| 1. Domain | 1.1 Scope of the Domain | Boundaries | The range of phenomena the science includes and excludes. | Studies how human societies perceive, use, transform, engineer, degrade, restore, and adapt to environmental systems, and how landscapes evolve in response to cultural, economic, and technological activities. Includes land-use change, resource extraction, agriculture, urbanization, deforestation, terracing, hydrological modification, hazard mitigation, ecosystem engineering, and long-term socioecological dynamics. Excludes purely natural environmental processes without human involvement; excludes human behavior unrelated to landscape outcomes. |
| | Scale | The spatial, temporal, or organizational level at which the science operates (e.g., quantum, cellular, social, cosmic). | Operates across site, regional, continental, and global scales, and across temporal ranges from short-term disturbance (e.g., deforestation, construction) to multi-millennial anthropogenic landscape evolution (agricultural regimes, settlement cycles). |
| 1.2 Ontological Commitments | Entities | The kinds of things assumed to exist within the domain (particles, organisms, agents, fields, etc.). | Humans, communities, technologies, tools, infrastructure, ecosystems, soils, water systems, vegetation, animals, climate regimes, geomorphological features, land covers, resources, feedback loops, hazards, settlement systems, engineered landscapes. |
| | Properties | The fundamental attributes these entities possess (mass, charge, genotype, preference, etc.). | Productivity, resilience, vulnerability, carrying capacity, ecological diversity, soil fertility, hydrological stability, energy flows, pollution loads, erosion intensity, landscape connectivity, disturbance magnitude, anthropogenic pressure, sustainability, environmental inertia, resource scarcity. |
| | Categories | The basic ontological types used to classify domain elements (substances, processes, relations, structures). | Land-use types (agricultural, pastoral, industrial, urban, forest); modification strategies (irrigation, terracing, burning, drainage, reforestation); hazard regimes (drought, flood, landslide, wildfire); socioecological systems (agrarian, urban, frontier, extractive); resource types (renewable, nonrenewable); feedback types (positive, negative, cascading). |
| 1.3 State-Variables | Variables | The measurable or definable properties that describe system conditions. | Land-cover composition; soil-nutrient levels; erosion rates; vegetation density; hydrological flow volumes; water availability; energy inputs; pollution concentrations; infrastructure footprint; settlement density; productivity indices; biodiversity measures; hazard frequency; vulnerability scores; resource extraction intensity. |
| | Parameterization | How variables encode and represent the system’s state. | Encoded via remote-sensing land-cover layers, GIS hydrology models, soil tests, vegetation indices (NDVI), climate datasets, infrastructure maps, archaeological landscape surveys, hazard logs, environmental-impact assessments, historical land-use reconstructions, energy-budget accounting, socioecological network metrics. |
| 1.4 Admissible Idealizations | Simplifications | Conceptual reductions used to make the domain tractable (point masses, rational agents, perfect gases). | Treating landscapes as static; assuming linear human impact; modeling human decision-making as rational and stable; representing ecosystems as homogeneous; ignoring cultural variation in environmental knowledge; collapsing multi-scalar feedback into single trends; assuming equilibrium conditions; simplifying hazard effects; idealizing uniform resource distribution. |
| | Validity Conditions | The limits and contexts in which idealizations hold or break down. | Break down in rapidly changing or highly complex landscapes; under strong cultural heterogeneity; during climate extremes or abrupt disturbances; where feedback loops are nonlinear; when informal or unrecorded land uses dominate; in highly fragmented or degraded ecosystems; in colonial/postcolonial contexts with layered land claims. |
| 1.5 Domain Assumptions | Structural Assumptions | Background ontological stances such as determinism, continuity, randomness, discreteness. | Human activity significantly reshapes ecological and geomorphological systems; environmental constraints shape human choices; landscapes record cumulative human activity; socioecological systems operate through feedback loops; sustainable or unsustainable regimes can be identified; human–environment relations are historically contingent yet patterned. |
