[1]

Chen H, Tang M, Ye H, Yuan F. 1999. Niche of bark beetles within Pinus armandi ecosystem in inner Qinling Mountains. Scientia Silvae Sinicae 35:41−45
[2]

Chen H, Tang M, Liu L, Wang HZ, Li ZB. 2007. Cytochemical localization of acid phosphatase activity in tissues of Pinus armandi infected by Leptographium qinlingensis. Symbiosis 43:65−70
[3]

Wang H, Hou P, Jiang J, Xiao R, Zhai J, et al. 2020. Ecosystem health assessment of Shennongjia National Park, China. Sustainability 12:7672

doi: 10.3390/su12187672
[4]

Ning H, Dai L, Fu D, Liu B, Wang H, et al. 2019. Factors influencing the geographical distribution of Dendroctonus armandi (Coleoptera: Curculionidae: Scolytidae) in China. Forests 10:425

doi: 10.3390/f10050425
[5]

Hong C, Bai B, Yi J. 2021. Risk analysis of Dendroctonus armandi in Shennongjia Forestry District. Forest Pest and Disease 40:17−22

doi: 10.19688/j.cnki.issn1671-0886.20200057
[6]

Cui H, Hu W, Tang W, Yang J, Yu H. 2022. Comparison of climatic characteristics inside and outside Pinus armandii forest in Shennongjia. Hubei Forestry Science and Technology 51:1−5

doi: 10.3969/j.issn.1004-3020.2022.02.002
[7]

Ning H, Tang M, Chen H. 2021. Impact of climate change on potential distribution of chinese white pine beetle Dendroctonus armandi in China. Forests 12:544

doi: 10.3390/f12050544
[8]

Bao Y, Han A, Zhang J, Liu X, Tong Z, et al. 2022. Contribution of the synergistic interaction between topography and climate variables to pine caterpillar (Dendrolimus spp.) outbreaks in Shandong Province, China. Agricultural and Forest Meteorology 322:109023

doi: 10.1016/j.agrformet.2022.109023
[9]

Hodkinson ID. 2005. Terrestrial insects along elevation gradients: species and community responses to altitude. Biological Reviews 80:489−513

doi: 10.1017/S1464793105006767
[10]

Guo H, He H, Li M. 2005. Study on the Relationship between the damage of Dendroctonus Valens LeConte and forest habitat condition. Acta Agriculturae Boreali-occidentalis Sinica 14:153−57

doi: 10.3969/j.issn.1004-1389.2005.04.039
[11]

Sultson SM, Goroshko AA, Verkhovets SV, Mikhaylov PV, Ivanov VA, et al. 2021. Orographic factors as a predictor of the spread of the siberian silk moth outbreak in the mountainous southern taiga forests of Siberia. Land 10:115

doi: 10.3390/land10020115
[12]

Guyot V, Jactel H, Imbaud B, Burnel L, Castagneyrol B, et al. 2019. Tree diversity drives associational resistance to herbivory at both forest edge and interior. Ecology and Evolution 9:9040−51

doi: 10.1002/ece3.5450
[13]

Hui G, Zhang G, Zhao Z, Yang A. 2019. Methods of forest structure research: a review. Current Forestry Reports 5:142−54

doi: 10.1007/s40725-019-00090-7
[14]

Jactel H, Moreira X, Castagneyrol B. 2021. Tree diversity and forest resistance to insect pests: patterns, mechanisms and prospects. Annual Review of Entomology 66:277−96

doi: 10.1146/annurev-ento-041720-075234
[15]

Montagnini F, González E, Porras C, Rheingans R. 1995. Mixed and pure forest plantations in the humid neotropics: a comparison of early growth, pest damage and establishment costs. The Commonwealth Forestry Review 74:306−14
[16]

Chen H, Tang M. 2007. Spatial and temporal dynamics of bark beetles in Chinese white pine in Qinling mountains of Shaanxi Province, China. Environmental Entomology 36:1124−30

doi: 10.1093/ee/36.5.1124
[17]

Kan Y, Shao H, Du C, Guo Y, Dai X. 2024. Comparison of the distribution of evapotranspiration on shady and sunny slopes in southwest China. Remote Sensing 16:4310

doi: 10.3390/rs16224310
[18]

Han J, Yin H, Xue J, Zhang Z, Xing Z, et al. 2023. Vertical distribution differences of the understory herbs and their driving factors on shady and sunny slopes in high altitude mountainous areas. Frontiers in Forests and Global Change 6:1138317

doi: 10.3389/ffgc.2023.1138317
[19]

Bo B, Yi J, Cui E, Hong C, Han J. 2023. Overview on prevention and control technology of Dendroctonus armandi. Hubei Forestry Science and Technology 52:68−72

doi: 10.3969/j.issn.1004-3020.2023.05.013
[20]

Pommerening A. 2006. Evaluating structural indices by reversing forest structural analysis. Forest Ecology and Management 224:266−77

doi: 10.1016/j.foreco.2005.12.039
[21]

Gonsamo A, D'odorico P, Pellikka P. 2013. Measuring fractional forest canopy element cover and openness – definitions and methodologies revisited. Oikos 122:1283−91

doi: 10.1111/j.1600-0706.2013.00369.x
[22]

Bettinger P, Tang M. 2015. Tree-level harvest optimization for structure-based forest management based on the species mingling index. Forests 6:1121−44

doi: 10.3390/f6041121
[23]

