to be stable, and the deep soil carbon stability decreased slightly. ④ Pearson correlation analysis showed that during the secondary forest succession process, SOC storage and chemical composition stability were significantly negatively correlated with soil total phosphorus content. In general, the content and storage of SOC in the 0-100 cm soil increased significantly during the secondary forest succession, playing the role of a "carbon sink." The stability of the chemical composition of SOC in the surface layer (0-30 cm) increased significantly, but in the deep layer (30-100 cm), it increased first and then decreased.

Multifaceted diversity changes reveal community assembly mechanisms during early stages of post-logging forest succession

Plant succession is a fundamental process of vegetation recovery on disturbed sites. Elucidating its mechanisms remains a challenge as succession is influenced by stochastic and deterministic processes related to abiotic and biotic filters. Here, we use a multifaceted diversity approach to reveal mechanisms of successional changes in European oak-hornbeam forests during the first 10 years after selective logging. As the mechanisms controlling succession may depend upon initial abiotic conditions and colonization potential of the surrounding vegetation, we compare changes in taxonomic, functional, and phylogenetic diversity between clearings connected with open habitats and those isolated inside forests. Despite fewer dispersal barriers and higher biomass production in connected clearings, similar mechanisms initially governed succession in post-logging sites. Both clearings had low taxonomic and functional diversity in the first year of succession, as evidenced by significant trait convergence, caused by the legacy of interactions between overstory and understory vegetation in pre-disturbance closed-canopy forests. Colonization by short-lived and light-demanding species in the second and third years after logging has markedly increased the overall taxonomic and functional diversity, as evidenced by significant trait divergence. Connected clearings had higher functional but lower taxonomic and phylogenetic diversity than isolated clearings from the fourth to ten years of succession, probably due to intense competition in more productive habitats. All diversity facets markedly decreased in the last years due to increasing asymmetric competition from regenerating trees. The successional processes were largely deterministic, driven by species’ life-history strategies and biotic interactions (competition) rather than abiotic constraints and stochastic events.

Effects of secondary forest succession on the richness and composition of frog species in humid tropical forest

ABSTRACT Our aim was to evaluate whether the richness and composition of anurans responded to the time of forest regeneration via secondary succession. We sampled the anuran community in a mosaic of areas at three different stages of secondary succession in the Atlantic Forest, southern Brazil. The anurans were collected from nine lentic ponds and from their margins up to a 50 m radius. The late secondary forest sheltered the higher species richness, followed by the primary forest. The spatial variation in species richness was related to the forest succession stage and predominance of arboreal vegetation on the pond edge. The species composition changed throughout the succession stages, regardless of the distance among areas. Along the gradient of forest succession, environmental changes have driven species distribution, limiting the occurrence of forest species and favoring the colonization of areas at the early succession stage by opportunist species. We could observe that the secondary forest succession was a determining factor in the anuran community structure, and with the advancement of the secondary succession, both richness and composition were partly restored. Thus, the conservation of secondary forests might be an efficient strategy to preserve the biodiversity in areas of the Atlantic Forest.

Variations and influencing factors of soil organic carbon during the tropical forest succession from plantation to secondary and old–growth forest

