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Spatial differentiation of the leaf area index in forests in ecological transition zones and its environmental response

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Abstract

The leaf area index (LAI) is a crucial vegetation parameter that characterizes leaf sparsity and canopy structure, and the study of the spatial distribution pattern of the forest LAI and its environmental response can help to reveal the adaptive capacity of forest vegetation to climate change in semiarid areas. In this paper, a remote sensing inversion model of the LAI, which pertains to the forest ecosystem of Xinglong Mountain in the transition zone between the Qinghai‒Tibet Plateau and Loess Plateau, was established by combining an optical instrumentation method, a remote sensing inversion method, and a generalized additive model (GAM). The results showed that (1) the Meris terrestrial chlorophyll index (MTCI) linear regression model provided the greatest explanatory power for the LAI in the Xinglong Mountain forest, with R2 = 0.88 and RMSE = 0.32. (2) The LAI was influenced mainly by the altitude, slope, profile curvature, aspect, planform curvature, temperature, precipitation, and evapotranspiration. According to the single-factor GAM, altitude (R2 = 0.43) explained most of the total variation in the LAI, followed by precipitation (R2 = 0.36). According to the multifactor GAM, the above influencing factors could explain 84.2% of the total variation in the LAI, which was significant (P < 0.001). (3) Interaction analysis revealed that the LAI was significantly influenced by the interaction between topographic and meteorological factors (P < 0.001). It was revealed that the topography of Xinglong Mountain is fragmented, the vertical band spectrum of vegetation is notable, and the forest LAI exhibits high spatial heterogeneity under the interaction between topographic and meteorological factors, reflecting the environmental response mechanism of vegetation growth in forest ecosystems in ecological transition zones.

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The datasets generated and analysed in this study are available from the corresponding author upon reasonable request.

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References

  • Ahlström A, Xia J, Arneth A, Luo Y, Smith B (2015) Importance of vegetation dynamics for future terrestrial carbon cycling. Environ Res Lett 10:054019

    Google Scholar 

  • Allevato E, Saulino L, Cesarano G, Chirico GB, D’Urso G, Falanga Bolognesi S, Rita A, Rossi S, Saracino A, Bonanomi G (2019) Canopy damage by spring frost in European beech along the Apennines: effect of latitude, altitude and aspect. Remote Sens Environ 225:431–440

    Google Scholar 

  • Barnes EM, Clarke TR, Richards SE, Colaizzi PD, Thompson T (2000) Coincident detection of crop water stress, nitrogen status, and canopy density using ground based multispectral data. In: Proceedings of the 5th International Conference on Precision Agriculture and other resource management July 16–19, 2000, Bloomington, MN USA

  • Birth GS, Mcvey GRJAJ (1968) Measuring the color of growing turf with a reflectance spectrophotometer. Agro J 60:640–643

    Google Scholar 

  • Cao B, Du YM, Li J, Li H, Li L, Zhang Y, Zou J, Liu QH (2015) Comparison of five slope correction methods for leaf area index estimation from hemispherical photography. IEEE Geosci Remote Sens Lett 12:1958–1962

    Google Scholar 

  • Chen JM, Cihlar J (1996) Retrieving leaf area index of boreal conifer forests using Landsat TM images. Remote Sens Environ 55:153–162

    Google Scholar 

  • Chen W, Li A, Hu Y, Li L, Zhao H, Han X, Yang B (2021) Exploring the long-term vegetation dynamics of different ecological zones in the farming-pastoral ecotone in northern China. Environ Sci Pollut Res Int 28:27914–27932

    PubMed  Google Scholar 

  • Chen JM, Cihlar J (1995) Quantifying the effect of canopy architecture on optical measurements of leaf area index using two gap size analysis methods. IEEE Trans Geosci Remote Sens

  • Clevers JGPW (1989) Application of a weighted infrared-red vegetation index for estimating leaf area index by correcting for soil moisture. Remote Sens Environ 29:25–37

    Google Scholar 

  • Compton JTJ (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ 8:127

    Google Scholar 

  • Dash J, Curran PJ (2010) The MERIS terrestrial chlorophyll index. Int J Remote Sens 25:5403–5413

    Google Scholar 

  • Daughtry C, Walthall CL, Kim MS, Colstoun E, Iii MM (2000) Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance. Remote Sens Environ 74:229–239

    Google Scholar 

  • Fang H, Baret F, Plummer S, Schaepman-Strub G (2019) An overview of global leaf area index (LAI): methods, products, validation, and applications. Rev Geophys 57:739–799

