Macroecological patterns of forest structure and allometric scaling in mangrove forests
Tóm tắt
Mangrove wetlands span broad geographical gradients, resulting in functionally diverse tree communities. We asked whether latitudinal variation, allometric scaling relationships and species composition influence mangrove forest structure and biomass allocation across biogeographical regions and distinct coastal morphologies.
Global.
Present.
Mangrove ecosystems.
We built the largest field‐based dataset on mangrove forest structure and biomass to date (
Allometric scaling relationships and forest structural complexity were consistent across biogeographical and coastal morphology gradients, suggesting that mangrove biomass is controlled by regional forcings rather than by latitude or species composition. For instance, nearly 40% of the global variation in biomass was explained by regional climate and hydroperiod, revealing nonlinear thresholds that control biomass accumulation across broad geographical gradients. Furthermore, we found that ecosystem‐level carbon stocks (average 401 ± 48 MgC/ha, covering biomass and the top 1 m of soil) varied little across diverse coastal morphologies, reflecting regional bottom‐up geomorphic controls that shape global patterns in mangrove biomass apportioning.
Our findings reconcile views of wetland and terrestrial forest macroecology. Similarities in stand structural complexity and cross‐site size–density relationships across multiscale environmental gradients show that resource allocation in mangrove ecosystems is independent of tree size and invariant to species composition or latitude. Mangroves follow a universal fractal‐based scaling relationship that describes biomass allocation for several other terrestrial tree‐dominated communities. Understanding how mangroves adhere to these universal allometric rules can improve our ability to account for biomass apportioning and carbon stocks in response to broad geographical gradients.
Từ khóa
Tài liệu tham khảo
Hijmans R. J.(2020).raster: Geographic data analysis and modeling. R package. 249.https://CRAN.R‐project.org/package=raster
Holdridge L., 1971, Forest environments in tropical life zones: A pilot study
Krauss K. W., 2020, Tropical cyclones and the organization of mangrove forests: A review, Annals of Botany, 125, 213
Liaw A., 2002, Classification and regression by randomForest, R News, 2, 18
R Core Team, 2020, R: A language and environment for statistical computing
WRI/IIED, 1986, World resources 1986