| | Implicit Commitments | Unstated but necessary assumptions that shape the field’s conceptual structure. | Assumes environmental change can be observed, measured, and modeled; assumes human effects are distinct from purely natural forces; assumes landscapes have interpretable anthropogenic signatures; assumes long-term trajectories can be reconstructed; assumes cultural values influence environmental action. |
| 1.6 Internal Coherence Requirements | Consistency | The demand that domain concepts do not contradict one another. | Land-use models must align with ecological constraints; archaeological and historical records must match environmental reconstructions; modification processes must be consistent with geomorphological evidence; hazard models must fit landscape conditions; sustainability assessments must reflect real productivity and degradation patterns. |
| | Compatibility | The requirement that entities, variables, and assumptions fit together into a unified descriptive framework. | Requires harmonization among ecology, geography, archaeology, climatology, hydrology, environmental engineering, and cultural anthropology. Explanations must integrate biophysical processes with cultural, economic, and technological drivers without contradiction. |
| 2. Evidence Layer | 2.1 Observable Phenomena | Observables | The aspects of the domain that can produce detectable signals accessible to measurement. | Deforestation fronts; terracing; irrigation canals; soil erosion features; sediment accumulation; vegetation die-off; urban sprawl; agricultural field boundaries; land-use transitions; water diversions; pollution plumes; mining scars; fire regimes; infrastructural imprints (roads, dams, levees); settlement expansion; ecosystem fragmentation; reforestation or restoration signs. |
| | Detection Limits | The boundaries of what can be resolved or sensed by current instruments or methods. | Low-resolution remote-sensing limitations; obscured features under canopy; rapid environmental change outpacing measurement frequency; incomplete archival land-use records; buried or eroded anthropogenic features; blended natural vs human-caused signals; noise in climate or hydrology datasets; inability to detect subterranean modifications; sensor saturation in highly reflective surfaces. |
| 2.2 Measurement Systems | Units | Standardized quantifications (meters, seconds, volts, decibels, dollars, etc.) necessary for consistent comparison. | Land-cover percentages; NDVI/vegetation indices; soil nutrient concentrations; sediment load (mg/L); water-flow volume (m³/s); erosion rate (mm/yr); carbon emissions or sequestration (tons CO₂e); land-use transition counts; pollutant ppm values; temperature/precipitation metrics; deforestation rate (ha/yr); infrastructure footprint area; biodiversity richness indices. |
| | Instruments | Devices and tools (microscopes, spectrometers, sensors, surveys, detectors) used to produce measurements. | Satellite imagery (Landsat, Sentinel, MODIS); LiDAR; drones; soil-testing kits; hydrology sensors; climate stations; GIS mapping tools; erosion pins and sediment traps; water-quality meters; carbon-flux chambers; archaeological survey instruments; paleoenvironmental coring devices; environmental DNA sampling. |
| 2.3 Operational Definitions | Definitions | Terms defined by specific measurement procedures, ensuring empirical clarity. | Land-use change defined as measurable shift in land-cover category; anthropogenic modification defined as landscape alteration exceeding natural baselines; degradation defined by significant loss of ecological productivity or resilience; erosion defined by quantifiable soil removal; hazard exposure defined by spatial intersection of population with risk zones; restoration defined as targeted intervention reversing degradation trends. |
| | Procedures | The explicit steps required to perform a measurement in a reproducible way. | Processing satellite imagery; classifying land cover; conducting ground-truthing surveys; measuring soil and water samples; mapping erosion features; running hydrological models; sampling pollen or charcoal for paleoenvironmental reconstruction; analyzing sediment cores; mapping anthropogenic structures; documenting agricultural and construction practices; calculating carbon budgets; integrating field + remote-sensing data. |
| 2.4 Data Acquisition | Protocols | Formal processes for gathering data under controlled or standardized conditions. | Standardized remote-sensing acquisition windows; multi-seasonal or annual monitoring; consistent soil and water sampling procedures; systematic transects for field surveys; harmonized land-cover classification frameworks; sensor calibration schedules; cross-validation with historical maps and archival imagery; structured documentation of anthropogenic features; long-term ecological monitoring networks. |
