| 1. Domain | 1.1 Scope of the Domain | Boundaries | The range of phenomena the science includes and excludes. | Studies the distribution, abundance, physiology, interactions, and ecological roles of marine organisms, and how physical, chemical, and geological processes structure ocean life. Includes plankton ecology, food webs, biogeochemical cycles, primary production, microbial processes, and ecosystem dynamics. Excludes purely physical, chemical, or geological processes except where they influence biology. |
| | Scale | The spatial, temporal, or organizational level at which the science operates (e.g., quantum, cellular, social, cosmic). | Operates from microbial genes → cellular processes → individual organisms → populations → communities → ecosystems → global biosphere. Time scales range from seconds (mixing, grazing) to millennia (evolution, carbon sequestration). |
| 1.2 Ontological Commitments | Entities | The kinds of things assumed to exist within the domain (particles, organisms, agents, fields, etc.). | Phytoplankton, zooplankton, bacterioplankton, viruses, nekton, benthos, larvae, marine snow, microbial consortia, food webs, trophic levels, functional groups, ecosystems, carbon pools, nutrients, dissolved organic matter. |
| | Properties | The fundamental attributes these entities possess (mass, charge, genotype, preference, etc.). | Biomass, growth rate, productivity, respiration, nutrient uptake, stoichiometry, grazing rate, diversity, size spectra, metabolic rate, elemental composition (C:N:P ratios), physiological traits, motility, mortality. |
| | Categories | The basic ontological types used to classify domain elements (substances, processes, relations, structures). | Phytoplankton groups (diatoms, dinoflagellates, cyanobacteria), zooplankton groups (copepods, krill), microbial types, trophic levels, functional groups, bloom types, ecosystem types (pelagic, benthic), size classes (pico–macro). |
| 1.3 State-Variables | Variables | The measurable or definable properties that describe system conditions. | Nutrient concentrations, chlorophyll-a, biomass, grazing pressure, primary productivity, oxygen, DOM/POC/PIC, stoichiometric ratios, temperature, light availability, turbidity, mixed-layer depth, pCO₂, microbial abundance. |
| | Parameterization | How variables encode and represent the system’s state. | States encoded through productivity models, chlorophyll–biomass relationships, growth/grazing functions, Redfield ratios, size-spectrum slopes, nutrient uptake kinetics, photophysiological parameters, P–E curves, carbon-cycle fluxes. |
| 1.4 Admissible Idealizations | Simplifications | Conceptual reductions used to make the domain tractable (point masses, rational agents, perfect gases). | Constant stoichiometry, uniform mixing, perfect nutrient recycling, steady-state populations, linear grazing, ignoring species-level differences, assuming well-behaved food-web compartments, neglecting viral lysis. |
| | Validity Conditions | The limits and contexts in which idealizations hold or break down. | Valid in broad regional averages or stable oceanic gyres; breaks down in coastal zones, upwelling regions, OMZs, bloom events, high-variability ecosystems, strong top-down control, and non-steady-state dynamics. |
| 1.5 Domain Assumptions | Structural Assumptions | Background ontological stances such as determinism, continuity, randomness, discreteness. | Marine life responds to physical and chemical forcing; biological rates depend on temperature, light, and nutrient supply; carbon and nutrient cycles are mediated by biological processes; trophic interactions shape community structure. |
| | Implicit Commitments | Unstated but necessary assumptions that shape the field’s conceptual structure. | Assumes organisms can be grouped into functional traits, biogeochemical signals are preserved, physiological responses scale to ecosystems, and food webs can be simplified into trophic pathways. |
| 1.6 Internal Coherence Requirements | Consistency | The demand that domain concepts do not contradict one another. | Requires consistency among biomass, productivity, nutrient distributions, food-web interactions, stoichiometry, biogeochemical fluxes, and physical forcing. |