IntroductionSoil organic carbon (SOC) accumulation changed with forest succession and hence impacted the SOC storage. However, the variation and underlying mechanisms about SOC during tropical forest succession are not fully understood.MethodsSoil samples at four depths (0–10 cm, 10–20 cm, 20–40 cm and 40–60 cm), litter, and roots of 0–10 cm and 10–20 cm were collected from three forest succession stages (plantation forest, secondary forest, and old– growth forest) in the Jianfengling (JFL) National Nature Reserve in Hainan Island, China. The SOC, soil enzyme activities, physiochemical properties, the biomass of litter and roots were analyzed.ResultsResults showed that forest succession significantly increased SOC at 0–10 cm and 10–20 cm depth (from 23.00 g/kg to 33.70 g/kg and from 14.46 g/kg to 22.55 g/kg, respectively) but not at a deeper depth (20–60 cm). SOC content of the three forest succession stages decreased with increasing soil depth and bulk density (BD). With forest succession from plantation to secondary and old–growth forest, the soil pH at 0–10 cm and 10–20 cm depth decreased from 5.08 to 4.10 and from 5.52 to 4.64, respectively. Structural equation model (SEM) results showed that the SOC at depths of 0–20 cm increased with total root biomass but decreased with increasing soil pH value. The direct positive effect of soil TP on SOC was greater than the indirect negative effect of decomposition of SOC by soil acid phosphatase (AP).DiscussionTo sum up, the study highlighted there was soil P– limited in tropical forests of JFL, and the increase in TP and total root biomass inputs were main factors favoring SOC sequestration during the tropical forest succession. In addition, soil acidification is of great importance for SOC accumulation in tropical forests for forest succession in the future. Therefore, forest succession improved SOC accumulation, TP and roots contributed to soil C sequestration.

亚热带森林演替阶段下不同光环境对芒萁光合生理的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 亚热带森林演替阶段下不同光环境对芒萁光合生理的影响 DOI: 10.5846/stxb202112273661 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（31971623）；浙江省"尖兵""领雁"研发攻关计划项目（2022C02019） Effects of different light environments on photosynthetic physiology of Dicranopteris dichotoma under successional stages in subtropical forests Author: Affiliation: Fund Project: The National Natural Science Foundation of China (31971623)； 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:光环境的变化是群落演替进程中植物进入和退出群落的重要因素。为研究亚热带森林次生演替不同阶段的光照对芒萁光合生理的影响，对灌草丛、马尾松林和常绿阔叶林这3种群落内盆栽芒萁的光响应过程和叶绿素荧光诱导动力学参数进行了研究。结果表明：芒萁在光强为400 μmol m-2 s-1左右且日变化幅度较小的马尾松林下净光合速率（Pn）最高，在光强50 μmol m-2 s-1左右的常绿阔叶林下次之，在400-1800 μmol m-2 s-1左右波动的灌草丛内最低。这是因为灌草丛内芒萁J点相对可变荧光（Vj）、K点标准化后的相对可变荧光（Wk）显著升高，以吸收光能为基础的光系统Ⅱ性能指数（PSⅡ）（PIABS）显著降低，而热耗散参数（φDo）基本不变，即强光破坏了芒萁光合机构PSⅡ的供体侧和受体侧，使其产生了光抑制。常绿阔叶林内芒萁叶绿素荧光诱导动力学参数与马尾松林下差异不明显，且最大净光合速率（Pmax）下降是光强变弱导致的，但是暗呼吸速率（Rd）、光补偿点（LCP）和光饱和点（LSP）均随之降低，可见芒萁光合机构对该光强有一定的适应性。由此可知，芒萁喜光但不耐强光，对弱光具有一定耐受性。 Abstract:The light changes of forest succession play important roles in the presence or absence of plant species in communities. To reveal the effects of light on photosynthetic physiology of Dicranopteris dichotoma at different stages of secondary succession in subtropical forests, light response process and chlorophyll fluorescence induction kinetic parameters of D. dichotoma growing in three different communities (scrub, Pinus massoniana forest, and evergreen broadleaf forest) were investigated in this experiment. The results showed that the net photosynthetic rate (Pn) was the highest in the P. massoniana forest with a light intensity of about 400 μmol m-2 s-1 and a small daily variation, followed by the evergreen broadleaf forest with a light intensity of about 50 μmol m-2 s-1, and the lowest in the scrub with a fluctuation of about 400-1800 μmol m-2 s-1. The lowest Pn in the scrub was because high light disrupted donor and acceptor sides of photosystem II (PSII) of D. dichotoma, and resulted in photoinhibition of D. dichotoma, which were proved by significantly increased relative variable fluorescence (Vj) at point J, normalized relative variable fluorescence (Wk) at point K, and significantly decreased PSII performance index (PIABS), and unchanged heat dissipation parameter (φDo). No significant differences in chlorophyll fluorescence induction kinetics between the D. dichotoma growing in evergreen broad-leaved forest and P. massoniana forest indicated that its PSII was not damaged, and the decrease of the maximum net photosynthetic rate (Pmax) was caused by the low light. At the same time, the reduced dark respiration rate (Rd), light compensation point (LCP), and light saturation point (LSP) showed that D. dichotoma photosynthetic system could adapt to the low light in the evergreen broad-leaved forest. This study showed that D. dichotoma was a light-loving but not light-tolerant species, with the modest low-light tolerance. 参考文献 相似文献 引证文献

