Posts Tagged 'regionalmodeling'

The future of reef ecosystems in the Gulf of Mexico: insights from coupled climate model simulations and ancient hot-house reefs

Shallow water coral reefs and deep sea coral communities are sensitive to current and future environmental stresses, such as changes in sea surface temperatures (SST), salinity, carbonate chemistry, and acidity. Over the last half-century, some reef communities have been disappearing at an alarming pace. This study focuses on the Gulf of Mexico, where the majority of shallow coral reefs are reported to be in poor or fair condition. We analyze the RCP8.5 ensemble of the Community Earth System Model v1.2 to identify monthly-to-decadal trends in Gulf of Mexico SST. Secondly, we examine projected changes in ocean pH, carbonate saturation state, and salinity in the same coupled model simulations. We find that the joint impacts of predicted higher temperatures and changes in ocean acidification will severely degrade Gulf of Mexico reef systems by the end of the twenty-first century. SSTs are likely to warm by 2.5–3°C; while corals do show signs of an ability to adapt toward higher temperatures, current coral species and reef systems are likely to suffer major bleaching events in coming years. We contextualize future changes with ancient reefs from paleoclimate analogs, periods of Earth’s past that were also exceptionally warm, specifically rapid “hyperthermal” events. Ancient analog events are often associated with extinctions, reef collapse, and significant ecological changes, yet reef communities managed to survive these events on evolutionary timescales. Finally, we review research which discusses the adaptive potential of the Gulf of Mexico’s coral reefs, meccas of biodiversity and oceanic health. We assert that the only guaranteed solution for long-term conservation and recovery is substantial, rapid reduction of anthropogenic greenhouse gas emissions.

Continue reading ‘The future of reef ecosystems in the Gulf of Mexico: insights from coupled climate model simulations and ancient hot-house reefs’

Climatic projections of Indian Ocean during 2030, 2050, 2080 with implications on fisheries sector

Climatic projections are essential to frame resilient strategies towards futuristic impacts of climate changes on fish species and habitat. The present study projects the variations of climatic variables such as Sea Surface Temperature (SST), Sea Surface Salinity (SSS), Sea Level Rise (SLR), Precipitation (Pr), and pH along the Indian Ocean. Climate projections for 2030, 2050 and 2080 were obtained as MIROC-ESM-CHEM, CMIP5 model output for each Representative Concentration Pathways (RCP) scenarios. Each climatic variable was assessed for any change against the reference year of 2015. The RCP scenarios showed an increasing trend for SLR and SST while a decreasing trend for SSS and pH. The study focuses on assessing the impacts of projected variations on marine and aquaculture system. The climate model projections show that the SST during 2080 is likely to rise by 0.69°C for the lowest emissions scenario and 2.6°C for the highest emissions scenario. Elevated temperature disturbs the homeostasis of fish and subjects to physiological stress in the habitat resulting in mortality. These thermal limits can predict distributional changes of marine species in response to climate change. Projections showed no significant changes in the pattern of precipitation. Changes in sea level rise and sea surface salinity reduce water quality, spawning and seed availability, increased disease incidence and damage to freshwater aquaculture system by salinization of groundwater. The results show that variation in SST and pH have a potential impact on marine fisheries while SSS, SLR, Precipitation affects the aquaculture systems. The synergic effects of climatic variations are found to have negative implications on capture fisheries as well as aquaculture system and are elucidated through this work.

Continue reading ‘Climatic projections of Indian Ocean during 2030, 2050, 2080 with implications on fisheries sector’

Optimum satellite remote sensing of the marine carbonate system using empirical algorithms in the global ocean, the Greater Caribbean, the Amazon Plume and the Bay of Bengal

Highlights

• Satellite salinity measurements enable estimation of surface carbonate parameters.

• Uncertainties within these observation-based estimates are well characterized.

• Monthly satellite salinity and temperature allows synoptic monitoring.

• Satellite observations allow study of seasonal, interannual and episodic variations.