| | Compatibility | The requirement that entities, variables, and assumptions fit together into a unified descriptive framework. | Must align with physical oceanography (mixing/light), chemical oceanography (nutrients/carbon), marine geology (sediment interactions), climatology (forcing), and ecology/evolution (life-history constraints). |
| 2. Evidence Layer | 2.1 Observable Phenomena | Observables | The aspects of the domain that can produce detectable signals accessible to measurement. | Chlorophyll-a, phytoplankton/zooplankton abundance, microbial counts, primary productivity, optical properties, particulate organic carbon (POC), dissolved organic matter (DOM), fluorescence, oxygen utilization, blooms, diel vertical migration, biogenic particle flux (marine snow). |
| | Detection Limits | The boundaries of what can be resolved or sensed by current instruments or methods. | Limited by optical sensor noise, minimum detectable biomass, microscopy resolution, flow-cytometry sensitivity, satellite signal–to–noise (clouds, aerosols), incubation bottle sensitivity, and inability to resolve rare taxa or deep microbial processes. |
| 2.2 Measurement Systems | Units | Standardized quantifications (meters, seconds, volts, decibels, dollars, etc.) necessary for consistent comparison. | Biomass (mg C/m³), chlorophyll-a (mg/m³), abundance (cells/L), productivity (mg C/m²/day), grazing rate (day⁻¹), nutrient uptake rate (µM/day), fluorescence units, optical backscatter, oxygen (µM), microbial gene counts. |
| | Instruments | Devices and tools (microscopes, spectrometers, sensors, surveys, detectors) used to produce measurements. | CTD–fluorometers, satellite ocean-color sensors, flow cytometers, epifluorescence microscopes, imaging flow cytobots, nets (bongo, MOCNESS), sediment traps, oxygen sensors, PAM fluorometers, optical backscatter sensors, particle-imaging systems, autonomous biogeochemical floats. |
| 2.3 Operational Definitions | Definitions | Terms defined by specific measurement procedures, ensuring empirical clarity. | Chlorophyll defined by fluorometric/spectrophotometric protocols; primary production defined via ¹⁴C uptake or O₂ evolution; biomass defined by C:N:P conversion factors; size classes defined by mesh or optical thresholds; microbial abundance defined by flow-cytometry gating. |
| | Procedures | The explicit steps required to perform a measurement in a reproducible way. | Net tows, bottle sampling, filtration, fixation, staining, microscopy counts, flow-cytometry runs, incubation assays (¹⁴C, ⁵⁵Fe, O₂), nutrient uptake incubations, sediment-trap retrieval, satellite product QC, CTD profiling with bio-optical sensors. |
| 2.4 Data Acquisition | Protocols | Formal processes for gathering data under controlled or standardized conditions. | Vertical profiles, diel sampling, seasonal time-series stations, long-term observatories, transects across fronts/upwelling zones, Lagrangian drifter-based sampling, autonomous glider/float missions, bloom tracking via satellite. |
| | Sampling | Rules determining which subset of the domain is measured and how representative it is. | Replicate bottles, multi-depth sampling, stratified sampling across water masses, size-fractionated sampling, day/night comparisons, multiple nets for different size classes, microbial replicates for genetic/flow-cytometry analysis. |
| 2.5 Data Character & Format | Data Types | The form raw evidence takes (time series, spectra, images, counts, qualitative records). | Chlorophyll profiles, biomass distributions, microscopy images, flow-cytometry scatter plots, productivity tables, grazing-rate datasets, diversity indices, satellite ocean-color maps, optical spectra, sediment-trap flux records, metagenomic reads. |
| | Resolution | The granularity or precision with which data is captured. | Determined by sensor precision, microscopy magnification, cytometer thresholds, satellite pixel size, temporal sampling frequency, incubation duration, net mesh size, sequencing depth, and CTD/bio-optical sampling intervals. |
| 2.6 Reliability & Calibration | Calibration | Adjustment procedures ensuring instruments produce accurate results. | Fluorometer calibration with standards, satellite–in situ matchups, cytometer bead calibration, microscope stage calibration, oxygen-sensor drift correction, net efficiency calibration, PAM fluorometer baseline calibration, sequencing QC. |
