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Climate change-induced salinity variation impacts on a stenoecious mangrove species in the Indian Sundarbans.

ABSTRACT: The alterations in the salinity profile are an indirect, but potentially sensitive, indicator for detecting changes in precipitation, evaporation, river run-off, glacier retreat, and ice melt. These changes have a high impact on the growth of coastal plant species, such as mangroves. Here, we present estimates of the variability of salinity and the biomass of a stenoecious mangrove species (Heritiera fomes, commonly referred to as Sundari) in the aquatic subsystem of the lower Gangetic delta based on a dataset from 2004 to 2015. We highlight the impact of salinity alteration on the change in aboveground biomass of this endangered species that, due to different salinity profile in the western and central sectors of the lower Gangetic plain, shows an increase only in the former sector, where the salinity is dropping and low growth in the latter, where the salinity is increasing.

SUBMITTER: Banerjee K

PROVIDER: S-EPMC5385663 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Anthropogenic perturbations have strong impact on water quality and ecological health of mangrove areas of Indian Sundarbans. Diversity in microbial community composition is important causes for maintaining the health of the mangrove ecosystem. However, microbial communities of estuarine water in Indian Sundarbans mangrove areas and environmental determinants that contribute to those communities were seldom studied. METHODS:Nevertheless, this study attempted first to report bacterial and archaeal communities simultaneously in the water from Matla River and Thakuran River of Maipith coastal areas more accurately using 16S rRNA gene-based amplicon approaches. Attempt also been made to assess the capability of the environmental parameters for explaining the variation in microbial community composition. RESULTS:Our investigation indicates the dominancy of halophilic marine bacteria from families Flavobacteriaceae and OM1 clade in the water with lower nutrient load collected from costal regions of a small Island of Sundarban Mangroves (ISM). At higher eutrophic conditions, changes in bacterial communities in Open Marine Water (OMW) were detected, where some of the marine hydrocarbons degrading bacteria under families Oceanospirillaceae and Spongiibacteraceae were dominated. While most abundant bacterial family Rhodobacteracea almost equally (18% of the total community) dominated in both sites. Minor variation in the composition of archaeal community was also observed between OMW and ISM. Redundancy analysis indicates a combination of total nitrogen and dissolved inorganic nutrients for OMW and for ISM, salinity and total nitrogen was responsible for explaining the changes in their respective microbial community composition. CONCLUSIONS:Our study contributes the first conclusive overview on how do multiple environmental/anthropogenic stressors (salinity, pollution, eutrophication, land-use) affect the Sundarban estuary water and consequently the microbial communities in concert. However, systematic approaches with more samples for evaluating the effect of environmental pollutions on mangrove microbial communities are recommended.

Project description:Impacts of climate change can differ substantially across species' geographic ranges, and impacts on a given population can be difficult to predict accurately. A commonly used approximation for the impacts of climate change on the population growth rate is the product of local changes in each climate variable (which may differ among populations) and the sensitivity (the derivative of the population growth rate with respect to that climate variable), summed across climate variables. However, this approximation may not be accurate for predicting changes in population growth rate across geographic ranges, because the sensitivities to climate variables or the rate of climate change may differ among populations. In addition, while this approximation assumes a linear response of population growth rate to climate, population growth rate is typically a nonlinear function of climate variables. Here, we use climate-driven integral projection models combined with projections of future climate to predict changes in population growth rate from 2008 to 2099 for an uncommon alpine plant species, Douglasia alaskana, in a rapidly warming location, southcentral Alaska USA. We dissect the causes of among-population variation in climate change impacts, including magnitude of climate change in each population and nonlinearities in population response to climate change. We show that much of the variation in climate change impacts across D. alaskana's range arises from nonlinearities in population response to climate. Our results highlight the critical role of nonlinear responses to climate change impacts, suggesting that current responses to increases in temperature or changes in precipitation may not continue indefinitely under continued changes in climate. Further, our results suggest the degree of nonlinearity in climate responses and the shape of responses (e.g., convex or concave) can differ substantially across populations, such that populations may differ dramatically in responses to future climate even when their current responses are quite similar.

Project description:Species distribution modeling (SDM) is an important tool to assess the impact of global environmental change. Many species exhibit ecologically relevant intraspecific variation, and few studies have analyzed its relevance for SDM. Here, we compared three SDM techniques for the highly variable species Pinus contorta. First, applying a conventional SDM approach, we used MaxEnt to model the subject as a single species (species model), based on presence-absence observations. Second, we used MaxEnt to model each of the three most prevalent subspecies independently and combined their projected distributions (subspecies model). Finally, we used a universal growth transfer function (UTF), an approach to incorporate intraspecific variation utilizing provenance trial tree growth data. Different model approaches performed similarly when predicting current distributions. MaxEnt model discrimination was greater (AUC - species model: 0.94, subspecies model: 0.95, UTF: 0.89), but the UTF was better calibrated (slope and bias - species model: 1.31 and -0.58, subspecies model: 1.44 and -0.43, UTF: 1.01 and 0.04, respectively). Contrastingly, for future climatic conditions, projections of lodgepole pine habitat suitability diverged. In particular, when the species' intraspecific variability was acknowledged, the species was projected to better tolerate climatic change as related to suitable habitat without migration (subspecies model: 26% habitat loss or UTF: 24% habitat loss vs. species model: 60% habitat loss), and given unlimited migration may increase amount of suitable habitat (subspecies model: 8% habitat gain or UTF: 12% habitat gain vs. species model: 51% habitat loss) in the climatic period 2070-2100 (SRES A2 scenario, HADCM3). We conclude that models derived from within-species data produce different and better projections, and coincide with ecological theory. Furthermore, we conclude that intraspecific variation may buffer against adverse effects of climate change. A key future research challenge lies in assessing the extent to which species can utilize intraspecific variation under rapid environmental change.

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Climate change-induced salinity variation impacts on a stenoecious mangrove species in the Indian Sundarbans.

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