Purpose
This page defines the canonical self-sufficiency calculation framework for Neobiome Intelligence. It establishes what formulas are used, which SSI indicators they quantify, and what architecture aggregates domain scores into a composite index. All calculation skills must cite this page as their methodological reference.
Framework architecture
Neobiome Intelligence uses a two-tier measurement model:
| Tier | Type | Indicators | Method |
|---|---|---|---|
| 1 — Hard ratios | Metered, calculable | I02 (food), I07 (energy + water) | Domain-specific ratio formulas (peer-reviewed) |
| 2 — Assessment | Qualitative/composite | I01, I03, I04, I05, I06, I08, I09, I10 | Wang (2025) QL/S dimensions; GEN CSA ordinal scoring |
Rationale: Domain-specific ratios (ESR, WSR, FSR) are the most mathematically explicit, widely cited, and peer-reviewed metrics available for community-scale self-sufficiency. Composite aggregation across qualitative indicators uses the Wang (2025) SSI architecture as its reference model, acknowledged as a working paper pending peer review. CR_002 CR_003
Tier 1 — Domain-specific ratio formulas
Energy Self-Sufficiency Rate (ESR)
[ \text{ESR} = \frac{E_{\text{self-consumed}}}{E_{\text{total demanded}}} ]
- Dimensionless ratio, range 0–1 (or expressed as %)
- (E_{\text{self-consumed}}) = energy produced locally and consumed on-site (kWh)
- (E_{\text{total demanded}}) = total community energy demand (kWh)
- Complementary metric: SCR (Self-Consumption Rate) = (E_{\text{self-consumed}} / E_{\text{total produced locally}}) CR_002
Applies to: i07_fulfilment_basic_needs.md
Empirical benchmark (Sieben Linden ecovillage): 67.1% electricity ESR, 100% heat ESR CR_002
Calibration caveat — design estimates overstate measured self-sufficiency. A solar community’s design-stage self-sufficiency can substantially exceed its measured rate: Kim et al. (2023) found 171% estimated → 133% actual (~78% realisation) over the first year, driven mainly by actual insolation falling short of the standard design assumption. So treat any modeled solar self-sufficiency as a P50 estimate and report the P90 (bad-year) band (D16 / pv_yield_p90), not the design figure alone. (Note: Kim’s rate is a generation-to-demand ratio, so it exceeds 100%; the ESR above is self-consumption-based and caps at 100% — but the design-overstates-actual direction applies to both.) LIT_047
Water Self-Sufficiency Ratio (WSR)
[ \text{WSR} = \frac{Q_{\text{lr}}}{Q_{\text{td}}} ]
- (Q_{\text{lr}}) = water sourced within the defined site boundary (recycled, rainwater, bore, stream) (L/day)
- (Q_{\text{td}}) = total water demand within that boundary (L/day)
- Boundary definition is critical — results vary substantially between building, neighbourhood, and village scales CR_002
Applies to: i07_fulfilment_basic_needs.md
Empirical benchmark (European ecovillages, n=60): 69% of ecovillages at or near 100% WSR; area size is the only statistically significant correlate (Spearman r = 0.561) CR_002
Food Self-Sufficiency Ratio (FSR)
[ \text{FSR} = \frac{\text{Production}}{\text{Production} + \text{Imports} - \text{Exports}} \times 100 ]
- Standard FAO methodology; percentage 0–100%
- Limitation: measures caloric mass, not dietary diversity
- Advanced variant — Supply-Side FSR (SSFSSR): converts all food to primary product equivalents (PPCRs) across 64 commodity groups for better cross-community comparability CR_002
Foodshed SSL (land-based variant):