Inclusion criteria influence species richness, diversity and forest structure with implications to deforestation permits in Rio de Janeiro State, Brazil

Deforestation requests to government decision-makers aim for the legal permission to remove secondary forests for economic reasons. In the State of Rio de Janeiro, Resolução Conama nº 06/1994 drives the analysis of successional stages of such forests. It does not define which inclusion criterion (diameter at breast height) should be used in forest inventories. We used Floresta da Cicuta as a case study to evaluate the influence of different inclusion criteria on species richness, diversity and structure parameters having Resolução Conama nº 06/1994 as background. Using Hill numbers, we found that the DBH ≥ 2.5 cm highlighted species richness. Species richness is improperly addressed in Resolução Conama nº 06/1994. The use of DBH ≥ 2.5 cm detected 30 individuals of threatened species, while DBH ≥ 10 cm detected only nine. Basal area was the most accurate parameter to identify the successional stage. Mean DBH and mean height misidentified successional stage. We strongly advise environmental authorities to demand the use of DBH ≥ 2.5 cm in forest inventories for deforestation requests. We strongly encourage the review of Resolução Conama nº 06/1994 by environmental authorities in order to reduce the risk of mistaken classification of successional stage of secondary forests.

Remote Sensing for Analyzing Forested Landscape Structure and Land-Use Histories in Guyana’s Bauxite Mining Landscapes

Monitoring secondary forest regrowth is a priority in forest restoration strategies. A site history helps in understanding the present status of natural regeneration in the three landscapes impacted by bauxite mining. Nonetheless, high rainfall in bauxite residue storage areas can facilitate natural regeneration of forest. This research analyzed the natural regeneration of forest after thirty years of different land use histories at three bauxite mining areas of the Upper Demerara—Berbice region of Guyana. There are no man made forest plantations in the three landscapes being reviewed. The methodology included: 1) the selection of three sampling landscapes with different land use histories 2) the generation Land Use/Land Cover maps using KMeans unsupervised classification of satellite images in each landscape and 3) the assessment of landscape structure of the land cover classes for year 2020 at class and landscape level using landscape metrics. The assessment of landscape structure of the land cover classes was carried-out with landscape metrics for the comparisons at class and landscape level. Principal component analysis enables the identification of main patterns among landscape-level metrics and land cover classes. Discriminant classification of the landscape classes was analyzed with the different metrics. The results suggest that Normalized Difference Vegetation Index and KMeans unsupervised classification can be used to evaluate the difference in natural forest regeneration among landscapes with differing land use histories. The landscape metrics revealed secondary stages of forest succession. The Landscape Shape Index and Edge Density were the most significant for landscape differentiation. The result of the various land uses reveals a mosaic of early, intermediate, and late successional sequences.