| | Error Characterization | Identification and quantification of noise, uncertainty, bias, and measurement error. | Miscounts, preservation artifacts, sensor drift, optical interference, bottle effects, incubation artifacts, contamination, sequencing bias, patchiness of plankton distributions, vertical migration aliasing, and satellite atmospheric correction errors. |
| 3. Structural Layer | 3.1 Patterns & Regularities | Laws / Relations | Stable, repeatable patterns governing how observables behave across conditions. | Chlorophyll-a, phytoplankton/zooplankton abundance, microbial counts, primary productivity, optical properties, particulate organic carbon (POC), dissolved organic matter (DOM), fluorescence, oxygen utilization, blooms, diel vertical migration, biogenic particle flux (marine snow). |
| | Invariants | Quantities or properties that remain constant under transformations (symmetries, conservation laws). | Limited by optical sensor noise, minimum detectable biomass, microscopy resolution, flow-cytometry sensitivity, satellite signal–to–noise (clouds, aerosols), incubation bottle sensitivity, and inability to resolve rare taxa or deep microbial processes. |
| 3.2 Causal Architecture | Mechanisms | Underlying processes or structures that produce the observed regularities. | Biomass (mg C/m³), chlorophyll-a (mg/m³), abundance (cells/L), productivity (mg C/m²/day), grazing rate (day⁻¹), nutrient uptake rate (µM/day), fluorescence units, optical backscatter, oxygen (µM), microbial gene counts. |
| | Pathways | Organized sequences of interactions forming a causal chain or network. | CTD–fluorometers, satellite ocean-color sensors, flow cytometers, epifluorescence microscopes, imaging flow cytobots, nets (bongo, MOCNESS), sediment traps, oxygen sensors, PAM fluorometers, optical backscatter sensors, particle-imaging systems, autonomous biogeochemical floats. |
| 3.3 Theoretical Vocabulary | Concepts | Core terms that encode the domain’s structure (force, gene, equilibrium, field). | Chlorophyll defined by fluorometric/spectrophotometric protocols; primary production defined via ¹⁴C uptake or O₂ evolution; biomass defined by C:N:P conversion factors; size classes defined by mesh or optical thresholds; microbial abundance defined by flow-cytometry gating. |
| | Classifications | Taxonomies, categories, or typologies that organize entities and relations. | Net tows, bottle sampling, filtration, fixation, staining, microscopy counts, flow-cytometry runs, incubation assays (¹⁴C, ⁵⁵Fe, O₂), nutrient uptake incubations, sediment-trap retrieval, satellite product QC, CTD profiling with bio-optical sensors. |
| 3.4 Formal Representations | Equations | Mathematical constructs expressing laws, relations, or mechanisms. | Vertical profiles, diel sampling, seasonal time-series stations, long-term observatories, transects across fronts/upwelling zones, Lagrangian drifter-based sampling, autonomous glider/float missions, bloom tracking via satellite. |
| | Models | Structured representations—mathematical, computational, or conceptual—used to predict and explain phenomena. | Replicate bottles, multi-depth sampling, stratified sampling across water masses, size-fractionated sampling, day/night comparisons, multiple nets for different size classes, microbial replicates for genetic/flow-cytometry analysis. |
| 3.5 Idealized Structures | Simplified Models | Purposeful abstractions that capture essential dynamics while omitting irrelevant detail. | Chlorophyll profiles, biomass distributions, microscopy images, flow-cytometry scatter plots, productivity tables, grazing-rate datasets, diversity indices, satellite ocean-color maps, optical spectra, sediment-trap flux records, metagenomic reads. |
| | Limit Conditions | Regimes where specific models or approximations hold (classical vs. quantum, linear vs. nonlinear). | Determined by sensor precision, microscopy magnification, cytometer thresholds, satellite pixel size, temporal sampling frequency, incubation duration, net mesh size, sequencing depth, and CTD/bio-optical sampling intervals. |
| 3.6 Integrative Frameworks | Unifying Theories | Higher-order structures that connect disparate laws or mechanisms under a coherent whole. | Fluorometer calibration with standards, satellite–in situ matchups, cytometer bead calibration, microscope stage calibration, oxygen-sensor drift correction, net efficiency calibration, PAM fluorometer baseline calibration, sequencing QC. |
