Qualitative Network Models Research Articles

Multiple stakeholders’ perspectives of marine social ecological systems, a case study on the Barents Sea

The Barents Sea ecosystem components and services are under pressure from climate change and other anthropogenic impacts. Following an Ecosystem-based management approach, multiple simultaneous pressures are addressed by using integrative strategies, but regular prioritization of key issues is needed. Identification of such priorities is typically done in a ‘scoping’ phase, where the characterization of the social-ecological system is defined and discussed. We performed a scoping exercise using an open and flexible multi-stakeholder approach to build conceptual models of the Barents Sea social-ecological system. After standardizing vocabulary, a complex hierarchical model structure containing 155 elements was condensed to a simpler model structure containing a maximum of 36 elements. To capture a common understanding across stakeholder groups, inputs from the individual group models were compiled into a collective model. Stakeholders' representation of the Barents Sea social-ecological system is complex and often group specific, emphasizing the need to include social scientific methods to ensure the identification and inclusion of key stakeholders in the process. Any summary or simplification of the stakeholders' representation neglects important information. Some commonalities are highlighted in the collective model, and additional information from the hierarchical model is provided by multicriteria analysis. The collective conceptual stakeholder model provides input to an integrated overview and strengthens prioritization in Ecosystem-based management by supporting the development of qualitative network models. Such models allow for exploration of perturbations and can inform cross-sectoral management trade-offs and priorities.

Evaluating ecosystem-based management alternatives for the Puget Sound, U.S.A. social-ecological system using qualitative watershed models

Population growth and the associated transformation of landscapes is a major management challenge for coastal ecosystems. Coastal conservation and management should be guided by social, cultural, economic, and ecological objectives, but integrative decision support tools appropriate for complex ecosystems remain underutilized. Evaluating alternative policies for objectives that span the interconnected terrestrial, freshwater, and estuarine habitats along coastlines is limited by the lack of appropriate quantitative tools and available data. We employed qualitative network models (QNMs) to evaluate multi-benefit outcomes of potential management interventions to address population growth and development using a case study of Puget Sound – a large, urbanized fjord-type estuary in Washington, U.S.A. With input from regional scientists and stakeholders, we developed a base conceptual model of the links among human stressors and ecosystem components across the terrestrial-freshwater-estuarine gradient of a generalized Puget Sound watershed. We simulated scenarios representing alternative strategies for accommodating human population growth, namely new development outside of urban centers versus redevelopment (densification) within urban centers, and characterized the responses of multiple recovery objectives and ecosystem stressors for each scenario. Of the urban redevelopment scenarios, reducing stormwater runoff and increasing green infrastructure provided the most favorable outcomes. On rural lands, limiting new development to existing transportation corridors and iincreasing floodplain and riparian habitat extent concomitant with new development produced similar outcomes. Moderate levels of coordinated interventions on both urban and rural lands had favorable outcomes for more ecosystem objectives compared to either moderate intervention applied separately. This study demonstrates the value of qualitative tools for cross-habitat evaluations of possible futures in complex ecosystem-based management systems.

Social-ecological approaches to shellfish aquaculture using qualitative network models

AbstractIntegrating social and ecological aspects of bivalve aquaculture in research and management processes can improve understanding of the system as a whole, and facilitate management decision-making. We created social-ecological conceptual models of Pacific oyster (Crassostrea gigas), Manila clam (Venerupis philippinarum), and Pacific geoduck (Panopea generosa) aquaculture in a USA estuary, which were the basis of qualitative network analysis to compare: (i) social-ecological models versus truncated ecological- and social- only models, and (ii) two geoduck models representing different stakeholder groups’ perspectives on nature-based recreation and environmental stewardship. The social-ecological models predicted different results compared to individual social or ecological models, including for abundance of invertebrates, eelgrass, and marine water quality. The two alternative geoduck models predicted outcomes that varied across multiple social-ecological variables, including the availability of local harvestable food, sense of place, and abundance of invertebrates in structured habitat. Results demonstrate the interconnectedness of the social and ecological components of the aquaculture system, and how predicted outcomes can vary depending on their inclusion in the model. This study also demonstrates the value in considering a suite of models that represents a range of group perspectives to identify areas of conflict and agreement, and to recognize bias inherent in the models.

