Distribution and drivers of global mangrove forest change, 1996–2010

Abstract

For the period 1996-2010, we provide the first indication of the drivers behind mangrove land cover and land use change across the (pan-)tropics using time-series Japanese Earth Resources Satellite (JERS-1) Synthetic Aperture Radar (SAR) and Advanced Land Observing Satellite (ALOS) Phased Array-type L-band SAR (PALSAR) data. Multi-temporal radar mosaics were manually interpreted for evidence of loss and gain in forest extent and its associated driver. Mangrove loss as a consequence of human activities was observed across their entire range. Between 1996-2010 12% of the 1168 1°x1° radar mosaic tiles examined contained evidence of mangrove loss, as a consequence of anthropogenic degradation, with this increasing to 38% when combined with evidence of anthropogenic activity prior to 1996. The greatest proportion of loss was observed in Southeast Asia, whereby approximately 50% of the tiles in the region contained evidence of mangrove loss, corresponding to 18.4% of the global mangrove forest tiles. Southeast Asia contained the greatest proportion (33.8%) of global mangrove forest. The primary driver of anthropogenic mangrove loss was found to be the conversion of mangrove to aquaculture/agriculture, although substantial advance of mangroves was also evident in many regions.

The state of the world’s mangroves in the 21st century under climate change

“…The scale of mangrove conversion to aquaculture has been historically dramatic, with an estimated 140,000 ha of mangrove lost to conversion in the 1950s-1980s (Primavera, 2000). A global-scale quantitative assessment of the proximate drivers of mangrove deforestation has only recently been produced (Thomas et al, 2017), and a qualitative survey of 10 mangrove experts by UNEP (2014) suggested that aquaculture is still one of the largest threats to mangroves globally, though other drivers such as overexploitation, pollution and coastal development are also important. All drivers are expected to increase in magnitude in the future (UNEP, 2014).…”

Remap: An online remote sensing application for land cover classification and monitoring

“…From these composites, Normalized Differenced Vegetation Index (Pettorelli, ), Normalized Difference Water Index (McFeeters, ) and several other index layers were generated for use as spectral predictors (Table ). The provision of spectral data for two time periods facilitates the estimation of change in land cover extent, which is important for monitoring the impact of threatening processes such as deforestation (Hansen et al., ), fragmentation (Haddad et al., ), coastal reclamation (Murray et al., ), aquaculture (Thomas et al., ) and water extraction (Tao et al., ). Future versions of Remap will allow users to choose any point in time between the launch of Landsat 5 and the present day to develop their classifications.…”

Back to the Basics: Biomimicry in Shrimp Farming

“…In terms of carbon footprints, Kauffman and colleagues (2017) reported new estimates of greenhouse gas (GHG) emissions resulting from the conversion of mangrove forests into aquaculture ponds and concluded that 1603 kg of carbon dioxide equivalent (CO2e) is emitted for every kilogram of shrimp produced on lands formerly occupied by mangroves. Future predictions are even more warning as 156,480 km2 of mangroves would need to be converted into shrimp farms in the coming 9 years, an area larger than the current extent of existing mangrove forests worldwide (134,300 km2) (Thomas et al, 2017). Thus horizontal expansion of shrimp farming is not an option to increase production in future, rather intensification is.…”