[ \text{SSL}_{\text{foodshed}} = \frac{\text{Available local agricultural area (ha)}}{\text{Land footprint of food consumption (ha)}} ]
Community is food-self-sufficient if SSL ≥ 1.0 CR_002
-
Primary behind the
SSL_foodshedmethod (Schreiber et al. 2021). TheSSL_foodshedvariant above is grounded in this peer-reviewed systematic review of 42 foodshed studies, which formalises the self-sufficiency threshold (ST = food production / food consumption × 100), its inverse (IST), and the foodshed-size method (land/radius to reach X% LFS) — upgrading the method’s provenance from the AI syntheses CR_002 / CR_003 to a directly-read primary. Its methodological caveat is binding on how NI reports food-SS: theoretical LFS overstates actual LFS (Zhou et al. 2012 — a favourable production:consumption ratio is not realisable without processing/storage/transport, economic incentive, seasonality management, and consumer preference), and same-region results diverge purely on optimisation/allocation assumptions (Peters 2009: 34% within 49 km vs Peters 2012: 69% within 238 km). Treat the food-SSI as an explicit, method-sensitive upper bound. LIT_077 -
The only NZ empirical value for the
SSL_foodshedDENOMINATOR — and why it is a cross-check, not an input (OT_190). Millar & Bould’s Blueskin & Karitane study computes the land footprint of food consumption for a real ~2,800-person NZ foodshed: 1,375.7 ha for full food self-sufficiency ≈ 0.49 ha/person, against 16,084 ha available — anSSL_foodshedof roughly 11.7, i.e. “just 9%” of the foodshed’s land (16% of its pastoral land) would meet its whole diet OT_190. Two things this does for the framework. (1) It populates the denominator with NZ data for the first time — every prior land figure in corpus is vegetable-only, a design estimate, or a practitioner estimate. (2) It shows the denominator’s composition is dominated by animal products: meat 0.287 + dairy 0.110 = 81% of 0.49 ha/person — so anSSL_foodshedcomputed from vegetable yields alone is measuring the small share. It also supplies a measured counterpoint to LIT_077’s theoretical-overstates-actual caveat directly above: anSSL_foodshedof ~11.7 coexists with an actual mass balance of 0.14 for four-legged meat and zero commercial production of fruit, vegetables, grains or beverages. 🔴 ⚠contested: true— do NOT adopt 0.49 ha/person as a model input. Three defects: Table 12’s yields are “modified ecological footprint data taken from… (Lawton, 2012)” rather than measured (the report’s own measured meat yield is 165 kg/ha against Table 12’s 230, now confirmed as Lawton’s national mutton/goat yield of 231.50 kg/ha, Appendix 3 Table 6 — so Defect 1’s provenance is resolved); the dairy row does not reconcile (332.1 ha computed vs 308.00 printed); and a suspected dairy-product-weight-against-milksolids unit mismatch that could make 0.49 ~25% too high — but Lawton reports dairy on a product-weight/liquid-milk basis (milk 9,960 kg/ha), NOT milk solids, so the mismatch is unconfirmed and Defect 3 stays open. Use as a cross-check on the model’s land requirements; Lawton (2012/2013) now retrieved → LIT_100 (resolves Defect 1, not Defect 3, so OT_190 stayscontested). OT_190
Applies to: i02_food_security_sustainable_agriculture.md
Tier 2 — Composite aggregation architecture
For the eight qualitative/composite indicators, Neobiome Intelligence adopts the Wang (2025) SSI as its reference architecture — the primary paper is now held: LIT_057 (SSI = ∛(SL × QL × S), eq 1). Note: this is a working paper (Feb 2025), v0/early-stage; peer-reviewed status pending.