Examining the Role of Marine Mammals and Seabirds in Southeast Alaska’s Marine Ecosystem Dynamics

Primary producers are the foundation of marine food webs and require reliable nutrient sources to maintain their important role with ecosystems. While marine mammals and seabirds can play critical roles in marine nutrient cycling, their contributions are often overlooked. Southeast Alaska’s marine environment supports abundant marine mammal and seabird populations in addition to valuable fisheries. Nonetheless, there is still relatively little known about nutrient sources and fluxes in this region which is a critical component of fisheries management. The goal of our study was to advance knowledge of the role of mammals and seabirds in marine nutrient cycling and to understand how changing marine mammal and seabird populations may alter ecosystem dynamics. We utilized qualitative network models (QNMs) to examine how a simulated Southeast Alaska ecosystem would respond to an increase in marine mammals, seabirds, and nutrients. Researchers are increasingly utilizing QNMs as a first step in the development of ecosystem-based fisheries management plans as their adaptable nature is well suited to address rapidly changing climatic conditions. Our results indicate that marine mammals and seabirds make important contributions to marine nutrient concentrations in the region and that these valuable ecosystem services should not be overlooked.

Trophic mediation and ecosystem stability: An assessment using qualitative network models

AbstractNontrophic interactions can contribute to negative and positive feedbacks within a community, thus affecting likelihood of regime shifts; however, assessing the nature and importance of these effects in a network remains challenging, especially for pelagic ecosystems. Here, we present a qualitative modeling approach for assessing the importance of different effects and resultant feedbacks for community stability, using a Southern Ocean example. A potentially important positive feedback in the Southern Ocean ecosystem involves production of a chemical cue, dimethyl sulfide (DMS), by some phytoplankton. Production of DMS can promote phytoplankton growth by attracting predators of phytoplankton‐grazers, and nutrients released as feces from those predators help fertilize the water column. We explored how uncertainties in the nature of this feedback affect community stability in a set of small, community models. We found that stability varied substantially depending on how the community was modeled, but that the interactions most important for determining stability were consistent across all models. Model stability was sensitive to the strength of phytoplankton competition, controls on phytoplankton, DMS production and release, and predator attraction to DMS, suggesting that the community could be destabilized by perturbation affecting these interactions. Incorporating DMS‐mediated feedbacks into a larger Southern Ocean network had a moderate impact on stability characteristics and altered the trophic level at which the system would be most vulnerable to perturbation.

Examining the expansion of qualitative network models towards integrating multifaceted human dimensions

Abstract Qualitative network models (QNMs) have become a popular tool to assess how ecosystems respond to a perturbation within ecosystem-based fisheries management strategies. Yet, the incorporation of humans into these models is often rudimentary, potentially limiting the accuracy and reliability of the model results. We developed QNMs focusing solely on the social components, derived from content analysis of the literature on the effects of the US Pacific halibut Individual Fishing Quota (IFQ) Program and evaluated how the QNMs performed with respect to simulating the programmatic effects on individual well-being components. The QNMs were effective at reproducing IFQ programmatic effects and demonstrating how well-being heterogeneity across user groups can be incorporated into network models. However, key mechanistic variables were omitted to maintain model stability, reducing our ability to fully replicate the IFQ system. We conclude that QNMs require improvement to incorporate human dimensions that reflect broader social realities. Yet, given the current structural limitations of these modelling frameworks coupled with the complexity of human decision making, there are likely to be continued issues with integrating humans accurately and representatively into these models.

Adaptive Behaviors to Marine Ecosystem Shifts: Examining Fishermen’s Strategies in Response to Abundant Juvenile Sablefish (Anoplopoma fimbria) in Alaska

