Macroecological patterns of forest structure and allometric scaling in mangrove forests

Global Ecology and Biogeography - Tập 30 Số 5 - Trang 1000-1013 - 2021
André Rovai1,2, Robert R. Twilley2, Edward Castañeda‐Moya3, Stephen R. Midway2, Daniel A. Friess4, Carl Trettin5, Jacob J. Bukoski6, Atticus Stovall7, Paulo Roberto Pagliosa1, Alessandra Fonseca1, Richard Mackenzie8, Aslan Aslan9, Sigit D. Sasmito10,11, Mériadec Sillanpää4,12, Thomas G. Cole13, J. Purbopuspito14, Matthew Warren15, Daniel Murdiyarso10,16, Wolfram Y. Mofu17, Sahadev Sharma18, Pham Hong Tinh19, Pablo Riul20
1Departamento de Oceanografia Universidade Federal de Santa Catarina Florianópolis Brazil
2Department of Oceanography and Coastal Sciences, College of the Coast & Environment, Louisiana State University, Baton Rouge, LA, USA
3Institute of Environment (OE 148), Florida International University, Miami, FL, USA
4Department of Geography, National University of Singapore, Singapore
5USDA Forest Service Southern Research Station, Cordesville, SC, USA
6Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, USA
7NASA Goddard Space Flight Center, Greenbelt, MD, USA
8Institute of Pacific Islands Forestry, Pacific Southwest Research Station, USDA Forest Service, Hilo, HI, USA
9Southeast Asian Regional Centre for Tropical Biology (SEAMEO BIOTROP), Bogor, Indonesia
10Center for International Forestry Research (CIFOR), Bogor, Indonesia
11Research Institute for the Environment and Livelihoods (RIEL), Charles Darwin University, Casuarina, Northern Territory, Australia
12Research Department, Green Forest Product and Tech. Pte. Ltd., Singapore, Singapore
13Department of Natural Resources and Environmental Management, University of Hawai‘i at Mānoa, Honolulu, HI, USA
14Soil Science Department, Faculty of Agriculture, Sam Ratulangi University, Kampus Kleak-Bahu, Manado, Indonesia
15Earth Innovation Institute, San Francisco, CA, USA
16Department of Geophysics and Meteorology, Institut Pertanian Bogor, Bogor, Indonesia
17Faculty of Forestry, University of Papua, Manokwari, Indonesia
18Institute of Ocean and Earth Sciences, University of Malaya, Kuala Lumpur, Malaysia
19Faculty of Environment, Hanoi University of Natural Resources and Environment, Hanoi, Viet Nam
20Departamento de Sistemática e Ecologia, Centro de Ciências Exatas e da Natureza, Universidade Federal da Paraíba, João Pessoa, Paraíba, Brazil

Tóm tắt

AbstractAim

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.

Location

Global.

Time period

Present.

Major taxa studied

Mangrove ecosystems.

Methods

We built the largest field‐based dataset on mangrove forest structure and biomass to date (c. 2,800 plots from 67 countries) to address macroecological questions pertaining to structural and functional diversity of mangroves spanning biogeographical and coastal morphology gradients. We used frequentist inference statistics and machine learning models to determine environmental drivers that control biomass allocation within and across mangrove communities globally.

Results

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.

Main conclusions

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.

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Tài liệu tham khảo

10.1371/journal.pone.0056569

10.1016/j.ecss.2009.10.013

10.1016/j.ecss.2020.106796

10.1007/s10265-008-0190-8

10.1038/nclimate3326

10.1007/s00468-002-0169-3

10.1088/1748-9326/ab7e4e

10.1007/s12237-020-00834-w

10.1016/j.scitotenv.2019.02.104

10.1073/pnas.1908597117

10.1016/j.foreco.2013.07.011

10.2307/1353075

10.1007/s10750-015-2178-4

10.1146/annurev-marine-010318-095333

10.1672/07-233.1

10.1007/978-3-319-62206-4_2

10.1007/s12237-011-9381-y

10.1007/s00468-001-0133-7

10.1038/25977

10.1038/35070500

10.1127/0340-269X/2003/0033-0251

10.1038/s41558-018-0225-7

10.2475/ajs.255.8.584

10.1111/j.1466-8238.2010.00584.x

10.1111/geb.12449

10.1038/s41558-018-0090-4

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

10.1111/conl.12060

10.1002/ecs2.2231

10.1016/j.rsma.2020.101375

10.1002/ecm.1405

10.1016/j.aquabot.2007.12.006

10.1007/s00468-012-0767-7

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

10.1071/FP11027

10.1007/s13157-020-01291-8

10.1002/ecm.1248

R Core Team, 2020, R: A language and environment for statistical computing

10.1016/S0025-3227(96)00111-9

10.1016/j.foreco.2020.118553

10.1111/geb.12409

10.1038/s41558-018-0162-5

10.2307/1351590

10.1038/s41561-018-0279-1

10.4324/9781849776608

10.3390/su10020472

10.1007/BF00477106

10.1002/fee.1937

10.1016/j.tree.2007.03.007

10.1017/S0266467400002431

10.1146/annurev-marine-122414-034025

WRI/IIED, 1986, World resources 1986