    Google Scholar 

  • Feng X, Fu B, Piao S, Wang S, Ciais P, Zeng Z, Lü Y, Zeng Y, Li Y, Jiang X, Wu B (2016) Revegetation in China’s Loess Plateau is approaching sustainable water resource limits. Nat Clim Chang 6:1019–1022

    Google Scholar 

  • Fengping Y, Zhaoyong H, Lin H, Jing C, Cui C, Zhang SX (2014) The relationship between net productivity of tree layers and climate factors in Pinus tabulaeformis and Pinus armandii forests in Huoditang forest area of Qinling Mountains. Acta Ecol Sin 34:12

    Google Scholar 

  • Fu B (2022) Ecological and environmental effects of land-use changes in the Loess Plateau of China. Chin Sci Bull 67:3769–3779

    Google Scholar 

  • Fu B, Wang S, Liu Y, Liu J, Liang W, Miao C (2017) Hydrogeomorphic ecosystem responses to natural and anthropogenic changes in the Loess Plateau of China. Annu Rev Earth Planet Sci 45:223–243

    CAS  Google Scholar 

  • Gao M, Piao S, Chen A, Yang H, Liu Q, Fu YH, Janssens IA (2019) Divergent changes in the elevational gradient of vegetation activities over the last 30 years. Nat Commun 10:2970

    PubMed  PubMed Central  Google Scholar 

  • Gitelson AA, Gritz Y, Merzlyak MN (2003) Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. J Plant Physiol 160:271–282

    CAS  PubMed  Google Scholar 

  • Gitelson AA, Kaufman YJ, Merzlyak MN (1996) Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sens Environ 58:289–298

    Google Scholar 

  • Gitelson AA, Viña A, Verma SB, Rundquist DC, Arkebauer TJ, Keydan G, Leavitt B, Ciganda V, Burba GG, Suyker AE (2006) Relationship between gross primary production and chlorophyll content in crops: Implications for the synoptic monitoring of vegetation productivity. J Geophys Res 111

  • Gonsamo A, Walter J-MN, Pellikka P (2011) CIMES: A package of programs for determining canopy geometry and solar radiation regimes through hemispherical photographs. Comput Electron Agric 79:207–215

    Google Scholar 

  • Gutiérrez-Jurado HA, Vivoni ER, Cikoski C, Harrison JBJ, Bras RL, Istanbulluoglu E (2013) On the observed ecohydrologic dynamics of a semiarid basin with aspect-delimited ecosystems. Water Resour Res 49:8263–8284

    Google Scholar 

  • Haboudane D (2004) Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modeling and validation in the context of precision agriculture. Remote Sens Environ 90:337–352

    Google Scholar 

  • Han C, Liu Y, Zhang C, Li Y, Zhou T, Khan S, Chen N, Zhao C (2021) Effects of three coniferous plantation species on plant-soil feedbacks and soil physical and chemical properties in semi-arid mountain ecosystems. Forest Ecosyst 8:1

    Google Scholar 

  • Hashimoto H, Wang W, Milesi C, White MA, Ganguly S, Gamo M, Hirata R, Myneni RB, Nemani RR (2012) Exploring simple algorithms for estimating gross primary production in forested areas from satellite data. Remote Sens 4:303–326

    Google Scholar 

  • Hastie T, Tibshirani R (2014) Generalized additive models. Wiley StatsRef: Statistics Reference Online

  • Houborg R, McCabe MF, Cescatti A, Gitelson AA (2015) Leaf chlorophyll constraint on model simulated gross primary productivity in agricultural systems. Int J Appl Earth Observ Geoinf 43:160–176

    Google Scholar 

  • Huang J, Guan X, Ji F (2012) Enhanced cold-season warming in semi-arid regions. Atmos Chem Phys 12:5391–5398

    CAS  Google Scholar 

  • Jia B, Guo W, He J, Sun M, Chai L, Liu J, Wang X (2022) Topography, diversity, and forest structure attributes drive aboveground carbon storage in different forest types in Northeast China. Forests 13:455

    Google Scholar 

  • Kaminski T, Scholze M, Vossbeck M, Knorr W, Buchwitz M, Reuter M (2017) Constraining a terrestrial biosphere model with remotely sensed atmospheric carbon dioxide. Remote Sens Environ 203:109–124

    Google Scholar 

  • Keyser AR, Kimball JS, Nemani RR, Running SW (2000) Simulating the effects of climate change on the carbon balance of North American high-latitude forests. Glob Change Biol 6:185

    CAS  Google Scholar 

  • Leblanc SG, Chen JM, Fernandes R, Deering DW, Conley A (2005) Methodology comparison for canopy structure parameters extraction from digital hemispherical photography in boreal forests. Agric for Meteorol 129:187–207