Over recent years there have been rapid changes occurring across marine ecosystems worldwide, with high latitude systems seeing ecosystem shifts emerging at unprecedented rates. The Gulf of Alaska and Bering Sea marine ecosystems have experienced substantial fluctuation in fish stocks, with some species experiencing considerable decreases while others thrive. Following the marine heatwave of 2014, sablefish (Anoplopoma fimbria) had a historically unparalleled juvenile recruitment class that is now dominating the stock composition. While this recruitment class bodes well for future fisheries, it is currently undermining the value of the fishery with limited incentives to retain the smaller and less valuable fish, compounding adverse effects on earnings in the fishery due to whale depredation that has been occurring for years. This study examines the well-being implications of fishermen’s adaptive strategies to these ecosystem conditions within the Alaska sablefish fishery using a socio-ecological system framework, operationalized as a qualitative network model (QNMs) and quantitative indicators. We examine the extent to which adaptation strategies, derived from a literature review and stakeholder interviews, are being utilized in the fishery with quantitative indicators. These strategies are then examined with QNMs that explore their impacts across the spectrum of well-being. By coupling quantitative indicators and QNMs, we were able to demonstrate how adaptive strategies can be examined to capture the multi-faceted well-being effects of fisheries participants’ adaptations to changing conditions. This study directly addresses several of the key guiding principles of the U.S. EBFM Road Map, including advancing our understanding of ecosystem processes, exploring trade-offs within an ecosystem, and maintaining resilient ecosystems, inclusive of community well-being. Thus this paper demonstrates how coupled socio-ecological models can elevate the inclusion of human adaptive behaviors, providing a framework for the development of policymaking that can mitigate adverse effects on both the participants and the resource by facilitating the mixture of adaptive strategies that maximizes desired well-being outcomes.

Participatory place-based integrated ecosystem assessment in Sitka, Alaska: Constructing and operationalizing a socio-ecological conceptual model for sablefish (Anoplopoma fimbria)

An integrated ecosystem assessment (IEA) is a framework that organizes science to aid in the transition from traditional single-species management towards ecosystem-based management. Within the Gulf of Alaska, we started a small-scale IEA framework with active engagement of local stakeholders in the fishing community of Sitka. The initial step of this framework was the development of conceptual models. Here, we present a co-produced conceptual model using data gathered from participatory focus groups and a literature review of ecosystem attributes driving the abundance of sablefish (Anoplopoma fimbria). We then assembled a qualitative network model (QNM), a mathematical representation of a conceptual system in which perturbations of individual components can be assessed for their qualitative effect. Simulations were conducted to test different biophysical scenarios, while evaluating tradeoffs across ecological and human dimension components. In contrast to large adult sablefish, juvenile and small adults responded similarly to most biophysical conditions. In general, human dimension components responded negatively to the tested scenarios. These results highlight the potential need for management strategies that differentiate between small and large adults, particularly if current sablefish stock assessment trends persist, such as the lack of older fish contributing to spawning biomass and uncertainties in estimates of year-class strength.

Using qualitative network models to assess the influence of mussel culture on ecosystem dynamics

The expansion of the aquaculture industry in the last several decades has raised concerns about potential ecological impacts of the industry. Bivalve culture, particularly mussel farming, relies on naturally occurring plankton and numerous studies have demonstrated top-down control on phytoplankton, increased nutrients through excretion of metabolic wastes and remineralization of faeces and pseudofaeces, and bottom-up effects on predators and scavengers through mussel fall-off. However, results are inconsistent between studies, and hydrodynamic conditions and nutrient availability are thought to play an important role in the magnitude and the direction of the ecological effects of mussel culture on the surrounding ecosystem. We used qualitative network models (QNMs), to outline a general model that integrates these environmental conditions and (1) evaluated the ability of different model configurations to reproduce known responses to perturbations, (2) analyzed the behaviour of key components to contrasting hydrodynamic and nutrient condition scenarios, and (3) identified the most influential features of the derived scenarios. The model that included uncertain linkages to characterize unknown relationships performed best based on predetermined validation criteria; the addition of semi-quantitative information on the relative strength of certain linkages improved accuracy and sign determinacy of outcomes. The presence of suspended mussel culture negatively affected primary producers, zooplankton and deposit-feeders, and had a positive effect on predators and scavengers, especially in low-energy environments. Hydrodynamic conditions were shown to have a major impact on the response of the community to mussel culture, while nutrient availability had a very minor impact.

Governing offshore fish aggregating devices in the Eastern Caribbean: Exploring trade-offs using a qualitative network model.

The use of moored Fish Aggregating Devices (FADs) in small-scale fisheries is a potential solution to food security concerns, economic development needs, and the overexploitation of nearshore coastal fisheries in the Eastern Caribbean. However, moored FADs also generate novel and largely unstudied governance challenges involving (1) the provisioning of FADs, (2) fisheries resource appropriation, (3) human wellbeing, and (4) food web impacts. We examine the relative performance of three governance scenarios to address these challenges: private-individual, community-based, and top-down governance. We construct a qualitative network model (QNM) of the fishery based on semi-structured interviews (n = 60) with fishers and fisheries managers, established food web and economic models, and expert knowledge. We simulate the social-ecological impacts of the three governance scenarios. The models suggest that community-based and top-down governance scenarios result in low levels of conflict, but provide limited incentives to develop and maintain moored FADs. The private-individual governance scenario tends to increase conflict and incentives for monitoring FADs, but has no impact on incentives for maintaining and deploying FADs.

