From Conceptual Debates to Concrete Pathways
Damien Beillouin (UR Hortsys) et Bruno Rapidel (UR Absys)
Land Sparing
High-yield production on a smaller area
Freeing land for conservation
Works best where: Intensification is possible without major environmental trade-offs, Wild species depend on large, undisturbed habitats, Governance can secure protected areas,…
Land Sharing
Lower-intensity, wildlife-friendly farming
Larger agricultural area
Works best where: Landscapes are already highly mosaic, Smallholders dominate, Cultural landscapes have intrinsic ecological value,…
Bending the biodiversity curve requires addressing three concrete questions:
This is where the sparing–sharing framework becomes operationally useful.
Implications for policy and practice:
- Intensify production on suitable land to spare natural habitats elsewhere.
- Focused interventions are often more effective than spreading low-intensity farming everywhere.
Implications for policy and practice:
- Yield alone is insufficient.
- Policies must also consider ecological health, social equity, and long-term sustainability.
Implications for policy and practice:
- Prioritize strict protected areas in landscapes with high biodiversity.
- Use high-yielding farmland to reduce pressure on remaining natural habitats.
- Spatial planning is central, but may overlook on-farm biodiversity in productive areas.
Implications for policy and practice:
- Integrate biodiversity into productive landscapes (trees, hedgerows, semi-natural patches).
- Landscape-scale, multifunctional management is necessary.
- Conservation policies must go beyond land sparing, addressing both spared and farmed areas.
Implications for policy and practice:
- Policies risk ignoring local social dynamics and smallholder needs.
- Conservation and productivity goals may not align with social justice if interventions are top-down.
Implications for policy and practice:
- Design transitions that consider smallholder capacity, equity, and local governance.
- Multi-criteria approaches are needed to ensure that environmental improvements do not exacerbate social inequalities.
The “which strategy is better?”
The real constraints are: - Socio-economic (farm size, tenure, labour) - Landscape configuration (fragmented vs. intact) - Governance (zoning enforceability) - Market incentives (price premiums, certification) - Climate constraints (water, soil fertility)
Most regions cannot implement a pure sparing or pure sharing model. The most effective solution is context-dependent!!
Empirical Evidence
- Sparing & sharing overlap; consider continuum approach (Sidemo-Holm, 2021)
- No universal solution; local context matters (Augustiny, 2025)
- Sparing & sharing can be complementary, not exclusive (Valente, 2022)
1. Conceptual & epistemic limitations
- Simplified yield-biodiversity models fail to capture multi-dimensional socio-ecological realities.
- Evidence is fragmented: site-specific, short-term, or taxonomically narrow.
- Weak integration of ecological theory, agronomy, and socio-economic contexts.
2. Scientific debates unresolved
- Trade-offs between yield, biodiversity, and social outcomes remain poorly quantified.
- Leakage, rebound effects, and global land-use consequences are incompletely understood.
- Lack of multi-criteria metrics integrating biodiversity, ecosystem services, and social equity.
(200 meta-analyses, 9,000 studies)
Source: Bonfanti et al., 2025)
1. Sources of evidence
- Second-order meta-analyses (Beillouin et al., 200+ MAs, 9,000+ studies): quantify average effects of practices on biodiversity.
- PREDICTS database: maps biodiversity responses across space, taxa, and land-use intensities.
- Other global syntheses: e.g., FAO, IPBES, FABLE modelling.
2. Core insight
- Biodiversity recovery requires bundles of complementary practices, not single measures.
- Integrating field- to landscape-level evidence from MAs + global databases (PREDICTS) supports quantitative pathways for sustainable agriculture.
Source: EAT Lancet et al., 2025; Hudson et al., 2017 (PREDICTS)
Key methodological constraints
Coarse land-use categories:
GLOBIO (that uses PREDICTS) aggregates agriculture into broad classes (e.g., “extensive” vs “intensive”), making it difficult to distinguish agroecological practices such as intercropping, agroforestry, or hedgerows.
Fixed MSA values per category:
Mean Species Abundance (MSA) is static (e.g., intensive agriculture = 10%), failing to reflect variability within practices or improvements from biodiversity-friendly farming.
No spatial configuration:
Effects of land sparing vs land sharing depend on landscape layout, corridors, and patch size, which is poorly considered.
Limited representation of ecosystem services:
Pollination, pest control, soil fertility, water retention benefits from diverse farming systems are ignored, underestimating potential win-win outcomes.
Socially Just Approaches to Agricultural Transitions