| | Sampling | Rules determining which subset of the domain is measured and how representative it is. | Stratified sampling across ecological zones; random sampling of land parcels; targeted sampling of degradation hotspots; watershed-based sampling frames; sampling along elevation gradients; sampling across land-use categories; longitudinal sampling for time-series reconstruction; subsampling sediments at fixed core intervals. |
| 2.5 Data Character & Format | Data Types | The form raw evidence takes (time series, spectra, images, counts, qualitative records). | Raster land-cover datasets; NDVI time-series; sediment and soil composition tables; hydrology flow logs; pollutant concentration datasets; GIS shapefiles; LiDAR-derived elevation models; archaeological landscape maps; paleoenvironmental core sequences; environmental DNA reads; multi-sensor fusion outputs; time-series hazard datasets. |
| | Resolution | The granularity or precision with which data is captured. | Determined by satellite pixel size, LiDAR point density, sediment-core sampling interval, soil- and water-testing precision, temporal collection frequency, GIS feature granularity, climate-station spacing, sensor accuracy, and historical map resolution. |
| 2.6 Reliability & Calibration | Calibration | Adjustment procedures ensuring instruments produce accurate results. | Cross-validating remote-sensing classifications with field surveys; calibrating hydrological and climate sensors; harmonizing coordinate systems; aligning land-cover maps across years; correcting atmospheric distortion; checking soil/water testing instruments; replicating sediment-core interpretation; validating archaeological landscape features through multiple lines of evidence. |
| | Error Characterization | Identification and quantification of noise, uncertainty, bias, and measurement error. | Misclassification of land cover; remote-sensing noise; cloud contamination; sampling bias in field surveys; erosion of anthropogenic features; diagenetic alteration of paleoenvironmental proxies; inconsistent historical documentation; temporal gaps; variability in soil/hydrology measurements; spatial interpolation artifacts; projection-induced distortions. |
| 3. Structural Layer | 3.1 Patterns & Regularities | Laws / Relations | Stable, repeatable patterns governing how observables behave across conditions. | Land-use intensification increases environmental pressure; deforestation accelerates erosion and hydrological instability; settlement expansion reduces biodiversity; irrigation alters soil chemistry and water cycles; positive feedback loops accelerate degradation, while negative feedback loops stabilize systems; human modification clusters along transportation corridors; hazard exposure correlates with settlement in risk-prone landscapes; agricultural terraces produce predictable geomorphological signatures; urban heat islands scale with built density. |
| | Invariants | Quantities or properties that remain constant under transformations (symmetries, conservation laws). | Conservation of mass/energy in ecological flows; erosion and sediment transport obey geomorphic laws; vegetation–soil feedbacks remain structurally consistent; settlement systems follow persistent spatial hierarchies; hydrological responses to land cover exhibit stable patterns; nutrient cycles follow persistent biogeochemical constraints; fire regimes reveal consistent fuel–climate–ignition relationships. |
| 3.2 Causal Architecture | Mechanisms | Underlying processes or structures that produce the observed regularities. | Resource extraction → landscape simplification → reduced resilience; Urbanization → impervious surfaces → altered runoff → flooding; Agriculture → soil disturbance → erosion → fertility decline; Deforestation → hydrological destabilization → drought/flood risk; Infrastructure → connectivity → increased pressure on ecosystems; Climate change → amplified hazard regimes → intensified landscape modification; Cultural practices → niche construction → long-term landscape engineering; Pollution → biophysical degradation → cascading ecological effects. |
| | Pathways | Organized sequences of interactions forming a causal chain or network. | Road construction → settlement infill → forest fragmentation → biodiversity loss; Irrigation expansion → salinization → declining yields; Overgrazing → vegetation loss → desertification; Mining → soil + water contamination → ecosystem collapse → social displacement; Fire suppression → fuel accumulation → catastrophic fires; Restoration investment → vegetation recovery → increased soil stability; Climate anomaly → crop failure → land abandonment → reforestation. |