    Google Scholar 

  • Leuning R, Zhang YQ, Rajaud A, Cleugh H, Tu K (2008) A simple surface conductance model to estimate regional evaporation using MODIS leaf area index and the Penman-Monteith equation. Water Resour Res 44

  • Liu J, Pattey E, Jégo G (2012) Assessment of vegetation indices for regional crop green LAI estimation from Landsat images over multiple growing seasons. Remote Sens Environ 123:347–358

    Google Scholar 

  • Liu Z, Chen JM, Jin G, Qi Y (2015) Estimating seasonal variations of leaf area index using litterfall collection and optical methods in four mixed evergreen–deciduous forests. Agric for Meteorol 209–210:36–48

    Google Scholar 

  • Liu F, Wang C, Wang X (2021) Sampling protocols of specific leaf area for improving accuracy of the estimation of forest leaf area index. Agric for Meteorol 298–299:108286

    Google Scholar 

  • Park J, Kim HS, Jo HK, Jung IIB (2019) The influence of tree structural and species diversity on temperate forest productivity and stability in Korea. Forests 10:1113

    Google Scholar 

  • Pfeifer M, Gonsamo A, Disney M, Pellikka P, Marchant R (2012) Leaf area index for biomes of the Eastern Arc Mountains: Landsat and SPOT observations along precipitation and altitude gradients. Remote Sens Environ 118:103–115

    Google Scholar 

  • Piao S, Wang X, Park T, Chen C, Lian X, He Y, Bjerke JW, Chen A, Ciais P, Tømmervik H, Nemani RR, Myneni RB (2019) Characteristics, drivers and feedbacks of global greening. Nat Rev Earth Environ 1:14–27

    Google Scholar 

  • Potithep S, Nagai S, Nasahara KN, Muraoka H, Suzuki R (2013) Two separate periods of the LAI–VIs relationships using in situ measurements in a deciduous broadleaf forest. Agric for Meteorol 169:148–155

    Google Scholar 

  • Qiang W, Lei L, Mountain C, Guangzhong Z, Peibin Y, Jixin T, Ecology, X.R. (2012). Soil physicochemical properties during forest succession in Xinglong Mountain, Gansu Province, 32:4700-4713

  • Qiu Z, Feng Z, Song Y, Li M, Zhang P (2020) Carbon sequestration potential of forest vegetation in China from 2003 to 2050: predicting forest vegetation growth based on climate and the environment. J Clean Product 252:119715

    Google Scholar 

  • Rouse JW, Haas RH, Schell JA, Deering DW (1974) Monitoring vegetation systems in the great plains with erts. NASA Spec Publ 351:309

    Google Scholar 

  • Shang J, Liu J, Huffman T, Qian B, Pattey E, Wang J, Zhao T, Geng X, Kroetsch D, Dong T, Lantz N (2014) Estimating plant area index for monitoring crop growth dynamics using Landsat-8 and RapidEye images. J Appl Remote Sens 8:085196

    Google Scholar 

  • Shirong L (1998) Prediction of net primary productivity of forests in China in response to climate change

  • Sims DA, Gamon JA (2002) Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remore Sens Environ 81:337–354

    Google Scholar 

  • Su J, Huang T, Zhao H, Li X (2023) Spatial and temporal dynamics of base flow in semi-arid montane watersheds and the effects of landscape patterns and topography. Environ Monit Assess 195:581

    CAS  PubMed  Google Scholar 

  • Sun H, Wang Q, Wang G, Lin H, Luo P, Li J, Zeng S, Xu X, Ren L (2018) Optimizing kNN for mapping vegetation cover of arid and semi-arid areas using landsat images. Remote Sens 10:1248

    Google Scholar 

  • Sun Y, Qin Q, Ren H, Zhang T, Chen S (2020) Red-edge band vegetation indices for leaf area index estimation from sentinel-2/MSI imagery. IEEE Trans Geosci Remote Sens 58:826–840

    Google Scholar 

  • Svenning JC, Sandel B (2013) Disequilibrium vegetation dynamics under future climate change. Am J Bot 100:1266–1286

    PubMed  Google Scholar 

  • Viña A, Gitelson AA, Nguy-Robertson AL, Peng Y (2011) Comparison of different vegetation indices for the remote assessment of green leaf area index of crops. Remote Sens Environ 115:3468–3478

    Google Scholar 

  • Wang Y, Peng D, Shen M, Xu X, Yang X, Huang W, Yu L, Liu L, Li C, Li X, Zheng S, Zhang H (2020) Contrasting effects of temperature and precipitation on vegetation greenness along elevation gradients of the Tibetan Plateau. Remote Sens 12:2751

