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Wang K, She D, Zhang X, Wang Y, Wen H, Yu J, Wang Q, Han S, Wang W. Tree richness increased biomass carbon sequestration and ecosystem stability of temperate forests in China: Interacted factors and implications. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 368:122214. [PMID: 39191057 DOI: 10.1016/j.jenvman.2024.122214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/29/2024] [Accepted: 08/12/2024] [Indexed: 08/29/2024]
Abstract
Biodiversity loss and forest degradation have received increasing attention worldwide, and their effects on forest biomass carbon storage and stability have not yet been well defined. This study examined 1275 tree plots using the field survey method to quantify the effects of tree diversity, tree sizes, and mycorrhizal symbiont abundance on biomass carbon storages (Cs) and NDVI (Normalized Difference Vegetation Index)-based ecosystem stability (standard deviation/mean NDVI = NDVI_S) during the field survey period from 2008 to 2018. Our data showed Cs and NDVI_S averaged at 31-108 t ha-1 and 32.04-49.28, respectively, and positive relations between Cs and NDVI_S were observed (p < 0.05). Large forest-type and regional variations were found in these two parameters. Broadleaf forests had 74% of Cs (p < 0.05) of the conifer forests, but no differences were in NDVI_S. Cold regions at high latitudes had 71% of NDVI_S in the warm regions at low latitudes, while no differences were in Cs. Moist regions at high longitudes had 2.04 and 1.28-fold higher Cs and NDVI_S (p < 0.05). The >700 m a.s.l. regions had 1.24-fold higher Cs (p < 0.01) than the <700 m a.s.l. regions, but similar NDVI_S (p > 0.05). Nature Reserves had 1.94-fold higher Cs but 30% lower NDVI_S than outside Reserves (p < 0.001). > 40-year-old forests had 1.3- and 2-fold higher Cs and NDVI_S than the young forests. Structural equation modeling and hierarchical partitioning revealed the driving paths responsible for these variations. Tree richness was positively associated with Cs and ecosystem stability, contributing 21.6%-30.6% to the total effects on them; tree sizes significantly promoted the Cs, but had negligible impacts on NDVI_S. MAT's total effects on NDVI_S of conifer forests were 40% higher than that of broadleaf forests, MAP's total effects on Cs varied with forest types; arbuscular mycorrhizal tree dominance exhibited a smaller positive impact on Cs and ecosystem stability in comparison to other factors. Our findings underscore that the significance of climatic-adapted forest management, diversity conservation, and big-sized tree protections can support the achievement of carbon neutrality in China from biomass carbon sequestration and ecosystem stability.
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Affiliation(s)
- Kai Wang
- State Key Laboratory of Subtropical Silviculture, College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou, 311300, Zhejiang, China; Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China; School of Tourism, Bohai University, Jinzhou, Liaoning, 121000, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Danqi She
- State Key Laboratory of Subtropical Silviculture, College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou, 311300, Zhejiang, China; Key Laboratory of Forest Plant Ecology (MOE), College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin, 150040, China
| | - Xiting Zhang
- Key Laboratory of Forest Plant Ecology (MOE), College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin, 150040, China; Leshan Normal University, School of Life Science, Leshan, 614000, China
| | - Yuanyuan Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
| | - Hui Wen
- Key Laboratory of Forest Plant Ecology (MOE), College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin, 150040, China
| | - Jinghua Yu
- Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China
| | - Qinggui Wang
- College of Life Science, Qufu Normal University, Qufu, 273165, China
| | - Shijie Han
- College of Life Science, Qufu Normal University, Qufu, 273165, China
| | - Wenjie Wang
- State Key Laboratory of Subtropical Silviculture, College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou, 311300, Zhejiang, China; Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China.