| 3.3 Theoretical Vocabulary | Concepts | Core terms that encode the domain’s structure (force, gene, equilibrium, field). | Socioecological systems, resilience, vulnerability, carrying capacity, feedback loops, landscape engineering, anthropogenic biomes, niche construction, land-use transitions, hazard regime, ecological footprint, sustainability, degradation, restoration trajectories, human agency, environmental determinism vs possibilism. |
| | Classifications | Taxonomies, categories, or typologies that organize entities and relations. | Landscape types (agrarian, urban, industrial, frontier); modification strategies (irrigation, terracing, burning, drainage, reforestation, damming); hazard categories (flood, drought, wildfire, erosion); socioecological regime types (sustainable, transitional, collapsing); resource-use systems (extensive, intensive); feedback classes (positive, negative, cascading). |
| 3.4 Formal Representations | Equations | Mathematical constructs expressing laws, relations, or mechanisms. | Soil-erosion equations (e.g., RUSLE); hydrological flow equations; carbon-budget calculations; nutrient-cycle equations; diffusion models of land-use change; feedback-system differential equations; hazard probability equations; resilience metrics; carrying-capacity equations; population–resource dynamic models; albedo–temperature equations for urban heat islands. |
| | Models | Structured representations—mathematical, computational, or conceptual—used to predict and explain phenomena. | GIS-based land-change models; agent-based socioecological simulations; hydrological watershed models; erosion–sedimentation models; climate–vegetation interaction models; hazard-exposure maps; long-term anthropogenic-landscape evolution models; ecosystem-service valuation models; urban-growth models; niche-construction simulations. |
| 3.5 Idealized Structures | Simplified Models | Purposeful abstractions that capture essential dynamics while omitting irrelevant detail. | Static landscapes; linear degradation trajectories; uniform cultural behavior; rational resource use; homogeneous soil or vegetation; perfect enforcement of land regulations; no political or economic inequality; stable climate baselines; absence of informal land-use practices; isolated subsystems without feedback loops. |
| | Limit Conditions | Regimes where specific models or approximations hold (classical vs. quantum, linear vs. nonlinear). | Fail under nonlinear feedbacks, rapid climate variability, political conflict, economic shocks, technological discontinuities, cultural heterogeneity, mixed land-tenure systems, unrecorded land-use practices, stochastic hazard events, strongly path-dependent systems, or long-term ecological legacies. |
| 3.6 Integrative Frameworks | Unifying Theories | Higher-order structures that connect disparate laws or mechanisms under a coherent whole. | Human behavioral ecology linking environmental constraints to decision-making; socioecological-systems theory unifying human and biophysical processes; landscape archaeology merging cultural history with geomorphology; resilience theory integrating feedbacks and adaptive cycles; political ecology linking power and environmental change; Earth-systems theory embedding human activity in global biogeochemical processes. |
| | Interdisciplinary Links | Points where the theory connects to adjacent sciences or larger explanatory systems. | Ecology, climatology, geomorphology, archaeology, environmental engineering, urban planning, economics (resource use), political science (land governance), sociology (environmental inequality), public health (exposure to hazards). |
| 4. Method Layer | 4.1 Inquiry Design | Experimental Design | Structured plans for manipulating variables to test causal claims. | Manipulating irrigation intensity in controlled plots; altering vegetation cover to test erosion sensitivity; applying different land-management treatments (burning, terracing, mulching) to compare landscape response; controlled watershed experiments; simulated hazard exposure (e.g., artificial flooding); experimental restoration treatments; agent-based models adjusting human land-use decisions. |
| | Observational Design | Systematic approaches for gathering non-manipulated data (surveys, field studies, natural experiments). | Longitudinal monitoring of land-cover change; hydrological field observation; erosion and sediment surveys; vegetation transects; archaeological landscape surveys; remote-sensing time-series; documentation of local land-use practices; natural experiments arising from droughts, floods, fires, policy shifts, or economic shocks; cross-regional comparisons of landscape modification histories. |