The Zoʻé perspective on what scientists call “forest management” and its implications for floristic diversity and biocultural conservation

Indigenous perspectives on forest management are grounded in traditional ecological knowledge (TEK), so that socioculture influences the ways Indigenous Peoples transform their landscapes. However, how socioculture structures Indigenous perspectives on forest management is unclear. Moreover, little is known about the influence of Indigenous landscape transformations on forest succession and floristic diversity. Here, we test hypotheses from biocultural and ecological theories suggesting that: (i) key social-ecological relationships with specific taxa structure Indigenous perspectives on forest management; (ii) such relationships guide sustainable management that generates resilient forest regrowth; and (iii) this management promotes floristic diversity by acting as an intermediate disturbance. We collected information about cosmology, occupation history and management among the Zoʻé, in Brazilian Amazonia. We also carried out floristic inventories in old-growth forests and in old Zoʻé swidden-fallow areas to analyze forest structure and alpha- and beta-diversity along a gradient of forest successional stages. We show that the Zoʻé perspective on forest management is structured by an ethical principle involving a social-ecological relationship with different beings, especially the spider monkey (<em>Ateles</em> sp.). This relationship generates mobility among the Zoʻé that allows forest regrowth in their fallow areas, so that in 28 years, forest basal area may equal that of old-growth forests. Also, Zoʻé forest management has increased alpha- and beta-diversity by increasing species richness and diversity in intermediate secondary forests and promoting floristic turnover at the landscape-level. These results show that some aspects of Zoʻé cosmology influence forest disturbance regimes that generate a sustainable social-ecological system, therefore being key for Zoʻé well-being and local biodiversity conservation. We believe that Indigenous perspectives about forest management should be included in forest conservation efforts aimed at protecting Amazonian biocultural diversity, thus valuing TEK and engendering sustainable social-ecological systems.

A dataset of species composition and biomass in successional stages of Tiantong typical evergreen broad-leaved forest (2008–2017)

As a basic properties of forest vegetation, forest succession law is the basis understanding . Typical evergreen broad-leaved forest a zonal vegetation in the subtropical area of China. The existing vegetation is mostly in different secondary succession stages due to human and natural disturbance. lant species is an important indicator of the forest ecosystem and the basis for the study o structure, function and dynamics of evergreen broad-leaved forest. According to CNERN monitoring standards, Zhejiang Tiantong Forest Ecosystem Observation and Research Station three three succession plots and established a dataset species composition 2008 to 2017. The succession plots are evergreen shrub plot, Schima Superba forest plot and Castanopsis fargesii forest plot, respectively species name, abundance, mean diameter and biomass of woody plants the plots. The database provides critical data for the study and application of succession, community assembly and forest restoration in subtropical typical evergreen broad-leaved forests.

Root Production and Microbe-Derived Carbon Inputs Jointly Drive Rapid Soil Carbon Accumulation at the Early Stages of Forest Succession

Plants and microbes are the primary drivers in affecting the formation and accrual of soil organic carbon (SOC) for natural ecosystems. However, experimental evidence elucidating their underlying mechanisms for SOC accumulation remains elusive. Here, we quantified plant and microbial contributions to SOC accrual in successional subtropical forests by measuring leaf-, root-, and microbial biomarkers, root and leaf litter inputs, and microbial C decomposition. The long-term monitoring results showed that SOC accumulated rapidly at the early-successional stage, but changed little at the mid- and late-successional stages. SOC accrual rate was positively correlated with fine-root production and microbial C turnover, but negatively with annual litterfall. Biomarker data exhibited that the rapid SOC accumulation was jointly driven by root- and microbe-derived C inputs from the early- to mid-successional stages. In contrast, aboveground litterfall considerably contributed to soil C accrual from the mid- to late-successional stages compared to belowground processes, although SOC accumulation is low. Our study revealed the importance of root production and microbial anabolism in SOC accrual at the early stages of forest succession. Incorporating these effects of belowground C inputs on SOC formation and accumulation into earth system models might improve model performance and projection of long-term soil C dynamics.

