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Keywords:

  • Australia;
  • competition;
  • ecological niche model;
  • intertidal;
  • sea level rise;
  • species distribution;
  • species distribution model;
  • species dominance;
  • tidal regime;
  • tropical forest

Abstract

Aim

Many mangrove communities form bands parallel to the shoreline with each community dominated by a single species. However, the key determinants of mangrove species distribution across the intertidal zone are not well understood. We aimed to quantify the relationship between species' dominance and the hydroperiod (defined as the duration of inundation in a year), soil salinity and the salinity of inundating water for three dominant species, Sonneratia alba, Rhizophora stylosa and Ceriops tagal.

Location

An extensive (20,000 ha), largely intact mangrove forest in northern Australia, of some note as mangrove forests are threatened globally.

Methods

We related species dominance to the explanatory variables by applying two statistical modelling approaches: generalized linear models (GLMs), where a set of competing models were evaluated; and boosted regression tree models (BRTs), an approach that automatically captures interactions and nonlinear relationships between variables.

Results

Both GLM and BRT models achieved strong predictive performance for all species based on cross-validation, with receiver operating characteristics above 0.85 for all species, and 88% of deviance explained for S. alba, 42% for R. stylosa and 35% for C. tagal. All models indicated that the hydroperiod was the key variable influencing distribution, followed by soil salinity. The salinity of inundating water was the least informative variable in the models. Ecological space, determined by gradients in hydroperiod and soil salinity, was partitioned between the three species with little overlap.

Main conclusions

As anticipated changes in sea level will alter the hydroperiod, our findings are critical for global forecasting of future distributions of mangrove communities, and for the design of mitigation and adaptation measures.