Posts Tagged 'individualmodeling'

Abalone populations are most sensitive to environmental stress effects on adult individuals

Marine organisms are exposed to stressors associated with climate change throughout their life cycle, but a majority of studies focus on responses in single life stages, typically early ones. Here, we examined how negative impacts from stressors associated with climate change, ocean acidification, and pollution can act across multiple life stages to influence long-term population dynamics and decrease resilience to mass mortality events. We used a continuous-size-structured density-dependent model for abalone (Haliotis spp.), calcifying mollusks that support valuable fisheries, to explore the sensitivity of stock abundance and annual catch to potential changes in growth, survival, and fecundity across the organism’s lifespan. Our model predicts that decreased recruitment from lowered fertilization success or larval survival has small negative impacts on the population, and that stock size and fishery performance are much more sensitive to changes in parameters that affect the size or survival of adults. Sensitivity to impacts on subadults and juveniles is also important for the population, though less so than for adults. Importantly, likelihood of recovery following mortality events showed more pronounced sensitivity to most possible parameter impacts, greater than the effects on equilibrium density or catch. Our results suggest that future experiments on environmental stressors should focus on multiple life stages to capture effects on population structure and dynamics, particularly for species with size-dependent fecundity.

Continue reading ‘Abalone populations are most sensitive to environmental stress effects on adult individuals’

A multistressor model of carbon acquisition regulation for macroalgae in a changing climate

It is widely hypothesized that noncalcifying macroalgae will be more productive and abundant in increasingly warm and acidified oceans. Macroalgae vary greatly in the magnitudes and interactions of responses of photosynthesis and growth to multiple stressors associated with climate change. A knowledge gap that exists between the qualitative “macroalgae will benefit” hypothesis and the variable outcomes observed is regulation of physiological mechanisms that cause variation in the magnitudes of change in primary productivity, growth, and their covariation. In this context, we developed a model to quantitatively describe physiological responses to coincident variation in temperature, carbonate chemistry and light supply in a representative bicarbonate‐using marine macroalga. The model is based on Ulva spp., the best understood dissolved inorganic carbon uptake mechanism among macroalgae, with data enabling synthesis across all parameters. At boundary layer pH < 8.7 most inorganic carbon is taken up through the external carbonic anhydrase (CAext) mechanism under all conditions of photosynthetic photon flux density, temperature, and boundary layer thickness. Each 0.1 unit decline in pH causes a 20% increase in the fraction of diffusive uptake of CO2 thereby lessening reliance on active transport of bicarbonate. Modeled downregulation of anion exchange‐mediated active bicarbonate transport associated with a 0.4 unit decline in pH under ocean acidification is consistent with enhanced growth up to 4% per day without increasing photosynthetic rate. The model provides a means to quantify magnitudes of change in productivity under factorial combinations of changing temperature, CO2, and light supply anticipated as climate changes.

Continue reading ‘A multistressor model of carbon acquisition regulation for macroalgae in a changing climate’

The challenge of scaling up from individual physiology to population level effects: using the Dynamic Energy Budget to describe and predict crustacean responses to climate variability

