How South Pacific mangroves may respond to predicted climate change and sea level rise

In the Pacific islands the total mangrove area is about 343,735 ha, with largest areas in Papua New Guinea, Solomon Islands, Fiji and New Caledonia. A total of 34 species of mangroves occur, as well as 3 hybrids. These are of the Indo-Malayan assemblage (with one exception), and decline in diversity from west to east across the Pacific, reaching a limit at American Samoa. Mangrove resources are traditionally exploited in the Pacific islands, for construction and fuel wood, herbal medicines, and the gathering of crabs and fish. There are two main environmental settings for mangroves in the Pacific, deltaic and estuarine mangroves of high islands, and embayment, lagoon and reef flat mangroves of low islands. It is indicated from past analogues that their close relationship with sea-level height renders these mangrove swamps particularly vulnerable to disruption by sea-level rise. Stratigraphic records of Pacific island mangrove ecosystems during sea-level changes of the Holocene Period demonstrate that low islands mangroves can keep up with a sea-level rise of up to 12 cm per 100 years. Mangroves of high islands can keep up with rates of sea-level rates of up to 45 cm per 100 years, according to the supply of fluvial sediment. When the rate of sea-level rise exceeds the rate of accretion, mangroves experience problems of substrate erosion, inundation stress and increased salinity. Rise in temperature and the direct effects of increased CO2 levels are likely to increase mangrove productivity, change phenological patterns (such as the timing of flowering and fruiting), and expand the ranges of mangroves into higher latitudes. Pacific island mangroves are expected to demonstrate a sensitive response to the predicted rise in sea-level. A regional monitoring system is needed to provide data on ecosystem changes in productivity, species composition and sedimentation. This has been the intention of a number of programs, but none has yet been implemented

Assessment of climate change downscaling and non-stationarity on the spatial pattern of a mangrove ecosystem in an arid coastal region of southern Iran.

Mangrove wetlands exist in the transition zone between terrestrial and marine environments and have remarkable ecological and socio-economic value. This study uses climate change downscaling to address the question of non-stationarity influences on mangrove variations (expansion and contraction) within an arid coastal region. Our two-step approach includes downscaling models and uncertainty assessment, followed by a non-stationary and trend procedure using the Extreme Value Analysis (extRemes code). The Long Ashton Research Station Weather Generator (LARS-WG) model along with two different general circulation model (GCMs) (MIRH and HadCM3) were used to downscale climatic variables during current (1968–2011) and future (2011–2030, 2045–2065, and 2080–2099) periods. Parametric and non-parametric bootstrapping uncertainty tests demonstrated that the LARS-WGS model skillfully downscaled climatic variables at the 95 % significance level. Downscaling results using MIHR model show that minimum and maximum temperatures will increase in the future (2011–2030, 2045–2065, and 2080–2099) during winter and summer in a range of +4.21 and +4.7 °C, and +3.62 and +3.55 °C, respectively. HadCM3 analysis also revealed an increase in minimum (∼+3.03 °C) and maximum (∼+3.3 °C) temperatures during wet and dry seasons. In addition, we examined how much mangrove area has changed during the past decades and, thus, if climate change non-stationarity impacts mangrove ecosystems. Our results using remote sensing techniques and the non-parametric Mann–Whitney two-sample test indicated a sharp decline in mangrove area during 1972,1987, and 1997 periods (p value = 0.002). Non-stationary assessment using the generalized extreme value (GEV) distributions by including mangrove area as a covariate further indicated that the null hypothesis of the stationary climate (no trend) should be rejected due to the very low p values for precipitation (p value = 0.0027), minimum (p value = 0.000000029) and maximum (p value = 0.00016) temperatures. Based on non-stationary analysis and an upward trend in downscaled temperature extremes, climate change may control mangrove development in the future