Computer-aided classification of successional stage in subtropical Atlantic Forest: a proposal based on fuzzy artificial intelligence

Due to the continuous variability of the forest regeneration process, patterns of indicator variables with membership in more than one successional stage may occur, making the classification of such stages a challenging and complex task. This study aims at presenting a comparative analysis of artificial intelligence methods as an alternative for computer-aided classification of successional stages in subtropical Atlantic Forest. As a research hypothesis, the authors consider that a fuzzy inference system should provide the best performance due to its ability to deal with uncertainties inherent to complex processes. The analyses were carried out using a database of the forest inventory of Santa Catarina, Southern Brazil. The data are composed of 177 sampling units of subtropical Atlantic Forest (mixed ombrophilous forest), characterized according to eighth indicator variables verified from the field by experts. This database was employed to train several machine learning methods under a tenfold cross-validation process. The overall accuracy (θ) and kappa coefficient were used to compare the performance between FIS and neural networks, classifier committees and support vector machine. Then, to verify if the classification by the FIS differed from the one performed by experts, the Kappa index and a statistical significance analysis by Pearson's [Formula: see text] test were determined. The hypotheses were verified with two-way tests at a significance level (α) 0.05, for a test power (1-β) 0.8 and minimum expected effect size between medium (ρ = 0.3). Statistical significance tests confirmed the hypothesis that FIS achieved the highest performance, with θ = 98.3% and a kappa value equal to 0.93 (almost perfect agreement) and showed no significant difference ([Formula: see text] = 0.047, p = 0.976) in comparison with the classification by experts. The use of FIS represents a promising alternative as a tool applicable for computer-aided classification of successional stages in subtropical Atlantic Forest. The results and conclusions should substantially impact the guidelines and decision-making process for deforestation authorizations and applicable compensation measures, which are based on the forest succession stage.

Open forest successional stages and landscape heterogeneity promote wild bee diversity in temperate forests

AbstractRecent studies have emphasized forests as crucial habitat for wild bees. In Europe, most forests are managed following the principles of close‐to‐nature silviculture, which combine timber production and nature conservation. However, open late and early successional stages within these forests are largely missing, which could be important for wild bees. This highlights that close‐to‐nature silviculture alone might not be sufficient to conserve bees within temperate forests. Open structures such as canopy gaps and road verges in forests could improve habitat for bees. To provide management recommendations for wild bee conservation in temperate forests, we analyzed how components of bee beta diversity varied between forest management types and tested how open structures, namely clear‐cuts, canopy gaps, and forest road verges influenced bee abundance, richness, and diversity. In addition, we analyzed the abundance and percent of red‐listed bee species at different scales. Bees were sampled using 90 pan traps on 45 (1 ha) plots in 2019 and 2020 in the Black Forest, Germany. Plots were selected in 15 triplets each consisting of three management types related to different successional stages: unmanaged, close‐to‐nature, and small clear‐cut. Beta diversity was not consistently nested highlighting the importance of different management and successional stages within the landscape to support bees in forests. Abundance, species richness, and Shannon diversity of bees were highest on clear‐cuts, compared to unmanaged‐ and close‐to‐nature plots. At landscape scale, wild bee abundance increased with canopy openness while wild bee diversity increased with landscape heterogeneity. Abundance‐ and percent of red‐listed bee species increased with the length of forest road verges. We advocate creating habitats at local scales which offer flowering and nesting resources by providing canopy gaps. At landscape scale, heterogeneity created through different forest successional stages is needed to conserve the entire community of wild bees.