Predicting how marine communities will be affected by environmental change is one of the most significant challenges facing researchers today. In order to tackle this challenge, a mechanistic understanding of climate impacts at the individual level is necessary, as variations in species physiological responses are often reflected in patterns at higher organisational levels such as populations and communities. In order to explore the relationship between individual physiology and higher-level dynamics more fully, the swimming crab Liocarcinus depurator (Linnaeus, 1758) was selected as a model species for experimental work in which whole organism responses (growth, respiration and allocation to reproduction) to climate drivers were investigated using a bio-energetic modelling approach. This species was selected as a model organism after analysis of epibenthic time-series from the Western English Channel monitoring Station L4 revealed that decapod crustaceans played a key role in structuring the benthic community, and that L. depurator was one of the most dominant species in the area, in terms of both abundance and biomass. A bio-energetic approach was used as the same time-series analysis identified water temperature and seasonal phytodetrital input (e.g. food) as the predominant drivers of variation in benthic community wet biomass at L4, with the two drivers appearing to primarily influence community biomass at different times of the year. It is possible that warmer water temperatures in the autumn trigger gonad development and a consequent increase in reproductive biomass, while the sedimentation of the spring phytoplankton bloom drives an increase in somatic biomass. This time-series analysis clearly highlighted the role of organism energetics, and the environmental conditions that influence energy allocation, in structuring benthic communities. Further work elucidated the relationship between environmental variables and individual energy budgets. L. depurator responses to climate drivers (temperature, hypoxia and ocean acidification) were tested experimentally, and a mechanistic Dynamic Energy Budget (DEB) model was parameterised to describe the life history characteristics of crustaceans. At an individual level the model was able to accurately describe and predict observed responses to environmental drivers, both in isolation and in multiple stressor scenarios. Experimental results suggested that L. depurator was broadly tolerant of those climate drivers tested in the short term. Over the longer term however, model scenarios suggested that OA and the combined stressors may have an adverse effect on growth. When the multi-stressor model was forced with environmental projections from a coupled hydrodynamic-biogeochemical model (NEMO-ERSEM), it could be used to make predictions regarding ultimate carbon mass, age-at-maturity and cumulative allocation to reproduction, which were used to infer possible population level effects such as species distributions and population viability. Model scenarios suggested that, in the future, the optimum settlement time for juvenile L. depurator would shift forward across the north-west European shelf, and that this crustacean species may be able to expand its range further into the northern North Sea. The DEB model presented here can provide a mechanistic underpinning of observed species responses to climate drivers, and more broadly, the thesis demonstrates how multi-stressor models can be built from data collected in single stressor experiments, thereby providing a way of synthesising single stressor data into a modelling environment. This approach allows us to simulate more complex, ecologically relevant conditions. At a broader scale, the coupled DEB-ERSEM model showed that it can provide insight into why changes in species’ distributions are predicted, as these distributions are an emergent property of the processes being modelled.

Continue reading ‘The challenge of scaling up from individual physiology to population level effects: using the Dynamic Energy Budget to describe and predict crustacean responses to climate variability’

Symbiont community diversity is more variable in corals that respond poorly to stress

Coral reefs are declining globally as climate change and local water quality press environmental conditions beyond the physiological tolerances of holobionts—the collective of the host and its microbial symbionts. To assess the relationship between symbiont composition and holobiont stress tolerance, community diversity metrics were quantified for dinoflagellate endosymbionts (Family: Symbiodiniaceae) from eight Acropora millepora genets that thrived under or responded poorly to various stressors. These eight selected genets represent the upper and lower tails of the response distribution of 40 coral genets that were exposed to four stress treatments (and control conditions) in a 10‐day experiment. Specifically, four ‘best performer’ coral genets were analyzed at the end of the experiment because they survived high temperature, high pCO2, bacterial exposure, or combined stressors, whereas four ‘worst performer’ genets were characterized because they experienced substantial mortality under these stressors. At the end of the experiment, seven of eight coral genets mainly hosted Cladocopium symbionts, whereas the eighth genet was dominated by both Cladocopium and Durusdinium symbionts. Symbiodiniaceae alpha and beta diversity were higher in worst performing genets than in best performing genets. Symbiont communities in worst performers also differed more after stress exposure relative to their controls (based on normalized proportional differences in beta diversity), than did best performers. A generalized joint attribute model estimated the influence of host genet and treatment on Symbiodiniaceae community composition and identified strong associations among particular symbionts and host genet performance, as well as weaker associations with treatment. Although dominant symbiont physiology and function contribute to host performance, these findings emphasize the importance of symbiont community diversity and stochasticity as components of host performance. Our findings also suggest that symbiont community diversity metrics may function as indicators of resilience and have potential applications in diverse disciplines from climate change adaptation to agriculture and medicine.