[ \text{SSI} = \sqrt[3]{\text{SL} \times \text{QL} \times \text{S}} ]
| Dimension | Formula component | Maps to SSI indicators |
|---|---|---|
| SL — Standard of Living | Weighted demand-share sum across nutrition, water, energy, waste + service thresholds for income, housing, health, education | I01 (financial), I02 (food), I07 (basic needs) |
| QL — Quality of Life | Adapted Bhutan GNH Index: 33 clustered indicators across education, living standards, community vitality, mental health, ecological diversity, governance | I03 (culture), I04 (human dev), I05 (governance), I10 (psychological) |
| S — Sustainability | Geometric mean of: ΔGrowth, government investment split, dependency sensitivity, technology adoption, innovation capacity, natural capital | I06 (resilience), I08 (innovation), I09 (environmental) |
Distance-bias penalty in SL (per Wang eqs 2–4, LIT_057): imports penalised with distance (γ_d,M 0.2× at ≤10 km → 1.0× at >100 km) and exports rewarded for being local (γ_d,X 1.0× at ≤10 km → 0.2× at >100 km) — incentivises local sourcing and nearby exports. ⚠ The NI model does not yet implement this distance-weighting, nor Wang’s domain priority weights (it uses equal weights as levers) — both are documented candidate enhancements to the SL layer. CR_002
Geometric mean rationale: borrowed from the Human Development Index — a village strong on SL but weak on sustainability is penalised more severely than a simple average would imply. CR_002
Implemented in the NI calc engine (frozen 2026-08, V0.12): SL layer only
The Neobiome Intelligence engine implements the SL (resource self-sufficiency) layer as the headline composite: the weighted geometric mean of Energy, Water and Food (non-substitutable survival domains, per the rationale above), with the arithmetic mean (WEF-nexus comparator) and the limiting domain (min) shown alongside; weights are equal by default and exposed as levers. Each domain is a supply-over-demand ratio. Energy is the weaker of local electricity and local heat (a Liebig minimum, “C2-min”: the two end-use services do not substitute, and heat is treated as a diagnostic that local wood and heat pumps usually hold above electricity, so electricity typically binds). Water is volume-weighted potable + non-potable. Food is the limiting macronutrient of carbohydrate, protein and fat (the “D-mac” redesign: each an SSR of produced over required, replacing the earlier veg-only measure). The full Wang SSI = ∛(SL × QL × S) is not computed here: QL and S are qualitative assessment dimensions (thesis side). Worked example, an illustrative Lower Moutere coordinate (no single pilot, per D_002): with a rainwater-only design the composite is roughly 0.95, water-limited (food closes on the site’s pastoral land). The binding domain is site-specific across real New Zealand sites: water where land is abundant, food where land is scarce or arable-only, electricity in the stressed winter. Regional climate from RD_022.
Conceptual foundation: Environmental Livelihood Security (Biggs et al. 2014 white paper; 2015 journal paper). The nexus-livelihoods framing the operational precedents below build on originates here. Biggs et al. coined Environmental Livelihood Security (ELS) by integrating the Sustainable Livelihoods Approach with the water–energy–food nexus, defining a system as secure when a balance is achieved between human demand on the environment and environmental impacts on humans across water, energy and food. That supply-versus-demand balance is the conceptual root of NI’s domain-ratio logic (ESR/WSR/FSR) and of the composite that aggregates them. The 2015 journal paper contributes a critical review of the four dominant nexus frameworks (Hoff/SEI 2011, FAO 2014, MuSIASEM, CLEWS) showing each neglects the livelihood scale LIT_099. The fuller primary is the 114-page IWMI white paper OT_194, which adds the complete ELS framework (Figure 21: the six livelihood capitals plus transforming processes, balanced against the water-energy-food-climate nexus), makes scale central to operationalizing ELS (community through region), and contributes a Part III primer on geospatial / Earth-observation methods for spatially assessing ELS at sub-national resolution, which resonates with NI’s coordinate-first, per-site approach. ⚠ Conceptual and methodological framing only: no value here is an NI calculation input.
National-scale precedent — WEF Nexus Index (Simpson et al. 2022). The WEF Nexus Index scores 181 nations on integrated water/energy/food security using the JRC:COIN composite-indicator method (min-max normalisation → hierarchical arithmetic-mean aggregation → equal pillar weighting, with an r ≥ 0.92 double-counting cut). It is a national-scale precedent for how NI’s self-sufficiency composite can be built and defended. Notably it makes the opposite aggregation choice to the geometric mean above: Simpson chose the arithmetic mean for substitutability and interpretability, while explicitly conceding the geometric mean is plausible because water/energy/food are not fully compensable. This is the documented counter-argument to weigh when NI’s aggregation rule is finalised. It also uses an access vs availability decomposition within each domain — a structural pattern worth considering for the NI domain scores. LIT_049
