{"title":"Characterizing the vertical variability of canopy structure from space: Implications for biodiversity, productivity, and ecosystem functioning","authors":"Trupti Satapathy, Debsunder Dutta","doi":"10.1016/j.agrformet.2025.110710","DOIUrl":null,"url":null,"abstract":"<div><div>The vertical variability of canopy structure plays a crucial role in regulating turbulent flux exchange, biodiversity, and ecosystem functioning. However, accurately measuring this variability over large areas is challenging. We utilize the Global Ecosystem Dynamics Investigation (GEDI) data to characterize the spatio-temporal variability of canopy structure across India’s diverse forest ecosystems for the first time. The GEDI-derived canopy metrics exhibited right-skewness, bimodality, and left-skewness influenced by growth patterns, seasonality, human activities, and climate. The Plant Area Volume Density (PAVD) data from GEDI was used to fit the shape parameters of the beta distribution function, effectively estimating the vertical variability of canopy structure using minimal data. The results show that the beta distribution function shape parameters accurately captured the vertical variability of canopy structure across different biomes (<span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> = 0.76 to 0.87, RMSE= 0.1 to 0.2). Clustering the beta distribution parameters identified six distinct foliage profiles in India, which affected radiation interception both diurnally and seasonally at various canopy heights. Further, multivariate functional diversity indices, such as functional richness and functional divergence, captured the combined effects of canopy structural attributes including canopy height, density, complexity, and vertical heterogeneity on biodiversity and productivity. A significant correlation (r = 0.35–0.668, p <span><math><mo>≤</mo></math></span> 0.05) was observed between these improved functional diversity metrics and above-ground biomass density across India’s forested regions. Additionally, we found that these functional diversity metrics are influenced by various environmental factors like climate, soil, and topography, which differ across forested regions. These findings enhance our understanding of the complex relationships between canopy structure, the environment, and productivity across India’s biomes and forest ecosystems from spaceborne observations.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"372 ","pages":"Article 110710"},"PeriodicalIF":5.6000,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural and Forest Meteorology","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168192325003302","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 0
Abstract
The vertical variability of canopy structure plays a crucial role in regulating turbulent flux exchange, biodiversity, and ecosystem functioning. However, accurately measuring this variability over large areas is challenging. We utilize the Global Ecosystem Dynamics Investigation (GEDI) data to characterize the spatio-temporal variability of canopy structure across India’s diverse forest ecosystems for the first time. The GEDI-derived canopy metrics exhibited right-skewness, bimodality, and left-skewness influenced by growth patterns, seasonality, human activities, and climate. The Plant Area Volume Density (PAVD) data from GEDI was used to fit the shape parameters of the beta distribution function, effectively estimating the vertical variability of canopy structure using minimal data. The results show that the beta distribution function shape parameters accurately captured the vertical variability of canopy structure across different biomes ( = 0.76 to 0.87, RMSE= 0.1 to 0.2). Clustering the beta distribution parameters identified six distinct foliage profiles in India, which affected radiation interception both diurnally and seasonally at various canopy heights. Further, multivariate functional diversity indices, such as functional richness and functional divergence, captured the combined effects of canopy structural attributes including canopy height, density, complexity, and vertical heterogeneity on biodiversity and productivity. A significant correlation (r = 0.35–0.668, p 0.05) was observed between these improved functional diversity metrics and above-ground biomass density across India’s forested regions. Additionally, we found that these functional diversity metrics are influenced by various environmental factors like climate, soil, and topography, which differ across forested regions. These findings enhance our understanding of the complex relationships between canopy structure, the environment, and productivity across India’s biomes and forest ecosystems from spaceborne observations.
期刊介绍:
Agricultural and Forest Meteorology is an international journal for the publication of original articles and reviews on the inter-relationship between meteorology, agriculture, forestry, and natural ecosystems. Emphasis is on basic and applied scientific research relevant to practical problems in the field of plant and soil sciences, ecology and biogeochemistry as affected by weather as well as climate variability and change. Theoretical models should be tested against experimental data. Articles must appeal to an international audience. Special issues devoted to single topics are also published.
Typical topics include canopy micrometeorology (e.g. canopy radiation transfer, turbulence near the ground, evapotranspiration, energy balance, fluxes of trace gases), micrometeorological instrumentation (e.g., sensors for trace gases, flux measurement instruments, radiation measurement techniques), aerobiology (e.g. the dispersion of pollen, spores, insects and pesticides), biometeorology (e.g. the effect of weather and climate on plant distribution, crop yield, water-use efficiency, and plant phenology), forest-fire/weather interactions, and feedbacks from vegetation to weather and the climate system.