Posts Tagged 'modeling'

The combined effects of increased temperature and ocean acidification on the early life history stages of Caribbean coral and its implication for the recovery potential of Florida reefs

The early life history stages of coral are an essential component determining the recovery potential of coral reefs through sexual reproduction and recruitment. The pelagic larval phase is inherent in all coral species regardless of differing reproductive strategies and is the only time in coral life history where large scale movement is possible allowing for the repopulation of reef areas both within and outside the natal reef habitat. In the face of climate change, the larval dispersal and recruitment phase will take place in a warmer more acidic ocean if we continue on the path of unabated fossil fuel emissions. While much research has focused on how increased temperature or ocean acidification affect coral larvae independently, our understanding of how these factors interact to shape larval response is limited, especially in regards to Caribbean coral species.

To gain a better understanding of how the early life history stages of Caribbean coral may be affected by climate change, this dissertation investigates the effects of increased temperature (2.5 °C above historical averages in the Florida Keys) and carbon dioxide levels (900-1000 parts per million CO2) on corals from the Florida Reef tract by investigating the effects on larval metabolism, survivorship, settlement, and post-settlement growth and survival. Additionally, a coupled biophysical model was developed to determine the potential changes in connectivity that may result from the biological effects of increased temperature and ocean acidification on the larval phase. The larval respiratory response of three Caribbean coral species revealed Orbicella faveolata as the most environmentally responsive with significant increases in respiration after 1 day exposure to increased temperature (68% greater than control conditions) with a counteracting effect of ocean acidification significantly decreasing respiration. The changes in metabolism over time correlated with decreased time to competency under elevated temperature in O. faveolata larvae, resulting in a greater number of settlers (76% greater than control) and a relative increase in local retention and self-recruitment rates as revealed by the biophysical model (5 and 7% greater than control respectively). However, when increased temperature occurred in combination with elevated CO2 levels, respiration was not significantly increased relative to control conditions and development of competency is minimally impacted. This resulted in a smaller increase in settlers (13% greater than control) and no significant changes in connectivity patterns. The post-settlement phase was similarly impacted with counteracting effects of increased temperature and ocean acidification on recruit growth.

Overall, this dissertation reveals the potential for adaptation to increased temperature in at least one important coral species (Orbicella faveolata) that is greatly diminished when encountered in combination with ocean acidification. These results encourage the reduction of carbon emissions to give coral species the chance to adapt to elevated temperatures through the recruitment of more resilient individuals without the additional stress of ocean acidification.

Continue reading ‘The combined effects of increased temperature and ocean acidification on the early life history stages of Caribbean coral and its implication for the recovery potential of Florida reefs’

Estimates of water-column nutrient concentrations and carbonate system parameters in the global ocean: a novel approach based on neural networks

 

A neural network-based method (CANYON: CArbonate system and Nutrients concentration from hYdrological properties and Oxygen using a Neural-network) was developed to estimate water-column (i.e., from surface to 8,000 m depth) biogeochemically relevant variables in the Global Ocean. These are the concentrations of three nutrients [nitrate (NO3−), phosphate (PO43−), and silicate (Si(OH)4)] and four carbonate system parameters [total alkalinity (AT), dissolved inorganic carbon (CT), pH (pHT), and partial pressure of CO2 (pCO2)], which are estimated from concurrent in situ measurements of temperature, salinity, hydrostatic pressure, and oxygen (O2) together with sampling latitude, longitude, and date. Seven neural-networks were developed using the GLODAPv2 database, which is largely representative of the diversity of open-ocean conditions, hence making CANYON potentially applicable to most oceanic environments. For each variable, CANYON was trained using 80 % randomly chosen data from the whole database (after eight 10° × 10° zones removed providing an “independent data-set” for additional validation), the remaining 20 % data were used for the neural-network test of validation. Overall, CANYON retrieved the variables with high accuracies (RMSE): 1.04 μmol kg−1 (NO3−), 0.074 μmol kg−1 (PO43−), 3.2 μmol kg−1 (Si(OH)4), 0.020 (pHT), 9 μmol kg−1 (AT), 11 μmol kg−1 (CT) and 7.6 % (pCO2) (30 μatm at 400 μatm). This was confirmed for the eight independent zones not included in the training process. CANYON was also applied to the Hawaiian Time Series site to produce a 22 years long simulated time series for the above seven variables. Comparison of modeled and measured data was also very satisfactory (RMSE in the order of magnitude of RMSE from validation test). CANYON is thus a promising method to derive distributions of key biogeochemical variables. It could be used for a variety of global and regional applications ranging from data quality control to the production of datasets of variables required for initialization and validation of biogeochemical models that are difficult to obtain. In particular, combining the increased coverage of the global Biogeochemical-Argo program, where O2 is one of the core variables now very accurately measured, with the CANYON approach offers the fascinating perspective of obtaining large-scale estimates of key biogeochemical variables with unprecedented spatial and temporal resolutions. The Matlab and R codes of the proposed algorithms are provided as Supplementary Material.