Continue reading ‘Symbiont community diversity is more variable in corals that respond poorly to stress’

Blue mussel (Genus Mytilus) transcriptome response to simulated climate change in the Gulf of Maine

The biogeochemistry of the Gulf of Maine (GOM) is rapidly changing in response to the changing climate, including rising temperatures, acidification, and declining primary productivity. These impacts are projected to worsen over the next 100 y and will apply selective pressure on populations of marine calcifiers. This study investigates the transcriptome expression response to these changes in ecologically and economically important marine calcifiers, blue mussels. Wild mussels (Mytilus edulis and Mytilus trossulus) were sampled from sites spanning the GOM and exposed to two different biogeochemical water conditions: (1) present-day conditions in the GOM and (2) simulated future conditions, which included elevated temperature, increased acidity, and decreased food supply. Patterns of gene expression were measured using RNA sequencing from 24 mussel samples and contrasted between ambient and future conditions. The net calcification rate, a trait predicted to be under climate-induced stress, was measured for each individual over a 2-wk exposure period and used as a covariate along with gene expression patterns. Generalized linear models, with and without the calcification rate, were used to identify differentially expressed transcripts between ambient and future conditions. The comparison revealed transcripts that likely comprise a core stress response characterized by the induction of molecular chaperones, genes involved in aerobic metabolism, and indicators of cellular stress. Furthermore, the model contrasts revealed transcripts that may be associated with individual variation in calcification rate and suggest possible biological processes that may have downstream effects on calcification phenotypes, such as zinc-ion binding and protein degradation. Overall, these findings contribute to the understanding of blue mussel adaptive responses to imminent climate change and suggest metabolic pathways are resilient in variable environments.

Continue reading ‘Blue mussel (Genus Mytilus) transcriptome response to simulated climate change in the Gulf of Maine’

Ocean acidification does not impair the behaviour of coral reef fishes

The partial pressure of CO2 in the oceans has increased rapidly over the past century, driving ocean acidification and raising concern for the stability of marine ecosystems1,2,3. Coral reef fishes are predicted to be especially susceptible to end-of-century ocean acidification on the basis of several high-profile papers4,5 that have reported profound behavioural and sensory impairments—for example, complete attraction to the chemical cues of predators under conditions of ocean acidification. Here, we comprehensively and transparently show that—in contrast to previous studies—end-of-century ocean acidification levels have negligible effects on important behaviours of coral reef fishes, such as the avoidance of chemical cues from predators, fish activity levels and behavioural lateralization (left–right turning preference). Using data simulations, we additionally show that the large effect sizes and small within-group variances that have been reported in several previous studies are highly improbable. Together, our findings indicate that the reported effects of ocean acidification on the behaviour of coral reef fishes are not reproducible, suggesting that behavioural perturbations will not be a major consequence for coral reef fishes in high CO2 oceans.

Continue reading ‘Ocean acidification does not impair the behaviour of coral reef fishes’

Coccolithophore growth and calcification in an acidified ocean: insights from community earth system model simulations

Anthropogenic CO2 emissions are inundating the upper ocean, acidifying the water, and altering the habitat for marine phytoplankton. These changes are thought to be particularly influential for calcifying phytoplankton, namely, coccolithophores. Coccolithophores are widespread and account for a substantial portion of open ocean calcification; changes in their abundance, distribution, or level of calcification could have far‐reaching ecological and biogeochemical impacts. Here, we isolate the effects of increasing CO2 on coccolithophores using an explicit coccolithophore phytoplankton functional type parameterization in the Community Earth System Model. Coccolithophore growth and calcification are sensitive to changing aqueous CO2. While holding circulation constant, we demonstrate that increasing CO2 concentrations cause coccolithophores in most areas to decrease calcium carbonate production relative to growth. However, several oceanic regions show large increases in calcification, such the North Atlantic, Western Pacific, and parts of the Southern Ocean, due to an alleviation of carbon limitation for coccolithophore growth. Global annual calcification is 6% higher under present‐day CO2 levels relative to preindustrial CO2 (1.5 compared to 1.4 Pg C/year). However, under 900 μatm CO2, global annual calcification is 11% lower than under preindustrial CO2 levels (1.2 Pg C/year). Large portions of the ocean show greatly decreased coccolithophore calcification relative to growth, resulting in significant regional carbon export and air‐sea CO2 exchange feedbacks. Our study implies that coccolithophores become more abundant but less calcified as CO2 increases with a tipping point in global calcification (changing from increasing to decreasing calcification relative to preindustrial) at approximately ∼600 μatm CO2.