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Wang K, Wang Y, Wen H, Zhang X, Yu J, Wang Q, Han S, Wang W. Biomass carbon sink stability of conifer and broadleaf boreal forests: differently associated with plant diversity and mycorrhizal symbionts? ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:115337-115359. [PMID: 37882924 DOI: 10.1007/s11356-023-30445-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 10/09/2023] [Indexed: 10/27/2023]
Abstract
Forest biomass carbon stability is crucial in achieving carbon neutrality in the high-latitude northern hemisphere, and identifying the differences among forest types and decoupling their associations with plant traits and geoclimatic conditions is the basis for precise forest management. We conducted a large-scale field survey in state-owned forest areas in northeastern China, covering a total of 280,000 km2 forest area, 1275 arbor plots (30 m × 30 m), 5285 shrub plots (5 m × 5 m), and 7076 herb plots (1 m × 1 m). We hypothesized that the conifer and broadleaf forest differences in biomass carbon (C) storage and stability (environmental stability to climatic changes-ES and recalcitrant stability to be decomposed-RS) are associated with mycorrhizal abundance (EcM: ectomycorrhizal, AM: arbuscular mycorrhizal, NM-AM: non-mycorrhizal or arbuscular mycorrhizal), taxon diversity traits (richness, Simpson, Shannon-Wiener, and evenness), and structural differences (diameter, height, and density) in the arbor, shrub, and herb layers. Our results showed that (1) conifer forests had 13.1 Mg/ha higher C stocks and 30.9% higher RS, but 8.6% lower ES than broadleaf forests (p < 0.05). Trees in conifer forests had 1.5 m taller and 2.4 cm thicker trees, but 15% less tree density than those in broadleaf forests. Herbs in conifer forests were 14% shorter and 57% denser than in broadleaf forests. (2) The abundance of EcM-symbiont trees in conifer forests was 15% higher than in broadleaf forests, while their EcM-symbiont shrubs and AM-symbiont herbs were 5-6% lower (p < 0.05). Broadleaf forests had 7% higher tree richness and 19% higher herb richness but 9% lower shrub richness than conifer forests (p < 0.05). Tree and herb evenness was 5-6% higher in conifer forests (p < 0.05). (3) Variations of biomass C sink traits could be explained more by plant diversity in conifer forests (7%) than in broadleaf forests (3.4%). Mycorrhizal symbionts could explain more in broadleaf forests (9.7%) than conifer forests (6.7%). In conifer forests, fewer EcM trees (higher AM trees) and AM herbs, higher tree richness were accompanied by higher biomass C storage and ES. Broadleaf forests underwent similar changes, characterized by an elevation in both RS and ES. (4) Our research emphasized that variations in carbon sequestration between conifer and broadleaf forests could be attributed to mycorrhizal symbionts and species diversity besides tree size-related structural differences. Our findings support the precise management of boreal forests to achieve carbon neutrality based on leaf blade types, plant diversity, and mycorrhizal symbionts.
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Affiliation(s)
- Kai Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuanyuan Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
| | - Hui Wen
- Key Laboratory of Forest Plant Ecology (MOE), College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin, 150040, China
| | - Xiting Zhang
- Key Laboratory of Forest Plant Ecology (MOE), College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin, 150040, China
| | - Jinghua Yu
- Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China
| | - Qinggui Wang
- College of Life Science, Qufu Normal University, Qufu, 273165, China
| | - Shijie Han
- College of Life Science, Henan University, Kaifeng, 475004, China
| | - Wenjie Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China.
- State Key Laboratory of Subtropical Silviculture, College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou, 311300, Zhejiang, China.
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Yang Y, Jing L, Li Q, Liang C, Dong Q, Zhao S, Chen Y, She D, Zhang X, Wang L, Cheng G, Zhang X, Guo Y, Tian P, Gu L, Zhu M, Lou J, Du Q, Wang H, He X, Wang W. Big-sized trees and higher species diversity improve water holding capacities of forests in northeast China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 880:163263. [PMID: 37028669 DOI: 10.1016/j.scitotenv.2023.163263] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 03/28/2023] [Accepted: 03/31/2023] [Indexed: 05/27/2023]
Abstract
High water-holding forests are essential for adapting to drought climates under global warming, and a central issue is which type of forests could conserve more water in the ecosystem. This paper explores how forest structure, plant diversity, and soil physics impact forest water-holding capacities. We investigated 720 sampling plots by measuring water-holding capacities from 1440 soil and litter samples, 8400 leaves, and 1680 branches and surveying 18,054 trees in total (28 species). Water-holding capacities were measured as four soil indices (Maxwc, maximum water-holding capacity; Fcwc, field water-holding capacity; Cpwc, soil capillary water-holding capacity; Ncpwc, non-capillary water-holding capacity), two litter metrics (Maxwcl, maximum water-holding capacity of litters; Ewcl, effective water-holding capacity of litters), and canopy interception (C, the sum of estimated water interception of all branches and leaves of all tree species in the plot). We found that water-holding capacity in the big-sized tree plots was 4-25 % higher in the litters, 54-64 % in the canopy, and 6-37 % in the soils than in the small-sized plots. The higher species richness increased all soil water-holding capacities compared to the lowest richness plot. Higher Simpson and Shannon-Wiener plots had 10-27 % higher Ewcl and C than the lowest plots. Bulk density had the strongest negative relations with Maxwc, Cpwc, and Fcwc, whereas field soil water content positively affected them. Soil physics, forest structure, and plant diversity explained 90.5 %, 5.9 %, and 0.2 % of the water-holding variation, respectively. Tree sizes increased C, Ncpwc, Ewcl directly (p < 0.05), and richness increased Ewcl directly (p < 0.05). However, the direct effects from the uniform angle index (tree distribution evenness) were balanced by their indirect effect from soil physics. Our findings highlighted that the mixed forests with big-sized trees and rich species could effectively improve the water-holding capacities of the ecosystem.