Mokkink LB, de Vet H, Diemeer S, Eekhout I. 2023. Sample size recommendations for studies on reliability and measurement error: an online application based on simulation studies. Health Services and Outcomes Research Methodology 23:241−65

doi: 10.1007/s10742-022-00293-9
[24]

McKenzie Z. 2024. A reconstruction and comparison of Grand Bahama pine forest age during the pre-major hurricane era using ridge regression and nested linear mixed-effects model. Trees, Forests and People 18:100723

doi: 10.1016/j.tfp.2024.100723
[25]

Kumar R, Nandy S, Agarwal R, Kushwaha SPS. 2014. Forest cover dynamics analysis and prediction modeling using logistic regression model. Ecological Indicators 45:444−55

doi: 10.1016/j.ecolind.2014.05.003
[26]

Mulder O, Sleith R, Mulder K, Coe NR. 2020. A Bayesian analysis of topographic influences on the presence and severity of beech bark disease. Forest Ecology and Management 472:118198

doi: 10.1016/j.foreco.2020.118198
[27]

Zhao CM, Chen WL, Tian ZQ, Xie ZQ. 2005. Altitudinal pattern of plant species diversity in Shennongjia Mountains, Central China. Journal of Integrative Plant Biology 47:1431−49

doi: 10.1111/j.1744-7909.2005.00164.x
[28]

Barton MG, Terblanche JS. 2014. Predicting performance and survival across topographically heterogeneous landscapes: the global pest insect Helicoverpa armigera (Hübner, 1808) (Lepidoptera: Noctuidae). Austral Entomology 53:249−58

doi: 10.1111/aen.12108
[29]

Haynes KJ, Bjørnstad ON, Allstadt AJ, Liebhold AM. 2013. Geographical variation in the spatial synchrony of a forest-defoliating insect: isolation of environmental and spatial drivers. Proceedings of the Royal Society B: Biological Sciences 280:20122373

doi: 10.1098/rspb.2012.2373
[30]

Castagneyrol B, Régolini M, Jactel H. 2014. Tree species composition rather than diversity triggers associational resistance to the pine processionary moth. Basic and Applied Ecology 15:516−23

doi: 10.1016/j.baae.2014.06.008
[31]

Zheng LL, Song M, Yin T, Yu FH. 2016. Feeding preference of Gynaephora menyuanensis and its relationships with plant carbon and nitrogen contents in an alpine meadow on the Tibetan Plateau. Acta Ecologica Sinica 36:2319−26

doi: 10.5846/stxb201410081973
[32]

Véle A, Horák J. 2018. The importance of host characteristics and canopy openness for pest management in urban forests. Urban Forestry & Urban Greening 36:84−89

doi: 10.1016/j.ufug.2018.10.012
[33]

Drake VA, Farrow RA. 1988. The influence of atmospheric structure and motions on insect migration. Annual Review of Entomology 33:183−210

doi: 10.1146/annurev.en.33.010188.001151
[34]

Fettig CJ, Klepzig KD, Billings RF, Munson AS, Nebeker TE, et al. 2007. The effectiveness of vegetation management practices for prevention and control of bark beetle infestations in coniferous forests of the western and southern United States. Forest Ecology and Management 238:24−53

doi: 10.1016/j.foreco.2006.10.011
[35]

Bouget C, Duelli P. 2004. The effects of windthrow on forest insect communities: a literature review. Biological Conservation 118:281−99

doi: 10.1016/j.biocon.2003.09.009
[36]

Zhang J, Zhao J, Cheng R, Ge Z, Zhang Z. 2022. Effects of neighborhood competition and stand structure on the productivity of pure and mixed Larix principis-rupprechtii forests. Forests 13:1318

doi: 10.3390/f13081318
[37]

Thomas E, Jalonen R, Loo J, Boshier D, Gallo L, et al. 2014. Genetic considerations in ecosystem restoration using native tree species. Forest Ecology and Management 333:66−75

doi: 10.1016/j.foreco.2014.07.015
[38]

Berthelot S, Frühbrodt T, Hajek P, Nock CA, Dormann CF, et al. 2021. Tree diversity reduces the risk of bark beetle infestation for preferred conifer species, but increases the risk for less preferred hosts. Journal of Ecology 109:2649−61

doi: 10.1111/1365-2745.13672
[39]

Shi W, Zeng W, Aritsara AN, Yi Y, Zhu S, et al. 2024. The interaction between climate and soil properties influences tree species richness in tropical and subtropical forests of Southern China. Forests 15:1441

doi: 10.3390/f15081441
[40]

Katzmarzyk PT, Denstel KD, Martin CK, Newton RL Jr, Apolzan JW, et al. 2022. Intraclass correlation coefficients for weight loss cluster randomized trials in primary care: The PROPEL trial. Clinical Obesity 12:e12524

doi: 10.1111/cob.12524
[41]

Bolker BM, Brooks ME, Clark CJ, Geange SW, Poulsen JR, et al. 2009. Generalized linear mixed models: a practical guide for ecology and evolution. Trends in Ecology & Evolution 24:127−35

doi: 10.1016/j.tree.2008.10.008
[42]

Sabatini FM, Jiménez-Alfaro B, Burrascano S, Lora A, Chytrý M. 2018. Beta-diversity of central European forests decreases along an elevational gradient due to the variation in local community assembly processes. Ecography 41:1038−48

doi: 10.1111/ecog.02809
[43]

Dupont E, Wood SN, Augustin NH. 2022. Spatial+: a novel approach to spatial confounding. Biometrics 78:1279−90

doi: 10.1111/biom.13656