Abstract

Improving our ability to monitor ocean carbonate chemistry has become a priority as the ocean continues to absorb carbon dioxide from the atmosphere. This long-term uptake is reducing the ocean pH; a process commonly known as ocean acidification. The use of satellite Earth Observation has not yet been thoroughly explored as an option for routinely observing surface ocean carbonate chemistry, although its potential has been highlighted. We demonstrate the suitability of using empirical algorithms to calculate total alkalinity (AT) and total dissolved inorganic carbon (CT), assessing the relative performance of satellite, interpolated in situ, and climatology datasets in reproducing the wider spatial patterns of these two variables. Both AT and CT in situ data are reproducible, both regionally and globally, using salinity and temperature datasets, with satellite observed salinity from Aquarius and SMOS providing performance comparable to other datasets for the majority of case studies. Global root mean squared difference (RMSD) between in situ validation data and satellite estimates is 17 μmol kg−1 with bias  < 5 μmol kg−1 for AT and 30 μmol kg−1 with bias  < 10 μmol kg−1 for CT. This analysis demonstrates that satellite sensors provide a credible solution for monitoring surface synoptic scale AT and CT. It also enables the first demonstration of observation-based synoptic scale AT and CT temporal mixing in the Amazon plume for 2010–2016, complete with a robust estimation of their uncertainty.

Continue reading ‘Optimum satellite remote sensing of the marine carbonate system using empirical algorithms in the global ocean, the Greater Caribbean, the Amazon Plume and the Bay of Bengal’

Seasonal patterns of surface inorganic carbon system variables in the Gulf of Mexico inferred from a regional high-resolution ocean-biogeochemical model

Uncertainties in carbon chemistry variability still remain large in the Gulf of Mexico (GoM), as data gaps limit our ability to infer basin-wide patterns. Here we configure and validate a regional high-resolution ocean-biogeochemical model for the GoM to describe seasonal patterns in surface pressure of CO2 (pCO2), aragonite saturation state (ΩAr), and air-sea CO2 flux during 2005–2014. Model results indicate that seasonal changes in surface pCO2 are strongly controlled by temperature across most of the GoM basin, except in the vicinity of the Mississippi-Atchafalaya River System delta, where runoff largely controls dissolved inorganic carbon (DIC) and total alkalinity (TA) changes. Our model results also show that seasonal patterns of surface ΩAr are driven by seasonal changes in DIC and TA, and reinforced by the seasonal changes in temperature. Simulated air-sea CO2 fluxes are consistent with previous observation-based estimates that show CO2 uptake during winter-spring, and CO2 outgassing during summer-fall. Annually, our model indicates a basin-wide mean CO2 uptake of 0.35 mol m−2 yr−1, and a northern GoM shelf (< 200 m) uptake of 0.93 mol m−2 yr−1. The observation and model-derived patterns of surface pCO2 and CO2 fluxes show good correspondence, thus contributing to improved constraints of the carbon budget in the region.

Continue reading ‘Seasonal patterns of surface inorganic carbon system variables in the Gulf of Mexico inferred from a regional high-resolution ocean-biogeochemical model’

Estimating relative immediacy of water-related challenges in Small Island Developing States (SIDS) of the Pacific Ocean using AHP modeling

We outline nine water-related challenges faced by the Small Island Developing States (SIDS) of the Pacific Ocean and map them with relevant sustainable development goals (SDGs). The challenges thus identified have been modeled using analytical hierarchy process (AHP) to find out their priority weights. Based on this weightage, the relative immediacy of each of these water-related challenges have been calculated, and classified as high, medium, and low. The findings reveal that the most immediate challenge in terms of their relative immediacy weightage is the ‘rising sea level’. This is followed by ‘low water quality and its availability’, and ‘spread of water-borne and vector-borne diseases’. Other challenges analyzed in this study pertains to overfishing and exploitation of exclusive economic zones; soil erosion and coastal inundation; increase in incidences of natural disasters; coral reef damage and increased ocean acidification; climate refugee; and changing precipitation pattern. This study would be instrumental for policy makers and inter-governmental organizations in directing the resource allocation for adaptation and mitigation efforts in the small islands.