Community-scale precedent — FEW four-component framework (Schmidt et al. 2022). A field-tested community-scale FEW-security assessment (114 households, three off-grid rural Alaska communities) decomposes each resource sector into four components — availability, access, quality and preference — within a “Society” frame, richer than the access/availability split above. Empirically, locally-harvested (subsistence) resources scored more secure than purchased ones on all four components, which the authors attribute to self-sufficiency — direct support for weighting local provisioning. The quality/preference axes matter: a resource can be available and accessible yet culturally inappropriate or low-quality, and so not register as “secure.” LIT_050
Systems-modelling / causal-nexus precedent — WEFE nexus (Hurtado et al. 2024). A complementary structural precedent to the composite-index approaches above: Hurtado et al. combine participatory systems modelling (Group Model Building) with network analysis to map the water-energy-food-ecosystems nexus of a water-stressed Spanish region as a causal loop diagram (47 variables) and then a directed network (47 nodes, 120 edges) whose centrality/clustering metrics locate leverage points. Two things it adds. (1) Method: it demonstrates representing the coupled resource system as an interdependent whole and finding intervention points structurally, rather than only scoring domains — a candidate front-end to the scoring layer. (2) Non-substitutability evidence: the integrated nexus is sparse (network density 5.6%, average path length 4.187), so isolated single-variable interventions have small effects and multiple simultaneous leverage points are required — a real-world corroboration of the non-substitutability premise behind NI’s geometric-mean aggregation choice (as opposed to Simpson’s compensatory arithmetic mean). The highest-centrality variables are effective regulation & governance and environmental awareness, not supply technology. ⚠ Spanish semi-arid case study — method and framing only; no hectare/hm3/centrality value is an NI calculation input. LIT_079
SSI indicator mapping
| SSI indicator | Tier | Formula / method | Primary source |
|---|---|---|---|
| I01 Financial & economic sufficiency | 2 | Wang SL — income and housing service thresholds | [[cr_002_quantitative_ss_frameworks |
| I02 Food security & sustainable agriculture | 1 | FSR / SSL_foodshed | [[cr_002_quantitative_ss_frameworks |
| I03 Local wisdom & cultural heritage | 2 | Wang QL — community vitality, cultural preservation sub-indicators | [[cr_002_quantitative_ss_frameworks |
| I04 Human development & social capital | 2 | Wang QL — education, health, social trust sub-indicators | [[cr_002_quantitative_ss_frameworks |
| I05 Good governance & transparency | 2 | Wang QL — governance sub-indicator; participatory indicator frameworks | [[cr_002_quantitative_ss_frameworks |
| I06 Resistance to external shocks | 2 | Wang S — dependency sensitivity (D), ΔGrowth | [[cr_002_quantitative_ss_frameworks |
| I07 Fulfilment of basic needs | 1 | ESR (energy) + WSR (water) | [[cr_002_quantitative_ss_frameworks |
| I08 Innovation & appropriate technology | 2 | Wang S — technology adoption (T), innovation capacity (C) | [[cr_002_quantitative_ss_frameworks |
| I09 Environmental sustainability | 2 | Ecological Footprint (gha) + MFA self-sufficiency coefficient; Wang S — natural capital (K_N) | [[cr_002_quantitative_ss_frameworks |
| I10 Psychological self-sufficiency | 2 | Wang QL — mental health, well-being, GNH sub-indicators | [[cr_002_quantitative_ss_frameworks |
Gullberg et al. (2025) — Seven-domain metabolic function framework
Status: captured for reference — architectural adoption pending design decision
Gullberg, Wang & Eriksson (2025) extend the single-domain ratio formula to seven metabolic functions within a single consistent system boundary. This is the only peer-reviewed study to do so. Captured here for reference; whether Neobiome Intelligence adopts this framework or the existing ESR/WSR/FSR approach is a design decision not yet made. LIT_022
Canonical formula (shared across all seven domains):
[ \text{SSI}_i = \frac{\text{Local provisioning potential for function } i}{\text{Total annual demand for function } i} \times 100% ]
Where local provisioning potential is constrained by the binding limiting factor specific to each solution (roof area, green area, wastewater volume, surplus heat).