Continue reading ‘Estimates of water-column nutrient concentrations and carbonate system parameters in the global ocean: a novel approach based on neural networks’

Deepwater carbonate ion concentrations in the western tropical Pacific since 250 ka: Evidence for oceanic carbon storage and global climate influence

We present new “size-normalized weight” (SNW)-Δ[CO32−] core-top calibrations for three planktonic foraminiferal species and assess their reliability as a paleo-alkalinity proxy. SNWs of Globigerina sacculifer and Neogloboquadrina dutertrei can be used to reconstruct past deep Pacific [CO32−], whereas SNWs of Pulleniatina obliquiloculata are controlled by additional environmental factors. Based on this methodological advance, we reconstruct SNW-based deepwater [CO32−] for core WP7 from the western tropical Pacific since 250 ka. Secular variation in the SNW proxy documents little change in deep Pacific [CO32−] between the Last Glacial Maximum and the Holocene. Further back in time, deepwater [CO32−] shows long-term increases from marine isotope stage (MIS) 5e to MIS 3 and from early MIS 7 to late MIS 6, consistent with the “coral reef hypothesis” that the deep Pacific Ocean carbonate system responded to declining shelf carbonate production during these two intervals. During deglaciations, we have evidence of [CO32−] peaks coincident with Terminations 2 and 3, which suggests that a breakdown of oceanic vertical stratification drove a net transfer of CO2 from the ocean to the atmosphere, causing spikes in carbonate preservation (i.e., the “deglacial ventilation hypothesis”). During MIS 4, a transient decline in SNW-based [CO32−], along with other reported [CO32−] and/or dissolution records, implies that increased deep-ocean carbon storage resulted in a global carbonate dissolution event. These findings provide new insights into the role of the deep Pacific in the global carbon cycle during the late Quaternary.

Continue reading ‘Deepwater carbonate ion concentrations in the western tropical Pacific since 250 ka: Evidence for oceanic carbon storage and global climate influence’

Response of export production and dissolved oxygen concentrations in oxygen minimum zones to pCO2 and temperature stabilization scenarios in the biogeochemical model HAMOCC 2.0 (update)

Dissolved oxygen (DO) concentration in the ocean is an important component of marine biogeochemical cycles and will be greatly altered as climate change persists. In this study a global oceanic carbon cycle model (HAMOCC 2.0) is used to address how mechanisms of oxygen minimum zone (OMZ) expansion respond to changes in CO2 radiative forcing. Atmospheric pCO2 is increased at a rate of 1 % annually and the model is stabilized at 2 ×, 4 ×, 6  ×, and 8 × preindustrial pCO2 levels. With an increase in CO2 radiative forcing, the OMZ in the Pacific Ocean is controlled largely by changes in particulate organic carbon (POC) export, resulting in increased remineralization and thus expanding the OMZs within the tropical Pacific Ocean. A potential decline in primary producers in the future as a result of environmental stress due to ocean warming and acidification could lead to a substantial reduction in POC export production, vertical POC flux, and thus increased DO concentration particularly in the Pacific Ocean at a depth of 600–800 m. In contrast, the vertical expansion of the OMZs within the Atlantic is linked to increases POC flux as well as changes in oxygen solubility with increasing seawater temperature. Changes in total organic carbon and increase sea surface temperature (SST) also lead to the formation of a new OMZ in the western subtropical Pacific Ocean. The development of the new OMZ results in dissolved oxygen concentration of  ≤  50 µmol kg−1 throughout the equatorial Pacific Ocean at 4 times preindustrial pCO2. Total ocean volume with dissolved oxygen concentrations of  ≤  50 µmol kg−1 increases by 2.4, 5.0, and 10.5 % for the 2 ×, 4 ×, and 8 × CO2 simulations, respectively.