| | Interdisciplinary Links | Points where the theory connects to adjacent sciences or larger explanatory systems. | Miscounts, preservation artifacts, sensor drift, optical interference, bottle effects, incubation artifacts, contamination, sequencing bias, patchiness of plankton distributions, vertical migration aliasing, and satellite atmospheric correction errors. |
| 4. Method Layer | 4.1 Inquiry Design | Experimental Design | Structured plans for manipulating variables to test causal claims. | Manipulating light, nutrients, temperature, grazing pressure, CO₂, and mixing in lab cultures or mesocosms to test growth, nutrient limitation, stoichiometry, grazing, and ecosystem responses. |
| | Observational Design | Systematic approaches for gathering non-manipulated data (surveys, field studies, natural experiments). | Shipboard surveys, mooring time series, satellite ocean-color monitoring, autonomous glider/float missions, diel sampling, bloom tracking, and long-term ecological observations without controlled manipulation. |
| 4.2 Testing & Validation | Hypothesis Testing | Procedures for evaluating whether evidence supports or contradicts specific claims. | Comparing predicted biomass trends, bloom dynamics, nutrient limitation patterns, grazing responses, export flux, and microbial-loop behavior with observations from microscopy, flow cytometry, fluorometry, sediment traps, and incubation assays. |
| | Replication | The requirement that results be independently reproducible under similar conditions. | Duplicate bottle samples, repeated chlorophyll analyses, replicate net tows, multiple flow-cytometry runs, repeated incubation assays, repeated metagenomic sequencing runs, cross-cruise comparisons, and reprocessed satellite datasets. |
| 4.3 Inference & Evaluation | Statistical Inference | Rules for drawing conclusions from noisy or incomplete data. | Estimating uncertainties in biomass, productivity, growth rates, grazing rates, size spectra, diversity indices, stoichiometry, and particle flux; using regression analysis, spectral analysis, PCA/EOFs, GAMs, Bayesian inference. |
| | Model Comparison | Criteria (fit, simplicity, predictive accuracy, robustness) used to evaluate competing models. | Evaluating NPZ models, food-web models, size-spectrum models, microbial-loop models, export-flux models, and coupled physical–biological models based on fit, predictive skill, parameter robustness, and ecological realism. |
| 4.4 Error Management | Error Analysis | Identification and quantification of random and systematic errors. | Identifying miscounts, preservation artifacts, sensor drift, bottle effects, patchiness in plankton distributions, incubation artifacts, sequencing errors, optical interference, net-mouth clogging, and flow-cytometer gating bias. |
| | Bias Control | Methods for minimizing subjective, instrumental, or procedural biases. | Randomized bottle order, blind counting, standardized sample preservation, matched in situ–satellite observations, calibration with reference beads, independent observers for microscopy, QC filters for sequencing, replicate nets. |
| 4.5 Adjudication & Revision | Peer Scrutiny | Collective evaluation of claims through critique, review, and debate. | Independent evaluation of taxonomy, biomass estimates, grazing rates, model fits, genetic identifications, and bloom interpretations across teams, labs, and research groups. |
| | Theory Revision | Procedures for modifying, replacing, or discarding models based on new evidence. | Updating trophic models, refining growth/grazing formulations, revising Redfield ratios, adjusting export-efficiency equations, reinterpreting microbial-loop roles, modifying species interactions based on new evidence. |
| 4.6 Integrity Conditions | Transparency | Requirements to disclose methods, data, assumptions, and limitations. | Full reporting of sampling times, mesh sizes, incubation methods, nutrient additions, sensor calibrations, sequencing pipelines, data exclusions, QC thresholds, and model assumptions. |
| | Ethical Standards | Norms ensuring responsible conduct in experimentation, data handling, and publication. | Responsible collection of marine organisms, adherence to protected-species rules, ethical sample disposal, transparency about uncertainties, accurate attribution of datasets, and minimal ecosystem disturbance during sampling. |