Integrated assessment of the spatial distribution and structural dynamics of deep benthic marine communities.

Characterizing the spatial distribution and variation of species communities and validating these characteristics with data from the field are key elements for an ecosystem-based approach to management. However, models of species distributions that yield community structure are usually not linked to models of community dynamics, constraining understanding and management of the ecosystem, particularly in data-poor regions. Here we use a qualitative network model to predict changes in Antarctic benthic community structure between major marine habitats characterized largely by seafloor depth and slope, and use multivariate mixture models of species distributions to validate the community dynamics. We then assess how future increases in primary production associated with anticipated loss of sea-ice may affect the ecosystem. Our study shows how both spatial and structural features of ecosystems in data-poor regions can be analyzed and possible futures assessed, with direct relevance for ecosystem-based management.

Assessment of Thalassia hemprichii seagrass metrics for biomonitoring of environmental status

Seagrass has long been known to be very sensitive to environmental changes, especially caused by human activities and has been used as a bioindicator for environmental condition of ecosystems. This research aimed to study 19 Thalassia hemprichii metrics (10 measured and 9 derived metrics) at two organizational levels (individual and population), to explore and confirm these metrics for development of a multimetric index of environmental quality. Seagrass meadows was selected along a gradient of an anthropogenic disturbance at Kepulauan Seribu (inhabited and uninhabited locations, fixed effect, namedly Status), 4 sites for each location (random effect nested in status) within intertidal and subtidal zones (random effect across Sites). We also briefly described about social-ecological system of seagrass being studied using a qualitative network model, for an understanding of interaction that affects the exploited seagrass ecosystems. The significance of variability between states, sites, and zones were examined using linear mixed effect model followed by exploratory factor analysis in the confirmatory factor analysis (CFA) framework (E/CFA strategy) to explore and confirm adequacy of the metrics as indicators for two-factor organizational levels (individual and population). Based on the analysis, leaf surface area, leaf wide, leaf area index, density, rhizome diameter, and Thalassia hemprichii cover differed significantly at the scale of interest and represented two levels of organizational levels (individual and population).

Rapid assessment of management options for promoting stock rebuilding in data-poor species under climate change.

The development of species recovery plans requires considering likely outcomes of different management interventions, but the complicating effects of climate change are rarely evaluated. We examined how qualitative network models (QNMs) can be deployed to support decision making when data, time, and funding limitations restrict use of more demanding quantitative methods. We used QNMs to evaluate management interventions intended to promote the rebuilding of a collapsed stock of blue king crab (Paralithodes platypus) (BKC) around the Pribilof Islands (eastern Bering Sea) to determine how their potential efficacy may change under climate change. Based on stakeholder input and a literature review, we constructed a QNM that described the life cycle of BKC, key ecological interactions, potential climate-change impacts, relative interaction strengths, and uncertainty in terms of interaction strengths and link presence. We performed sensitivity analyses to identify key sources of prediction uncertainty. Under a scenario of no climate change, predicted increases in BKC were reliable only when stock enhancement was implemented in a BKC hatchery-program scenario. However, when climate change was accounted for, the intervention could not counteract its adverse impacts, which had an overall negative effect on BKC. The remaining management scenarios related to changes in fishing effort on BKC predators. For those scenarios, BKC outcomes were unreliable, but climate change further decreased the probability of observing recovery. Including information on relative interaction strengths increased the likelihood of predicting positive outcomes for BKC approximately 5-50% under the management scenarios. The largest gains in prediction precision will be made by reducing uncertainty associated with ecological interactions between adult BKC and red king crab (Paralithodes camtschaticus). Qualitative network models are useful options when data are limited, but they remain underutilized in conservation.