    Google Scholar 

  • Westervelt DM, Horowitz LW, Naik V, Tai APK, Fiore AM, Mauzerall DL (2016) Quantifying PM2.5-meteorology sensitivities in a global climate model. Atmos Environ 142:43–56

    CAS  Google Scholar 

  • Wigmosta MS, Vail LW, Lettenmaier DP (1994) A distributed hydrology-vegetation model for complex terrain. Water Resour Res 30:1665–1679

    Google Scholar 

  • Willmer JNG, Püttker T, Prevedello JA (2022) Global impacts of edge effects on species richness. Biol Conserv 272:109654

    Google Scholar 

  • Wu Z, Zhang S (2018) Study on the spatial–temporal change characteristics and influence factors of fog and haze pollution based on GAM. Neural Comput Appl 31:1619–1631

    Google Scholar 

  • Wu C, Niu Z, Tang Q, Huang W (2008) Estimating chlorophyll content from hyperspectral vegetation indices: modeling and validation. Agric for Meteorol 148:1230–1241

    Google Scholar 

  • Xu Z, Man X, Cai T, Shang Y (2022) How potential evapotranspiration regulates the response of canopy transpiration to soil moisture and leaf area index of the Boreal Larch Forest in China. Forests 13:571

    Google Scholar 

  • You Q, Chen D, Wu F, Pepin N, Cai Z, Ahrens B, Jiang Z, Wu Z, Kang S, AghaKouchak A (2020) Elevation dependent warming over the Tibetan Plateau: patterns, mechanisms and perspectives. Earth-Sci Rev 210:103349

    Google Scholar 

  • Yuqing X, Fengjin X, Li Y (2022) Review on the spatiotemporal distribution of net primary productivity of forest ecosystems in China and its response to climate change

  • Zellweger F, Coomes D, Lenoir J, Depauw L, Maes SL, Wulf M, Kirby KJ, Brunet J, Kopecky M, Malis F, Schmidt W, Heinrichs S, den Ouden J, Jaroszewicz B, Buyse G, Spicher F, Verheyen K, De Frenne P (2019) Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe. Glob Ecol Biogeogr 28:1774–1786

    PubMed  PubMed Central  Google Scholar 

  • Zhang Y, Ta N, Guo S, Chen Q, Zhao L, Li F, Chang Q (2022) Combining spectral and textural information from UAV RGB images for leaf area index monitoring in Kiwifruit orchard. Remote Sens 14:253

    Google Scholar 

  • Zhang X, Shao Q, Wang B, Niu X, Ning J, Chen M, Zhang T, Liu G, Liu S, Niu L, Huang H (2023) Spatiotemporal analysis of ecosystem status in China’s national key ecological function zones. Remote Sens 15:4641

    Google Scholar 

  • Zhou T, Du W, Wang J, Zhang L, Gao J, Shi N, Wang L, Wu Y, Tian B (2023) Divergent responses of plant functional traits and biomass allocation to slope aspects in four perennial herbs of the alpine meadow ecosystem. Front Plant Sci 14:1092821

    PubMed  PubMed Central  Google Scholar 

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Funding

This study was supported by the National Natural Science Foundation of China (NSFC) under the project "Formation mechanism and spatial and temporal variations in the integrated vegetation carrying capacity on the Loess Plateau arid and water-scarce zone" (U21A2005), the project of the Gansu Xinglong Mountain Forest Ecosystem National Positioning Observation and Research Station (2022132261), and the project of “Spatial pattern and environmental response of the root architecture of main plants in inland salt marsh wetlands” (41861009).

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Authors and Affiliations

  1. Gansu Province Wetland Resources Protection and Industrial Development Engineering Research Center, College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou, 730100, Gansu, China

    Geyang Li, Chengzhang Zhao, Dingyue Liu, Chenglu Huang, Peixian Zhang, Suhong Wang & Xianshi Wu

  2. Xinglongshan Forest Ecosystem National Positioning Observation and Research Station, Lanzhou, 730100, China

    Lei Ling

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  1. Geyang Li
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Contributions

Chengzhang Zhao and Geyang Li: Formulation of the overarching research goals and aims. Geyang Li: Data analysis and manuscript writing. Geyang Li and Dingyue Liu: Visualization. Geyang Li, Dingyue Liu, Lei Lin, Chenglu Huang, Peixian Zhang, Suhong Wang, Xianshi Wu: Investigation. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Chengzhang Zhao.

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Li, G., Zhao, C., Liu, D. et al. Spatial differentiation of the leaf area index in forests in ecological transition zones and its environmental response. Eur J Forest Res 143, 1307–1320 (2024). https://doi.org/10.1007/s10342-024-01682-0

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