Seven metabolic functions and empirical results (Knivsta, Sweden, 3 density cases):
| Function | Binding factor | Case 1 (dense, 929p) | Case 2 (SF, 929p) | Case 3 (SF, 102p) |
|---|---|---|---|---|
| Electricity supply | Roof area (PV) | 140% | 260% | 150% |
| Heat supply | Graywater heat + biogas + surplus | 66% | 31% | 48% |
| Transportation (biogas) | Wastewater volume | 24% | 10% | 10% |
| Freshwater supply | Roof area (rainwater) | 100% | 140% | 220% |
| Graywater management | Green area | 3,502% | 25,517% | 46,727% |
| Vegetable supply | Green area (urban farming) | 38% | 210% | 400% |
| Nitrogen recovery | Wastewater volume | 78% | 78% | 78% |
| Phosphorus recovery | Wastewater volume | 98% | 98% | 98% |
Key finding: Building density and green area share are the dominant variables across all seven domains simultaneously. Full SS requires demand-side reduction: “entirely self-sufficient urban areas are unrealistic with the current level of consumption.” LIT_022
Relationship to SSI 10-indicator framework:
The Gullberg 7-function framework is NOT in conflict with the SSI 10-indicator framework — they operate at different levels. Gullberg provides precision calculation methodology for physical/material resource flows (Tier 1 hard ratios). The SSI framework additionally covers social, economic, cultural, and governance dimensions (Tier 2 composite assessment).
| Gullberg metabolic function | SSI indicator(s) | NI Tier |
|---|---|---|
| Electricity supply | I07 | Tier 1 (ESR) |
| Heat supply | I07 | Tier 1 (ESR-heat) |
| Transportation (biogas) | I07, I09 | Tier 1/2 |
| Freshwater supply | I07 | Tier 1 (WSR) |
| Graywater management | I09, I07 | Tier 2 |
| Vegetable food supply | I02 | Tier 1 (FSR) |
| N and P recovery | I09, I02 | Tier 2 |
Not covered by the 7-function framework (assessed separately under Tier 2): I01 (financial), I03 (culture/wisdom), I04 (human development), I05 (governance), I06 (resilience), I08 (innovation), I10 (psychological). LIT_022
Methodological lineage — Eco-cycle Model (Ranhagen & Frostell 2014). The Gullberg seven-function approach sits in the KTH eco-cycle / industrial-ecology tradition formalised in Eco-cycle Model 2.0 for Stockholm Royal Seaport — a multi-level framework (established theory → ecosphere anchoring → functions/flows map → annual resource-flow accounts for energy/CO2/water, drawn as Sankey diagrams) and the methodological ancestor of this metabolic-function calculation work. It also frames the core Neobiome tension as Scenario A (small-scale self-sufficiency) vs Scenario B (large-scale/centralized), concluding that a realistic district vision combines both. OT_053
NZ calibration note: All seven input data categories have NZ equivalents (NIWA, Stats NZ, BRANZ HEEP, MfE biosolids guidelines). NZ-specific calibration targets: electricity demand baseline (RT_077); per-capita water consumption (RT_078). Annual-average calculations only — seasonal variation requires supplementary analysis for battery sizing and off-grid design. LIT_022
What this framework does not yet cover
- Building/shelter self-sufficiency — no community-scale formula simultaneously covers food, energy, water, and building materials. LBC covers building at net-positive pass/fail only. CR_002
- Temporal dynamics — most formulas are annual snapshots. Wang SSI includes a growth-curve indicator (R² of SSI over 5–10 years); not yet integrated into Neobiome skills.
- NZ-specific calibration — NZ household energy/water/food consumption baselines needed before ESR/WSR/FSR can be calculated for a specific Neobiome pilot site.
Related pages
- environmental_livelihood_security — the FEW-nexus + livelihoods framing behind the supply/demand-balance approach (framework, lineage, precedents)
- i02_food_security_sustainable_agriculture.md
- i07_fulfilment_basic_needs.md
- i09_environmental_sustainability.md
- Sources: cr_002_quantitative_ss_frameworks.md cr_003_consensus_community_ss.md
Connections
Links to
Referenced by
SSI indicators (10): I01: Financial & Economic Self-Sufficiency · I02: Food Security & Sustainable Agriculture · I03: Local Wisdom & Cultural Heritage · I04: Human Development & Social Capital · I05: Good Governance & Transparency · I06: Resistance to External Shocks · I07: Fulfilment of Basic Needs · I08: Innovation & Appropriate Technology · I09: Environmental Sustainability · I10: Psychological Self-Sufficiency
Sources (6): CR_001 · LIT_001 · LIT_012 · LIT_077 · LIT_099 · OT_194
Concepts (2): EDT–SSI Convergence · Environmental Livelihood Security (FEW-Nexus +…