Dealing with high uncertainty in qualitative network models using Boolean analysis

Abstract Models for predicting ecological behaviour typically require large volumes of data for parameterisation, which is a problem because data are scarce. Qualitative modelling (QM) provides an alternative by exploring the entire range of possible parameter values. When a parameter value is completely unknown, QM typically invokes the Principle of Indifference (PoI), for example by sampling the parameter from a uniform prior distribution. However, if PoI is invoked in this probabilistic way, there may be multiple possible methods for defining a parameter space and sampling values from it, and, worryingly, two different but equally defensible methods can lead to different predictions about ecosystem responses. We investigated how probabilistic PoI can give rise to problems in QM, and developed an alternative method based on Boolean PoI that does not suffer the same limitations. We used a case study that involved predicting the responses of multiple species to the suppression of a pest. The unknown model parameters were interaction strengths between species. For the standard probabilistic method, we drew the parameters randomly from uniform (PoI) and other distributions. For our new Boolean PoI method, we instead simply specified the ranges of “possible” parameter values, and developed a Boolean analysis technique to summarise model predictions. As expected, invoking probabilistic QM yielded different predictions (species‐response probabilities) for different but equally defensible parameterisation and sampling schemes. Sometimes differences were large enough to impact decision‐making. In contrast, our new Boolean PoI approach simply classifies outcomes (species responses) as certain, possible, or impossible. Encouragingly, some species responses that were not consistently resolved under probabilistic PoI were shown by our method to be in fact governed by simple rules. Our method can also identify key species whose responses determine whole‐system outcomes. Our non‐probabilistic representation of uncertainty circumvents the philosophical problems in standard implementations of PoI for QM. Our Boolean analysis method summarises results in a way that is interpretable and potentially useful to conservation decision makers. A priority for future research is to increase the efficiency of our Boolean approach to allow it to deal with problems of higher complexity (more interactions).

Global and Domestic Networks Advancing Prospects for Institutional and Social Change: The Collective Action Response to Violence Against Journalists

Violence against journalists has emerged as a global human rights issue as the number of those killed in the profession has steadily risen in the new millennium. This research utilized a collective action framework, applying an adapted qualitative network model to examine organizational mobilization, transnational and domestic engagement, normative appeals, information dissemination, lobbying, and prospects for institutional and societal change. Through the Mexico case model application, the study found that instrumental change occurred through adoption of legal and policy institutions. Future research should expand upon social change measurements utilized in this study. We conclude the model can be adapted and utilized in other country cases or in cross-national research.

Linking ecosystem processes to communities of practice through commercially fished species in the Gulf of Alaska

Abstract Marine ecosystems are complex, and there is increasing recognition that environmental, ecological, and human systems are linked inextricably in coastal regions. The purpose of this article was to integrate environmental, ecological and human dimensions information important for fisheries management into a common analytical framework. We then used the framework to examine the linkages between these traditionally separate subject areas. We focused on synthesis of linkages between the Gulf of Alaska marine ecosystem and human communities of practice, defined as different fisheries sectors. Our specific objective was to document the individual directional linkages among environmental, ecological, and human dimensions variables in conceptual models, then build qualitative network models to perform simulation analyses to test how bottom-up and top-down perturbations might propagate through these linkages. We found that it is both possible and beneficial to integrate environmental, ecological, and human dimensions information important for fisheries into a common framework. First, the conceptual models allowed us to synthesize information across a broad array of data types, representing disciplines such as ecology and economics that are more commonly investigated separately, often with distinct methods. Second, the qualitative network analysis demonstrated how ecological signals can propagate to human communities, and how fishery management measures may influence the system. Third, we found that incorporating multi-species interactions changed outcomes because the merged model reversed some of the ecological and human outcomes compared with single species analyses. Overall, we demonstrated the value of linking information from the natural and social sciences to better understand complex social–ecological systems, and the value of incorporating ecosystem-level processes into a traditionally single species management framework. We advocate for conceptual and qualitative network modelling as efficient foundational steps to inform ecosystem-based fisheries management.

A dynamic genetic-hormonal regulatory network model explains multiple cellular behaviors of the root apical meristem of Arabidopsis thaliana.