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Affiliation(s)
- Yanbo Yang
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Lixin Jing
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Qi Li
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Chentao Liang
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Quanxing Dong
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Shuting Zhao
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Yuwen Chen
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Danqi She
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Xu Zhang
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Lei Wang
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Guanchao Cheng
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Xiting Zhang
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Yufeng Guo
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Panli Tian
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Lin Gu
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Meina Zhu
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Jing Lou
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Qian Du
- Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Huimei Wang
- State Key Laboratory of Subtropical Silviculture, College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou 311300, Zhejiang, China
| | - Xingyuan He
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Wenjie Wang
- State Key Laboratory of Subtropical Silviculture, College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou 311300, Zhejiang, China; Key Laboratory of Forest Plant Ecology, Ministry of Education, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China.
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Tian P, Wang L, Li Q, Liang C, She D, Liu S, Chen Y, Yao L, Wang W, Wang H, Wang W. Feasibility of urban bird occurrence and nest amount evaluation by the street-view image virtual survey. Proc Biol Sci 2023; 290:20230406. [PMID: 37072036 PMCID: PMC10113023 DOI: 10.1098/rspb.2023.0406] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 03/21/2023] [Indexed: 04/20/2023] Open
Abstract
Bird observation mainly relies on field surveys, which are time-consuming and laborious. In this study, we explored using street-view images in the virtual survey of urban birds and nests. Using the coastal city of Qingdao as the study area, 47 201 seamless spherical photos at 2741 sites were collected using the Baidu street-view (BSV) map. Single-rater-all photo checks and seven-rater-metapopulation checks were used to find inter-rater repeatability, the best viewing layer for BSV collection, and possible environments affecting the results. We also collected community science data for comparison. The BSV time machine was used to assess the temporal dynamics. Kappa square test, generalized linear model, redundancy ordination and ArcMap were used in the analysis. Different rater repeatability was 79.1% in nest evaluations and 46.9% in bird occurrence. A re-check of the different-rating photos can increase them to 92% and 70%. Seven-rater statistics showed that more than 5% sampling ratio could produce a non-significant different bird and nest percentage of the whole data, and the higher sampling ratio could reduce the variation. The middle-viewing layer survey alone could produce 93% precision of the nest checks by saving 2/3 of the time used; in birds, selecting middle and upper-view photos could find 97% of bird occurrences. In the spatial distribution, the nest's hotspot areas from this method were much greater than the community science bird-watching sites. The BSV time machine made it possible to re-check nests in the same sites but challenging the re-check of bird occurrences. The nests and birds can be observed more in the leafless season, on wide, traffic-dense coastal streets with complex vertical structures of trees, and in the gaps of tall buildings dominated by road forests. Our results indicate that BSV photos could be used to virtually evaluate bird occurrence and nests from their numbers, spatial distribution and temporal dynamics. This method provides a pre-experimental and informative supplement to large-scale bird occurrence and nest abundance surveys in urban environments.