Aboveground net primary productivity mediates the responses of soil respiration to nutrient additions in two tropical montane rainforests

Tropical forests play a dominant role in mediating carbon (C) dioxide exchange between the terrestrial biosphere and the atmosphere. Plant production and microbial decomposition in tropical ecosystems are generally considered to be limited by soil nutrients, especially soil phosphorus (P), but the impact of nutrient inputs on soil respiration is little reported. We measured soil respiration rate (Rs) and its autotrophic (Ra) and heterotrophic components (Rh) during 2012–2017 in the nutrient addition experiments conducted in a primary and secondary tropical montane forest in Mt. Jianfengling, South China. Nutrient addition did not affect Rh, but promoted Ra and Rs in these two forests. The actual nutrient responsible for Ra and Rs increases differed between the forests, with a significantly positive P effect in the primary forest and a significantly positive nitrogen (N) effect in the secondary forest. The Ra and Rs increases induced by nutrient additions were likely attributed to the stimulation of aboveground net primary productivity (ANPP) rather than other factors. These results suggested that the ANPP induced increases in both Ra and Rs varied with forest successional stages and nutrient types. Our findings provide compelling evidence that N and P inputs may promote soil respiration in tropical montane forests, which has an important implication for predicting soil C efflux in tropical forests under increasing atmospheric N and P depositions.

The contributions of soil biochemical characteristics and soil organic carbon (SOC) structure to SOC mineralization rate during forest succession on the Loess Plateau, China

AbstractSoil organic carbon (SOC) mineralization is a process driven by microorganisms and is considered to be one of the main forms of carbon loss in land restoration. However, the interaction of SOC structures and bacteria that drive SOC mineralization remain unclear. Therefore, four forest succession stages were investigated on the Loess Plateau of Northern China: (1) primary stage Betula platyphylla (BP); (2) transitional stage which were two mixed communities of Populus davidiana and Quercus wutaishanica with different proportions (PQ1); (3) (PQ2) and (4) the late stage was climax communities of Quercus wutaishanica (QW). The Illumina sequencing of the 16S rRNA gene and Fourier transformation infrared (FTIR‐ATR) spectroscopy were used to clarify the regulation mechanism of microbial activity on SOC mineralization during forest succession through the perspective of SOC structures. Our results indicated higher aromatics‐C in QW contributed to decreased SOC mineralization ratio (SMR). Redundancy analysis confirmed SOC structures–bacteria interaction and revealed the groups Acidobacteria correlated with recalcitrant SOC structures while Proteobacteria and Bacteroides correlated with labile SOC structures, respectively. Moreover, the partial least squares path model revealed that the SOC and C:N ratio act on soil bacteria community characteristics, and the higher abundance of Acidobacteria and the increase of aromatics‐C decreased SMR. Collectively, these findings highlight the importance of bacteria–SOC structures interaction in decreased SMR and contribute to an improved understanding of how forest succession regulates carbon mineralization.

Size‐dependent intraspecific variation in wood traits has little impact on aboveground carbon estimates in a tropical forest landscape

Abstract There is increasing evidence that intraspecific trait variation plays a role in governing rates of ecosystem functioning. While wood traits such as wood specific gravity (WSG) and wood carbon concentration (WCC) are key drivers of forest aboveground carbon (AGC) stocks, the sources of intraspecific variation in these wood traits and the consequences of this variation on AGC are poorly known, especially in the tropics. Here, we investigated intraspecific variation in wood specific gravity (WSG) and wood carbon concentration (WCC) from 556 individual trees belonging to 15 species that well characterize different successional stages of seasonal evergreen forests in Southeast Asia. Specifically, we tested the contribution of individual or species characteristics (tree size, growth rate and regeneration guilds) and local environmental conditions (topographic wetness index and successional stages) to intraspecific variation in WSG and WCC, and assessed the consequences of intraspecific variation in these wood traits on AGC estimates in 14 permanent forest plots established along a successional gradient in Khao Yai National park, Thailand. We found that tree size was the main driver of intraspecific variation in WSG and WCC as tree sizes increased from 10–100 cm in diameter, WSG increased by 7.3%, while WCC increased by 2.4% in heartwood, 1.6% and 2.7% in sapwood without and with volatile carbon included. There was no effect of the topographic wetness and other local environment condition in wood traits led to a slight overestimation of AGC in young secondary forests (+0.09% to +1.29%) and a small underestimation in older forests (−0.86% to −2.87%), but overall AGC estimates (13 of 14 forest plots) remained within error margins (the 95% interval). Our study provides evidence that tree size variation translates into intraspecific variability in wood traits, whereas local environmental conditions related to topography successional stages had no effect on wood trait variability. While size‐dependent variation in WSG and WCC have largely been undocumented and thus ignored in forest carbon assessment approaches, we highlight that it has a limited impact on AGC estimates, indicating that it does not invalidate current forest carbon stock estimation approaches. Read the free Plain Language Summary for this article on the Journal blog.