The study of the concerted action of hormones and transcription factors is fundamental to understand cell differentiation and pattern formation during organ development. The root apical meristem of Arabidopsis thaliana is a useful model to address this. It has a stem cell niche near its tip conformed of a quiescent organizer and stem or initial cells around it, then a proliferation domain followed by a transition domain, where cells diminish division rate before transiting to the elongation zone; here, cells grow anisotropically prior to their final differentiation towards the plant base. A minimal model of the gene regulatory network that underlies cell-fate specification and patterning at the root stem cell niche was proposed before. In this study, we update and couple such network with both the auxin and cytokinin hormone signaling pathways to address how they collectively give rise to attractors that correspond to the genetic and hormonal activity profiles that are characteristic of different cell types along A. thaliana root apical meristem. We used a Boolean model of the genetic-hormonal regulatory network to integrate known and predicted regulatory interactions into alternative models. Our analyses show that, after adding some putative missing interactions, the model includes the necessary and sufficient components and regulatory interactions to recover attractors characteristic of the root cell types, including the auxin and cytokinin activity profiles that correlate with different cellular behaviors along the root apical meristem. Furthermore, the model predicts the existence of activity configurations that could correspond to the transition domain. The model also provides a possible explanation for apparently paradoxical cellular behaviors in the root meristem. For example, how auxin may induce and at the same time inhibit WOX5 expression. According to the model proposed here the hormonal regulation of WOX5 might depend on the cell type. Our results illustrate how non-linear multi-stable qualitative network models can aid at understanding how transcriptional regulators and hormonal signaling pathways are dynamically coupled and may underlie both the acquisition of cell fate and the emergence of hormonal activity profiles that arise during complex organ development.

Using Conceptual Models and Qualitative Network Models to Advance Integrative Assessments of Marine Ecosystems

ABSTRACTThe complexity of ecosystem-based management (EBM) of natural resources has given rise to research frameworks such as integrated ecosystem assessments (IEA) that pull together large amounts of diverse information from physical, ecological, and social domains. Conceptual models are valuable tools for assimilating and simplifying this information to convey our understanding of ecosystem structure and functioning. Qualitative network models (QNMs) may allow us to conduct dynamic simulations of conceptual models to explore natural–social relationships, compare management strategies, and identify tradeoffs. We used previously developed QNM methods to perform simulations based on conceptual models of the California Current ecosystem's pelagic communities and related human activities and values. Assumptions about community structure and trophic interactions influenced the outcomes of the QNMs. In simulations where we applied unfavorable environmental conditions for production of salmon (Oncorhynchus spp.), intensive management actions only modestly mitigated declines experienced by salmon, but strongly constrained human activities. Moreover, the management actions had little effect on a human wellbeing attribute, sense of place. Sense of place was most strongly affected by a relatively small subset of all possible pair-wise interactions, although the relative influence of individual pair-wise interactions on sense of place grew more uniform as management actions were added, making it more difficult to trace effective management actions via specific mechanistic pathways. Future work will explore the importance of changing conceptual models and QNMs to represent management questions at finer spatial and temporal scales, and also examine finer representation of key ecological and social components.

Mechanisms driving Antarctic microbial community responses to ocean acidification: a network modelling approach

Rising atmospheric CO2 concentrations and the subsequent changes to ocean chemistry may have pronounced effects on marine microbial communities, particularly for the cold Southern Ocean. Changes to the microbial community in this region could affect the way nutrients are cycled, impact the efficiency of carbon drawdown, and cause shifts in food supply to higher trophic levels. Increased CO2 could affect the bioavailability of iron to phytoplankton. Fertilisation experiments show that iron can influence phytoplankton community composition, favouring large phytoplankton species in iron-replete conditions. The potential interactive effects of CO2 and iron bioavailability are currently poorly understood but are likely to be important in determining CO2-induced changes to the microbial community. We employ a qualitative network modelling approach to evaluate alternative hypotheses regarding the effects of elevated CO2 on Antarctic microbial communities in incubation experiments. We used a sequential approach to model development and testing, where we first formulated a base model for microbial community interactions, and then sequentially added direct and indirect effects of elevated CO2 on particular groups. We found that model simulations were most consistent with observations from incubation experiments when we assumed an indirect effect of CO2 on phytoplankton. In particular, when we assumed a negative effect of elevated CO2 on the uptake of iron by large phytoplankton, as a result of a decrease in iron bioavailability. Our findings show that qualitative network models can be used to test hypotheses relating to results from experimental studies, and help identify key processes to target in future studies.

Evaluating community impacts of ocean acidification using qualitative network models

Evaluating community impacts of ocean acidification using qualitative network models