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Affiliation(s)
- Panli Tian
- Key Laboratory of Forest Plant Ecology, Northeast Forestry University, Harbin 150040, People's Republic of China
| | - Lei Wang
- Key Laboratory of Forest Plant Ecology, Northeast Forestry University, Harbin 150040, People's Republic of China
| | - Qi Li
- Key Laboratory of Forest Plant Ecology, Northeast Forestry University, Harbin 150040, People's Republic of China
| | - Chentao Liang
- Key Laboratory of Forest Plant Ecology, Northeast Forestry University, Harbin 150040, People's Republic of China
| | - Danqi She
- Key Laboratory of Forest Plant Ecology, Northeast Forestry University, Harbin 150040, People's Republic of China
| | - Siyu Liu
- State Key Laboratory of Subtropical Silviculture, College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou 311300, People's Republic of China
| | - Yuwen Chen
- Key Laboratory of Forest Plant Ecology, Northeast Forestry University, Harbin 150040, People's Republic of China
| | - Liuyang Yao
- Key Laboratory of Forest Plant Ecology, Northeast Forestry University, Harbin 150040, People's Republic of China
| | - Weiqi Wang
- School of Information Science and Technology, University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Huimei Wang
- State Key Laboratory of Subtropical Silviculture, College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou 311300, People's Republic of China
| | - Wenjie Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Science, Changchun 130102, People's Republic of China
- State Key Laboratory of Subtropical Silviculture, College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou 311300, People's Republic of China
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Yang Y, Zhong Z, Jing L, Li Q, Wang H, Wang W. Plant community phylogeny responses to protections and its main drivers in boreal forests, China: General pattern and implications. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 864:161151. [PMID: 36572317 DOI: 10.1016/j.scitotenv.2022.161151] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 12/04/2022] [Accepted: 12/19/2022] [Indexed: 06/17/2023]
Abstract
Patterns of the phylogenetic structure have been broadly applied to predict community assembly processes. However, the distribution pattern of evolutionary diversity and its drivers under nature conservation are still poorly understood in boreal forests. Here, we investigated 1738 sampling plots and subplots from distinct protection intensities (PIs) zones in five representative National Nature Reserves (NNRs). Multiple comparisons, redundancy analysis, and linear mixed model were performed to identify the changes in community phylogeny across different PIs and NNRs and the drivers for these variations. Our results showed considerable plant community phylogeny variations in different NNRs. As indicated by SesMPD (standardized mean pairwise distance) and SesMNTD (standardized the mean nearest taxon distance), trees, shrubs, and herbs presented overdispersed, clustered, and random distribution patterns, respectively, in different PIs. Protection resulted in the phylogenetic structure between the nearest species of trees showing a more overdispersed pattern (p < 0.05). Protection decreased the phylogenetically clustered degree between the nearest species of shrubs (p > 0.05), while the herbs still maintained a random pattern. Community traits explained the most to phylogeny variation of different communities (24 %-71 %, p < 0.01), followed by geoclimatic factors (2 %-24 %) and conservation processes (1 %-21 %). The higher mean annual precipitation and under branch height at the lower latitude area accompanied the higher SesMPD and SesMNTD. The higher PIs attended with higher tree SesMPD, and the longer protection time resulted in higher shrub PSR (phylogenetic species richness) and PSV (phylogenetic species variability). Including the location of NNRs, community traits, and years of protection, rather than only emphasizing PI itself, could optimize community phylogenetic structure and preserve the evolutionary potential of biodiversity.
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Affiliation(s)
- Yanbo Yang
- Key Laboratory of Forest Plant Ecology, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemistry Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Zhaoliang Zhong
- College of Resources & Environment, Jiujiang University, Jiujiang 332005, China
| | - Lixin Jing
- Key Laboratory of Forest Plant Ecology, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemistry Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Qi Li
- Key Laboratory of Forest Plant Ecology, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemistry Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
| | - Huimei Wang
- Key Laboratory of Forest Plant Ecology, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemistry Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China.
| | - Wenjie Wang
- Key Laboratory of Forest Plant Ecology, Heilongjiang Provincial Key Laboratory of Ecological Utilization of Forestry-based Active Substances, College of Chemistry, Chemistry Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China; Urban Forests and Wetland Group, Northeast Institute of Geography and Agroecology, Changchun 130102, China; State Key Laboratory of Subtropical Silviculture, College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou, 311300, China.
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