Continue reading ‘Estimating relative immediacy of water-related challenges in Small Island Developing States (SIDS) of the Pacific Ocean using AHP modeling’

Spatial patterns in aragonite saturation for the north central California shelf

Ocean acidification is exacerbated along the California shelf due to the upwelling of deep CO2 rich waters. This process of upwelling is driven by along-shore winds, which vary in strength by season. We present the relationship between along-shore wind and aragonite undersaturation utilizing an empirical formula to determine aragonite saturation from salinity, temperature, and dissolved oxygen. Our models show that stronger along-shore winds are correlated with a higher percentage of the water column undersaturated in aragonite. In addition, pteropod and juvenile krill density decrease in upwelled water which is cold, salty, and low in aragonite. With a predicted increase in along-shore winds, California shelf waters will become more undersaturated in aragonite and lead to a decrease in pteropod and krill density.

Continue reading ‘Spatial patterns in aragonite saturation for the north central California shelf’

Effects of an aquaculture pesticide (diflubenzuron) on non-target shrimp populations: extrapolation from laboratory experiments to the risk of population decline

Highlights

• Diflubenzuron (DFB) in salmon lice treatment can kill non-target crustaceans.

• We developed an age-structured model to assess effects of DFB on shrimp populations.

• The model predicts decline in shrimp abundance by 8%–99%, depending on DFB scenario.

• Environmental fluctuations contribute to the risk of shrimp population decline.

• Future environmental warming and ocean acidification may further impact populations.

Abstract

Marine aquaculture production has lately experienced high economic growth, but also concerns related to production and environmental contamination. For the Atlantic salmon aquaculture industry, the ectoparasitic crustacean salmon louse (Lepeophtheirus salmonis) has become a major problem. A common method to control populations of salmon lice within farm cages is treatment by various pharmaceuticals. One of the pesticides used in medicated feed for salmon is diflubenzuron (DFB), which acts as a chitin synthesis inhibitor and thereby interferes with the moulting stages during the development of this crustacean. However, DFB from fish feed may also affect non-target crustaceans such as the northern shrimp (Pandalus borealis), which is an economically and ecologically important species. Nevertheless, the actual risk posed by this chemical to shrimp populations in nature is largely unknown. Laboratory experiments have demonstrated that both larval and adult shrimp exposed to DFB through medicated fish feed have reduced survival compared to control. Moreover, the effects of DFB exposure are more severe under conditions of higher temperature and reduced pH (ocean acidification), which can be expected in a future environment. The aim of this study is to make the individual-level information from laboratory studies more relevant for risk assessment at the population level. We have developed a density-dependent age-structured population model representing a northern shrimp population located in a hypothetical Norwegian fjord containing a fish farm, under both ambient and future environments. Our model is based on thorough documentation of shrimp biology and toxicological effects from the laboratory experiments. Nevertheless, extrapolating the reported individual-level effects of DFB to the population level poses several challenges. Relevant information on shrimp populations in Norwegian fjords is sparse (such as abundances, survival and reproductive rates, and density-dependent processes). The degree of exposure to DFB at different distances from aquaculture farms is also uncertain. We have therefore developed a set of model scenarios representing different DFB application schemes and different degrees of exposure for the shrimp populations. The model predicts effects of DFB exposure on population-level endpoints such as long-term abundance, age structure and the probability of population decline below threshold abundances. These model predictions demonstrate how the risk of DFB to shrimp populations can be enhanced by factors such as the timing (season) of DFB applications, the percentage of the population affected, future environmental conditions and environmental stochasticity.

Continue reading ‘Effects of an aquaculture pesticide (diflubenzuron) on non-target shrimp populations: extrapolation from laboratory experiments to the risk of population decline’


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Ocean acidification in the IPCC AR5 WG II

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