Continue reading ‘Response of export production and dissolved oxygen concentrations in oxygen minimum zones to pCO2 and temperature stabilization scenarios in the biogeochemical model HAMOCC 2.0 (update)’

Energetic costs of calcification under ocean acidification

Anthropogenic ocean acidification threatens to negatively impact marine organisms that precipitate calcium carbonate skeletons. Past geological events, such as the Permian-Triassic Mass Extinction, together with modern experiments generally support these concerns. However, the physiological costs of producing a calcium carbonate skeleton under different acidification scenarios remain poorly understood. Here, we present an idealized mathematical model to quantify whole-skeleton costs, concluding that they rise only modestly (up to ∼10%) under acidification expected for 2100. The modest magnitude of this effect reflects in part the low energetic cost of inorganic, calcium carbonate relative to the proteinaceous organic matrix component of skeletons. Our analysis does, however, point to an important kinetic constraint that depends on seawater carbonate chemistry, and we hypothesize that the impact of acidification is more likely to cause extinctions within groups where the timescale of larval development is tightly constrained. The cheapness of carbonate skeletons compared to organic materials also helps explain the widespread evolutionary convergence upon calcification within the metazoa.

Continue reading ‘Energetic costs of calcification under ocean acidification’

Potential sources of variability in mesocosm experiments on the response of phytoplankton to ocean acidification (update)

Mesocosm experiments on phytoplankton dynamics under high CO2 concentrations mimic the response of marine primary producers to future ocean acidification. However, potential acidification effects can be hindered by the high standard deviation typically found in the replicates of the same CO2 treatment level. In experiments with multiple unresolved factors and a sub-optimal number of replicates, post-processing statistical inference tools might fail to detect an effect that is present. We propose that in such cases, data-based model analyses might be suitable tools to unearth potential responses to the treatment and identify the uncertainties that could produce the observed variability. As test cases, we used data from two independent mesocosm experiments. Both experiments showed high standard deviations and, according to statistical inference tools, biomass appeared insensitive to changing CO2 conditions. Conversely, our simulations showed earlier and more intense phytoplankton blooms in modeled replicates at high CO2 concentrations and suggested that uncertainties in average cell size, phytoplankton biomass losses, and initial nutrient concentration potentially outweigh acidification effects by triggering strong variability during the bloom phase. We also estimated the thresholds below which uncertainties do not escalate to high variability. This information might help in designing future mesocosm experiments and interpreting controversial results on the effect of acidification or other pressures on ecosystem functions.

Continue reading ‘Potential sources of variability in mesocosm experiments on the response of phytoplankton to ocean acidification (update)’

A data–model synthesis to explain variability in calcification observed during a CO2 perturbation mesocosm experiment (update)

The effect of ocean acidification on growth and calcification of the marine algae Emiliania huxleyi was investigated in a series of mesocosm experiments where enclosed water volumes that comprised a natural plankton community were exposed to different carbon dioxide (CO2) concentrations. Calcification rates observed during those experiments were found to be highly variable, even among replicate mesocosms that were subject to similar CO2 perturbations. Here, data from an ocean acidification mesocosm experiment are reanalysed with an optimality-based dynamical plankton model. According to our model approach, cellular calcite formation is sensitive to variations in CO2 at the organism level. We investigate the temporal changes and variability in observations, with a focus on resolving observed differences in total alkalinity and particulate inorganic carbon (PIC). We explore how much of the variability in the data can be explained by variations of the initial conditions and by the level of CO2 perturbation. Nine mesocosms of one experiment were sorted into three groups of high, medium, and low calcification rates and analysed separately. The spread of the three optimised ensemble model solutions captures most of the observed variability. Our results show that small variations in initial abundance of coccolithophores and the prevailing physiological acclimation states generate differences in calcification that are larger than those induced by ocean acidification. Accordingly, large deviations between optimal mass flux estimates of carbon and of nitrogen are identified even between mesocosms that were subject to similar ocean acidification conditions. With our model-based data analysis we document how an ocean acidification response signal in calcification can be disentangled from the observed variability in PIC.

Continue reading ‘A data–model synthesis to explain variability in calcification observed during a CO2 perturbation mesocosm experiment (update)’


Subscribe to the RSS feed

Powered by FeedBurner

Follow AnneMarin on Twitter

Blog Stats

  • 1,001,025 hits

OA-ICC HIGHLIGHTS

Ocean acidification in the IPCC AR5 WG II

OUP book