| 4.2 Testing & Validation | Hypothesis Testing | Procedures for evaluating whether evidence supports or contradicts specific claims. | Testing whether specific human activities cause measurable changes in erosion, water flow, biodiversity, or soil fertility; validating land-cover classifications with ground truth; testing climate–land interaction models; evaluating whether settlement density predicts environmental degradation; assessing restoration efficacy; validating hazard-risk models; testing for anthropogenic signatures in geomorphological features. |
| | Replication | The requirement that results be independently reproducible under similar conditions. | Re-running land-cover classification on independent imagery; repeating soil and water sampling across seasons; recoring sediment layers; replicating vegetation transects; repeating archaeological landscape mapping with new teams; retesting restoration outcomes after additional growing seasons; rerunning hydrological or socioecological models with updated data. |
| 4.3 Inference & Evaluation | Statistical Inference | Rules for drawing conclusions from noisy or incomplete data. | Spatial regression linking land-use to environmental metrics; multilevel modeling for socioecological data; time-series analysis of landscape change; geostatistical interpolation of erosion or soil variables; Bayesian modeling of hazard probability; structural–equation models linking social drivers to environmental outcomes; causal-inference models integrating human and biophysical variables. |
| | Model Comparison | Criteria (fit, simplicity, predictive accuracy, robustness) used to evaluate competing models. | Comparing land-change models (cellular automata, agent-based, statistical); evaluating competing erosion or hydrology models; contrasting climate-impact scenarios; comparing restoration-strategy outcomes; testing alternative socioecological feedback frameworks; evaluating competing hazard models; cross-validating archaeological landscape reconstructions. |
| 4.4 Error Management | Error Analysis | Identification and quantification of random and systematic errors. | Identifying misclassified land-cover pixels; quantifying remote-sensing noise; detecting inconsistent soil or hydrology measurements; correcting GPS and LiDAR positional error; distinguishing natural vs anthropogenic erosion; addressing gaps in historical land-use data; modeling uncertainty in paleoenvironmental proxies; correcting interpolation artifacts. |
| | Bias Control | Methods for minimizing subjective, instrumental, or procedural biases. | Triangulating remote-sensing data with ground surveys; using multiple classifiers for land-cover mapping; stratified sampling across ecological zones; independent replication of archaeological mapping; controlling for political or economic bias in human-impact attribution; harmonizing multi-source data; standardizing field protocols; applying sensitivity analysis to model parameters. |
| 4.5 Adjudication & Revision | Peer Scrutiny | Collective evaluation of claims through critique, review, and debate. | Reinterpreting landscape maps with new evidence; reviewing land-cover classification rules; challenging degradation or restoration claims with independent data; reanalyzing sediment cores with new proxies; auditing model assumptions; external review of socioecological interpretations; resolving discrepancies across datasets (remote sensing, archaeological, ecological). |
| | Theory Revision | Procedures for modifying, replacing, or discarding models based on new evidence. | Updating human–environment interaction models with improved climate data; revising degradation trajectories; incorporating new understanding of cultural practices and niche construction; updating resilience and vulnerability frameworks; modifying long-term socioecological cycle models; refining hazard-exposure concepts with more accurate spatial data. |
| 4.6 Integrity Conditions | Transparency | Requirements to disclose methods, data, assumptions, and limitations. | Full disclosure of data sources, spatial resolutions, classification schemes, sampling methods, calibration steps, model assumptions, and uncertainty bounds; sharing code, GIS layers, and metadata when permissible; documenting interpretive limits for paleoenvironmental reconstruction. |
| | Ethical Standards | Norms ensuring responsible conduct in experimentation, data handling, and publication. | Ensuring land rights and sovereignty are respected; collaborating with Indigenous and local communities; preventing ecological harm during fieldwork; protecting sensitive archaeological landscapes; responsibly communicating hazard or degradation data; avoiding misuse of environmental assessments for political displacement or exploitation. |