Quadros, Aline F, Nordhaus, Inga, Reuter, Hauke ORCID: https://orcid.org/0000-0002-7751-9244 and Zimmer, Martin ORCID: https://orcid.org/0000-0002-1549-8871 (2019) Modelling of mangrove annual leaf litterfall with emphasis on the role of vegetation structure. Estuarine, Coastal and Shelf Science, 218 . pp. 292-299. DOI https://doi.org/10.1016/j.ecss.2018.12.012.

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Understanding local patterns of species-specific litterfall can help predict spatial differences in the amount and quality of organic matter input to systems under different environmental conditions. However, little is known about the drivers of differences in litterfall production in mangroves. Here we combined data from leaf litterfall (LL) studies (n = 13) and floristic studies (n = 16) conducted in the mangroves of the Ajuruteua peninsula (North of Brazil), at sites composed mainly of Rhizophora mangle and/or Avicennia germinans. We investigated the relationship between LL and vegetation parameters (height, diameter, basal area, density, and relative density) using partial least-squares regressions (PLS-R), building four models with different combinations of these parameters. Vegetation parameters explained 69–85% of the annual LL of A. germinans and 50–66% of R. mangle. Relatively strong, univariate significant relationships were also found between basal area and A. germinans LL (R2 = 0.40), and between height and R. mangle LL (R2 = 0.41). Nonetheless, models with four to five predictors yielded better fits. To illustrate the applicability of our approach we used the PLS-R models to calculate the LL of simulated sites. This simulation indicated a clear increase in LL production along the transition from Avicennia- to Rhizophora-dominated mangroves. As the leaf litter of these species differ substantially in chemical composition and decomposability, such transition in species composition will likely affect nutrient dynamics in the region. Thus, we suggest reporting species-specific site characteristics along with LL in future studies to obtain more robust models to predict future LL production at sites of changing vegetation structure.

Document Type: Article
Programme Area: UNSPECIFIED
Research affiliation: Integrated Modelling > Spatial Ecology and Interactions
Ecology > Mangrove Ecology
Refereed: Yes
Open Access Journal?: No
DOI: https://doi.org/10.1016/j.ecss.2018.12.012
ISSN: 02727714
Date Deposited: 17 Jun 2019 12:01
Last Modified: 01 Oct 2020 12:58
URI: http://cris.leibniz-zmt.de/id/eprint/2090

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