Posts Tagged 'communitymodeling'

Using fuzzy logic to determine the vulnerability of marine species to climate change

Marine species are being impacted by climate change and ocean acidification, although their level of vulnerability varies due to differences in species’ sensitivity, adaptive capacity and exposure to climate hazards. Due to limited data on the biological and ecological attributes of many marine species, as well as inherent uncertainties in the assessment process, climate change vulnerability assessments in the marine environment frequently focus on a limited number of taxa or geographic ranges. As climate change is already impacting marine biodiversity and fisheries, there is an urgent need to expand vulnerability assessment to cover a large number of species and areas. Here, we develop a modelling approach to synthesize data on species-specific estimates of exposure, and ecological and biological traits to undertake an assessment of vulnerability (sensitivity and adaptive capacity) and risk of impacts (combining exposure to hazards and vulnerability) of climate change (including ocean acidification) for global marine fishes and invertebrates. We use a fuzzy logic approach to accommodate the variability in data availability and uncertainties associated with inferring vulnerability levels from climate projections and species’ traits. Applying the approach to estimate the relative vulnerability and risk of impacts of climate change in 1074 exploited marine species globally, we estimated their index of vulnerability and risk of impacts to be on average 52 ± 19 SD and 66 ± 11 SD, scaling from 1 to 100, with 100 being the most vulnerable and highest risk, respectively, under the ‘business-as-usual’ greenhouse gas emission scenario (Representative Concentration Pathway 8.5). We identified 157 species to be highly vulnerable while 294 species are identified as being at high risk of impacts. Species that are most vulnerable tend to be large-bodied endemic species. This study suggests that the fuzzy logic framework can help estimate climate vulnerabilities and risks of exploited marine species using publicly and readily available information.

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Using multiple lines of evidence to assess the risk of ecosystem collapse

Effective ecosystem risk assessment relies on a conceptual understanding of ecosystem dynamics and the synthesis of multiple lines of evidence. Risk assessment protocols and ecosystem models integrate limited observational data with threat scenarios, making them valuable tools for monitoring ecosystem status and diagnosing key mechanisms of decline to be addressed by management. We applied the IUCN Red List of Ecosystems criteria to quantify the risk of collapse of the Meso-American Reef, a unique ecosystem containing the second longest barrier reef in the world. We collated a wide array of empirical data (field and remotely sensed), and used a stochastic ecosystem model to backcast past ecosystem dynamics, as well as forecast future ecosystem dynamics under 11 scenarios of threat. The ecosystem is at high risk from mass bleaching in the coming decades, with compounding effects of ocean acidification, hurricanes, pollution and fishing. The overall status of the ecosystem is Critically Endangered (plausibly Vulnerable to Critically Endangered), with notable differences among Red List criteria and data types in detecting the most severe symptoms of risk. Our case study provides a template for assessing risks to coral reefs and for further application of ecosystem models in risk assessment.

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Understanding the impacts of anthropogenic stressors on species, ecosystems, and fishing communities

Anthropogenic modifications of marine environments result from a variety of activities and have effects across social and ecological dimensions. Humans inhabit linked systems, where our actions such as resource extraction, pollution and development influence species in both direct and indirect ways and feedback to influence the human communities dependent on living marine resources. In order to understand the consequences of our actions and develop strategies to plan for future environmental change, we need a diverse set of tools able to incorporate various levels of complexity. This necessitates the improvement and modification of existing tools, development of novel approaches and unique applications of methods from across fields. In this dissertation I address the ways in which we can use and improve existing tools in ecology to advance our understanding and management of marine resources. In the first Chapter I introduce a method to incorporate life stage specific responses to a stressor, ocean acidification, to gain a broader understanding of population level vulnerability. In the second Chapter I extend this work to address ecosystem level change from ocean acidification in the California Current, using an ecosystem model to determine changes in biomass and fisheries catch. In the third chapter, I work to improve our understanding of how multiple stressors acting across life history can be magnified or mitigated, based solely on biological characteristics of populations. Finally, in the fourth Chapter I introduce ecologists and natural scientists to a broader understanding of research on risk in order to improve our methods for approaching ecosystem based fisheries management. My work spans ecological scales from populations to ecosystems and links between social and ecological systems.

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Multiple stressors and the functioning of coral reefs

Coral reefs provide critical services to coastal communities, and these services rely on ecosystem functions threatened by stressors. By summarizing the threats to the functioning of reefs from fishing, climate change, and decreasing water quality, we highlight that these stressors have multiple, conflicting effects on functionally similar groups of species and their interactions, and that the overall effects are often uncertain because of a lack of data or variability among taxa. The direct effects of stressors on links among functional groups, such as predator-prey interactions, are particularly uncertain. Using qualitative modeling, we demonstrate that this uncertainty of stressor impacts on functional groups (whether they are positive, negative, or neutral) can have significant effects on models of ecosystem stability, and reducing uncertainty is vital for understanding changes to reef functioning. This review also provides guidance for future models of reef functioning, which should include interactions among functional groups and the cumulative effect of stressors.

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Exposure history determines pteropod vulnerability to ocean acidification along the US West Coast

The pteropod Limacina helicina frequently experiences seasonal exposure to corrosive conditions (Ωar  < 1) along the US West Coast and is recognized as one of the species most susceptible to ocean acidification (OA). Yet, little is known about their capacity to acclimatize to such conditions. We collected pteropods in the California Current Ecosystem (CCE) that differed in the severity of exposure to Ωar conditions in the natural environment. Combining field observations, high-CO2 perturbation experiment results, and retrospective ocean transport simulations, we investigated biological responses based on histories of magnitude and duration of exposure to Ωar < 1. Our results suggest that both exposure magnitude and duration affect pteropod responses in the natural environment. However, observed declines in calcification performance and survival probability under high CO2 experimental conditions do not show acclimatization capacity or physiological tolerance related to history of exposure to corrosive conditions. Pteropods from the coastal CCE appear to be at or near the limit of their physiological capacity, and consequently, are already at extinction risk under projected acceleration of OA over the next 30 years. Our results demonstrate that Ωar exposure history largely determines pteropod response to experimental conditions and is essential to the interpretation of biological observations and experimental results.

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Size-dependent response of foraminiferal calcification to seawater carbonate chemistry (update)

The response of the marine carbon cycle to changes in atmospheric CO2 concentrations will be determined, in part, by the relative response of calcifying and non-calcifying organisms to global change. Planktonic foraminifera are responsible for a quarter or more of global carbonate production, therefore understanding the sensitivity of calcification in these organisms to environmental change is critical. Despite this, there remains little consensus as to whether, or to what extent, chemical and physical factors affect foraminiferal calcification. To address this, we directly test the effect of multiple controls on calcification in culture experiments and core-top measurements of Globigerinoides ruber. We find that two factors, body size and the carbonate system, strongly influence calcification intensity in life, but that exposure to corrosive bottom waters can overprint this signal post mortem. Using a simple model for the addition of calcite through ontogeny, we show that variable body size between and within datasets could complicate studies that examine environmental controls on foraminiferal shell weight. In addition, we suggest that size could ultimately play a role in determining whether calcification will increase or decrease with acidification. Our models highlight that knowledge of the specific morphological and physiological mechanisms driving ontogenetic change in calcification in different species will be critical in predicting the response of foraminiferal calcification to future change in atmospheric pCO2.

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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.

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Ocean acidification in the IPCC AR5 WG II

OUP book