Continue reading ‘Coccolithophore growth and calcification in an acidified ocean: insights from community earth system model simulations’

Reduced nitrogenase efficiency dominates response of the globally important nitrogen fixer Trichodesmium to ocean acidification

The response of the prominent marine dinitrogen (N2)-fixing cyanobacteria Trichodesmium to ocean acidification (OA) is critical to understanding future oceanic biogeochemical cycles. Recent studies have reported conflicting findings on the effect of OA on growth and N2fixation of Trichodesmium. Here, we quantitatively analyzed experimental data on how Trichodesmium reallocated intracellular iron and energy among key cellular processes in response to OA, and integrated the findings to construct an optimality-based cellular model. The model results indicate that Trichodesmium growth rate decreases under OA primarily due to reduced nitrogenase efficiency. The downregulation of the carbon dioxide (CO2)-concentrating mechanism under OA has little impact on Trichodesmium, and the energy demand of anti-stress responses to OA has a moderate negative effect. We predict that if anthropogenic CO2 emissions continue to rise, OA could reduce global N2 fixation potential of Trichodesmium by 27% in this century, with the largest decrease in iron-limiting regions.

Continue reading ‘Reduced nitrogenase efficiency dominates response of the globally important nitrogen fixer Trichodesmium to ocean acidification’

Studentized bootstrap model-averaged tail area intervals

In many scientific studies, the underlying data-generating process is unknown and multiple statistical models are considered to describe it. For example, in a factorial experiment we might consider models involving just main effects, as well as those that include interactions. Model-averaging is a commonly-used statistical technique to allow for model uncertainty in parameter estimation. In the frequentist setting, the model-averaged estimate of a parameter is a weighted mean of the estimates from the individual models, with the weights typically being based on an information criterion, cross-validation, or bootstrapping. One approach to building a model-averaged confidence interval is to use a Wald interval, based on the model-averaged estimate and its standard error. This has been the default method in many application areas, particularly those in the life sciences. The MA-Wald interval, however, assumes that the studentized model-averaged estimate has a normal distribution, which can be far from true in practice due to the random, data-driven model weights. Recently, the model-averaged tail area Wald interval (MATA-Wald) has been proposed as an alternative to the MA-Wald interval, which only assumes that the studentized estimate from each model has a N(0, 1) or t-distribution, when that model is true. This alternative to the MA-Wald interval has been shown to have better coverage in simulation studies. However, when we have a response variable that is skewed, even these relaxed assumptions may not be valid, and use of these intervals might therefore result in poor coverage. We propose a new interval (MATA-SBoot) which uses a parametric bootstrap approach to estimate the distribution of the studentized estimate for each model, when that model is true. This method only requires that the studentized estimate from each model is approximately pivotal, an assumption that will often be true in practice, even for skewed data. We illustrate use of this new interval in the analysis of a three-factor marine global change experiment in which the response variable is assumed to have a lognormal distribution. We also perform a simulation study, based on the example, to compare the lower and upper error rates of this interval with those for existing methods. The results suggest that the MATA-SBoot interval can provide better error rates than existing intervals when we have skewed data, particularly for the upper error rate when the sample size is small.

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Linking social preferences and ocean acidification impacts in mussel aquaculture

Ocean Acidification (OA) has become one of the most studied global stressors in marine science during the last fifteen years. Despite the variety of studies on the biological effects of OA with marine commercial species, estimations of these impacts over consumers’ preferences have not been studied in detail, compromising our ability to undertake an assessment of market and economic impacts resulting from OA at local scales. Here, we use a novel and interdisciplinary approach to fill this gap. We experimentally test the impact of OA on commercially relevant physical and nutritional attributes of mussels, and then we use economic discrete choice models to assess the marginal effects of these impacts over consumers’ preferences and wellbeing. Results showed that attributes, which were significantly affected by OA, are also those preferred by consumers. Consumers are willing to pay on average 52% less for mussels with evidences of OA and are willing to increase the price they pay to avoid negative changes in attributes due to OA. The interdisciplinary approach developed here, complements research conducted on OA by effectively informing how OA economic impacts can be analyzed under the lens of marginal changes in market price and consumer’ welfare. Thereby, linking global phenomena to consumers’ wellbeing, and shifting the focus of OA impacts to assess the effects of local vulnerabilities in a wider context of people and businesses.

Continue reading ‘Linking social preferences and ocean acidification impacts in mussel aquaculture’


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Ocean acidification in the IPCC AR5 WG II

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