Changes in the Distribution Preference of Soil Microbial Communities During Secondary Succession in a Temperate Mountain Forest.

Soil microbes play a crucial role in a forest ecosystem. However, whether the distribution of bacteria and fungi in different forest succession stages is random or following ecological specialization remains to be further studied. In the present study, we characterized soil bacterial and fungal communities to determine their distribution preference, with different succession communities in a temperate mountain forest. The Kruskal–Wallis method was used to analyze structural differences between bacterial and fungal communities in different succession processes. The specificity of soil microbial distribution in a secondary forest was studied by network analysis. The torus-translation test was used to analyze the species distribution preference of soil microbes in different succession stages. Results showed that the species composition of soil bacteria and fungi differed significantly in different succession processes. The modularity index of fungi (0.227) was higher than that of bacteria (0.080). Fungi (54.47%) had specific preferences than bacteria (49.95%) with regard to forests in different succession stages. Our work suggests that the distribution pattern of most soil microbes in a temperate mountain forest was not random but specialized in temperate mountain forests. Different microbes showed different distribution preferences. Fungi were more sensitive than bacteria during secondary succession in a temperate mountain forest. In addition, microbe–environment relations varied during secondary succession. Our results provided new insight into the mechanism through which complex soil microbial communities responded to changes in forest community succession.

Mapping Spatiotemporal Changes in Forest Type and Aboveground Biomass from Landsat Long-Term Time-Series Analysis—A Case Study from Yaoluoping National Nature Reserve, Anhui Province of Eastern China

A natural reserve’s forest is an important base for promoting natural education, scientific research, biodiversity conservation and carbon accounting. Dynamic monitoring of the forest type and forest aboveground biomass (AGB) in a nature reserve is an important foundation for assessing the forest succession stage and trend. Based on the Landsat images covering the National Nature Reserve of Yaoluoping in Anhui province spanning from 1987 to 2020, a total of 42 Landsat scenes, the forest cover product set was first developed by using the well-established vegetation change tracker (VCT) model. On this basis, a new vegetation index, NDVI_DR, which considers the phenological characteristics of different forest types, was proposed to distinguish coniferous forest from broad-leaved forest. Next, multiple modeling factors, including remote sensing spectral signatures, vegetation indices, textural measures derived from gray level co-occurrence matrix and wavelet analysis and topographic attributes, were compiled to model the AGB in 2011 by forest type separately by using the stochastic gradient boosting (SGB) algorithm. Then, using the 2011 Landsat image as the base, all the Landsat images in the other years involved in the modelling were relatively normalized by using the weighted invariant pixels (WIP) method, followed by an extrapolation of the 2011 AGB model to other years to create a time-series of AGB. The results showed that the overall accuracy of the VCT-based forest classification products was over 90%. The annual forest type classifications derived from NDVI_DR thresholding gained an overall accuracy above 92%, with a kappa coefficient above 0.8. The 2011 forest-type-dependent SGB-based AGB estimation model achieved an independent validation R2 at 0.63 and an RMSE at 11.18 t/ha for broad-leaved forest, and 0.61 and 14.26 t/ha for coniferous forest. The mapped time-series of AGB showed a gradual increasing trend over the past three decades. The driving factors responsible for the observed forest cover and AGB changes were analyzed to provide references for reasonable protection and development. The proposed methodology is a reliable tool for evaluating the management status, which can be extended to other similar regions.