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A lifecycle model approach for predicting mangrove extent. | LitMetric

A lifecycle model approach for predicting mangrove extent.

Sci Total Environ

Water Research Laboratory, School of Civil and Environmental Engineering, UNSW, Sydney, NSW, Australia.

Published: November 2024

AI Article Synopsis

  • Tidal changes affect where mangroves grow, but we don't fully understand why some survive better than others in different areas.
  • A new model was created to study how Avicennia marina mangroves grow at different stages, focusing on important steps like reproduction and seedling survival.
  • This model was tested in Australia and showed that the health of mangroves depends on many factors, with estuaries that have less tidal change being better for their growth.

Article Abstract

Tidal dynamics are a well-known driver of mangrove distribution, with most predictive measures using some form of tidal parameter (tidal plane or hydroperiod) to define mangrove extent. However, these methods often fail to consider the causative reason why mangroves thrive or perish at a specific elevation or how mangrove survivability thresholds can differ across a species' lifecycle. The lack of understanding of the drivers influencing mangrove establishment has resulted in poor success rates for mangrove restoration and creation projects worldwide. A novel mangrove lifecycle model that uses a multi-forcing threshold approach is proposed to simulate Avicennia marina viability across establishment and development phases. The lifecycle model includes critical threshold stages for reproduction, seed dispersal, seedling establishment and development, and mature tree survival. The model was validated at 37 sites in eastern Australia to predict mangrove extent across various estuary types and tidal dynamic conditions. The model accurately calculated the upper (RMSE = 0.0676, R = 0.8932) and lower (RMSE = 0.0899, R = 0.7417) mangrove surface elevations, providing physiological reasoning for establishment and development. Based on the various conditions tested, the model results highlight the highly dynamic spatial and temporal conditions where Avicennia forests thrive. It was found that stressors influencing mangrove establishment were the primary factor for mangrove extent across all sites. However, estuarine typology is important in forcing threshold limits and establishment opportunities. Estuaries with limited tidal decay (from the oceanic forcing) provide more opportunities for mangroves to establish than estuaries with significant tidal attenuation. Regardless of estuary typology, all sites tested had substantial spatial variability through time. Results from the lifecycle model suggest that mature Avicennia forests establish and thrive under a wide range of hydrologic conditions. This resilience suggests that mature mangroves may be able to withstand increases in climatic and hydrologic pressures via biophysical adaptations, although the upper thresholds and acceptable rates of change are difficult to predict. Overall, this study highlights the value of a new causal method for estimating mangrove extent across various lifecycle stages, locations, and time periods.

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Source
http://dx.doi.org/10.1016/j.scitotenv.2024.175962DOI Listing

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